energy modeling methodology
DESCRIPTION
The research is focused on developing an energy modeling methodology for small to medium sized architecture firms that can be used to help inform early concept, schematic, and design development decisions.TRANSCRIPT
ENERGY MODELING METHODOLOGYL E V E R A G I N G T E C H N O L O G Y T O D E L I V E R S M A RT E R , M O R E S U S TA I N A B L E B U I L D I N G D E S I G N S
AUTHOR - CHRISTOPHER WINGATE
FACULTY ADVISOR - BLAINE BROWNELL
MS&R ADVISOR - THOMAS MEYER
DATE - AUGUST 2012
MADE POSSIBLE BY A PARTNERSHIP BETWEEN THE UNIVERSITY OF MINNESOTA
SCHOOL OF ARCHITECTURE AND MEYER, SCHERER & ROCKCASTLE, LTD
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
1. University of Minnesota Master of Architecture program, www.arch.design.umn.edu.
2. Meyer Scherer & Rockcastle, ltd. www.msrltd.com.
3. Karges-Faulconbridge, Inc. www.kfiengineers.com.
Energy Modeling Methodology is the result of a unique col-
laboration between the academic and professional worlds
of architecture. Renee Cheng, Head of the University of
Minnesota School of Architecture, created a semester long
work/study program that pairs Master of Architecture stu-
dents with local design firms to conduct research projects.
This paper is a result of the pilot semester of the project.1
Students enrolled in the program split their time between
the classroom and the office, but their focus is always di-
rected by the research project. This structure harnesses the
strengths of the university and the private sector in con-
ducting mutually beneficial research. Architecture firms
benefit from the exploration of innovative processes, tools,
and techniques by university students and faculty, and the
university is able to vet its research in the real world, us-
ing experienced professionals to shape academic concepts
into adoptable methodologies. At the center of it all is an
invaluable opportunity for students; they gain experience
and make connections in the field while learning a unique
skill set that makes them attractive to future employers.
Energy Modeling Methodology was written and researched
by Christopher Wingate while paired with Meyer Scherer
& Rockcastle, ltd.2 The research is focused on develop-
ing an energy modeling methodology for small to medium
sized architecture firms that can be used to help inform ear-
ly concept, schematic, and design development decisions.
A UNIQUE COLLABORATION
COLLABORATIVE RESEARCH BETWEEN THE UNIVERSITY AND THE PROFESSION
PROFESSIONAL PRACTICE
• Implement research on real projects and generate real world results
• Research reviewed by experienced professionals
• Research must fit within existing budgets, schedules, and work flows
ACADEMIC RESEARCH
• Explores the latest approaches, innovations, and technologies
• Encourages the technical and conceptual understanding of
tools and processes through extended investigation
Profession MS&R architecture
KFI engineering
Research ProjectENERGY MODELING
AcademicUNIVERSITY OF MINNESOTA
COLLEGE OF DESIGN
University of Minnesota School of ArchitectureProgram Coordinator - Renee Cheng, Head of School of Architecture
Faculty Advisor - Blaine Brownell, Assistant Professor
Student Researcher - Christopher Wingate, M.Arch Candidate
Meyer Scherer & Rockcastle, Ltd.Program Coordinator - Thomas Meyer, FAIA
Project Support - Allison Salzman, AIA
- Sam Edelstein
PROJECT TEAM
Karges-Faulconbridge, Inc.Energy Simulation Engineer - Katherine R. Edwards
OPTIMIZED ENERGY MODELING PROCESS
• Inform decisions throughout the design process
• Easy to use
• Communicates graphically
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
5 10 15 20 25 30 35 40 4540 35 30 25 20 15 10 545
110%
224%
36%4
36%
512%
612%
Chart Title
Wingate(U of M)
Brownell
MS&
R team
Edwards
Wingate(MS&R)
Wingate(TA)
1. NCARB Intern Development Program, www.ncarb.org
2. ARCH 5516 Thermal and Luminous Design, http://www.zeropluscampus.umn.edu/
Energy Modeling Methodology wouldn’t have been pos-
sible without the collaborative efforts of multiple organiza-
tions and individuals.
The program was structured to split the student research-
er’s time between the classroom and the office. Christo-
pher Wingate spent 10 hours per week conducting research
for academic credit under the guidance of faculty advi-
sor Blaine Brownell and an additional 15 hours per week
at Meyer Scherer & Rockcastle. Research completed at
MS&R was overseen by Thomas Meyer, founding princi-
pal, and counted for IDP credit.1 A team of MS&R profes-
sionals also provided weekly feedback on the progress of
the project. Katherine Edwards, an energy simulation en-
gineer from KFI, collaborated on portions of the research.
Energy Modeling Methodology was also informed by
Christopher Wingate’s position as a teaching assistant for
Thermal and Luminous Design, a graduate studio focused
on sustainable design through energy modeling.2 The
teaching position ran concurrently with the work/study
program.
Firms that participate in the work/study program receive
a strong return on their investment. During this study,
MS&R invested 301 hours of its time into the program. It
benefited from an additional 259 hours funded by the Uni-
versity of Minnesota. In a business climate that makes re-
search and development difficult, this work/study program
enables firms to push the profession forward by leveraging
the resources and expertise of the University of Minnesota.
PROJECT TIMELINE AND HOURS WORKED
PROJECT TIMELINE
JAN
UA
RYFEBRU
ARY
MA
RC
HA
PRIL
MAY
JUN
EJU
LY
ACADEMIC HOURSPROFESSIONAL HOURS
110%
224%
36%4
36%
512%
612%
Chart Title
ACADEMIC259 hours
MS&R301 HOURS
KFI74
HOURS WORKED BY INSTITUTION
Chris Wingate, U of M Student Researcher
Chris Wingate, U of M Teaching Assistant
Blaine Brownell, U of M Faculty Advisor
MS&R Energy Modeling Team
Katherine Edwards, KFI Engineer
Chris Wingate, MS&R Student Researcher
66
38
75
74
155
Combined Total Hours Spent on the Project 634
226
KEY RESEARCH HOURS
The horizontal lines of the graph split each month into four representative weeks. Each person’s
weekly hours are represented additively at these intersections. The height of the highest peak or
valley at each week represents the total hours worked by all people on the project. Individual
weekly hours are read by measuring the difference between the peak of the category and the
peak directly below it.
HOURS WORKED BY INDIVIDUAL
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
COMPARING ENERGY MODELING SOFTWARE : EQUEST AND IES VE
Energy Modeling Methodology development began by
choosing an energy modeling software. When the research
project started, MS&R had already narrowed its search
for an energy modeling program down to eQUEST by the
Department of Energy and IES VE by Integrated Environ-
mental Solutions.1,2 MS&R initially wanted to use energy
modeling at the beginning of the design process to help in-
form conceptual and schematic design decisions, so a set
of selection criteria was developed with that goal in mind.
The criteria was based around the steps necessary to cre-
ate, analyze, and compare energy models of early concep-
tual schemes. Please see the following three pages for the
full selection criteria matrix and score comparison between
eQUEST and IES VE.
Each category in the selection criteria matrix represents a
step necessary to create an energy model or to run an energy
modeling analysis. The categories are:
1. Climate Analysis - Use the software to analyze the site’s
specific climate and its ramifications on design.
2. Design Model - Create an energy model from a design
concept .
3. Base Model - Create a baseline energy model to com-
pare performance of design options against.
4. Solar Shading - Use the software to run a shadow study.
5. Daylighting - Use an energy model to test daylighting
performance.
6. Thermal Analysis - Use energy modeling to analyze
thermal performance.
7. Conceptual Model Comparisons - Compare the perfor-
mative characteristics of multiple concept models.
The subcategories are similar across each category, analyz-
ing characteristics such as the time required to complete a
task, ease of using the software, and the graphical quality
of its output. This structure allowed the research team to
compare software in a variety of ways. By averaging the
software’s scores in each subcategory, a metric emerged that
gave a quick overview of the energy modeling program.
For example, the average score of each category’s Time Re-
quired subcategory was calculated and given the title Speed.
This metric is a score out of 5 that illustrates the amount of
time it takes to complete a given task with the software. A
higher score is always related to better performance. The
other subcategories were scored and averaged in the same
manner. The results can be seen at the bottom of the selec-
tion criteria in the scoring boxes labeled Speed, Ease of Use,
Data Quality, Graphics, and Workflow.
The scores were also tallied for each category. The overall
scores for each software were calculated in the box labeled
Total Score.
IES VE received a higher total score than eQUEST. It also
outscored eQUEST in every subcategory, with the largest
margins in Graphics and Workflow. This is due to IES VE
being designed and marketed to architects as well as en-
gineers. Although both software platforms will accurately
model the energy performance of a building, IES VE is de-
signed with visual thinkers in mind, emphasizing the ability
to create spatially complex three dimensional energy mod-
els and run graphically rich analyses.
After scoring the software, the research team created an-
other matrix that highlighted the selection criteria that most
heavily impacted a software’s ability to influence early de-
sign decisions. We found that the most important aspect of
a successful energy model was its ability to match the three
dimensional qalities of the design concept. The process of
creating an energy model always involves simplifying a de-
sign model, but a successful energy model will still retain
the feel of the design intent, convincing the design team
that the architecture is actually shaping the energy model’s
performance. IES VE uses a Sketchup plugin to create its
energy models, giving architects the ability to easily capture
the volumetric intent of their designs. By contrast, eQUEST
creates an energy model by tracing over an AutoCAD draw-
ing, extruding floor plans, and controlling other geometric
elements with spreadsheet-based parameters. This severs
the connection between design intent and energy analysis,
inturrupting the feedback loop necessary to turn analytical
tests into generative project ideas.
1. eQUEST, doe2.com/equest
2. IES VE, www.iesve.com
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
0
20
22
27
1926
2511
1018
2528
25 24SPEED EASE OF USE DATA QUALITY GRAPHICS WORKFLOW TOTAL SCORE
2.32.34.53.74.0 117SPEED EASE OF USE DATA QUALITY GRAPHICS WORKFLOW TOTAL SCORE
3.74.24.74.04.1 161ENERGY MODELING SOFTWARE COMPARISON
Climate Analysis
Ease of Use
Time Required
Graphical Output
Quality of Data
Climate-Specific Design Strategies Included
File Import / Export Options
Base Model
Ease of Use
Time Required
Graphical Output
Quality of Data
Base Model Helps Understand Effects of Design Options
File Import / Export Options
Concept Model Studies
Ease of Use
Time Required
Graphical Output
Quality of Data
Strength of Link Between Actual Design and Design Model
File Import / Export Options
Daylighting
Ease of Use
Time Required
Graphical Output
Quality of Data
Ability to Test a Design’s Affect on Daylighting Levels
File Import / Export Options
Design Model
Ease of Use
Time Required
Graphical Output
Quality of Data
File Import / Export Options
Solar Shading
Ease of Use
Time Required
Graphical Output
Quality of Data
Integration of Solar Shading with Thermal Analysis
File Import / Export Options
Thermal Analysis
Ease of Use
Time Required
Graphical Output
Quality of Data
Accuracy Compared to Other Accepted Modeling Programs
File Import / Export Options
IES VEeQUEST
Category Averages and Total Score
Score Notes
0
0
0
0
0
0
5
5
5
3
3
5
5
4
3
3
3
2
3
1
3
1
1
1
3
5
3
1
1
5
3
4
4
3
3
5
5
4
3
3
5
5
3
5
2
4
3
Clear, concise results.
Five minutes.
Three simple graphs combine key information.
Included data gives great overview, but not enough for detailed analysis.
A few basic climate-specific design strategies are included, but other tools outperform it.
Graphics can only be exported as image files, not vectors.
4
2
4
0
0
1
4
5
4
5
4
5
3
5
4
3
5
5
5
5
5
4
4
5
3
5
3
5
4
5
5
3
3
4
3
After you have a fully defined design model, it automatically matches a base model to it.
Five minutes, after you have a fully defined design model.
None .
The only data included is kBTU / square foot.
Base model is automatically created, but its data is severely limited.
None.
Creating geometry is very easy. Geometry and building data can be defined in Sketchup.
One hour per massing study to model. Four additional hours to analyze.
Analysis results are graphically rich, but can only be exported as image files.
You can run the full suite of analyses on massing models once they are in IES.
Massing model geometry is imported from sketchup. Easy workflow.
You have to get the geometry into IES through Sketchup. Can’t import directly from Rhino.
10 minutes to 12 hours depending on quality settings.
Results can be viewed in a number of formants including contours, perspectives, etc.
Full suite of daylight analysis tools available including the very accurate Radiance engine.
Daylighting levels can be analyzed in plan, section, and perspective renderings.
Geometry must come into IES from Sketchup. Graphic output limited to image files.
Once shades are in, they can be accounted for in all daylight and thermal analyses.
Thirty minutes. Shading devices modeled in Sketchup, so creation is fast.
Analysis results are graphically rich, but can only be exported as image files.
IES models the impact of shading accurately.
IES models the impact of shading on daylight and thermal analyses accurately.
Shading geometry imported from Sketchup. Graphic output limited to image files.
Geometry is imported from sketchup. Assigning model data can be overwhelming at first.
Two to four hours to create geometry. Four to eight hours to assign model data.
Analysis results are graphically rich, but can only be exported as image files.
Full suite of analyses available once model is defined in IES.
Creating geometry in sketchup allows for strong 3D correlation between idea and model.
Design model geometry is imported from sketchup. Easy workflow.
Scheduling and HVAC systems input is complicated without help from M/E consultant.
Ten to sixty minutes depending on complexity of model.
Analysis results are graphically rich, but can only be exported as image files.
Output a bevy of graphs and raw data. Highly accurate with correct HVAC systems.
IES with APACHE HVAC module is highly accurate. Without module it is inaccurate.
HVAC systems must be manipulated in IES.
Geometry must be traced from AutoCAD plans. Wizard for inputting model data.
One hour per massing study to model. Two additional hours to analyze.
Charts and graphs are easy to create but somewhat limited in scope.
Can quickly compare design options by looking at key energy use metrics. No daylighting.
Model is simplistic 3D extrusion of AutoCAD. Doesn’t feel like the design at all.
Must retrace AutoCAD drawings to create model. Graphical output is image file only.
No separate daylight analysis included, although daylighting does affect thermal analysis.
No separate daylight analysis included, although daylighting does affect thermal analysis.
Must view daylight as a potential energy savings strategy (lower lighting load).
Daylighting levels can not be simulated, only how daylight affects energy performance.
No way to view daylighting levels.
None. Daylighting analysis is turned on via a check box.
Shading devices must be defined via text inputs for each opening.
Add an extra two hours to modeling process.
Must view effects of shading as a potential energy savings strategy (lowered cooling load).
eQUEST is considered an accurate modeling program.
eQUEST accurately simulates the effects of shading on energy use.
None. Shading is defined via text inputs for each opening.
Modeling is tedious. Inputting model data is made easier by wizard and smart presets.
Two to four hours to create geometry. Four to eight hours to assign model data.
Results displayed in simplistic charts and graphs. No plan overlays or 3D views available.
Energy use and ROI feedback is accurate. Daylighting studies not available.
Must retrace AutoCAD drawings to create model. Graphical output is image file only.
Scheduling an HVAC systems input is helped by a wizard and smart default settings.
Five to thirty minutes depending on complexity of model.
Charts and graphs clearly illustrate impacts of design options, but aesthetically lacking.
eQUEST is an acceptable energy modeling software for a variety of certification programs.
eQUEST is an acceptable energy modeling software for a variety of certification programs.
HVAC systems must be manipulated in eQUEST.
Base model is created automatically.
Base model is created automatically.
Base model has same graphical output as the design model. Simplistic charts and graphs.
The automatically created base model has the same functionality as your design model.
Base and design models have same functionality. Can be seamlessly compared.
Created automatically, so same import/export problems as the design model.
Not available.
Not available.
Not available.
Not available.
Not available.
Not available.
Strength of Link Between Actual Design and Concept Model Creating geometry in sketchup allows for strong 3D correlation between idea and model.5
Score Notes
2 Model is simplistic 3D extrusion of AutoCAD. Doesn’t feel like the design at all.
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
0
20
22
27
1926
2511
1018
2528
25 24SPEED EASE OF USE DATA QUALITY GRAPHICS WORKFLOW TOTAL SCORE
2.32.34.53.74.0 117SPEED EASE OF USE DATA QUALITY GRAPHICS WORKFLOW TOTAL SCORE
3.74.24.74.04.1 161ENERGY MODELING SOFTWARE COMPARISON
Climate Analysis
Ease of Use
Time Required
Graphical Output
Quality of Data
Climate-Specific Design Strategies Included
File Import / Export Options
Base Model
Ease of Use
Time Required
Graphical Output
Quality of Data
Base Model Helps Understand Effects of Design Options
File Import / Export Options
Concept Model Studies
Ease of Use
Time Required
Graphical Output
Quality of Data
Strength of Link Between Actual Design and Design Model
File Import / Export Options
Daylighting
Ease of Use
Time Required
Graphical Output
Quality of Data
Ability to Test a Design’s Affect on Daylighting Levels
File Import / Export Options
Design Model
Ease of Use
Time Required
Graphical Output
Quality of Data
File Import / Export Options
Solar Shading
Ease of Use
Time Required
Graphical Output
Quality of Data
Integration of Solar Shading with Thermal Analysis
File Import / Export Options
Thermal Analysis
Ease of Use
Time Required
Graphical Output
Quality of Data
Accuracy Compared to Other Accepted Modeling Programs
File Import / Export Options
IES VEeQUEST
Category Averages and Total Score
Score Notes
0
0
0
0
0
0
5
5
5
3
3
5
5
4
3
3
3
2
3
1
3
1
1
1
3
5
3
1
1
5
3
4
4
3
3
5
5
4
3
3
5
5
3
5
2
4
3
Clear, concise results.
Five minutes.
Three simple graphs combine key information.
Included data gives great overview, but not enough for detailed analysis.
A few basic climate-specific design strategies are included, but other tools outperform it.
Graphics can only be exported as image files, not vectors.
4
2
4
0
0
1
4
5
4
5
4
5
3
5
4
3
5
5
5
5
5
4
4
5
3
5
3
5
4
5
5
3
3
4
3
After you have a fully defined design model, it automatically matches a base model to it.
Five minutes, after you have a fully defined design model.
None .
The only data included is kBTU / square foot.
Base model is automatically created, but its data is severely limited.
None.
Creating geometry is very easy. Geometry and building data can be defined in Sketchup.
One hour per massing study to model. Four additional hours to analyze.
Analysis results are graphically rich, but can only be exported as image files.
You can run the full suite of analyses on massing models once they are in IES.
Massing model geometry is imported from sketchup. Easy workflow.
You have to get the geometry into IES through Sketchup. Can’t import directly from Rhino.
10 minutes to 12 hours depending on quality settings.
Results can be viewed in a number of formants including contours, perspectives, etc.
Full suite of daylight analysis tools available including the very accurate Radiance engine.
Daylighting levels can be analyzed in plan, section, and perspective renderings.
Geometry must come into IES from Sketchup. Graphic output limited to image files.
Once shades are in, they can be accounted for in all daylight and thermal analyses.
Thirty minutes. Shading devices modeled in Sketchup, so creation is fast.
Analysis results are graphically rich, but can only be exported as image files.
IES models the impact of shading accurately.
IES models the impact of shading on daylight and thermal analyses accurately.
Shading geometry imported from Sketchup. Graphic output limited to image files.
Geometry is imported from sketchup. Assigning model data can be overwhelming at first.
Two to four hours to create geometry. Four to eight hours to assign model data.
Analysis results are graphically rich, but can only be exported as image files.
Full suite of analyses available once model is defined in IES.
Creating geometry in sketchup allows for strong 3D correlation between idea and model.
Design model geometry is imported from sketchup. Easy workflow.
Scheduling and HVAC systems input is complicated without help from M/E consultant.
Ten to sixty minutes depending on complexity of model.
Analysis results are graphically rich, but can only be exported as image files.
Output a bevy of graphs and raw data. Highly accurate with correct HVAC systems.
IES with APACHE HVAC module is highly accurate. Without module it is inaccurate.
HVAC systems must be manipulated in IES.
Geometry must be traced from AutoCAD plans. Wizard for inputting model data.
One hour per massing study to model. Two additional hours to analyze.
Charts and graphs are easy to create but somewhat limited in scope.
Can quickly compare design options by looking at key energy use metrics. No daylighting.
Model is simplistic 3D extrusion of AutoCAD. Doesn’t feel like the design at all.
Must retrace AutoCAD drawings to create model. Graphical output is image file only.
No separate daylight analysis included, although daylighting does affect thermal analysis.
No separate daylight analysis included, although daylighting does affect thermal analysis.
Must view daylight as a potential energy savings strategy (lower lighting load).
Daylighting levels can not be simulated, only how daylight affects energy performance.
No way to view daylighting levels.
None. Daylighting analysis is turned on via a check box.
Shading devices must be defined via text inputs for each opening.
Add an extra two hours to modeling process.
Must view effects of shading as a potential energy savings strategy (lowered cooling load).
eQUEST is considered an accurate modeling program.
eQUEST accurately simulates the effects of shading on energy use.
None. Shading is defined via text inputs for each opening.
Modeling is tedious. Inputting model data is made easier by wizard and smart presets.
Two to four hours to create geometry. Four to eight hours to assign model data.
Results displayed in simplistic charts and graphs. No plan overlays or 3D views available.
Energy use and ROI feedback is accurate. Daylighting studies not available.
Must retrace AutoCAD drawings to create model. Graphical output is image file only.
Scheduling an HVAC systems input is helped by a wizard and smart default settings.
Five to thirty minutes depending on complexity of model.
Charts and graphs clearly illustrate impacts of design options, but aesthetically lacking.
eQUEST is an acceptable energy modeling software for a variety of certification programs.
eQUEST is an acceptable energy modeling software for a variety of certification programs.
HVAC systems must be manipulated in eQUEST.
Base model is created automatically.
Base model is created automatically.
Base model has same graphical output as the design model. Simplistic charts and graphs.
The automatically created base model has the same functionality as your design model.
Base and design models have same functionality. Can be seamlessly compared.
Created automatically, so same import/export problems as the design model.
Not available.
Not available.
Not available.
Not available.
Not available.
Not available.
Strength of Link Between Actual Design and Concept Model Creating geometry in sketchup allows for strong 3D correlation between idea and model.5
Score Notes
2 Model is simplistic 3D extrusion of AutoCAD. Doesn’t feel like the design at all.
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
IES VEeQUEST
While comparing eQuest and IES VE, the research team
concluded that one of the most important aspects of an en-
ergy modeling software is its ability to create a model that
matches the three dimensional intent of the design. The
images on the right show the considerable differences be-
tween the programs’ approach to modeling.
eQuest creates a model by tracing and extruding masses
from an autoCAD plan. Other geometric information, like
pitched rooves and glazing, is controlled by check boxes.
The final model resembles an extruded box, modified by
spreadsheet-like inputs. Complex sectional characteristics
are impossible to capture.
IES VE uses a Sketchup plugin to create its energy models.
This allows designers to accurately represent the design in-
tent in their energy models. The 3D model is able to cap-
ture complex geometry, important sectional characteristics,
and the intent of the design, building confidence that the
energy model actually responds to changes in the archi-
tecture. This is the number one reason why IES VE was
chosen over eQuest as MS&R’s energy modeling software.
EQUEST AND IES VE COMPARISON - CREATING AN ENERGY MODEL IN EQUEST AND IES VE
MODELING IN EQUEST AND IES VE
Source Drawing - AutoCAD Source Drawing - AutoCAD or Revit
Creating Rooms - Tracing Plans Creating Rooms - Extruding Plans
Modeling Roof - Check Box Modeling Roof - 3D Geometry
Final Model - Simple Box Final Model - Complex Geometry
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
INTEGRATED ENERGY DESIGN
CLIMATE CHANGE AND THE IMPACT OF THE BUILT ENVIRONMENT
Climate change. Global warming. Extreme weather. These
themes seem to dominate news headlines as humanity’s im-
pact on the planet shifts from scientific theory to a force
that can be experienced first hand with increasing frequen-
cy. From the destruction of coral reefs to the shrinking of
the world’s glaciers, it is clear that our climate is changing.
The scientific community is in agreement that humanity is
causing the change, and carbon dioxide is our weapon of
choice. As we pump CO2 into the atmosphere by burning
fossil fuels, it acts as a “greenhouse” gas, trapping the sun’s
heat in our atmosphere and leading to a gradual increase
in the Earth’s temperature. Scientists predict this will have
dire consequences including rising sea levels, the increasing
frequency of severe weather, drought, and a massive destruc-
tion of ecosystems across the globe. It is time for humanity
to act, and the built environment is poised to play a pivotal
role in redefining our relationship with climate.
Architecture 2030 sums up the important role the built en-
vironment has to play in the fight against climate change on
its website:1
“Problem: The Building Sector
Solution: The Building Sector”
Architecture 2030 explains that the building sector con-
sumes nearly half of all energy produced in the United
States. It was also responsible for 46.7% of U.S. CO2 emis-
sions in 2010. To make matters worse, building sector en-
ergy consumption and CO2 emissions are projected to rise
faster than any other source between now and 2030.
The graph U.S. Energy Consumption by Subdivided Sector
shows that the vast majority of energy use attributed to the
building sector is used to operate buildings. This includes
all the energy needed to heat, cool, and light buildings over
their life spans. For an even clearer illustration on how op-
erating buildings impacts energy use, look at the graph U.S.
Electricity Consumption By Sector; a full 75% of the elec-
tricity used in the U.S. goes into operating buildings.
If architects design buildings that are more energy efficient,
we can drastically reduce the energy demands of the planet
and slow the pace of global warming. With enough down-
ward pressure, we can even reach carbon neutrality. So
what are these targets and what does it take to get there?
Architecture 2030 provides a guideline.
1. Architecture 2030. www.architecture2030.org U.S. ELECTRICITY CONSUMPTION BY SECTOR1
U.S. ENERGY CONSUMPTION BY SECTOR1
U.S. ENERGY CONSUMPTION BY SUBDIVIDED SECTOR1
“WE TEND TO RUSH TOWARD THE COMPLEX WHEN TRYING TO SOLVE A DAUNTING PROBLEM, BUT IN THIS CASE, SIM-
PLICITY WINS. BETTER BUILDINGS, RESPONSIBLE ENERGY USE AND RENEWABLE ENERGY CHOICES ARE ALL WE NEED TO
TACKLE BOTH ENERGY INDEPENDENCE AND CLIMATE CHANGE.”
- Edward Mazaria, Architect and founder of Architecture 2030
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
1. Architecture 2030. www.architecture2030.org
Architecture 2030 is optimistic about the positive impact
the built environment can have on reducing domestic energy
use over the next twenty years. It points to the projection
that by 2035, approximately 75% of the built environment
will be either new or renovated.1 Architecture 2030 calls
for architects to seize this opportunity, challenging them to
design each new or renovated building to meet ever increas-
ing energy targets, leading us to carbon neutrality by 2030.
Architecture 2030 developed its energy reduction targets
by working backward from the greenhouse gas emissions
reductions scientists predicted were necessary to reach by
2050 to avoid catastrophic climate change. In an interview
with BLDG BLOG, Ed Mazaria explains, “Working back-
wards from those reductions, and looking at, specifically,
the building sector – which is responsible for about half of
all emissions – you can see what we need to do today. We
need an immediate, 50% reduction in fossil fuel, greenhouse
gas-emitting energy in all new building construction. And
since we renovate about as much as we build new, we need
a 50% reduction in renovation, as well. If you then increase
that reduction by 10% every five years – so that by 2030 all
new buildings use no greenhouse gas-emitting fossil fuel en-
ergy to operate – then you reach a state that’s called carbon
neutral. And you get there by 2030. That way we meet the
targets that climate scientists have set out for us.”1
Meeting these targets requires the design of more energy
efficient buildings, the development of new building tech-
nologies and systems, and the implementation of renewable
energy sources. Of these categories, it is building design
that can have the greatest impact on energy reductions. It is
design that will create buildings that are in tune with their
natural environments and harvest the local climate to con-
dition their interiors, resulting in a more efficient, and more
appealing, built environment.
Environmentally sensitive designs require an environmen-
tally sensitive design approach, one that seeks to understand
the climate at the outset of the process, collaborates with the
entire design team on sustainable strategies, and adopts the
tools necessary to test and develop them into sustainable ar-
chitecture. Integrated Energy Design shows what this new
process might look like.
ARCHITECTURE 2030 - A ROAD MAP TO RECOVERY
MEETING THE 2030 CHALLENGE1
COMPOSITION OF THE BUILDING SECTOR BY 20351
ARCHITECTURE 2030 FOSSIL FUEL ENERGY REDUCTION TARGETS1
“THE MAJOR PART [OF A BUILDING’S ENERGY USE] - 40% - IS DESIGN. EVERY TIME WE DESIGN A BUILDING, WE SET UP ITS
ENERGY CONSUMPTION PATTERN AND ITS GREENHOUSE GAS EMISSIONS PATTERN FOR THE NEXT 50-100 YEARS. THAT’S
WHY THE BUILDING SECTOR AND THE ARCHITECTURE SECTOR IS SO CRITICAL. IT TAKES A LONG TIME TO TURN OVER.”
- Edward Mazaria, Architect and founder of Architecture 2030
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
“AN INTEGRATED DESIGN MIGHT BEGIN WITH THE REDUCTION OF HEAT LOADS IN THE OCCUPIED SPACE THROUGH
THE USE OF ENERGY-EFFICIENT LIGHTING FIXTURES AND DAY LIGHTING. THAT MAY MAKE IT POSSIBLE TO REDUCE SUP-
PLY-AIR FLOW RATES, LEADING TO LESS PRESSURE DROP IN THE AIR-DISTRIBUTION SYSTEM AND ALLOWING FOR SMALLER
FANS TO BE INSTALLED. FURTHER, AS A RESULT OF ALL OF THOSE DOWNSTREAM CHANGES, IT MAY ALSO BE POSSIBLE TO
SPECIFY A SMALLER COOLING PLANT.”
- Energy Design Resources
1. Integrated Energy Design, Energy Design Resources, www.energydesignresources.com
Meeting the Architecture 2030 challenge requires rethinking
how a project is delivered, bringing together owners, design-
ers, and consultants to work towards creating sustainable
and energy efficient buildings. Integrated Energy Design,
a process developed by Energy Design Resources, outlines
how to accomplish that.1 Of the process’s six steps, the first
three provide the strongest guidance for our Energy Model-
ing Methodology.
1. Plan for energy efficiency right from the beginning of
the design process.
The diagram on the right illustrates that the greatest po-
tential to affect the energy use of a building occurs at the
beginning of the design process. As the design continues,
decisions are locked into place, making changes difficult.
Therefore, it is imperative that planning for energy efficien-
cy is implemented from the start.
2. Identify integrated design strategies that will reduce life-
time costs while also improving occupant comfort.
Energy Design Resources gives an example of why integrat-
ed design strategies are so effective. “An integrated design
might begin with the reduction of heat loads in the occu-
pied space through the use of energy-efficient lighting fix-
tures and daylighting. That may make it possible to reduce
supply-air flow rates, leading to less pressure drop in the
air-distribution system and allowing for smaller fans to be
installed. Further, as a result of all of those downstream
changes, it may also be possible to specify a smaller cooling
plant.”2 This process can result in energy savings, cost sav-
ings, and increased occupant comfort.
3. Run whole-system analyses that treat a building as a
complete system, taking into account the interactions
among all of the building’s systems.
According to Energy Design Resources, “Whole-systems
analysis is an evaluative process that treats a building as
a series of interacting systems instead of looking at build-
ing systems as individual components that function in iso-
lation.” It takes a specialized tool to run a whole-systems
analysis, and that tool is energy modeling. In order to de-
liver more sustainable buildings, we need to redefine our de-
sign process, planning for energy efficiency from the start,
developing integrated sustainable design strategies, using
energy modeling to analyze building performance.
INTEGRATED ENERGY DESIGN
Prog
ram
min
g
Phase of design process
Sche
mat
icde
sign
Des
ign
deve
lopm
ent
Cons
truc
tion
Cons
truc
tion
docu
men
ts
Occ
upan
cy
Level ofdesign e�ort
Potentialcost-e�ective
energy savings
Source: ENSAR Group and E SOURCE
Energy-saving opportunities and the design sequenceFigure 1:
ENERGY SAVING OPPORTUNITIES AND THE DESIGN SEQUENCE1
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
In 27 BC, Vitruvius wrote a definition of architecture that
is still relevant. He wrote that architecture must exhibit
three qualities - firmness, commodity, and delight. Firm-
ness is concerned with structure and construction systems;
commodity is related to function, program, and budget; and
delight describes the beauty, aesthetics, and emotional im-
pact of a building.
A cornerstone of Energy Modeling Methodology is that
building performance is viewed as an integral part of archi-
tecture. Energy modeling doesn’t reside outside of the design
process, it is used to enhance architecture’s core qualities.
Designing for energy performance is a natural extension of
the Vitruvian Triangle. The emotional impact of a building
is enhanced by optimizing its use of natural daylight, archi-
tecture’s environmental impact should be considered just as
its function, program, and budget are, and energy perfor-
mance directly effects a building’s structure and materiality.
Integrated energy modeling into the design process enhances
a design team’s ability to understand the issues that affect a
project, fully explore the impact of their design on architec-
ture’s core qualities, and deliver a richer, more sustainable
final project.
VITRUVIUS REDEFINED
THE VITRUVIAN TRIANGLE REDEFINED - USING ENERGY MODELING TO ENHANCE DESIGN
Firmness
Com
modity D
eligh
t
Architecture
Beau
tyA
esth
etics
Emot
iona
l Im
pact
Construction Systems
Materiality
Structure
Function
Program
Budget
Firmness
Com
modity D
eligh
tBe
auty
Aes
thet
icsEm
otio
nal I
mpa
ctD
aylig
ht
Energy Performance
Construction Systems
Materiality
Structure
Function
Program
Budget
Environmental Im
pact
THE VITRUVIAN TRIANGLE
AN ANCIENT ROMAN ARCHITECT NAMED VITRUVIUS
WROTE THAT A BUILDING MUST BE CONSIDERED “WITH
REFERENCE TO FUNCTION, STRUCTURE, AND BEAUTY.”
...THINK OF THE VITRUVIAN FACTORS AS THE LEGS OF A
TRIPOD CALLED ARCHITECTURE. NONE CAN STAND
ALONE; EACH IS DEPENDENT UPON THE OTHER TWO TO
FORM THE WORK OF ARCHITECTURE.1
- James O’Gorman, from ABC of Architecture.
Architecture
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
1. Tom Fisher, Lecture, September 2010, University of Minnesota College of Design
Before we can push the design process forward, we must first
understand the thought process that powers it. Thomas Fisher,
Dean of the University of Minnesota’s College of Design, dia-
grammed how design thinking was distinct from problem solving
in a 2011 lecture to his Principles of Design Theory class.
Deductive and inductive reasoning are two types of problem
solving. Throughout their academic lives, students are taught
the value of linear thought processes, training them to search for
one correct solution to a given problem. Deductive reasoning
is more commonly known as the scientific method. It involves
making a hypothesis, running experiments to test the hypothesis,
and evaluating the resulting evidence to determine if it is correct.
Inductive reasoning works in reverse; a person makes an array of
observations, constructs generalizations that connect the obser-
vations, and arrives at a conclusion when a generalized statement
can be used to explain the entire set of observations. Although
these processes are useful, it is important to realize that they will
only lead to solutions that lay in the original field of inquiry.
These processes explain existing phenomena, they do not create
new phenomena.
Creativity is powered by design thinking, a decidedly non-linear
process. Design thinking involves addressing a problem by look-
ing at a multitude of issues that define it and using them to gener-
ate and explore new avenues of possibility. Some discoveries will
push the process forward while others will cause the designer to
take a step back, revisiting prior assumptions. Still others will
redefine the original problem all together, generating a unique
trajectory of their own. It is precisely design thinking’s chaotic,
non-linear nature that enables it to create in innovative discover-
ies. Architecture is very much a product of design thinking.
DESIGN THINKING1
DESIGN THINKING EVOLVED
INDUCTIVE REASONING1
CONCLUSIONS
GENERALIZATIONS
FACTS, EVIDENCE,
OBSERVATIONS
HYPOTHESIS
EXPERIMENTS
DATA COLLECTION,
EVIDENCE, OBSERVATIONS
DEDUCTIVE REASONING1
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
While non-linear design thinking powers creative innova-
tion, architects must also inhabit the linear world of the
design process to deliver a project. Energy modeling exists
in this overlap, acting as a catalyst to help architects make
informed decisions at each stage of development, leading
to projects that can meet the Architecture 2030 challenge.
The creative process by its very nature pulls inspiration
from a variety of sources, ensuring that the final result of
a design, as well as the criteria used to judge it, will be
unique. It is usually the architect’s own narrative that is
used to test the merit of early conceptual development.
As a project progresses, the design must meet a variety of
other demands, from structural loads to fire safety require-
ments. Energy performance should be thought of in the
same way; the conceptual intent of a design must be bal-
anced against given performance standards to improve the
quality of the project. Energy modeling should be used at
each stage of design to ensure energy performance and sus-
tainability are addressed throughout the process.
Over time, this enhanced design process will result in ac-
cumulated sustainable expertise within the office. Energy
modeling reacts to the specifics of a project, but the sustain-
able strategies it points to can be abstracted and digested
as new and improved rules of thumb. Future designs will
start from an ever-more informed position, improving
the sustainability and energy efficiency of each successive
building.
DESIGN PROCESS AND ENERGY MODELING
DESIGN PROCESS AND ACCUMULATED EXPERTISE FROM ENERGY MODELING
DESIGN PROCESS WITH ENERGY MODELING
DESIGN PROCESS
DESIGNDEVELOPMENT
SCHEMATICDESIGNCONCEPT
CONSTRUCTIONDOCUMENTS
ENER
GY
MO
DEL
ING
ENER
GY
MO
DEL
ING
ENER
GY
MO
DEL
ING
ENER
GY
MO
DEL
ING
ACCUMULATED EXPERTISE FROM ENERGY MODELING
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
REVITSKETCHUP
RHINO
RHINO
SKETCHUP
IES VE
INDESIGN
3D PRINTER
VRAY
PHOTOSHOP
PHYSICALMODEL
VRAY
PHOTOSHOP
INDESIGN
ILLUSTRATOR
AUTOCAD
TOOLS OF DESIGN
DESIGN STUDY TOOLS AND WORKFLOW
DO
CU
MEN
TAT
ION
VIS
UA
LIZ
ATIO
N
AN
ALY
SIS
DES
IGN
MO
DEL
DESIGN THINKING
DesignStudy
DesignStudy Design
Study
DesignStudy
REVIT
DESIGN STUDY - THE MOLECULE OF DESIGN THINKING
PRIM
ARY
MO
DEL
Architectural offices must accept that there is no single
piece of software that consolidates all of the functional-
ity necessary to create and execute a design. Rather, firms
must work with a collection of tools, developing a work-
flow that matches the character of the office.
The diagram on the right maps the software tools and
workflow patterns MS&R uses during design studies. The
studies themselves are the building block of the design pro-
cess. Each study uses the project’s current state as input,
explores the design, and creates output that can inform the
project and spark the next study.
MS&R uses Revit as its primary modeling software and
treats Rhino and Sketchup as design models. Design mod-
els can be thought of as digital sketches; the software en-
ables quick explorations of ideas. However, much like a
sketch can’t inform the project until it leaves the design-
er’s desk and is shared with the team, the results of design
models don’t become fully interwoven into the project until
they are deposited into Revit.
Energy modeling software enables MS&R to analyze the
performance of design studies. IES VE uses Sketchup to
create the 3D geometry for the energy model. It is not
possible to import Rhino geometry directly into IES VE,
however Sketchup can be used to translate Rhino geometry
and then export it to IES VE.
MS&R’s software and workflow fosters collaboration
within a design team while still allowing for individual cre-
ative freedom.
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
MS&R uses a variety of software throughout the design
process. Design Phases and Software Implementation il-
lustrates when and how each software is used. The dia-
gram also shows the weighted emphasis of the software at
each stage of design. Rhino, Grasshopper, and Sketchup
are used heavily in the beginning of the process, leveraging
the ability of the software to quickly model and explore
multiple concepts. Revit is integrated throughout, building
up the digital model as the design progresses. Once the
Construction Documents phase is reached, the majority of
digital modeling occurs within the detailed Revit model.
Energy modeling is used during every phase, but it has the
greatest impact on design at the beginning of the process.
It is used during Concept and Schematic Design to analyze
the climate and test the performance of early design stud-
ies, helping inform and improve design decisions.
Energy modeling has long been thought of as too compli-
cated and specialized to be utilized in the design process
effectively. Viewing it alongside other design software puts
it in perspective; it is simply another tool that helps address
a specific set of decisions that must be made during the
design process. Effective implementation of energy model-
ing allows design teams to address a wider scope of issues,
improving design decisions and ultimately the performance
of the building itself.
DESIGN PHASES AND TECHNOLOGY
DESIGN PHASES AND SOFTWARE IMPLEMENTATION
DESIGNDEVELOPMENT
SCHEMATICDESIGNCONCEPT
CONSTRUCTIONDOCUMENTS
CONSTRUCTIONADMINISTRATION
BUIL
DIN
G IN
FOR
MAT
ION
MO
DEL
ING
Zoning Analysis
Program Studies
Existing Conditions
Quantity Analysis
Test Fit Program
Program Refinement
Prelim. Systems Definition
Prelim. Systems Integration
Infrastructure Identification
Final Systems Definitions
System Integration
Typical Details
Door / Finish Schedules
Coordination
Quantity Analysis
Final Systems Integration
Final Design Development
Construction Sequencing
Atypical Details
Contract Documents
RFI’s
Supplemental Sketches
Construction Sequencing
Share Model with Engineer
Prelim. Daylight Analysis
Prelim. Thermal Analysis
Share Model with Engineer
Detailed Daylight Analysis
Detailed Thermal Analysis
Share Model with Engineer
Regulatory Compliance Model
Climate Analysis
Initial Daylight Analysis
Initial Shadow Studies
Massing and Energy Use
Glazing Percentage Studies
Concept Comparison
Multiple Schemes
Site Analysis
Existing Conditions
Massing Studies
Spatial Quality
3D Printed Models
Design Options
Model Complex Geometry
Visualization
Design Options
Model Complex Geometry
Visualization
Model Complex Geometry
3D Detailing
RH
INO
GR
ASS
HO
PPER
SKET
CH
UP
DIG
ITA
L SK
ETC
HIN
G
REV
ITM
AIN
MO
DEL
IES
VE
ENER
GY
MO
DEL
NEWFORMA
ADOBE CS5SUPP
LEM
ENTA
L CLIMATE CONSULTANT Climate Analysis
Communication Management
Presentation
Communication Management
Presentation, Rendering
Communication Management
Presentation, Rendering
Information Management
Presentation
RFI’s, Info Management
Weighted Emphasis of Software
Light heavy
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
The inputs that go into an energy model are common
across all software packages. The modeling software
combines climate data with information about the build-
ing form, construction types, occupancy types, occupancy
loads, building systems, and building system schedules to
analyze the energy use of the building.
These inputs can be broken into categories by looking at
whether the architect or engineer is responsible for them
during the design process. Climate is a given condition
directly related to the project’s site. Building form, con-
struction types, and occupancy types are controlled by the
architect’s programming and design. Occupancy loads,
building systems, and building systems schedules are in the
engineer’s domain.
An energy model can be represented as a stacked set of
inputs. When each input is defined with project specific in-
formation, the model will be at its most accurate, as shown
in Fully Defined Energy Model.
If you don’t input project specific information into a cat-
egory, the model will instead rely on pre loaded default
settings. In this state, an energy model will still perform
analyses, it just won’t be as accurate as a model that has
been fully defined by project specific information. As each
input becomes project-specific, the results become more ac-
curate.
ENERGY MODELING INPUTS Energy ModelingInput Category
Design TeamResponsibility
ENERGY MODELING INPUTS AND DESIGN TEAM RESPONSIBILITY
1
2
34, 5
6, 7
DEFINING ENERGY MODELING INPUTS
Input Defined by Engineers
Undefined Energy Model Input(Program Default)
Key
Energy ModelClimate Data
Building Form
Construction Types
Occupancy Types
Occupancy Loads
Building Systems
Building Systems Schedules
Fully Defined Energy Model
Energy ModelClimate Data
Building Form
Construction Types
Occupancy Types
Occupancy Loads
Building Systems
Building Systems Schedules
Partially Defined Energy Model
1) Climate Data
2) Building Form
3) Construction Types
4) Occupancy Types
5) Occupancy Loads
6) Building Systems
7) Building System Schedules
Architect
Engineer
Input Defined by Architects
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
Analyze climate
Analyze site
Explore program
Identify energy budget
Identify construction budget
Identify design strategies
Create massing studies
Explore siting options
Explore design options
Initial investigation of materials
Analyze climate
Identify building systems budget
Identify systems design strategies
Develop building systems narrative
Explore building systems design options
DESIG
N D
EVELO
PMEN
TC
ON
CEPT
/ SCH
EMAT
IC D
ESIGN
COMBINE DESIGN
FINALIZE DESIGN
ARCHITECTSENGINEERS
Detailed exploration ofbuilding geometry
Detailed exploration ofconstruction systems
Detailed exploration of materials
Calculate heating, cooling, and lighting loads
Size building systems
CURRENT ENERGY MODELING TIMELINE
Currently, energy modeling, if it happens at all, occurs at
the end of design development. Engineering consultants
create an energy model by defining each input based on
the finalized design. Because the design is actually a com-
posite of decisions made during the duration of the design
process, the engineers in effect collapse a tree of decisions
made over time and turn them into energy modeling inputs.
The results of this type of energy model are an accurate
prediction of how the building will perform, but they are
an ineffective design tool. The current process places en-
ergy modeling too late in the design process, turning it into
more of an autopsy of performance rather than a genera-
tive tool to inform the design.
If we want energy modeling to be used to facilitate design
decisions, it must be implemented at the start of a proj-
ect and used throughout its duration. The following pages
diagram what this process looks like.
ENERGY MODELING TIMELINE - CURRENT PRACTICE
Energy ModelClimate Data
Building Form
Construction Types
Occupancy Types
Occupancy Loads
Building Systems
Building Systems Schedules
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
Analyze climate
Analyze site
Explore program
Identify energy budget
Identify construction budget
Identify design strategies
Create massing studies
Explore siting options
Explore design options
Initial investigation of materials
Analyze climate
Identify building systems budget
Identify systems design strategies
Develop building systems narrative
Explore building systems design options
DESIG
N D
EVELO
PMEN
TC
ON
CEPT
/ SCH
EMAT
IC D
ESIGN
COMBINE DESIGN
FINALIZE DESIGN
ARCHITECTSENGINEERS
Detailed exploration ofbuilding geometry
Detailed exploration ofconstruction systems
Detailed exploration of materials
Size building systems
Calculate heating, cooling, and lighting loads
Simulate energy use
ENERGY MODELING TIMELINE - PHASE I
Energy Modeling Timeline - Proposed Phase I shows how
to implement energy modeling at the earliest stages of de-
sign. At the beginning of a project, the design team starts
an energy model by defining Climate Data and Occupancy
Types with project-specific information. When the team
begins exploring massing and materials, they input infor-
mation about Building Form and Construction Types into
the model for different design options, running compara-
tive tests between them. At this stage, the software’s output
is accurate enough to evaluate the relative performance of
the options.
Think of relative performance testing like a concept sketch.
Concept sketches allow designers to evaluate how well dif-
ferent designs conform to the site and embody the concept,
but are understood to not initially tackle issues like ADA
accessibility and fire egress. Relative performance testing
in energy modeling is similar; it informs the designers how
different options perform against one another even though
the results are not 100% accurate.
If engineers and architects share an energy model, it can
be passed from architects to engineers as design develop-
ment begins. Energy Modeling Timeline - Proposed Phase
1 realigns the creation of an energy model more closely
with the way decisions are made during the design process.
Phase II explores the potential of sharing an energy model
during design development.
ENERGY MODELING TIMELINE - PHASE 1
Energy ModelClimate Data
Building Form
Construction Types
Occupancy Types
Occupancy Loads
Building Systems
Building Systems Schedules
Energy ModelClimate Data
Building Form
Construction Types
Occupancy Types
Occupancy Loads
Building Systems
Building Systems Schedules
Energy ModelClimate Data
Building Form
Construction Types
Occupancy Types
Occupancy Loads
Building Systems
Building Systems Schedules
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
Analyze climate
Analyze site
Explore program
Identify energy budget
Identify construction budget
Identify design strategies
Create massing studies
Explore siting options
Explore design options
Initial investigation of materials
Analyze climate
Identify building systems budget
Identify systems design strategies
Develop building systems narrative
Explore building systems design options
Detailed exploration ofbuilding geometry
Detailed exploration ofconstruction systems
Detailed exploration of materials
Size building systems
Calculate heating, cooling, and lighting loads
Official energy model for certification
DESIG
N D
EVELO
PMEN
TC
ON
CEPT
/ SCH
EMAT
IC D
ESIGN
COMBINE DESIGN
FINALIZE DESIGN
ARCHITECTSENGINEERS
Energy Modeling Timeline - Phase II illustrates the power
of sharing an energy model between architects and engi-
neers during design development. As the design progresses
and the model’s default settings are replaced by project-
specific information, the results become more accurate. In
Phase II, engineers and architects collaborate on the same
energy model, using their combined knowledge to fully de-
fine all of its inputs and ensure accurate results.
After schematic design, architects hand the model to the
engineers who fill in its inputs for occupancy loads, build-
ing systems, and building systems schedules. If the engi-
neers hand the model back to the architects, both parties
now have an energy model fully defined with project-spe-
cific information.
Equipped with a fully defined model, architects can now
fine tune a project during Design Development by using the
energy model to run iterative tests. Not only can the results
be used to test how different options for building form and
construction types perform against one another, the results
are now an accurate projection of the building’s energy use.
Both relative performance comparisons and accurate per-
formance projections are useful. By sharing an energy
model, architects and engineers can start with relative
comparisons early in the design process and work towards
accurate projections as the design is developed. This will
help the team integrate building performance into the en-
tire design process, keeping projects on track to reach Ar-
chitecture 2030’s performance goals.
ENERGY MODELING TIMELINE - PHASE II
ENERGY MODELING TIMELINE - PHASE II
Energy ModelClimate Data
Building Form
Construction Types
Occupancy Types
Occupancy Loads
Building Systems
Building Systems Schedules
Energy ModelClimate Data
Building Form
Construction Types
Occupancy Types
Occupancy Loads
Building Systems
Building Systems Schedules
Energy ModelClimate Data
Building Form
Construction Types
Occupancy Types
Occupancy Loads
Building Systems
Building Systems Schedules
Energy ModelClimate Data
Building Form
Construction Types
Occupancy Types
Occupancy Loads
Building Systems
Building Systems Schedules
Energy ModelClimate Data
Building Form
Construction Types
Occupancy Types
Occupancy Loads
Building Systems
Building Systems Schedules
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
Concept design provides an ideal opportunity for design
teams to set aggressive energy goals and leverage energy
modeling to steer projects towards them. During this
phase, designers have a great deal of flexibility in exploring
strategies to minimize energy use and maximize building
performance. At the same time, the project schedule pres-
sures the design team to be efficient in their explorations
and design recommendations. Integrating energy modeling
along with a clearly defined process will make the most out
of this opportunity by helping designers make informed
decisions.
The goal of the Energy Modeling Methodology during con-
cept design is to help inform design decisions. To achieve
this, it must be:
• Easy to use
• Able to efficiently compare design options
• Produce graphical output
A clearly defined process will help the design team utilize
energy modeling efficiently. The process should follow
these principles chronologically:
• Define energy goals
• Understand and diagram climate
• Identify possible passive and energy efficient design
strategies
• Use energy modeling to compare design options
• Interpret results holistically
SMARTER CONCEPTS
PROCESS GOAL
GUIDING PRINCIPLES
METHODOLOGY
Easy to use
Able to efficiently compare design options
Produce graphical output
Define energy goals
Understand and diagram climate
Identify passive and energy efficient design strategies
Use energy modeling to compare design options
Interpret results holistically
Help inform design decisions during concept design
CONCEPT DESIGN ENERGY MODELING METHODOLOGY
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
1. Lever House, photo by David Shankbone, Photobucket. media.photobucket.com/image/lever%20
house/HansPB/USA/Lever_House_by_David_Shankbone.jpg.
Sustainable and energy efficient buildings come in a variety
of shapes and sizes but they share one thing in common -
they respond to their local climates. Unfortunately, this is
the exception rather than the rule for today’s built environ-
ment. Beginning with the Lever House in 1952, buildings
became sealed boxes, separating themselves from climactic
considerations and instead relying on cheap energy from
fossil fuels to run HVAC systems that conditioned their in-
teriors.
Architects must reverse this trend using a design process
that embraces site sensitivity and uses passive strategies to
harness local climactic conditions. This process starts with
a thorough understanding of climate before design begins.
Two excellent tools that help a design team understand
their site’s climate and its impact on design are IES VE and
Climate Consultant. The following pages give an overview
of the tools.
CLIMATE ANALYSIS
PASSIVE DESIGN STRATEGIES FOR LAKE ITASCA BIOLOGICAL RESEARCH CENTER
LEVER HOUSE, 1952, 1ST SEALED CURTAIN WALL SKYSCRAPER 1
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
CLIMATE
Tulsa_bayStudy 00131/July/2012 at 12:46 PM INTEGRATED
ENVIRONMENTALSOLUTIONS LTD
Climate metrics
Copyright © 2012 IES Limited All rights reserved
Copyright © 2012 IES Limited All rights reserved
Copyright © 2012 IES Limited All rights reserved
Summer is potentially most dominant - the design must minimise cooling energy. Latitude is mid - solar radiation on south/east/west walls is significant. Solar radiation on roofs is significant. Summer is hot/warm. Summer also has a large diurnal range. Humidity is often greater than normal comfort limits. Winter is mild. There may be seasonal destructive storms (Hurricanes, Typhoons). Wind patterns: Typically westerly winds. Insects may be an issue.
Max annual temperature (Jul) 102.9 °FWarmest six months Jul Aug Jun May Sep Oct Coldest month JanMin annual temperature (Jan) -0.9 °FColdest six months Jan Dec Feb Nov Mar Apr Number of months warmer than 50.0°F mean = 8
Diurnal temperature swing3:0 months swing > 68 °F, of which 0 are in the warmest 6M0 months swing 59 to 68 °F, of which 0 are in the warmest 6M11 months swing 50 to 59 °F, of which 5 are in the warmest 6M1 months swing 41 to 50 °F, of which 1 are in the warmest 6M0 months swing < 41 °F
Max. moisture content 0.021 lb/lbMin. moisture content 0.000 lb/lbMean moisture content 0.009 lb/lbMean relative humidity 66.9 %
Annual mean speed 15.8 ft/sAnnual mean direction E of N 179.6°
Annual rainfall 40.591" inDriest month Jan with 1.539" in rainfallWettest month May with 5.598" in rainfallWettest summer month MayWettest winter month AprDriest summer month JulDriest winter month JanWettest six months May Sep Jun Apr Oct Mar
Annual hourly mean global radiation(a) 187.0 Btu/h•ft2
Mean daily global radiation(b) 1420.5 Btu/ft2
Annual solar resource(c) 519.3 Btu/ft2.yrAnnual mean cloud cover(d) 3.9 oktas
HDD(64.4) = 4094.3CDD(50.0) = 5114.8
Tulsa Intl Airport
ASHRAE 90.11 3A Warm humid Koeppen-Geiger1 Cfa Humid temperate (mild winters), Fully humid; no dry
season, Hot summer (sub-tropical), Mild winters, hot muggy summers with thunderstorms
Chosen weather file is TulsaTMY2.fwtRainfall location: Tulsa, USA
Temperature2:
Warmest month Jul
Moisture and humidity4:
Wind5:
Precipitation6:
Solar energy7:
Degree days8:
The climate report provides the headlines you need to know about the weather file you have selected
1. The Ashrae 90.1 climate classes are based around the Koeppen-Geiger classification system, but provide better definition in temperate and maritime zones. See also Koeppen Geiger and Kottek, Greiser,Beck, Rudolf and Rubel
2. Note the coincidence of wet or dry seasons and warm or cold seasons e.g. Wet summers, dry summers, wet winters etc
3. A good diurnal swing (monthly mean of the daily swing) during the warmest months indicates the potential for passive night time cooling and the use of thermal mass
4. Moisture content the nominal comfort range is 0.004-0.012 lb/lb If moisture content is 0.020 lb/lb or above either all year or in summertime it is an issue. High humidity high temp. cause comfort stress.
5. Wind speeds:less than 4.9 ft/s light and calm4.9-26 ft/s breeze26-45 ft/s strong breezegreater than 45 ft/s gale and above
6. Typically what does annual rainfall mean:Wet 67 inchesTemperate 20 to 59 inchesDry 12 inchesDesert 4 inches
7. Globally what is the range?a. 48 to 143b. 634 to 2061c. 254 to 697d. 1.5 to 8
8. Globally what is the range?HDD 32 to 11432CDD 32 to 11732
Page 1 of 1
7/31/2012file:///M:/Projects/2012001TUL/IES/Tulsa_bayStudy%20001/Toolkits/Climate/Report/Climate...
Climate Metrics, an automated report within the IES VE
energy modeling software, gives an excellent overview of
climactic conditions. The report consists of three columns,
one containing climate graphs, the second containing criti-
cal climate metrics, and the third serving as an explanation
of how to read and interpret the first two.
The center graph in the first column is a strong start-
ing point for analyzing climate. It quickly illustrates the
months that have cold stress (require cooling), heat stress
(require heating), or are comfortable (require little to no
conditioning). It also shows when peak temperatures and
rainfall occurs, and what months contain diurnal swings of
greater than 9 degrees. In a snapshot, designers can start
to understand the climate. If there are more heating stress
months than cooling, the design should place emphasis on
minimizing heating loads. If diurnal swings of greater than
9 degrees occur in the summer, there may be potential to
use night flushing as a passive cooling strategy. And if these
strategies didn’t immediately pop in your head, no worry;
the explanatory column on the right points them out for
you.
The information in the middle column has been paired
down to the most important climate metrics. Reading and
digesting it will give design teams a strong initial under-
standing of climate. For a more in depth study, turn to
Climate Consultant.
CLIMATE ANALYSIS - IES VE
GRAPHIC CLIMATE ANALYSIS FOR TULSA, OKLAHOMA
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
1. Climate Consultant, www.energy-design-tools.aud.ucla.edu/
Climate Consultant is a free tool developed by UCLA.1 It
is an excellent source for graphically representing climactic
information.
The tool is used by loading a climate file and clicking
through the various graphic representations of the data.
Everything from monthly temperature range to wind roses
are covered.
Walking through the Climate Consultant is an excellent
way to study certain aspects of climate in detail. During
the development of Energy Modeling Methodology, I was
asked to research the climate in Tulsa for a library MS&R
was working on. The design team was interested in how
to cool a garden space next to the library using passive
strategies. By looking at the graph Temperature Range,
we quickly saw that the average temperature in July was
85 degrees. We also learned from the Dry Bulb x Relative
Humidity graph that the relative humidity hovered around
66% in July. This combination of heat and humidity meant
that passive cooling strategies relying on evapotranspira-
tion wouldn’t be that effective. However, the wind patterns
in the area showed that the summer breezes came directly
from the south. This positioned them to flow right through
the project’s outdoor garden. After learning this, the design
team focused its initial passive cooling strategies around
shading and harnessing the wind to passively condition the
outdoor garden.
CLIMATE ANALYSIS - CLIMATE CONSULTANT
TEMPERATURE RANGE MONTHLY DIURNAL AVERAGES
DRY BULB AND RELATIVE HUMIDITY SKY COVER RANGE
WIND VELOCITY RANGE WIND ROSE
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
1. The Psychrometric Chart is part of the Climate Consultant software.
www.energy-design-tools.aud.ucla.edu/PSYCHROMETRIC CHART SHOWING NATURAL VENTILATION AND INTERNAL HEAT GAIN
After a design team becomes familiar with climate, the next
step is to determine how it might affect design. Luckily, a
tool has been developed that clearly illustrates the effec-
tiveness of a variety of passive design strategies in a given
climate - the psychrometric chart.1
Psychrometric charts work by setting up a system of axes
capable of graphing dry-bulb temperature, humidity ratio,
relative humidity, and wet-bulb temperature. Climate data
points are then graphed on the chart, usually in the form
of hourly data for the entire year. Once these points are
graphed, you can get a quick visual overview of the climate
by looking at the pattern of dots.
A comfort zone is then imposed on the chart. This shows
the ranges of temperature and humidity that people are
comfortable in. Dots that land inside this area don’t need
any heating, cooling, or humidity alteration to maintain
human comfort. Dots that sit outside of it show the hours
in the year where the climate does need conditioning to
reach comfort levels.
Finally, a series of passive design strategies can be selected
in the upper left hand corner. The user clicks on a strat-
egy and an associated area is graphed on the psychromet-
ric chart showing the climactic conditions it can effectively
temper. One a strategy is active, the chart also calculates
the percentage of yearly hours it effectively conditions.
Users can quickly cycle through the passive strategies, get-
ting visual feedback on how effective each strategy is in
their specific climate.
PSYCHROMETRIC CHART SHOWING HUMAN COMFORT ZONE
PSYCHROMETRIC CHART
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
36Meyer, Scherer & Rockcastle, ltd
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SITE
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CLIMATE
At latitude 36 degrees, Tulsa is far enough north to escape the long
periods of heat in summer, yet far enough south to miss the extreme
cold of winter. The influence of warm moist air from the Gulf of
Mexico is often noted, due to the high humidity, but the climate is
essentially continental characterized by rapid changes in temperature.
Generally the winter months are mild. Temperatures occasionally fall
below zero but only last a very short time. Temperatures of 100
degrees or higher are often experienced from late July to early
September, but are usually accompanied by low relative humidity and
a good southerly breeze. The fall season is long with a great number
of pleasant, sunny days and cool, bracing nights.
Rainfall is ample for most agricultural pursuits and is distributed
favorably throughout the year. Spring is the wettest season, having an
abundance of rain in the form of showers and thunderstorms. The
steady rains of fall are a contrast to the spring and summer showers
and provide a good supply of moisture. The greatest amounts of
snow are received in January and early March. The snow is usually
light and only remains on the ground for brief periods.
Climate Overview
Max annual temperature (July) 102.9 F
Min annual temperature (Jan) 0.9 F
Mean relative humidity 66.9 %
Annual mean wind speed 15.8 ft/s
Annual rainfall 40.59 in
Mean daily global radiation 1420.5 Btu/sqft
Annual mean cloud cover 3.9 oktas
Heating Degree Days 4094.3
Cooling Degree Days 5114.8
By the Numbers
TULSA CLIMATE DIAGRAM
The power of diagrams lies in their ability to bring phe-
nomena into the visual realm, facilitating understanding
and communication. In architecture, where practitioners
are inherently visual people, diagraming a phenomena en-
ables it to be part of the design conversation. Climate is
not exempt from this rule; if climactic considerations are
to be interwoven into the design process, they must be dia-
grammed throughout a project’s development.
After researching climate, designers should immediately
begin diagramming its most important aspects alongside
a project’s other generative forces. The graphic on the
right was developed to facilitate MS&R’s understanding
of the Tulsa climate and how it affected the design of a
library they were working on. By simply overlaying climac-
tic information like wind direction and magnitude and the
sun path over an aerial view, they now become generative
forces for the design. Can the design harness the summer
winds and block the winter winds? Will the project be
shaded by nearby buildings?
Adding key climate metrics to the graphic helps the design
team gain a more nuanced understanding of how climate
might affect the design. Will the high daily global radiation
place an extreme cooling load on unshaded areas of the
site? Does the high relative humidity make natural ventila-
tion an ineffective strategy?
Finally, writing a short climate overview acts like a text-
based version of a diagram; it quickly brings together sa-
lient information into a format that facilitates understand-
ing and communication.
DIAGRAMMING CLIMATE
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
INVESTIGATED SUSTAINABLE STRATEGIES FOR THE TULSA GARDEN
A project’s diagrams should continue to address climate
throughout the design process. After completing the ini-
tial climate analysis for Tulsa, I explored passive and active
strategies for conditioning the project’s outdoor garden
space. First I created a graphic that combined the existing
spatial constraints of the site with the climactic conditions
that affected the design. Important climate metrics were
placed on the sheet, ensuring they would be referenced dur-
ing the process.
Wind flow and annual rainfall stood out as potential driv-
ers of passive design, and they were added to the diagram.
The resulting design proposal then looked at the ways wa-
ter could be passively collected, stored, cooled, and then
used to condition the garden and the interior of the library.
A combination of evapotranspiration and harnessing the
wind patterns might help further condition the air in the
garden, and this precooled air sould then be drawn through
an air / ground heat exchanger and used to condition the
library’s interior.
DIAGRAMMING CLIMATE
39Meyer, Scherer & Rockcastle, ltd
GARDEN STUDY
context
1
22
33
45
467
567
10
88
1111
12
1
9
Max annual temperature (July) 102.9 F
Min annual temperature (Jan) 0.9 F
Mean relative humidity 66.9 %
Annual mean wind speed 15.8 ft/s
Annual rainfall 40.59 in
Mean daily global radiation 1420.5 Btu/sqft
Annual mean cloud cover 3.9 oktas
Climate Metrics
1. Capture rainfall on roof and in garden
2. Store rainfall in underground cisterns
3. Potential to cool rainfall through a ground
heat exchanger
4. Explore cooling library interior through
indirect evaporative cooling by running water
over roof
5. PV panels produce electricity and shade roof
6. Study integrating irrigation system for garden
and green wall with canopy structure
7. Use tensile fabric to shade garden
8. Verify if garden and greenwall can condition
outdoor areas through evapotranspiration
9. Explore using summer breezes from the south
to help condition garden
10. Investigate collecting air at northern end of
garden and funneling it into an air ground heat
exchanger
11. Test viability of using an air ground heat
exchanger to precondition ventilation air for
the library
12. Consider using preconditioned air for library
ventilation
Investigated Strategies
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
1. IES VE MicroFLO User Guide. www.iesve.com/content/downloadasset_2287 TULSA GARDEN WIND FLOW ANALYSIS - DESIGN OPTION
IES VE was used to conduct a wind flow analysis for
MS&R’s Tulsa Central Library project. After earlier dia-
grams identified the possibility of using the site’s wind flow
patterns to passively cool the project’s garden space, the
design team wanted to explore the issue in more detail us-
ing energy modeling.
MicroFlo is a computational fluid dynamics application
that is a part of IES VE.1 It can be used to study internal
or external air flow. For this study, the design team was
interested in how a design option would affect wind flow
through the garden area between the library and parking
ramp. The project’s garden, library, parking ramp, and sur-
rounding buildings were modeled as simple masses. The
team then referenced the initial climate studies to deter-
mine the average summer wind speed and direction. The
values, 16 feet per second blowing from South to North,
were input in MicroFlo. The software then computed wind
flow patterns through the site.
The images show the results of the analysis. They each
depict a sectional slice of the modeled wind field that cuts
through the garden. As the scale shows, red areas represent
wind speeds of 16 feet per second and dark blue areas rep-
resent zones with speeds near 0 feet per second.
The design option explored in the lower image interrupts
wind flow at the garden’s surface but still allows air to cir-
culate above. The design team used this information to
inform the next round of design explorations.
WIND ANALYSIS
TULSA GARDEN WIND FLOW ANALYSIS - INITIAL CONDITION
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
Massing studies are a cornerstone of concept design. Dia-
grams, hand sketches, and digital and physical models help
architects visualize, test, and refine early massing concepts.
Energy modeling can add another layer of analysis to the
mix, allowing the design team to consider a massing op-
tion’s impact on energy performance as well.
Using energy modeling to test massing concepts ensures
that issue of energy efficiency and sustainability will shape
the design from its earliest stages. Because the design teams
have so much creative freedom at the start of a project,
feedback from early energy modeling can put a design on
track to meet aggressive performance goals. Unfortunate-
ly, this inherent strength is also the process’s greatest chal-
lenge; because there are so many initial variables, it can
be difficult to compare and analyze the performance of di-
vergent concepts against one another. However, if design
teams adopt a process that starts by clearly defining goals
and ends with a wholistic comparison of design options
across a wide range of selection criteria, the methodology
can overcome this challenge and help inform those crucial
initial design decisions.
CONCEPT MASSING STUDIESDEFINE THE GOAL• What questions are you trying to answer?
• What variables are you testing?
1
CREATE SELECTION CRITERIA• Design decisions are complicated with a multitude of influences. Clear selection criteria
facilitates decision making
• Use existing standards as selection criteria when possible.
2
3 BUILD AN ENERGY MODEL• Simplify the model.
• Model only the detail necessary to facilitate decision making.
5
RUN ANALYSES• What analyses are necessary to shape your decision?
• What output is required to match your selection criteria?
• Are there additional analyses that can give you a more holistic view of performance?
4
INTERPRET RESULTS HOLISTICALLY• Always think holistically. Sustainability is not an end goal, it is part of good design.
• Balance energy modeling results with other important design aspects when making
design decisions.
CONCEPTUAL MASSING STUDIES COMPARISON
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
Lake Itasca Biological Research Station, a MS&R project
targeting net-zero energy use, was used as the platform
to develop much of the Energy Modeling Methodology.
When research began, the project had already completed
Schematic Design and was awaiting the start of Design
Development. This allowed the research team freedom to
focus on process development rather than project deliver-
ables because the work was conducted outside of the stan-
dard fee and scheduling pressures of a project. This spe-
cific portion of the methodology, Concept Massing Studies,
revisited early concept studies as the basis of comparison.
Although these studies were conducted well after initial
design decisions had been made, the process that emerged
will be implemented on future MS&R projects to steer
concept design.
An early challenge for the design team was to choose a
massing option that not only responded to the project’s de-
sign drivers but also put it on track to achieve its net-zero
energy goal. In response, I created a process that combined
energy modeling with other selection criteria in compre-
hensively evaluating three different massing schemes. The
first step in the comparison was defining its goal. The goal
was defined as:
“Comprehensively compare massing options across selec-
tion criteria that integrating the project’s main design driv-
ers with energy performance.”
CONCEPTUAL MASSING OPTIONS FOR ITASCA BIOLOGICAL RESEARCH STATION
DEFINE THE GOAL
DEFINE THE GOAL 1
Comprehensively compare massing options across selection
criteria that integrating the project’s main design drivers with
energy performance.
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
Using energy modeling to help in the comparison of con-
ceptual massing options is a powerful tool that is inher-
ently difficult to use; because there are so many initial vari-
ables at play, it is a challenge to compare analysis results
between massing options. However, by developing clear
selection criteria, the design team can facilitate massing op-
tion comparisons that will help steer the project in a suc-
cessful direction.
MS&R always strives to work with the client to clearly
define a project’s goals at the outset of design. These goals
become the benchmark of the project, acting as both a gen-
erative force and a set of criteria to judge design decisions
against.
When creating selection criteria to facilitate the compari-
son of concept massing options, the research team began
with the project’s goals. They were split into categories,
Economic, Social, Cultural, and Environmental. The last
category, Environmental, already contained aggressive per-
formance standards that could be analyzed by energy mod-
eling. The first three, while outside the domain of energy
modeling, are integral to the project’s success. Including
the entire lists ensures that massing options are compared
in a holistic manner.
DESIGN PERFORMANCE SELECTION CRITERIA FOR THE ITASCA BIOLOGICAL RESEARCH STATION
CREATE SELECTION CRITERIAECONOMIC
• Efficient to operate
• On budget
• Functional
SOCIAL
• Sensitive to historic fabric
• Building will be the visitor arrival point, meeting place, and social center
• Interior and exterior public spaces
CULTURAL
• Contemporary building that will not be confused with original historic buildings of the field station
• Embody the “field station” experience by enhancing outdoor activities and nature appreciation
• Posses a compelling identity
ENVIRONMENTAL
• Approach “zero net energy” within the limits of the budget
• Use natural light to illuminate interior during operating hours
• Utilize passive design strategies and make them an experiential and educational part of the building
CREATE SELECTION CRITERIA 2 Balance the Economic, Social, and Environmental impacts of
various massing options
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
1. IESNA Illumination guidelines are published by IESNA. Pacific Northwest National Laboratory repub-
lished them on their website. www.wbdg.org/pdfs/usace_lightinglevels.pdf
While outlining selection criteria for the Itasca concept
massing comparisons, the research team searched for exist-
ing standards that could be used to augment the list. The
environmental category called for the design to use natu-
ral light to illuminate the interior during operating hours.
IESNA standards exist that govern the lighting levels in
various programmatic spaces.1 The research team adapted
them to the project’s program and used them as a bench-
mark to test natural lighting performance when comparing
massing options.
IESNA lists nine categories that cover a variety of pro-
grams in its lighting standards. Attached to each are a
range of illuminance values required by the categories. The
research team listed the various programs the Itasca proj-
ect contained and, consulting the IESNA standards, chose
the illuminance levels that matched. The selection criteria
called for the design to use natural light to illuminate the
interiors during operating hours; this chart contained the
lighting levels required to meet this goal. And energy mod-
eling analyses were later used to test if the concept massing
options could hit these targets.
ECONOMIC
SOCIAL
CULTURAL
ENVIRONMENTAL
• Approach “zero net energy” within the limits of the budget
• Usenaturallighttoilluminateinteriorduringoperatinghours
• Utilize passive design strategies and make them an experiential and educational part of the building
CREATE SELECTION CRITERIA 2 Balance the Economic, Social, and Environmental impacts of various massing options
DESIGN PERFORMANCE SELECTION CRITERIA FOR THE ITASCA BIOLOGICAL RESEARCH STATION
ILLUMINANCE CATEGORIES AND ILLUMINANCE VALUES FOR GENERIC TYPES OF ACTIVITIES IN INTERIORS
TypeofActivity
Simple orientation for short temporary visits
Public spaces with dark surroundings
Performance of visual tasks of high contrast or large size
Working spaces where visual tasks are only occasionally performed
Lux
Performance of visual tasks of medium contrast or small size
Performance of visual tasks of low contrast or very small size
Performance of visual tasks of low contrast or very small size over a prolonged period
Performance of very prolonged and exacting visual tasks
Performance of very special visual tasks of extremely low contrast and small size
A
B
C
D
E
F
G
H
I
IlluminanceCategory
20-30-50
50-75-100
100-150-200
200-300-500
500-750-1000
1000-1500-2000
2000-3000-5000
10000-15000-20000
5000-7500-10000
2-3-5
5-7.5-10
10-15-20
20-30-50
50-75-100
100-150-200
200-300-500
1000-1500-2000
500-750-1000
General lighting throughout spaces
Illuminance on task
Illuminance on task, obtained by a combina-
tion of general and local lighting
RangesofIlluminance ReferenceWork-Plane
Foot Candles
ITASCA DAYLIGHTING TARGETS
ItascaProgrammaticSpaces
Office Area
Lab Area
Mechanical
Auditorium
Lux
Lobby
Rest Rooms
Circulation
E
D
D
D
B
B
B
IlluminanceCategory
General lighting throughout spaces
Illuminance on task
RangesofIlluminance ReferenceWork-Plane
Foot Candles
500-750-1000 50-75-100
200-300-500 20-30-50
200-300-500 20-30-50
50-75-100 5-7.5-10
50-75-100 5-7.5-10
50-75-100 5-7.5-10
200-300-500 20-30-50
USE EXISTING STANDARDS FOR SELECTION CRITERIA
• Modify existing standards for your project to create selection criteria
• Using existing standards as selection criteria when possible
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
1. IES VE Sketchup Plugin User Guide. http://www.iesve.com/content/downloadasset_2867
Energy modeling is used to analyze and compare the per-
formative aspects of massing options. When creating the
energy model, it is important to simplify it as much as pos-
sible. At this early stage of design, it is important for an
energy model to be quick to make and to be able to provide
enough information to facilitate a relative comparison.
These energy models don’t have to accurately predict the
building’s energy use down to the nearest kBtu/sf. Instead
they need to contain only the detail necessary to differen-
tiate them from one another and capture each concept’s
unique features that may affect energy use.
The building’s geometry should be simplified. Any rooms
that are similar should be grouped together into a single
zone. The images on the right show an early concept plan
for Itasca. The second image illustrates how the energy
model combines multiple offices into a single zone as well
as combining the lab spaces and their support areas. This
speeds up the modeling process considerably while still
keeping enough definition to provide results accurate
enough to facilitate a relative comparison.
COMBINE SIMILAR ROOMS INTO SINGLE ZONES WHEN BUILDING AN ENERGY MODEL1
BUILDING AN ENERGY MODEL
LAB SPACESOFFICE OFFICE
AUDITORIUM
CIRCULATION
LOBBY
REST ROOMS
BUILD AN ENERGY MODEL 3 Simplify, simplify, simplify. Model only the level of detail
necessary to facilitate decision making.
ITASCA CONCEPT SKETCH WITH DETAILED ROOM DIVISIONS
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
1. IES VE Sketchup Plugin User Guide. http://www.iesve.com/content/downloadasset_2867
Because IES VE uses a Sketchup plugin to create its energy
models, going from concept sketch to three dimensional en-
ergy model is quick and easy. The images on the right start
by showing a concept drawing that has been imported into
Sketchup. Because the most important differences were the
sectional characteristics and glazing placement between the
massing options, these were captured in detail. Again, us-
ing Sketchup makes modeling this detail very easy.
When creating an energy model in Sketchup, do not model
wall thickness. Energy models deal in zones, looking at the
space between defining elements, not at the elements them-
selves. Define the geometry with simple planes.1
After the sketchup model is complete, the IES Plugin au-
tomates the process that converts it into an energy model.
The plugin searches the model for enclosed areas and turns
them into zones that can be read by IES VE. Finally, it ex-
ports the converted model into IES VE where the full suite
of analyses can be run on it.
BUILDING AN ENERGY MODEL
A) CONCEPT SKETCH B) SKETCHUP MODEL
C) SKETCHUP IES ENERGY MODELING PLUG IN D) IES ENERGY MODEL (DAYLIGHT ANALYSIS SHOWN)
1) CONCEPT DRAWING
2) SKETCHUP MODEL
3) SKETCHUP IES ENERGY MODELING PLUG IN
4) IES ENERGY MODEL
A
B
C
D
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
1. IES VE ApacheSim User Guide. www.iesve.com/content/downloadasset_2883
2. IES VE FlucsDL User Guide. http://www.iesve.com/content/downloadasset_2307
Once an energy model is created, design teams need to
choose analyses that will provide them with the infor-
mation necessary to make an informed decision. For the
Itasca project, our selection criteria was broken into four
categories: economic, social, cultural, and environmental.
Energy modeling analyses can help test the performance of
the concept massing options in the environmental category.
The environmental category of the selection criteria called
for a building that approaches zero net energy, uses natural
light, and utilizes passive design strategies. The first two
criteria, energy use and natural lighting, can be easily ana-
lyzed by an energy model. It is much more difficult and
time consuming to analyze passive design strategies with
an energy model, so the design team instead relied on cli-
mate research and the psychrometric chart to determine
what passive strategies might be effective.
A massing concept’s energy use can be determined by run-
ning a thermal analysis with IES VE ApacheSim.1 Remem-
ber that the performance comparisons between massing
options will be relative; define the building geometry and
make quick assumptions about the rest of the energy mod-
eling inputs. When running a thermal analysis, focus on
heating and cooling loads instead of energy use, as building
systems, an unknown at this point in the process, have little
effect on them.
Daylight analyses use IES VE Flucs DL. Run tests for the
winter and summer solstice. Then measure and graph
lighting levels in foot candles to enable comparisons with
the lighting selection criteria.
RUNNING ANALYSES
CONCEPT 1
CONCEPT SKETCH ENERGY MODEL DAYLIGHTING ANALYSIS
CONCEPT 2
CONCEPT 3
CONCEPT 3
KBTU/SF
7070
71
74
79
RUN ANALYSES4 Chose analyses that will help inform decision making in a holistic manner
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
Thermal Loads - 70 kBtu/sf
Total Floor Area - 13295 sf
Exterior Wall Area - 10262 sf
Glazing to Floor Area Ratio - 9.82%
Thermal Loads - 70 kBtu / SF
Total Floor Area - 13295 sf
Exterior Wall Area - 10262 sf
Glazing to Floor Area Ratio - 9.82%
Thermal Loads - 74 kBtu / SF
Total Floor Area - 12069 sf
Exterior Wall Area - 7902 sf
Glazing to Floor Area Ratio - 15.44%
Thermal Loads - 79 kBtu / SF
Total Floor Area - 11497 sf
Exterior Wall Area - 10867 sf
Glazing to Floor Area Ratio - 21.30%
Concept 1
Concept 2
Concept 3
Concept 4
SOCIA
L
CONCEPTS THERMAL ANALYSIS Sens
itive t
o Hist
oric
Fabr
ic
DAYLIGHTING ANALYSIS Build
ing w
ill be
the v
isitor
arriv
al po
int an
d soc
ial ce
nter
Inter
ior an
d Exte
rior P
ublic
Spac
es
Contem
porar
y buil
ding w
ith un
ique c
harac
ter
Contem
porar
y buil
ding w
ith un
ique c
harac
ter
Embo
dy th
e “Fie
ld Sta
tion”
expe
rienc
e
CULTURAL
Appro
ach n
et ze
ro en
ergy
Use na
tural
light
Use pa
ssive
desig
n tha
t are
expe
rienti
al
ENVIRO
NMENTA
L
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COMPARING CONCEPT MASSING OPTIONS
The final steps in comparing conceptual massing options is
compiling the analyses, interpreting the results, and mak-
ing a decision. The most important thing to remember is
to think holistically.
The graphic on the right brings together the four massing
options, the energy modeling results, and the original selec-
tion criteria. Architecture must respond to a wide range of
factors; combining all of this information helps ensure that
each concept is evaluated against the full range of selection
criteria.
To facilitate the decision making process, the concepts can
be scored for each selection criteria. Design teams can
also weight the scores if certain aspects of the project are
deemed more critical than others.
After scoring the concept options, the design team elected
to continue in the direction of Concept 4. Although it had
the highest energy use with 79 kBtu/sf, it also contained a
much higher glazing percentage than the rest of the models.
The concept outperformed the rest in daylighting and was
the only one to achieve the IESNA lighning benchmarks.
And the unique section, with skylights on the south stream-
ing into a sun corridor and then through a translucent pan-
el and into the lab, received high marks for using passive
design strategies as experiential elements.
If the concept massing comparison wasn’t done holistically,
this option may have been tossed out for its higher energy
use. But, after looking at the full range of design drivers, it
was decided to be the best direction for the project.
INTERPRETING RESULTS
INTERPRET RESULTS HOLISTICALLY5 Balance energy modeling results with other important
design aspects when making design decisionsDESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
Energy modeling is a perfect match for the design devel-
opment phase. During design development, large-scale
decisions have been made, a concept has been locked in,
and the project team spends the majority of their time fine
tuning the design. Energy modeling thrives in this environ-
ment, leveraging its strength as an analytical tool that is
most effective when studying isolated variables. Designers
can use energy modeling to help dial in a range of design
development decisions using iterative analyses.
An iterative analysis takes one variable, be it the R value of
a wall, the building’s glazing percentage, or the geometry or
a room, testing baseline performance against a series of op-
tions that all slightly modify it. By using iterative analyses,
the design team can optimize conditions. In practice, this
usually involves using energy modeling to find a range of
optimized conditions and setting them as bracketed targets
for the design to hit.
ITERATIVE ANALYSIS
PROCESS GOAL
GUIDING PRINCIPLES
METHODOLOGY
Easy to use
Able to efficiently compare design options
Produce graphical output
Create a baseline energy model of the schematic design
Identify key aspects of the design to fine tune
Use iterative analysis to bracket optimized conditions
Interpret results holistically
Aid designers in fine tuning a design
DESIGN DEVELOPMENT ENERGY MODELING METHODOLOGY
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE ANALYSIS
1 1/2" = 1'-0"1 Section - Double Stud Wall
BACKFILL
12” COMPACTED GRAVEL FILL
UNDISTURBED SOIL
11” COMPACTED GRAVEL FILL
1 1/2” FLOWABLE FILL
TOTAL R VALUE OF ASSEMBLY 57.47
WALL ASSEMBLY
5/8” Hardy Panel
5/8” OSB Sheathing
3 1/2” Cellulose Blown Insulation
1” Rigid Insulation - Extruded Polystyrene
2 1/2” Cellulose Blown Insulation
5/8” OSB
1” Rigid Insulation - Extruded Polystyrene
5/8” Gypsum Board
.08
5
0.63
13.65
9.75
21.45
.63
5 1/2” Cellulose Blown Insulation
5
.56
Material R Value
WALL SECTION AND R-VALUES
As buildings strive to reach higher levels of energy efficien-
cy, the quality of their envelopes becomes very important.
Having a well insulated, well designed, and well construct-
ed envelope is critical to the performance of a design. So
just how much insulation is necessary? Energy modeling
can help answer this perennial question.
R-value is a measurement of thermal resistance used to
describe the performance of building materials. It is ex-
pressed as the thickness of the material divided by its ther-
mal conductivity. Materials with higher insulating capaci-
ties have a higher R-value. The R-value for an assembly is
calculated by adding the R-values of its component parts
together. U-value, used to describe the thermal resistance
of windows, is simply the reciprocal of R-value.
Energy modeling and iterative analysis can help design
teams dial in optimized target R-values for a building’s en-
velope.
As a target, the values help guide the design while still al-
lowing for the flexibility necessary to address design de-
cisions holistically. While iterative analysis will provide a
range of optimized R-values, it is still up to the design team
to factor in the cost, durability, constructability, sustain-
ability, and aesthetic and conceptual impact of designing
the envelope to achieve the recommended values.
OPTIMIZING R-VALUES
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
1. IES VE ApacheSim User Guide, http://www.iesve.com/content/downloadasset_2883
OPTIMIZING R-VALUES
The design team for MS&R’s Itasca Biological Research
Center wanted to determine target values for effective lev-
els of insulation in the project’s envelope. The process be-
gan by creating a base energy model, setting the envelope’s
R-values to code-minimum levels. The performance of this
base condition was analyzed using IES VE ApacheSim and
graphed as the design’s total annual heating and cooling
load.1
Each assembly was then studied independently using itera-
tive analysis. With the rest of the building remaining at
code-minimum levels, each successive iteration would raise
the R-value of the assembly being tested by 5 and model
its impact on heating and cooling loads. Eleven iterations
were completed for each assembly.
The results all show that heating and cooling loads are re-
duced when the assembly’s R-value is increased. However,
by studying the slope of each graph, the design team could
see where the performance benefits of additional R value
began to plane out. When the cost of increasing an as-
sembly’s R-value is factored in, it became clear that these
changes in slope signaled the point where increased insula-
tion no longer carried a strong return on investment. These
target values were highlighted in yellow. The lighter shade
of yellow indicated increased R-values that, while not re-
turning a large performance benefit, might still be neces-
sary to achieve the project’s net-zero energy targets. The
orange line marks where the R-values were previously set
during schematic design.
The top row of graphs also illustrates the relative perfor-
mance benefits of addressing one assembly against anoth-
er. The graphs show that increasing the window R-value
ITASCA ITERATIVE ANALYSIS OF R-VALUES
ITASCA ENERGY MODELING Design Model
Wall R Value Roof R Value Slab R Value Window R ValueWall R Value Heating Loads Cooling Loads Total Loads Roof R Value Heating Loads Cooling Loads Total Loads Slab R Value Heating Loads Cooling Loads Total Loads Window R Value Heating Loads Cooling Loads Total Loads
13 619827 133190 753017 30 619827 133190 753017 10 619827 133190 753017 1.5 619827 133190 75301715 606219 134041 740260 35 610011 132955 742966 15 578573 139255 717828 2 542684 135236 67792020 585561 136064 721625 40 602558 133113 735671 20 556004 142875 698879 3 466900 145821 61272125 572214 137022 709236 45 596704 133215 729919 25 540864 145434 686298 4 428415 152660 58107530 563177 137661 700838 50 591980 133288 725268 30 530198 147311 677509 5 405152 157421 56257335 556650 138115 694765 55 588089 133352 721441 35 522290 148740 671030 6 376684 178931 55561540 551702 138445 690147 60 584833 133421 718254 40 516184 149870 666054 7 365494 182487 54798145 547822 138699 686521 65 582076 133503 715579 45 511331 150786 662117 8 357087 185288 54237550 544698 138904 683602 70 579720 133601 713321 50 507375 151544 658919 9 350540 187547 53808755 542131 139080 681211 75 577687 133715 711402 55 504103 152174 656277 10 345291 189409 53470060 539987 139237 679224 80 575913 133820 709733 60 501334 152719 654053 11 340991 190969 53196065 538173 139384 677557 85 574368 133953 708321 65 499110 153159 652269 12 337402 192294 529696
Wall R Value Roof R Value Slab R Value Window R Value
650000
700000
750000
650000
700000
750000
650000
700000
750000
650000
700000
750000
500000
550000
600000
30 35 40 45 50 55 60 65 70 75 80 85500000
550000
600000
10 15 20 25 30 35 40 45 50 55 60 65500000
550000
600000
1 2 3 4 5 6 7 8 9 10 11 12500000
550000
600000
13 15 20 25 30 35 40 45 50 55 60 65
Model DataFloor Area 11740Volume 215865Ext. Wall Area 10434Ext. Opening Area 3300Ext. Roof Area 13223
30 35 40 45 50 55 60 65 70 75 80 85 10 15 20 25 30 35 40 45 50 55 60 65 1 2 3 4 5 6 7 8 9 10 11 1213 15 20 25 30 35 40 45 50 55 60 65
Current: R63 Current: R178 Current: R93 Current: R4.3
Wall R-Value Roof R-Value Slab R-Value Window R-Value
Ann
ual h
eatin
g an
d co
olin
g lo
ad (
kBtu
/sf)
Scal
e co
nsist
ent
acro
ss a
ssem
blie
s
ITASCA ENERGY MODELING Design Model
Wall R Value Roof R Value Slab R Value Window R ValueWall R Value Heating Loads Cooling Loads Total Loads Roof R Value Heating Loads Cooling Loads Total Loads Slab R Value Heating Loads Cooling Loads Total Loads Window R Value Heating Loads Cooling Loads Total Loads
13 619827 133190 753017 30 619827 133190 753017 10 619827 133190 753017 1.5 619827 133190 75301715 606219 134041 740260 35 610011 132955 742966 15 578573 139255 717828 2 542684 135236 67792020 585561 136064 721625 40 602558 133113 735671 20 556004 142875 698879 3 466900 145821 61272125 572214 137022 709236 45 596704 133215 729919 25 540864 145434 686298 4 428415 152660 58107530 563177 137661 700838 50 591980 133288 725268 30 530198 147311 677509 5 405152 157421 56257335 556650 138115 694765 55 588089 133352 721441 35 522290 148740 671030 6 376684 178931 55561540 551702 138445 690147 60 584833 133421 718254 40 516184 149870 666054 7 365494 182487 54798145 547822 138699 686521 65 582076 133503 715579 45 511331 150786 662117 8 357087 185288 54237550 544698 138904 683602 70 579720 133601 713321 50 507375 151544 658919 9 350540 187547 53808755 542131 139080 681211 75 577687 133715 711402 55 504103 152174 656277 10 345291 189409 53470060 539987 139237 679224 80 575913 133820 709733 60 501334 152719 654053 11 340991 190969 53196065 538173 139384 677557 85 574368 133953 708321 65 499110 153159 652269 12 337402 192294 529696
Wall R Value Roof R Value Slab R Value Window R Value
733321
738321
743321
748321
712269
732269
752269
679696
729696
717557
727557
737557
747557
708321
713321
718321
723321
728321
733321
30 35 40 45 50 55 60 65 70 75 80 85652269
672269
692269
10 15 20 25 30 35 40 45 50 55 60 65529696
579696
629696
1 2 3 4 5 6 7 8 9 10 11 12677557
687557
697557
707557
717557
13 15 20 25 30 35 40 45 50 55 60 65
Model DataFloor Area 11740Volume 215865Ext. Wall Area 10434Ext. Opening Area 3300Ext. Roof Area 13223
30 35 40 45 50 55 60 65 70 75 80 85 10 15 20 25 30 35 40 45 50 55 60 65 1 2 3 4 5 6 7 8 9 10 11 1213 15 20 25 30 35 40 45 50 55 60 65
Current: R63 Current: R178 Current: R93 Current: R4.3
Ann
ual h
eatin
g an
d co
olin
g lo
ad (
kBtu
/sf)
Scal
e to
fit
data
per
ass
embl
y
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
ITASCA BIOLOGICAL FIELD STATION - Design Development Daylight Optimization08.21.2012
Target Standard - LEED 2009 Credit 8.1: Daylight
LEED Credit 8.1 - 10 foot candle minimum daylight in 75% of
occupied space at 9:00 am and 3:00 pm on September 21st.
LEED Innovation in Design Credit - 25 foot candle minimum
daylight in 95% of occupied space at 9:00 am and 3:00 pm on
September 21st.
Standard Used - LEED Innovation in Design Credit
Model - IES VE FlucsDL with sky set to Clear Sky
Results File - 120820 Sun Co LEEED Daylight Study
SUN CORRIDOR DAYLIGHT STUDY
Average Daylight FC - 37.5
Meet LEED 8.1 Daylight Target - NO
Meet LEED IDC Daylight Target - NO
Average Daylight FC - 62.5
Meet LEED 8.1 Daylight Target - YES
Meet LEED IDC Daylight Target - NO
Average Daylight FC - 87.3
Meet LEED 8.1 Daylight Target - YES
Meet LEED IDC Daylight Target - YES
Option 3
Remove every other window
17% Glazing
Option 2
Remove every fourth window
29% Glazing
Option 1
Starting condition
46% Glazing
ITASCA BIOLOGICAL FIELD STATION - Design Development Daylight Optimization08.21.2012
Target Standard - LEED 2009 Credit 8.1: Daylight
LEED Credit 8.1 - 10 foot candle minimum daylight in 75% of
occupied space at 9:00 am and 3:00 pm on September 21st.
LEED Innovation in Design Credit - 25 foot candle minimum
daylight in 95% of occupied space at 9:00 am and 3:00 pm on
September 21st.
Standard Used - LEED Innovation in Design Credit
Model - IES VE FlucsDL with sky set to Clear Sky
Results File - 120820 Sun Co LEEED Daylight Study 4
Average Daylight FC - 42.3
Meet LEED 8.1 Daylight Target - YES
Meet LEED IDC Daylight Target - YES
Average Daylight FC - 62.8
Meet LEED 8.1 Daylight Target - YES
Meet LEED IDC Daylight Target - YES
Average Daylight FC - 83.3
Meet LEED 8.1 Daylight Target - YES
Meet LEED IDC Daylight Target - YES
SUN CORRIDOR DAYLIGHT STUDY
Option 6
Remove every 4th window. Decrease size of all windows.
13% Glazing
Option 5
Remove every 4th window. Decrease size of all windows.
16% Glazing
Option 4
Remove every 4th window. Decrease size of all windows.
20% Glazing
ITASCA GLAZING PERCENTAGE OPTIMIZATION
Glazing percentage has a strong impact on a project’s ener-
gy use and daylighting potential. It is important to balance
these effects when using energy modeling to optimize them.
The study on the right was used to optimize the glazing
percentage on Itasca’s south facing sun corridor. Daylight-
ing targets were developed before beginning the analysis.
Because the project is pursuing LEED certification, the
design team used LEED Credit 8.1 - Daylighting and an
associated Innovation in Design credit to serve as the tar-
get. The standard called for 95% of a design’s regularly
occupied spaces to achieve daylighting levels between 25
and 500 foot candles measured at 9:00 am and 3:00 pm on
September 21st.
IES VE includes a LEED Credit 8.1 navigator that analzes
the design for credit compliance. I simply modeled the sun
corridor with a variety of glazing percentages in IES VE,
ran the navigator, and interpreted the results. The top im-
age shows the graphical output from the IES VE analysis.
It marks areas of the design that comply with the standard
in green. It also reports the percentage of the design that
complies. This allowed me to quickly hone in on glazing
percentages and patterns that achieved the standard.
After running a series of iterative analyses, I found the min-
imum glazing percentage that still achieved the daylighting
targets. Thermal analysis was carried out by engineering
consultants, revealing that the minimum condition actually
didn’t out perform the original heavily glazed design due
to a balance between passive heating gains and lowered
heat losses. Because of this, the design team felt free to
maximize the glazing to capture the unique site views of
Lake Itasca.
OPTIMIZING GLAZING PERCENTAGE
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
Option 1
Starting Condition
Option 2
Raised Skylight
Option 3
Lowered North glazing to view height
Average Daylight FC - 28.9
Meet LEED 8.1 Daylight Target - YES
Meet LEED IDC Daylight Target - NO
Average Daylight FC - 31
Meet LEED 8.1 Daylight Target - YES
Meet LEED IDC Daylight Target - NO
Average Daylight FC - 29.5
Meet LEED 8.1 Daylight Target - YES
Meet LEED IDC Daylight Target - NO
ITASCA BIOLOGICAL FIELD STATION - Design Development Daylight Optimization08.21.2012
Target Standard - LEED 2009 Credit 8.1: Daylight
LEED Credit 8.1 - 10 foot candle minimum daylight in 75% of
occupied space at 9:00 am and 3:00 pm on September 21st.
LEED Innovation in Design Credit - 25 foot candle minimum
daylight in 95% of occupied space at 9:00 am and 3:00 pm on
September 21st.
Standard Used - LEED Innovation in Design Credit
Model - IES VE FlucsDL with sky set to Clear Sky.
Results File - 120820 Lab LEED Daylight Study
LAB DAYLIGHT STUDY
ITASCA BIOLOGICAL FIELD STATION - Design Development Daylight Optimization08.21.2012
Target Standard - LEED 2009 Credit 8.1: Daylight
LEED Credit 8.1 - 10 foot candle minimum daylight in 75% of
occupied space at 9:00 am and 3:00 pm on September 21st.
LEED Innovation in Design Credit - 25 foot candle minimum
daylight in 95% of occupied space at 9:00 am and 3:00 pm on
September 21st.
Standard Used - LEED Innovation in Design Credit
Model - IES VE FlucsDL with sky set to Clear Sky
Results File - 120820 Lab LEED Daylight Study 4
Average Daylight FC - 39.7
Meet LEED 8.1 Daylight Target - YES
Meet LEED IDC Daylight Target - YES
Average Daylight FC - 38.2
Meet LEED 8.1 Daylight Target - YES
Meet LEED IDC Daylight Target - YES
Average Daylight FC - 41.1
Meet LEED 8.1 Daylight Target - YES
Meet LEED IDC Daylight Target - YES
Option 6
One large skylight in center
32% Roof Glazing. 21% North Facade Glazing.
Option 5
Two skylights at edges of room
26% Roof Glazing. 21% North Facade Glazing.
Option 4
Thin and wide skylight
32% Roof Glazing. 21% North Facade Glazing.
LAB DAYLIGHT STUDY
Daylighting can be optimized by analyzing glazing percent-
age as well as glazing design. Intelligent sizing and place-
ment of glazing will facilitate daylighting. The studies
shown on this page were completed to optimize glazing in
the Itasca Biological Research Center’s lab spaces. Once
again, an iterative approach to energy modeling was used.
Because the study was focused solely on the labs, I created
a new energy model of a single lab space and an adjacent
section of sun corridor. The sun corridor was included be-
cause the labs are designed to pull daylight from the sun
corridor. Like the glazing percentage optimizations shown
on the previous page, these studies used LEED Credit 8.1 -
Daylighting as the target and the IES VE navigator to test
for compliance.
What is unique about the challenge of studying the place-
ment of glazing is that there are unlimited possibilities; it
would be impossible to methodically test all of the pos-
sible permutations in search of an optimal design. Instead,
designers must analyze results for trends, leading them to-
wards designs that meet the criteria.
The first set of analyses studies the effect of moving a
north-facing skylight up. The results indicated that this
brought more daylight into the interior. The second set of
studies builds off this and shows the minimum glazing size
and placement of three design options that all achieve the
target daylighting levels.
OPTIMIZING DAYLIGHT
ITASCA DAYLIGHTING ANALYSIS
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT
OPTIMIZING DAYLIGHT
ITASCA BIOLOGICAL FIELD STATION - Design Development Daylight Optimization08.21.2012
LAB SECTION 1
Daylight Performance -
Thermal Performance -
Achieves LEED 2009 Credit 8.1: Daylight
Achieves LEED 2009 IDC Credit for Optimal Daylighting Performance
Average Daylight = 43.6FC
ITASCA BIOLOGICAL FIELD STATION - Design Development Daylight Optimization08.21.2012
LAB SECTION 3
Daylight Performance -
Thermal Performance -
Achieves LEED 2009 Credit 8.1: Daylight
Achieves LEED 2009 IDC Credit for Optimal Daylighting Performance
Average Daylight = 41.4 FC
The final step in the daylight optimization studies was to
test the resulting geometries holistically. After finding two
glazing options for the lab space that achieved the daylight-
ing targets, they were diagrammed to test their ability to fa-
cilitate the project’s other goals. In a sense, this brought the
process full circle, combining a detailed daylighting analy-
sis with the original climate diagrams to help te team make
an informed design decision. Both options lent themselves
well to harnessing the site’s wind flow patterns, bringing
in the summer breezes through low windows in the south
facade and allowing them to vent out of the operable sky-
light. However, Lab Section 3 provided additional shading
for the skylights from the summer sun, added more south
facing roof surface area for mounting PV panels, and fur-
thered some of the project’s original aesthetic intentions.
By using a combination of analysis techniques and always
striving to present results graphically and in a holistic man-
ner, the design team was able to make well informed de-
cisions throughout the process. This kept the project on
track to be successful in not only meeting energy perfor-
mance goals, but also in achieving excellence in the other
areas of architecture described by Vitruvius - firmness,
commodity, and ultimately, delight.
OPTIMIZING DAYLIGHT
ITASCA DAYLIGHT ANALYSIS AND SECTIONAL STUDIES
DESIGN PROCESS 2.0
PROJECT TIMELINE
ARCHITECTURE 2030
CLIMATE ANALYSIS
A UNIQUE COLLABORATION
EQUEST AND IES VE COMPARISON
ABOUT THE STUDY
TOOLS OF DESIGN
ENERGY MODELING TIMELINE
ENERGY MODELING& CONCEPT DESIGN
INTEGRATED ENERGY DESIGN
WHY ENERGY MODEL?
CLIMATE CHANGE
DESIGN THINKING EVOLVED
VITRUVIUS REDEFINED
ENERGY MODELING INPUTS
PSYCHROMETRIC CHART
DIAGRAMMING CLIMATE
CONCEPT MASSING STUDIESWIND ANALYSIS
OPTIMIZING R-VALUES
ENERGY MODELING& DESIGN DEVELOPMENT
OPTIMIZING DAYLIGHT
OPTIMIZING GLAZING %
CONCEPT MASSING STUDIES
SMARTER CONCEPTS
ITERATIVE DEVELOPMENT