digital realm: parametric-enabled paradigm in ... · the last decade research into the...

International Journal of Architecture, Engineering and ConstructionVol 4, No 3, September 2015, 174-183

Digital Realm: Parametric-enabled Paradigm in

Architectural Design Process

Naglaa A. Megahed∗

Architecture and Urban Planning Department, Faculty of Engineering, Port Said University, Port Said, Egypt

Abstract: With the rise of digital design tools in architecture, this study aims to participate in the currentdebate taking into account a holistic approach of the parametric paradigm and some of the major potentialitiesthat emerge from its use in the discipline. This paper therefore aims to review this new paradigm and propose aconceptual framework based on its models, levels and systems that support the architectural design process. Thisframework may help architects realize the potential of parametric tools by using and thinking of parameterizationas a general procedure from the initial stage of form-finding to the process of manufacturing. However, the paperargues that the parametric-enabled paradigm is often incorrectly mistaken as an emerging architectural stylerather than a computational tool. Therefore, a critical awareness of both the potentials and limitations ofparametric paradigms is imperative in the effective use of these models and in understanding how they willcontinue to change the architectural profession.

Keywords: Architectural design, geometry, optimization, parametric models, parameterization

DOI: 10.7492/IJAEC.2015.018

1 INTRODUCTION

During each period of civilization, architecture has re-flected the level of societal development by integratingthe state of the art from various fields of human activ-ity. In contemporary architectural design, parametrictools are the latest advancement in digitally aided de-sign. Thus, the question of whether parameterizationcan assist the architectural design process is an impor-tant topic to explore.Parametric modeling is a relatively new science,

originally developed for solving the complex geometryof automotive design. Recently, this new paradigm hasbeen applied to assist the architectural design of com-plex building patterns, envelopes and structures. Fur-ther, these recent and continuous developments havebegun to exert a significant influence on the archi-tecture profession (Schumacher 2012; Svoboda et al.2014). It has become a well-utilized tool in many typesof design, especially after the emergence of modelingsoftware and the accurate results of optimization. Thecomputer can aid designers in exploring a wide rangeof options that the designer would not or may not havethe time to explore on their own by traditional meth-ods (Jester 2014; Lee et al. 2012). This digital realmraised the questions of how architects could use digital

and parametric tools and at what stage parameteriza-tion should enter the architectural design process. Thisdebate also leads to the other questions posed in thisstudy:

• Could digital tools improve the architectural de-sign process or are they just a way to expressmodernity and fashionable paradigm? If so,

• How are these tools utilized in the architecturaldesign process, and what influence do they haveon the form-finding process?

• Could parametric modeling convert the designprocess from form-making to form-finding? If so,

• Is the most effective use of parametric softwaresimply to generate unusual forms? If so,

• Are we now entering a completely digital archi-tecture age in which form follows software?

• Finally, what should be the extended role andinfluence of architects?

These are some of the questions that are raised byall those involved with parameterization in the archi-tectural profession. The answers to these questions areclosely linked to each other, and are still the subject ofsignificant research in the field.

*Email: [email protected]

174

http://dx.doi.org/10.7492/IJAEC.2015.018

mailto:[email protected]

Megahed/International Journal of Architecture, Engineering and Construction 4 (2015) 174-183

Although a lot of scholars’ papers discuss the para-metric paradigm in architecture, a holistic approachhas been neglected in this literature until now. Mostimportantly, limited efforts have been made to devel-op a multidisciplinary framework that helps architectsgain the required knowledge to realize the parametricparadigm. In this context, this review paper proposesa more holistic view and tackles the abovementionedresearch questions.

2 RESEARCH METHODOLOGY

In order to present a holistic approach of the role ofparametric-enabled paradigm in architectural designprocess and answer the research questions, the studybegins with a brief review of the current developmentsin parametric design, models and techniques as well astheir relations to the architectural design process. Inaddition, the results obtained from this review are usedto propose a conceptual framework that supports de-sign exploration and the customization of the desiredperformance. Then, the expanded role of the architectis discussed and some misconceptions regarding para-metric applications are presented.

3 BACKGROUND: ARCHITECTURALDESIGN DEVELOPMENTS

Beyond just a process of finding solutions, architec-tural design also involves redefining design problemsand searching for better solutions (Yu et al. 2013).Whether or not it utilizes the aid of computers, theprocess involves design activities which can be catego-rized as either routine or non-routine. However, duringthe last decade research into the architectural designprocess utilizing ideas and models drawn from digi-tal technologies has resulted in a better understand-ing of design as a process, particularly routine designand recently have the potential role to support cre-ativity throughout non-routine activities (Gero 1990;Gero and Maher 2013). This digital realm has en-abled designers to work with highly complex geome-try and enormous data to explore a whole new designfield that requires computation techniques. Accordingto Woodbury (2010), parametric tools support the cre-ation, management and organization of complex digitaldesign models. By changing the parameters of an ob-ject, a potentially infinite range of possibilities can becreated (Kolarevic 2003).Recently in the fabrication industry, a new gener-

ation of 3D parametric modeling tools have becomeavailable. In addition, new software and techniques forCAM modeling and computer numerically controlled(CNC) fabrication hold the potential to make it easierto implement modeling of buildings and their subsys-tems. As a result, famous and international architec-tural offices are deeply committed to researching the

potential role of digital technologies (Feng 2013; Jester2014; Oxman 2008).

3.1 Variations in the Architectural DesignProcess

Due to the open-edit nature of the design process,which is often based on the trial-and-error method,problems and solutions cannot be clearly identified andseparated. Each set of problems and solutions cannotbe broken into parts that can be solved separately; in-stead, it has to be treated as a whole (Gero and Maher1988). Moreover, there is no perfect solution, only pre-ferred solutions. This means that the architect needs tobe able to decide when to stop exploring different ideas(Parthenios 2005; Xia 2008). This phase will basicallydetermine the buildingąŕs shape, space, envelope andother expressive parameters as well as essential factorsregarding the environmental forces. In this context,variations in design are a fundamental part of the de-sign process (Hernandez 2006; Lin et al. 2013).As is generally the case in architectural design,

different designers have their own design strategies; forexample, some designers prefer to start from functionalanalysis, while other designers focus on geometric mod-eling as the priority. However, parametric design is adynamic, rule-based process controlled by variationsand parameters in which multiple design solutions canbe developed in parallel. It is up to designers to decidehow many of these conditions to consider (Yu et al.2013).

3.2 Evolving Parametric-enabled Paradigm

In order to understand what “parameter” means, itis helpful to look briefly at several definitions of thisterm. Generally, the term “parameter” originates inmathematics; it is a derivative of the word “parame-ter” which is technically defined as numerical or othermeasurable factors. Parameters are the constants inan equation, a set of equations or a computer programthat limits what the equation will produce (Hudson2010). While today the term “parameter” is general-ly related to the computational world, it has existedmuch longer and has always influenced great architec-ture. Advancements in technology have made paramet-ric modeling more powerful, but the thought processbehind the software has existed for centuries (Coyne2014; Jester 2014). However, as architects have adopt-ed parametric modeling as a design tool, the definitionof the term “parameter” has become confused (Davis2013).For architectural design, the parametric-enabled

paradigm is a key concept in modern design. Thisparadigm is a process based on algorithmic thinkingthat enables the expression of parameters and rulesthat define, encode and clarify the relationship betweendesign intent and design response (Woodbury 2010).

175


4 PARAMETRIC-ENABLEDPARADIGM: A HOLISTICAPPROACH

This section presents a holistic approach of the roleof parametric-enabled paradigm in architectural de-sign. To fully understand this role, this section isgoing to deal with three aspects: a) presenting theconceptual framework of different parametric modelsthroughout the architectural design process; b) identi-fying strengths, limitations and misconceptions regard-ing the paradigm, and; c) clarifying the expanded roleof the architect during the digital realm.

4.1 Models of Architectural Design Process

According to the previous background, digital realmpresents flexible tools to search for the most suitablevariations in the design process. Parametric mod-eling has become increasingly prevalent in architec-tural design in recent years. Previous studies have ar-gued that parametric tools advance design processes indifferent approaches (Attar et al. 2009; Burry 2003;Caetano et al. 2015; Chokhachian and Atun 2014;Dino 2012; Kolarevic 2003; Rybczynski 2013; Holzeret al. 2007; Kotnik 2010; Larsson et al. 2012; Oost-erhuis et al. 2004; Oxman 2008; Stavric and Marina2011; Woodbury et al. 2006). In spite of all the dif-ferences in modeling and editing software, parametricdesign tools are utilized mainly in multidisciplinary de-sign optimization (Aish and Woodbury 2005; Yu et al.2013). This study tries to review these optimizationapproaches and presents a conceptual framework basedon the available literature on different parametric mod-els. This framework divides the models of design pro-cess into two main approaches (see Figure.1). The firstapproach concerns the parameterization of geometricoptimization and the second approach refers to digitalfabrication and project management. Generally, theseapproaches that support the variation in parametricdesign include formation models, generative models,performance models and fabrication models. However,the framework does not focus on one specific model;instead, it provides a panorama for all parameteriza-tion models in the architectural design process with ascope broader than merely discussing model’s detail toprovide the required knowledge for architects to un-derstand the research debate. The components of theframework are summarized below.

4.1.1 Parameterization for geometric optimiza-tion

This approach concerns the parameterization of geo-metric optimization in order to generate many arraysof parametric designs which describe alternative solu-tions to structural systems and environmental factorswithin constrained optimization. In this context, thereis a broad range of parametric models, ranging from

simple to complex, which aid designers. These modelsinclude formation, generation and performance, whichcan be applied to architectural content and design tasksfrom the early conceptual stage.

A) Formation models.

Digital and parametric tools have transformed theconcept of form into the interactive and continuousconcept of formation (Oxman 2008). Regardless oftheir implementation and sophistication, all formationparametric models can be categorized into the follow-ing two types: those that perform variations and thosethat generate new designs via a combination of param-eterized geometrical entities. In addition, a formationparametric model can also be a combination of bothtypes (see Figure.2), although this is very unusual dueto the complexity of the model (Hernandez 2006).

• Variational Geometry Model(VGM). This is asimple kind of parametric model based on thedeclarative nature of the parameters to constructshapes. The idea behind a VGM model is thatthe geometrical components are controlled bymeans of changing the values of the parametersor constraints without changing the topology.

• Associative Geometry Model (AGM). This is thesecond type of parametric models that createmore complex structures. It offers another de-gree of complexity beyond the parameterizationof the geometrical components, which is done byconstructing combinations according to specificrules. In the AGM, the important aspect is thespatial relations and rules of combination be-tween the primitive components which determinedifferent design compositions.

• Hybrid Geometry Model (HGM). AlthoughHGMs are less frequently used than VGMs orAGMs, they offer the best of both models andcan be very robust for design exploration. Dueto the complexity of design exploration, the bestoption is composing two models separately: onefor parametric variations and one for parametriccombinations (Hernandez 2006).

B) Generative models.

These models have recently enabled architects to ex-plore and generate thousands of design possibilitieswithin new CAD environments in an unprecedentedmanner. These modeling systems are based on shapegrammars, evolutionary models and other computa-tional design principles which utilize primitive shapesand have shape-specific rules. They are structured tostimulate the designerąŕs creativity by guiding the de-signer through possible design spaces constrained byalgorithms (Caetano et al. 2015; Krish 2011; Oxman2008).

176


Figure 1. Conceptual framework of parameterization models in the architecturaldesign process: from concept to reality

Figure 2. Parametric modeling schema of a column formation. Redrawn basedon Hernandez’s original schema (2006)

• Shape grammars. They are specific classes ofrule-based expert systems in artificial intelligencewhich generate geometric shapes(Tepavčević andStojaković 2012). An implemented shape gram-mar allows the rapid production of alternativeshapes following one grammar, which providesa computational approach to formalizing genera-tive systems of designs. This generative processconsists of (a) shape rules that define how an ex-isting shape can be transformed; and (b) a gener-ation engine that selects and processes rules(Liaoet al. 2015; Oxman 2008; Pauwels et al. 2015).

• Evolutionary models. This is another state-of-the-art evolutionary algorithm model for find-ing the optimal building model based on mim-icking rules. The use of bio-mimicry approachesto inform the parametric model is how the evolu-tionary model differs and works. However, thesemodels require detailed building parameters tobe specified(Oxman 2008; Yang et al. 2012).

C) Performance-based model.

The parameters are not just numbers relating toCartesian geometry; they also have great potential in

177


addressing performative issues as a tool that allows thenavigation of the parametric search space with respec-t to measurable performance criteria. This computa-tional tool models building performance in areas suchas structure, energy, daylighting, artificial illuminationand acoustics. There is a wide range of digital toolsfor simulation, analysis and evaluation of most per-formance aspects. The idea of animation as simula-tion provides architects with an additional opportunityto explore new methods of visualization (Attar et al.2009; Burry 2003; Chaszar et al. 2006; Dino 2012;Kolarevic 2003; Rybczynski 2013). However, a few ofthese models recently began to provide generative andmodification capabilities that are interactive with thepreviously illustrated models.Current theories and technologies of digital design

suggest a shift from analytical simulation to simula-tion for synthesis and generation. These approachesidentify generative processes with performance. In-stead of analysing the performance of a design andmodifying it according to results, performance-basedsimulations can directly modify the geometry of theoriginal designs. In such approaches, the desired per-formance can be activated as a performative mecha-nism to generate and modify designs digitally. Thus,when focusing on the interrelations between structuralmorphology and energy-related aspects, geometry be-comes a key interdisciplinary interface (Oxman 2008;Turrin et al. 2010).

4.1.2 Parameterization for digital fabrication andproject management

In a deep sense, parameterization is not new. Whatis new is the parallel development of an architecturaldesign industry that facilitates fabrication technologyand enables mass customization through digitally con-trolled variation (Aish and Woodbury 2005).

A) Fabricating model.

Another interesting type of modeling consists of fab-ricating models with the aid of parametric design usedin digital fabrication and project management in whichthe design merges into fabrication in a process of directtransfer of data from a 3D modeling software to a CNCmachine. These models make it possible to shape stan-dard building materials using standard machining pro-cesses in order to create customized architecture (Ko-larevic 2003; Larsson et al. 2012). This model employsdigital design and fabrication strategies based on com-putational concepts through the following processes.

• Reverse engineering and digital manipulation.While the digital environment can be invalu-able when deriving, representing and promot-ing designs to construction, a great number ofarchitects still rely on physical modeling tech-niques as a rapid and tangible way to arrive up-on a desired formal scenario. Digital scanning

techniques and computationally based program-ming software have recently allowed architects toscan a physical model for promotion into a digi-tal model which, in turn, allows for further phys-ical manipulation (Panchuk 2006; Schodek et al.2005).

• A file-to-factory process. The concept of the dig-ital chain or file-to-factory process has been ex-plored by researchers and also in several teach-ing projects during the last few years (Larsenand Schindler 2008). This concept refers to theseamless merging of the design process into fabri-cation through direct transfer of data from a 3Dmodeling software to a CNC machine that trans-lates the numerical data into production paths,cutting the material in the desired shape. Theseprocesses allow for a new degree of design con-trol and inspire a renewed architectural interest:in production that incorporates more customizeddetails (Larsson et al. 2012; Oosterhuis et al.2004).

B) Building Information Model (BIM).

One of the most important features of parametricmodeling is that it supports the incorporation of tech-nical knowledge and expertise during the design pro-cess. The BIM can also be used to perform analysisand simulation. Among these different simulation dis-ciplines, the design of sustainable buildings and energysimulation has attracted the most interest among ar-chitects. In this context, BIM technology seems to be anatural companion to building simulation applications(Svetel et al. 2014). The result is a data-rich mod-el that integrates all the information on the construc-tion, including architectural design, structural designand the process of construction and maintenance. Inaddition, architects, structural engineers, builders andowners can effectively generate and coordinate complexdigital documentation (Cavieres et al. 2011; Svobodaet al. 2014).

4.2 Strengths, Limitations and Misconcep-tions

Following the outline of parametric models and theirconceptual framework that support design explorationand optimization in the whole architectural design pro-cess, the paper identifies the limitations of the paramet-ric paradigm as well as some of the major potentialitiesthat emerge from its use in the discipline.

4.2.1 Strengths of the parametric paradigm

This paradigm possesses major potentialities as digitalrealm opens up new fields of possibility. Most impor-tantly, computer numerical control machinery enablesthe fabrication of complex designs directly from com-puter representation. The cost of such fabrication is

178


dropping dramatically and thus opening new realms ofpractical possibility (Woodbury et al. 2006), especiallywith recent software that enables quick analytical feed-back to geometry in order to customize the preferableperformance. Current technologies are, to a certainextent, capable of the integration of design synthe-sis formation processes that are directly informed byperformance-based simulations. The process is com-prised of a generate/evaluate/modify cycle in searchof the optimal performance (Dino 2012; Hudson et al.2011; Hu 2014). As a result, mass production will soonbe overhauled by the principles of customization. Withfabrication models, CAD/CAM digital environmentsare designed to suppress intermediary analogue repre-sentations (2D drawings, 3D visualizations, 3D physi-cal models, written specifications or other), taking ad-vantage of a common digital language (Malé-Alemanyand Sousa 2003; Oosterhuis 2012). Thus, as it entersan exciting new phase, architecture will never be thesame.

4.2.2 Limitations of the parametric paradigm

Parametric applications, models and paradigms playan important role in the process of architectural design.However, they have some limitations as well. Whilemany programs are becoming available to architects,the ability to properly understand and use the softwareis the most important factor, and will vary between de-signers. Parametric systems are principally based onalgorithmic principles, which may require additionaleffort. In addition, buildings and projects, in gener-al, are conceived within a complex web of regulations,various technical constraints and environmental condi-tions, and are meant to operate in a highly dynamicsocio-economic context. Thus, much of the effort inparametric design resides in establishing the relation-ship between parameters. Varying these parametersproduces different designs within a family of designs.The power of algorithms lies in the ability to solve awide range of computational problems, including, butnot limited to, sorting and searching, data structureoperations and combinatorial problems. Therefore, thecomplexity of parametric design becomes even morecompounded in the case of designing bigger structuresor entities (Aish and Woodbury 2005; Cormen 2001;Coyne 2014; Dino 2012; Kolarevic 2003; Peters 2011;Woodbury et al. 2006).

4.2.3 Misconceptions regarding the parametricparadigm

As digital applications developed, morphological ma-nipulations can hardly be separated from the softwarethat defined them. Pierluigi Serraino has written ex-tensively on the theme that form follows software. Hisassessment is that different software tools afford differ-ent ways of design thinking and expression. Like anyprofession, architecture may be a system in flux. New

technologies for CAD environments do not change thisreality; instead, such technologies become players in it(Laiserin 2008; Loukissas 2009; Serraino 2002).Generally, parameterization is a design method, not

a style that can be applied to any design process. Com-putation can eliminate the need for physical modelingor trial-and-error strategies in form optimization, de-sign analysis and synthesis. The goal should be a fine-tuned tool or a set of tools that will truly assist thearchitect during conceptual design and will be so trans-parent that the architect focuses on the design and noton the tool. Another misconception is parametric de-sign is the only way to generate complex geometry. Asa matter of fact, complex geometry in architecture waspresent even before computation was applied in archi-tectural design. However, researchers are now directinggreat attention towards parametric modeling. This ismainly due to the recently emerging visual parametricmodeling tools which hide the algorithmic complexi-ty of parametric models behind a visual programminginterface (Dino 2012; Parthenios 2005).

4.3 The Expanded Role of the Architect

Recent parametric applications in architecturalprojects may illustrate how issues of the parametric-enabled paradigm have been explored and have dealtwith architecture, which requires rethinking how wetraditionally operate as architects. In pre-digital archi-tecture, architects and designers had only traditionaltools to design with. While theory and sketching arestill important to the design process, it is clear thatthe field has made an irrevocable shift to the digitalrealm (Chokhachian and Atun 2014; Jester 2014).Most of the Late Modernist architects and others use

digital parametric tools to maintain a modernist aes-thetic. They have been systematically exploring thepotential of these fine-tuned tools. Beyond the stylisticarchitectural product, most project forms are complextopographical models that were difficult in both repre-sentation and in fabrication in the pre-digital age andcontain many levels of parameterization. Parametricprocesses are very interesting because of the level ofcomplexity they can allow us to reach. Although somepeople may think that parametric design is just archi-tects being lazy, as a matter of fact, parametric de-sign and its processes are easy to learn but extremelyhard to master. Parametric design is now more a pro-cess of learning how to integrate BIM-authoring toolswith concept design, analysis and simulation tools. Thequestion then becomes as follows: what is the archi-tect’s role in all of the design phases? Certainly, archi-tects do not have any effect on the invention of digi-tal tools; instead, they have just accepted and imple-mented them (Abdelmohsen 2008; Chokhachian andAtun 2014; Kolarevic 2005; Rybczynski 2013). In thiscontext, the parametric-enabled paradigm contains awarning that if we do not quickly adapt and take this

179


opportunity, somebody else will; as a result, the role ofarchitects will be marginalized even further.As illustrated in parametric models, computers have

moved beyond digital drafting and now aid architectsin their design exploration and decisions. As a result,the role of the architect is expanding and being rede-fined. The architect himself is going through a stageof transformation, where he has to extend the scopeof his expertise; regulate the mechanisms of knowledgeconstruction and representation; define resources forproblem-solving contexts and manage methods of dataexchange in this new parametric-enabled paradigm, allwhile maintaining the traditional role of the architect.Although this new position may weigh on the architect,it is nonetheless important.The computer can be used to help designers, but the

designers themselves must still understand the contex-tual impacts. Architects that utilize computers mustunderstand that the computer does not replace designfundamentals. It only helps design exploration in anew way, which can act as both a generative and an-alytical method during this exploration, and had re-cently gained great acceptance from practicing archi-tects. However, this does not mean that the digitalparametric system replaces the designer, but that thehuman designer externalizes some of his working in-telligence into the computer to carry out certain de-sign tasks. At the same time, learning this technologyshould not divert architects from the fact that they areartists, and thus harnessing this tool should encouragethe architects to think beyond the tool. Through theircreative work, architects tend to understand culture,society, history and time, which is reflected throughbuildings that represent signs of peopleąŕs social values,beliefs and feelings (Abdelmohsen 2008; Chokhachianand Atun 2014; Dino 2012).

5 RESULTS AND DISCUSSIONS

Architecture and its supporting technologies are ac-companied by rapid change. Implementing this vi-sion means some of the existing variables are delet-ed and others are added. In most cases, as as an ar-chitect begins to work on a real architecture project,he deals with the available technology to constructhis architecture. In addition, the implementation ofnew digital technologies in the design processes is,in a sense, a rational development, from the initialstage of form-finding to the process of manufacturing(Oosterhuis 2012; Stavric and Marina 2011). Howev-er, there is no precise definition and there are oth-er related terms and synonyms related to these tech-nologies. Parametric design is another tool that ar-chitects have to learn(Rybczynski 2013). Such para-metric culture opens up a new line of theoretical dis-course that emphasizes the relationship between archi-tecture and other disciplines. With the introduction

of the parametric-enabled paradigm, one is able to ob-serve a major shift in architectural thinking which willfundamentally change our perspective of architectureand its relation to mathematics (Kotnik 2010).This paper presents a holistic approach for under-

standing the current state of the parametric-relatedparadigm in its broader context. This approach isbased on parametric models which may be incorpo-rated into the architectural design process in the nearfuture, together with some critical remarks about theirrelevance to architecture (see Fig. 3). In my view,there are two reasons to think about parameterization:the first concerns geometric optimization, and the sec-ond concerns models of digital fabrication. Consideringthe interaction between parameters and constraints,designers switched between the different models of theproposed framework to facilitate the discovery of newforms and enhance designs for better performance andproject management.In recent years, many researchers have investigated

the possibility of linking parametric tools with struc-tural analysis and optimization processes. In doing so,architects and structural engineers can explore and ex-amine their designs from the conceptual design phase(Holzer et al. 2007). This requires precise thinkingin order to build interactive models that are flexibleenough for doing variations. Therefore, the designermust expect which kinds of variations he wants to ex-plore in order to determine the kinds of transformationsthe parametric model should do. This is a very diffi-cult task due to the unpredictable nature of the designprocess (Dino 2012). However, parametric design re-quires some thinking at the beginning to identify thelogic behind the design and establish the relationshipsbetween objects. In turn, it is much easier to modify aparametric design than it is to make a change in a non-parametric one. The success of a parametric model liesin the interactive establishment of the constants of thedesign. These constants become applicable to differ-ent scenarios and the result of this interactive processis the design of customized objects; the whole processis circular and repetitive (Aish and Woodbury 2005;Woodbury 2010; Yu et al. 2013).In architecture, there are many parametric models

that cover objective issues, but nothing has yet to coverthe aspects that model human sociability and respons-es to environments. These limits in parameterizationexplain why parametric design only flourishes in theproduction of elegant geometric forms which are moreresponsive to algorithmic control, but which encountermore difficulty to produce architecture controlled byissues of history and culture (Coyne 2014). This, inturn, may explain why parametric modeling has notbeen applied in all architecture, engineering and theconstruction industry. In addition, more human effortbeyond just using a computer is required to build ac-curate parametric models. In this context, many archi-tects may love digital parameterization, but they may

180


Figure 3. Architectural design process: parameters and development

still love their pencils and papers even more. Criticsshould allow the paradigm to just evolve on its own andthen time will tell if parameterization has a long-termfuture in the profession of architecture.

6 CONCLUSION

During the last few years there has been an extraor-dinary improvement in digital tools used to presentor communicate the results of architectural projects.Parametric models enable digital designers to createmore complex structures and remarkable built environ-ments, as well as new understandings of architecturalspaces, both real and virtual. By setting up the log-ical control in the parametric model, multiple designvariations can be generated, modified and evaluated interms of efficiency, quality and design exploration.

The presented paper is first of all meant to providea more holistic approach that aids architects to under-stand various parametric models. These models canthen be used to propose a step for a conceptual frame-work which focuses on understanding the impact of theparametric-enabled paradigm in the architectural de-sign process. The assumption is that there are impor-tant benefits to the implementation of parametric mod-eling techniques. However, such benefits are highly de-pendent on adequate modeling strategies which requireadditional efforts to establish the interactive relation-ship between varied parameters, rules and constraints.Parametric modeling will never replace a designer’s in-tuition and experience, but the software will become anew tool that can aid architects in design explorationand decisions.

REFERENCES

Abdelmohsen, S. (2008). “Building information model-ing and architectural practice: On the verge of a newculture.

Aish, R. and Woodbury, R. (2005). “Multi-level inter-action in parametric design.” In Smart Graphics.

Attar, R., Aish, R., Stam, J., Brinsmead, D., Tessier,A., Glueck, M., and Khan, A. (2009). “Physics-basedgenerative design.” CAAD Futures Conference, 231–244.

Burry, M. (2003). “Between intuition and process:Parametric design and rapid prototyping, in brankokolarevic (ed).” Architecture in the Digital Age.

Caetano, I., Santos, L., and Leitão, A. (2015). “Fromidea to shape, from algorithm to design: A frame-work for the generation of contemporary facades.”Computer-Aided Architectural Design Futures. TheNext City-New Technologies and the Future of theBuilt Environment, Springer, 527–546.

Cavieres, A., G. R.and Gentry, R., and Al-Haddad, T.(2011). “Knowledge-based parametric tools for con-crete masonry walls: Conceptual design and prelim-inary structural analysis.” Automation in Construc-tion, 716–728.

Chaszar, A., Kienzl, N., and Stoller, P. (2006). “Envi-ronmental engineering: Integrating computer simu-lation into the design process in a chaszar.

Chokhachian, A. and Atun, R. (2014). “A frameworkfor exploring the role of parametric design on designprocedure..” unspoken issues in architectural educa-tion - Gazimagusa, North Cyprus, 121–140 (April).

Cormen, T. (2001). “Introduction to algorithms.” TheMIT Press.

Coyne, R. (2014). “What’s wrong with parametricism.”

181


Reflections on Digital Media & Culture.Davis, D. (2013). “Modelled on software engineering:Flexible parametric models in the practice of archi-tecture.” Ph.D. thesis, RMIT University, RMIT U-niversity.

Dino, I. (2012). “Creative design exploration by para-metric generative systems in architecture.” METUJournal of Faculty of Architecture, 29(1), 207–224.

Feng, H. (2013). “Interactive design computation-a casestudy on quantum design paradigm.” Frontiers ofArchitectural Research, 2, 252–262.

Gero, J. (1990). “A locus for knowledge-based systemsin caad education.” The MIT Press, 49–60 In TheElectronic Design Studio: Architectural Knowledgeand Media in the Computer Era, CAAD Futures.

Gero, J. and Maher, M. (1988). “A future role ofknowledge-based systems in the design process.”CAAD Futures ’87, 81–90.

Gero, J. and Maher, M. (2013).Modeling creativity andknowledge-based creative design. Psychology Press.

Hernandez, C. (2006). “Thinking parametric design:introducing parametric gaudi.” Design Studies, 27,309–324.

Holzer, H., Hough, R., and Burry, M. (2007). “Para-metric design and structural optimisation for earlydesign exploration..” International Journal of Archi-tectural Computing, 5(4), 625–643.

Hu, M. (2014). “Performance-based design strategy andparametric design goal setting.” 102ND ACSA annu-al meeting, Miami Beach, Florida, 841–848 (April).

Hudson, R. (2010). “Strategies for parametric design inarchitecture: An application of practice led research.university of bath.” Ph.D. thesis, Ph.D. thesis.

Hudson, R., Shepherd, p., and Hines, D. (2011). “Avi-va stadium: A case study in integrated parametricdesign.” International Journal of Architectural Com-puting, 9(2), 187–204.

Jester, P. (2014). “Shifting gears: Exploring parametricdesign to renovate an urban waterfront. university ofmaryland.” M.S. thesis, M.S. thesis.

Kolarevic, B. (2003). Architecture in the Digital Age -Design and Manufacturing. Spon Press, New Yorkpp.13-28.

Kolarevic, B. (2005). “Architecture in the digital age:Design and manufacturing.

Kotnik, T. (2010). “Digital architectural design asexploration of computable functions.” InternationalJournal of Architectural Computing, 8(1), 1–16.

Krish, S. (2011). “A practical generative designmethod.” Computer-Aided Design, 43, 88–100.

Laiserin, J. (2008). “Digital environments for early de-sign: Form-making versus form-finding.” First Inter-national Conference on Critical Digital: What Mat-ters(s)?, Harvard University Graduate School of De-sign, Cambridge, USA, 235–242 (April).

Larsen, K. and Schindler, C. (2008). “From concept toreality: Digital systems in architectural design andfabrication..” International Journal of Architectural

Computing, 6(4), 397–413.Larsson, M., Kaiser, A., and Girhammar, U. (2012).“From file to factory: Advanced manufacture of en-gineered wood elements - innovative design solutionsfor multi-storey timber buildings throughout the en-tire building process.” World Conference on Tim-ber Engineering, WCTE: Final Papers, New ZealandTimber Design Society.

Lee, J., Gu, N., Jupp, J., and S., S. (2012). “Evaluatingcreativity in parametric design processes and prod-ucts: A pilot study, in gero, j.” Design Computingand Cognition DCCąŕ12.

Liao, K., De Vries, B., Kong, J., and Zhang, K. (2015).“Pattern, cognition and spatial information process-ing: Representations of the spatial layout of ar-chitectural design with spatial-semantic analytics.”16th International Conference, CAAD Futures, S?oPaulo, Brazil, 547– 562 (July).

Lin, B., Yu, Q., L. Z., and Zhou, X. (2013). “Researchon parametric design method for energy efficiency ofgreen building in architectural scheme phase.” Fron-tiers of Architectural Research, 2, 11–22.

Loukissas, Y. (2009). “Keepers of the geometry, in sim-ulation and its discontents.” MIT Press.

Malé-Alemany, M. and Sousa, J. P. (2003). “Hyper [d-m] process.” Proceedings of the 20th Conference onEducation in Computer Aided Architectural Design,eCAADe, 343–346.

Oosterhuis, K. (2012). “Simply complex, toward anew kind of building.” Frontiers of Architectural Re-search, 1, 411–420.

Oosterhuis, K., Bier, H., Aalbers, C., and Boer, S.(2004). “File to factory and real time behavior in ar-chitecture.” Conference Proceedigs ACADIA, ACA-DIA: Responsive Environment, Cambridge, 294–305.

Oxman, R. (2008). “Digital architecture as a challengefor design pedagogy: theory, knowledge, models andmedium.” Design Studies, 29, 99–120.

Panchuk, N. (2006). “An exploration into biomimicryand its application in digital & parametric (architec-tural) design.” M.S. thesis, Waterloo, Ontario, Cana-da.

Parthenios, P. (2005). “Analog vs. digital: why both-er?.” Proceedings of 1st International Conference onCritical Digital, Cambridge.

Pauwels, P., Strobbe, T., Eloy, S., and De Meyer, R.(2015). “Shape grammars for architectural design:The need for reframing.” 16th International Con-ference, CAAD Futures, S?o Paulo, Brazil, 507–526(July).

Peters, T. (2011). “Experimental green strategies: Re-defining ecological design research.” ArchitecturalDesign.

Rybczynski, W. (2013). “Lost amid the algorithms.”Architect, 102(6), 150–158.

Schodek, D., Bechthold, M., Griggs, K., Kao, K., andSteinberg, M. (2005). “Digital design and manufac-turing: CAD/CAM applications in architecture and

182


architectural design.Schumacher, P. (2012). “The autopoiesis of architec-ture, volume ii: A new agenda for architecture.

Serraino, P. (2002). History of Form*Z. Springer Sci-ence & Business Media.

Stavric, M. and Marina, O. (2011). “Parametric model-ing for advanced architecture.” International Journalof Applied Mathematics and Informatics, 1(5), 9–16.

Svetel, I., Jarić, M., and Budimir, N. (2014). “BIM:Promises and reality.” Spatium, (32), 34–38.

Svoboda, L., Novak, J., Kurilla, L., and Jan Zeman, J.(2014). “A framework for integrated design of algo-rithmic architectural forms.” Advances in Engineer-ing Software.

Tepavčević, B. and Stojaković, V. (2012). “Shape gram-mar in contemporary architectural theory and de-sign.” Facta Universitatis-series: Architecture andCivil Engineering, 10(2), 169–178.

Turrin, M., Von Buelow, P., Kilian, A., and Sariy-ildiz, I. (2010). “Performance-based design of solst:a roof system integrating structural morphology andsolar energy transmittance.” Proceedings of the In-ternational Association for Shell and Spatial Struc-tures (IASS), Spatial Structures: Temporary andPermanent Structures for Expo, Shanghai, China, 8-

12 November 2010, China Architecture & BuildingPress.

Woodbury, R. (2010). “Elements of parametric design.”Routledge.

Woodbury, R., Williamson, S., and Beesley, P. (2006).“Parametric modeling as a design representationin architecture: A process account..” Third C-DEN/RCCI International Conference on Education,Innovation, and Practice in Engineering Design,Canadian Design Engineering Network, Toronto,ON, Canada, 158– 165 (July).

Xia, C. (2008). “Research on design methods of energy-efficient design for building scheme.” Ph.D. thesis,Tsinghua University, Beijing.

Yang, Z., Li, X., C., B., Schnier, T., Tang, K., and Yao,X. (2012). “An efficient evolutionary approach to pa-rameter identification in a building thermal model.”IEEE Transactions on Systems, Man, and Cybernet-ics, Part C: Applications and Reviews, Vol. 42, 957–969.

Yu, R., Gu, N., and Ostwald, M. (2013). “Comparingdesigners’ problem-solving behavior in a parametricdesign environment and a geometric modeling envi-ronment.” Buildings, 3(3), 621–638.

183

digital realm: parametric-enabled paradigm in ... · the last decade research into the...

Documents