professor sujeeva setunge head, civil engineering discipline school of civil, environmental and...
TRANSCRIPT
Doing more with less in managing civil infrastructure: Current challenges and knowledge required for
optimised and sustainable decisions
Professor Sujeeva Setunge
Head, Civil Engineering Discipline
School of Civil, Environmental and Chemical EngineeringRMIT UniversityMelbourne
Civil Environmental and Chemical Engineering
Outline
• Life cycle of infrastructure
• Decision parameters
• Current challenges – doing more with less
• Research projects and outcomes
• A new project – would you like to join ?
Civil Environmental and Chemical Engineering
Plan
Design
Construct
OperateMaintain
Refurbish
Demolish
Life Cycle of Civil Infrastructure
Civil Environmental and Chemical Engineering
Plan
Design
Construct
OperateMaintain
Refurbish
Demolish
Life Cycle of Civil Infrastructure
Civil Environmental and Chemical Engineering
Operate• Risk of failure• Operating Cost• Energy/water use
Maintain
• Timing & Method of inspection,
• Maintenance methods
• Cost
Refurbish
• Refurbish or demolish ?
• Best Material/technique
• Cost
• Sustainability
• Climate change
• Disaster resilience
• Regulatory compliance
• Other ----
Resources constraints
Decision Parameters
Civil Environmental and Chemical Engineering
What is needed to “Do More with Less” ?
• Optimum timing and method of inspections – no more, no less
• Efficient use of inspection data
– Reactive maintenance decisions
– Proactive decision making –forecasting of deterioration
• Maintenance/capital works decisions
– Optimised for the available budget
– Budget required to provide minimum level of service
• Risk of failure
– Probability ? Consequences ?
– Mitigation or adaptation ?
• New challenges
– Vulnerability under disasters, climate change
Civil Environmental and Chemical Engineering
Knowledge gaps
• Forecasting deterioration of different infrastructure
– Using condition data
– Modelling exact mechanisms and reduction in capacity
• Likelihood of failure
– What happens if you do “nothing”
– Extreme events – flood, bush fire, earthquake, storm surge
– Climate change
• Consequences of failure
– Impact on the managing authority
– Impact on the community
– Impact on other stakeholders
• Strengthening of Infrastructure
Civil Environmental and Chemical Engineering
Methods of Deterioration Prediction
Based on condition data• Consecutive inspections of the same components• At least two sets of good data required• One set of data can be used as a snap shot, predictions can be
approximate
Based on understanding of deterioration mechanismsExamples
• Chloride induced corrosion of reinforced concrete structures• Sulphate attack in sewers• Carbonation of concrete structures• Corrosion of steel
Further challengesComponent level ?Network level ?Incorporating interdependencies of multiple assets ?
Civil Environmental and Chemical Engineering
Community Buildings in Australia
• Project funded by Australian Research Council
• Six local councils and Municipal Association as partners
• Condition data collected by partners
• Deterioration forecasting and decision making models developed by researchers
• Stochastic model based on Markov process is used for deterioration prediction and risk estimation
• Integrated software tool developed by RMIT hosted in cloud, field implementation at six local councils
www.assethub.com.au
Civil Environmental and Chemical Engineering
Simplified CAMS Workflow
Create building component hierarchy
Upload component
data
Upload condition
data
Replacement cost report
Deterioration Prediction
CAMS Mobile
Excel Import
RMIT University©2014 School of Civil, Environmental &
Chemical Engineering
Upload level of
service and replacemen
t costs
Excel Import
Display buildings in map using
geo coordinates
Data explorerScenario based risk cost analysis
Backlog maintenance
Excel Import
Civil Environmental and Chemical Engineering
Some Screenshots
RMIT University©2014
School of Civil, Environmental & Chemical Engineering
Civil Environmental and Chemical Engineering
CAMS Analytical OutputData Explorer
Civil Environmental and Chemical Engineering
Civil Environmental and Chemical Engineering
CAMS Analytical OutputScenario Based Backlog analysis – Backlog/Surplus
Civil Environmental and Chemical Engineering
CAMS Analytical OutputScenario Based Analysis
Civil Environmental and Chemical Engineering
CAMS Analytical OutputAnalysis of a selected building – Building Deterioration
Civil Environmental and Chemical Engineering
Technology
Based on Microsoft’s Web Applications Development Platform– Microsoft .NET, SQL Server 2008
Hosted on Amazon Web Services in Sydney– Best in class security, scalability and performance
Each CAMS account runs on a separate database– Data segregation
Cloud based– No hardware or special software required– New features and updates are immediately available for all users– Runs on any compatible browser.
No installations required
RMIT University©2014
School of Civil, Environmental & Chemical Engineering
Civil Environmental and Chemical Engineering
CAMS is available for implementation in interested councils – we will upload data and configure the system for your needs,
• Hands on training workshop scheduled in July 2015. – We will communicate to LGs via MAV
• Training videos available in youtube https://www.youtube.com/channel/UCey4F6BuCknHdDlxkm2bj9w/playlists
• Please contact [email protected] if you are interested in trying.
Civil Environmental and Chemical Engineering
Civil Environmental and Chemical Engineering
Civil Environmental and Chemical Engineering
Civil Environmental and Chemical Engineering
Deterioration modelling of bridges
Level 1- Routine
Maintenance Inspection
Level 2- Structure Condition
Inspection
Level 3- Engineering
Investigation
Element Condition
1 2 3 4
Slab (8P) 70 15 10 5
Girder (2P)
60 30 10 0
BUILDINGS HIERARCHYDeterioration curves of timber elements
Fig. A.1.Deterioration curve of pile Fig. A.2.Deterioration curve of Abutment Fig. A.3. Deterioration curve of Cross beam
Fig. A.4. Deterioration curve of Deck Fig. A.5. Deterioration curve of Girder Fig. A.6.Deterioration curve of Kerbs
Fig. A.7. Deterioration curve of Railing barriers
0.0
0.5
1.0
1.5
2.0
2.5
0 20 40 60 80 100
Age in years
Con
ditio
n
Age VS Condition
0.00.5
1.01.52.0
2.53.0
3.54.0
0 50 100 150Age in years
Con
ditio
n
Age vs Condition
0.00.51.01.52.0
2.53.03.54.0
0 50 100 150
Age in years
Conditi
on
Age vs Condition
0.00.51.01.52.02.53.03.54.0
0 20 40 60 80Age in years
Con
ditio
n
Age vs Condition
0.00.51.01.52.02.53.03.54.0
0 50 100 150Age in years
Con
ditio
n
Age vs Condition
0.00.51.01.52.02.53.03.54.0
0 50 100 150Age in years
Con
ditio
n
Age vs condition
0.00.51.01.52.02.53.03.54.0
0 20 40 60 80Age in years
Con
ditio
n
Age vs Condition
PileAbutment Cross beam
DeckGirder
Kerbs
Barriers
Markov Process used for forecasting
Non-linear optimisation to derive the transition matrices
Civil Environmental and Chemical Engineering
Effect of Climate Change on Seaports
• Project funded by National Climate Change Adaptation Research Facility
• Failure mechanisms and related models adopted for critical elements
• Climate change parameters established
• Changes needed to maintenance regimes identified
• Research into effect of change in sea salinity commenced.
Modelling climate system
• Components
• Interaction
• Human component
• 40 emission scenarios
• 23 global circulation models
• Selected two emissions scenarios
• Hotter/drier/most likely
RMIT University©2012 Civil, Environmental & Chemical Engineering 26
Example: Carbonation of concrete
RMIT University©2012 Civil, Environmental & Chemical Engineering 27
Start
Define exposure and structural design
Input climate variables (T, RH, CO2) and material properties
Calculate carbonation penetration depth, xc(t)
IF xc(t) > cover IF t=2100
NO
YES
Next simulation run
Next year step
Corrosion initiation and damage modelling
IF (finished runs)
Nex
t sim
ulati
on ru
n
NO
Calculate statistics – mean depth, corrosion initiation & damage probability
NO
YES
YES
Outcome for Ports
RMIT University©2012 Civil, Environmental & Chemical Engineering 28
Intervention required
Deterioration threshold
USAid project – modelling of piles at Port Suva
29RMIT University August 2014 Sujeeva Setunge
RMIT University August 2014 Sujeeva Setunge 30
The change in sea salinity on seaports
It is very likely that regions of the ocean with high salinity where evaporation dominates have become more saline, while regions of low salinity where precipitation dominates have become fresher since the 1950s.
This has been confirmed recently by the ARGO Global salinity program – with over 3500 sensors floating worldwide
Laboratory experiments to examine effect of sea salinity on chloride ingress in concrete• Simulated environments varied salinity, humidity,
temperature, and concrete mix design
• Samples were taken at varying depths of concrete to see how the environments changed the rate of ingress.
31RMIT University August 2014 Sujeeva Setunge
Testing continued for six months(Ph.D research – Andrew Hunting)
– notable chloride ingress into the concrete down to depths of 20 mm
– 38.6% increase in chloride content in concrete
– 93% increase in penetration rate in porous concrete
– Humidity increases ingress at the beginning of tests
32
5 10 15 20 25 30 35 40 450.0000
0.0200
0.0400
0.0600
0.0800
0.1000
0.1200
Chloride Content of high porosity vs. low porosity
HPLS Cabinet 0-10mm
HPLS Cabinet 0-20mm
HPLS Cabinet 20-30mm
LPHS Cabinet 0-10mm
LPHS Cabinet 10-20mm
LPHS Cabinet 20-30mm
Salinity
Ch
lori
de
con
ten
t
RMIT University August 2014 Sujeeva Setunge
Civil Environmental and Chemical Engineering
Summary
• Developing capabilities to deliver “more with less” requires addressing the problem from two directions–Fundamental research to understand mechanisms of degradation, accurate predictive modelling, laboratory experiments and field trials to validate
–Top down approach to develop decision making strategies based on limited data which can offer immediate solutions to industry
• RMIT has developed a niche capability to cover both aspects
What’s new ?
Civil Environmental and Chemical Engineering
Automated council tree inventory using airborne LiDAR and aerial imagery
Airborne LiDAR and imagery
Individual tree detection3D tree parameter extraction
Composition, structure and distribution over council area: number of trees, tree density, tree health, leaf area, and species diversity
Location, height, canopy size and extension and species composition
Spatially enabled 3D treesIntegration within council
GIS
Identify and examine the underlying factors that affect
the growth and health of trees
Models for monitoring the changing trend in local council
Tree risk assessment
Planning… …
Will deliver a cost effective tool to conduct tree census
Civil Environmental and Chemical Engineering
1) Develop and validate a new methodology to integrate airbone LiDAR and aerial imagery for improved characterization of tree canopy;
2) Extraction of geometric and physical parameters of individual tree, including location, height, canopy size and extension and species composition;
3) Deliver a cost effective tool to conduct tree census;4) Identify and examine the underlying factors that affect the growth
and health of trees;5) Validate the tool using existing data;6) Disseminate the developed toolkit to the LG and offer training.
Expected outcomes and deliverables
If you like to join this new project, please let us [email protected]
Civil Environmental and Chemical Engineering
Centre for Pavement Excellence Asia Pacific
• Established by Brian O’Donnell, formerly from local govt. and EA forming a consortium of RMIT/ARRB/EA/Latrobe University
• Aims to utilise federal govt. funding available as Aus-aid for Asia Pacific countries, while delivering outcomes for local practitioners
• Will develop guidelines for improved stabilisation of unbound pavements
Civil Environmental and Chemical Engineering
Resilience of critical road structures – bridges, floodways and culverts under natural hazards
Structures:
• BRIDGES• CULVERTS• FLOOD-
WAYS
Hazards:
• EARTHQUAKE• FLOOD• BUSHFIRE• CLIMATE
CHANGE
Enhancing Resilience of Critical Road Structures: Bridges, Culverts and Flood Ways under Natural Hazards
Thank you