Transcript A Framework for AEC/FM Total Project Systems

A GIS-Based Decision Support System for Optimal
Renewal Planning of Sewers
Mahmoud Halfawy, Leila Dridi, & Samar Baker
NRC-Centre for Sustainable Infrastructure Research
INFRA 2007
5-7 November 2007
Québec
Background
• Fragmentation of sewer management data and
processes.
• Need for proactive and optimized renewal planning.
• State-of-practice in sewer management software.
• Challenges for integrating sewer management data,
processes, and software systems.
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NRC-CSIR Integrated
Asset Management Project
• Objective:
– Develop consistent/generalized models and protocols for asset
management process systematization and data integration –
Bridging the vertical (departmental) and horizontal (crossdisciplinary) gaps.
– Develop algorithms and a set of interoperable GIS-based decision
support tools for optimizing and coordinating asset management
plans for water, sewer, and road networks.
• Project Partners: City of Regina.
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Integration of Municipal
Asset Mgt Processes
Vertical Integration
Condition Assessment
Condition Assessment
Condition Assessment
Inspection/Monitoring
Inspection/Monitoring
Maintenance Mgt
Risk Assessment
Risk Assessment
Risk Assessment
Deterioration Modeling
Deterioration Modeling
Deterioration Modeling
Performance Modeling
Performance Modeling
Performance Modeling
Asset Prioritization
Asset Prioritization
Asset Prioritization
Rehab Methods
Rehab Methods
Rehab Methods
Renewal Planning
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Horizontal Integration
Renewal Planning
Optimized & Coordinated Plans
Renewal Planning
4
Prepare Asset Data
Repository
Define planning
horizon
Calculate condition index
Specify budget
scenario
Calculate risk index
Calculate prioritization
ranking
Specify condition/risk
minimum
requirements
Select feasible
rehabilitation options
Specify option criteria &
run MOO & calculate
Pareto fronts
Revise budget
scenario and/or
condition/risk
requirements
Apply Delta
Tables
Select a satisfying
solution
no
Year = Year + 1
Solution
found?
yes
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The Renewal
Planning Step-Wise
Algorithm
Year = 1
Create Delta Tables
no
Year = yes
horizon?
Print
Renewal
plan for
one
scenario
End5
Data and Process Integration Using
Centralized Shared Repositories
Sewer Management Stakeholders
Intranet/
Extranet
GIS and Data Management Services
Spatial and Inventory Data
Performance Data
Maintenance and
rehabilitation Data
Work Order and Operational
Data
Inspection and Condition Data
Integrated
Asset Data
Repository
Financial/Cost Data
Simulation Models/Results
Deterioration/Life cycle cost Data
References to other databases (ERP, CIS, SCADA, etc.)
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ESRI Classes::ComplexEdgeFeature
ESRI Classes::SimpleJunctionFeature
Sewer/Stormwater Line Abstract Class::SewerLine
{GeometryType = esriGeometryPolyline}
«SubtypeField» -Subtype : esriFieldTypeInteger = 1
-FacilityID : esriFieldTypeString
-InstallDate : esriFieldTypeDate
-LifecycleStatus : ssDomainLifecycleStatus = Active
Facility Abstract Class::SewerFacility
«SubtypeField» -Subtype : esriFieldTypeInteger = 1
-FacilityID : esriFieldTypeString
-InstallDate : esriFieldTypeDate
-LocationDescription : esriFieldTypeString
-LifecycleStatus : ssDomainLifecycleStatus = Active
-Elevation : esriFieldTypeDouble
SewerInspectionRecordsAssociation
Part of the UML
class diagram for
the integrated
sewer data
model
SewerHydraulicModelAssociation
SewerRiskAssessmentRecordAssociation
Sewer/Stormwater Line Abstract Class::SewerLine
-Material : ssDomainSewerMaterial
-Diameter : esriFieldTypeInteger
-StartElevation : esriFieldTypeDouble
-StartElevationDescription : esriFieldTypeString = INV
-EndElevation : esriFieldTypeDouble
-EndElevationDescription : esriFieldTypeString = INV
-InstallationDate : esriFieldTypeDate
-InstalledBy : esriFieldTypeString
-maintainedBy : esriFieldTypeString
-FinalBook : esriFieldTypeString
-Status : ssDomainLifecycleStatus = ACTIVE
-Revisit : esriFieldTypeString
-SurveyedLength : esriFieldTypeDouble = 0.0
-StreetKeyNumber : esriFieldTypeString
Network Feature Class::ssManhole
-InstallationDate : esriFieldTypeDate
-MaintainedBy : esriFieldTypeString
-RimElevation : esriFieldTypeDouble
-SumpElevation : esriFieldTypeDouble
-Material : esriFieldTypeString
-Enabled : bool = True
-Revisit : bool = False
-Comments : esriFieldTypeString
Network Feature Class::ssGravityMain
Network Feature Class::Force
-Depth : esriFieldTypeInteger
-Diameter : ssDomainPressurizedMainDiameter
-GroundSurfaceType : esriFieldTypeString
-PressureRating : esriFieldTypeString
-CrossSectionShape : ssDomainGravityMainShapes = Circular
-UpstreamInvert : esriFieldTypeDouble
-DownstreamInvert : esriFieldTypeDouble
-Diameter : ssDomainMainDistributionDiameter = 0
-Slope : esriFieldTypeDouble
Subtype
ssGM Subtype::Main
-Subtype : esriFieldTypeInteger = 1
CCTVInspectionRecord
-InspectionDate : esriFieldTypeDate
-InspectionCrew : esriFieldTypeString
-Contractor : esriFieldTypeString
-CCTVFileName : esriFieldTypeString
-TapeNumber : esriFieldTypeString
-VCRCount : esriFieldTypeInteger
-TotalTime : esriFieldTypeDouble
-SheetNumber : esriFieldTypeInteger
-ReportNumber : esriFieldTypeInteger
-StartMHID : esriFieldTypeOID
-EndMHID : esriFieldTypeOID
-StreetName : esriFieldTypeString
-FromStreet : esriFieldTypeString
-ToStreet : esriFieldTypeString
-CameraDirection : esriFieldTypeString
-FlowDirection : esriFieldTypeString
-WRCRating : esriFieldTypeDouble
ssGM Subtype::Trunk
-Subtype : esriFieldTypeInteger = 2
CCTVInspectionRecordsAssociationClass
-NumberOfInspectionRecords : esriFieldTypeSmallInteger
CCTVAssessmentRecord
1
1..*
-InspectionDate : esriFieldTypeDate
-SheetNumber : esriFieldTypeInteger
-StartPoint : esriFieldTypeDouble
-EndPoint : esriFieldTypeDouble
-DefectCode : esriFieldTypeString
-Description : esriFieldTypeString
-Severity : esriFieldTypeString
-Score : esriFieldTypeInteger
SewerRiskAssessmentAttributes
SewerHydraulicAttributes
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-SewerID : esriFieldTypeOID
-InletNodeID : esriFieldTypeOID
-OutletNodeID : esriFieldTypeOID
-Description : esriFieldTypeString
-Tag : esriFieldTypeString
-Shape : esriFieldTypeString
-MaxDepth : esriFieldTypeDouble
-Length : esriFieldTypeDouble
-Roughness : esriFieldTypeDouble
-InletOffset : esriFieldTypeDouble
-OutletOffset : esriFieldTypeDouble
-InitialFlow : esriFieldTypeDouble
-MaxFlow : esriFieldTypeDouble
-EntryLossCoeff : esriFieldTypeDouble
-ExitLossCoeff : esriFieldTypeDouble
-AvgLossCoeff : esriFieldTypeDouble
-FlapGate : bool = NO
-HydraulicConditionRating : esriFieldTypeDouble
-SewerID : esriFieldTypeOID
-GroupID : esriFieldTypeSmallInteger
-MostRecentInspectionDate : esriFieldTypeDate
-MostRecentConditionRating : esriFieldTypeDouble
-DeteriorationModelID : esriFieldTypeSmallInteger
-RemainingServiceLife : esriFieldTypeDouble
-ProbabilityOfFailure : esriFieldTypeDouble
-RiskAssessmentFormulaID : esriFieldTypeSmallInteger
-RiskFactor1 : esriFieldTypeDouble
-RiskFactor2 : esriFieldTypeDouble
-RiskFactor3 : esriFieldTypeDouble
-RiskFactor4 : esriFieldTypeDouble
-RiskFactor5 : esriFieldTypeDouble
-RiskFactor6 : esriFieldTypeDouble
-RiskFactor7 : esriFieldTypeDouble
-RiskFactor8 : esriFieldTypeDouble
-RiskFactor9 : esriFieldTypeDouble
-RiskFactor10 : esriFieldTypeDouble
-RiskFactor11 : esriFieldTypeDouble
-WeightedRiskFactor : esriFieldTypeDouble
-RiskIndex : esriFieldTypeDouble
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Renewal Planning
Algorithm Implementation
• Define an integrated data model and build asset data repository
(inventory, hydraulic data, condition data, repair/incidence records, risk
parameters, cost data, service levels, etc.).
• Define an integrated condition rating index.
• Define /calibrating deterioration curves.
• Define risk assessment model.
• Define asset prioritization criteria.
• Define renewal technologies database, and algorithm for selecting
feasible options.
• Define a multi-objective optimization (MOO) algorithm (maximize
condition, minimize risk, and minimize budget).
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Sanitary sewers and Vitrified Clay (2881 records)
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Sanitary sewers and pipe condition = 3 (823 records)
Deterioration Modeling
• Largely depends on the quantity and quality of available
condition data.
– May use deterministic or probabilistic models
– Employs many different techniques: regression analysis, Markov
processes, ANN, fuzzy models, etc.
• Our approach:
– Store a library of known or previously calibrated models
– If a sewer or a group has sufficient data to do regression analysis, define
a new model or calibrate an existing model.
– If data is not enough, assist user to select a “suitable” model based on
his/her intuition/experience with the system and the data available.
– As more data become available, the models can be re-defined or recalibrated.
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Condition, Risk & Prioritization
Analysis Tool
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Risk Assessment &
Prioritization Models
•
•
•
•
Risk = Consequence of Failure * Probability of Failure
Criticality factors affecting consequence of failure:
– Sewer type, diameter, depth, embedment soil, land use, road classification,
traffic volume, proximity to critical assets, socio-economic impact, site
seismicity, etc.
Procedure:
– Calculate a Risk Factor (1-5 scale) that reflects the consequence of failure
using a weighted average equation.
– Calculate the likelihood of failure index (LFI) for the sewer, based on its
current age and expected service life.
– Risk Index = RF * LFI
Prioritization ranks sewers based on their “priority index” (1-5 scale) to select
candidates for renewal.
• Priority index is derived from the condition index and risk indices
according to a set of user-defined rules.
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Renewal Methods
Selection Tool
•
Applicability criteria for method selection:
–
–
–
•
Sewer characteristics (diameter, material, depth, type: gravity or
pressure, structural condition state, hydraulic capacity, etc.)
Method characteristics (renewal type (NS/SS/FS), limitations, site and
installation requirements)
Site characteristics (soil type, traffic, water table, etc.)
Cost vs. Condition Improvement:
–
–
–
–
Expected condition improvement
Technology construction cost
Technology overall cost (socio-economic cost)
Expected operational cost after improvement
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Renewal Methods
Selection Tool (Cont.)
Renewal Technologies
Fully Structural
Rehabilitation - Lining
Replacement
Semi-Structural
Non-Structural
Open-Cut(Dig)
Pipe Bursting
Pipe Removal
In-Line
Off-Line
Sliplining
CIPP
Horizontal Directional
Drilling (HDD)
Close fit pipe
Pipe Jacking
Formed in place
Micro-Tunelling
Thermoformed
Auger Boring
Spiral wound
Panel lining
UCL
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GA-Based Multi-Objective
Optimization Tool
•
•
•
•
•
Trade-offs of the renewal
costs vs. network condition Network Average Condition/Risk Index
and risk improvements.
5
Three objective functions
4
for cost, condition, and
S5
Min Condition/Risk Index Limit
S4
risk.
3
Solution using the NSGA II
Dominated Solution
2
S3
algorithm and the Open
Beagle class library.
S2
1
Calculate 2 Pareto fronts
S1
for condition-cost and riskBudget
cost criteria.
Budget Range
Evaluate feasible solutions
and select or synthesize a
solution.
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Conclusions & Future Work
• Integrated approaches and DSSs are critical for supporting proactive
asset management strategies.
• The proposed approach and software prototype provided promising
results.
• Work is ongoing to refine/improve several models employed in the
prototype, and to validate the software with more data sets. These
activities are conducted in collaboration with the City of Regina as well
as other industry partners.
• The software modular architecture facilitated incremental development
and testing, and would also facilitate future extensions, refinement,
and interoperability with other (e.g. legacy) software systems.
• Need to define an industry-wide agenda for developing and adopting
open/standard integrated data & process models, and software
architectures.
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