Assessing Risk for Bridge Management

AASHTO SCOBS T-1 CommitteeJune 27, 2016

NCHRP 20-07/Task 378

Western Management and Consulting, LLC

Paul D. Thompson

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Research Team

Jeff Western, P.E. Co-PIWestern Mgmt and Consulting, LLC

Patricia ByeAsst PIWestern Mgmt and Consulting, LLC

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Paul D. ThompsonCo-PIConsultant

Meghann Valeo, P.E.ResearcherWestern Mgmt and Consulting, LLC

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Briefing Comment NoteNCHRP 20-07/Task 378This investigation was sponsored by TRB under the NCHRP Program. Data reported are work in progress. The contents of this presentation has not been reviewed by the project panel or NCHRP, nor do they constitute a standard, specification, or regulation.

Waseem Dekelbab, PhD, PE, PMPSenior Program OfficerNational Cooperative Highway Research Program500 Fifth Street, NWWashington, DC 20001WDekelbab@nas.edu

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Briefing OverviewOverview of NCHRP 20-07/Task 378

ObjectivesResearch Approach Proposed AASHTO Guidelines

Review Phase I Research Results Literature Review and AnalysisMethodology Development

Comments and Feedback 46/27/16

Research ObjectivesDevelop AASHTO Guidelines for assessing bridge risk

• Data-driven risk assessment at bridge level

• Natural and man-made hazards

• Suitable for Bridge Management System (BMS)

Incorporate Risk Management into Asset Management

• Reconcile data, techniques, jargon, and management methods

• Consider risk in project priorities, resource allocation, and performance management

• Clear definitions, especially “service disruption”

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1. Understanding of Approaches• Review of Literature & Practice• Synthesis

2. Methodology Development• Hazards• Likelihood• Data Availability

3. Guidelines Comments/Feedback• T-1• T-18• SCOBS

4. Final Deliverables• Proposed Methodology• Proposed Guidelines

Major Elements of Project

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Key Findings: Literature Review • Hazard likelihood well documented on a site-specific basis, but

difficult to characterize large groups of bridges as in BMS• Readily-available geographic likelihood data for natural hazards • Often missing link between adverse event and service disruption • Interested in both structural integrity and network resilience • By scouring the literature we found some feasible models

• Some judgment will still be necessary, but we are documenting structured assessment methods– Site-based risk assessments– Network-level planning metrics

• Rapidly developing technologies leave considerable room for future research and enhancement.

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Risk Assessment Approach: Florida

• Excel spreadsheet tools:– Project Level Analysis Tool (PLAT): Risk and LCCA on one bridge– Network Analysis Tool (NAT): Efficiency and resilience of the network

• Likelihood expressed as probability, consequence in dollars • Considers hurricanes, wildfires, tornadoes, flooding, collisions, overloads, fatigue, and

advanced element deterioration• FDOT has efficient means to collect a few additional items for risk analysis

e.g. scour assessment, fatigue details86/27/16

Risk Assessment Approach: Minnesota

• Risk assessment spreadsheet (BRIM), to identify and rank STIP projects

• Relies on judgment-based tables of resilience scores, summarized as Bridge Performance Index (BPI)

• Considers condition, scour, fracture criticality, fatigue, overweight trucks, over-height trucks, driver loss of control, and overtopping of the bridge or approach

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BPI table for superstructure condition

BPI table for scour

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Risk Assessment Approach: New York

• Judgment-based decision tree to compute a Vulnerability Rating

• Relies on modest additional field assessment data

• Used for priority-setting within the safety assurance program, without considering project costs or long-term costs

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Diversity of approaches• All of the systems that link into asset management are

network-wide bridge-level assessments

• All rely primarily rely on BMS data, but each adds a few additional items

• In each case agencies developed a separate module or spreadsheet, not integral to the BMS

• Each system is based on either utility or social cost, but only the social cost based system is fully linked with life cycle cost

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Guidelines Outline IA. Introduction

Background on risk assessment and management, risk-based asset management, and bridge management systemsHow to use this document

B. Bridge Management System Framework for RiskRisk in bridge management systemsPerformance concerns and measuresHazards affecting bridgesAnalyzing risk in AASHTOWare Bridge ManagementGlossary

C. Risk AssessmentDefining hazard scenarios and performance criteria Risk Assessment worksheets

Estimating likelihood of service disruption scenarios (by hazard class)Estimating the consequences of service disruption (performance concerns)

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Guidelines Outline IID. Applications to Risk Management

Risk management treatmentsLevel of service standards for vulnerability/resilienceMitigation costs and treatmentsIncorporating risk in asset management

E. Incorporating Risk in Bridge Management SystemsEstablished risk assessment toolsMethodology in AASHTOWare Bridge ManagementComputation of recovery costs

F. Future Research Needs

G. References and Resources

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Role of Risk in Bridge Management

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• Multi-objective risk management is new in BMS

• Work along-side life cycle cost analysis

• Fit within BMS framework of benefit/cost analysis

• Use readily available data6/27/16

Targeted Software Applications• Can be implemented in AASHTOWare Bridge Management 5.2.3• Other BMS developers can also implement• Stand-alone spreadsheet analysis also feasible

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Architecture: Modular Approach

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Agencies choose based on their risk management concerns and data availability.

Some modules may have multiple computation methods, at varying levels of data requirements.

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Worksheets: Estimation Approaches

Worksheet Philosophy • Take advantage of all available

data. • Use judgment.• Only replace data that might

be gathered later through improved inspection processes or research.

Types of Worksheets• Likelihood of Service

Disruption per Hazard• Consequences of Service

Disruption

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Multiple ways of estimating the likelihood and consequences.

Flexibility to adjust analysis to suit an agency’s needs.

Likelihood of Service DisruptionWorksheets: Hazards Example

For Earthquake hazard, need to estimate metrics that can be applied to probabilities of future seismic events.

Oregon research approach:• Identify bridges in selected

areas potentially impacted from a seismic event.

• Describe potential damage to State highway bridges from six representative earthquake scenarios most likely to occur.

Source: Seismic Vulnerability Of Oregon State Highway Bridges - Mitigation Strategies to Reduce Major Mobility Risk (Oregon State 2009)

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Hazard scenario

District

Respondent

Recollection of past incidents

ID Bridge Year Duration(days)

Impact

123456789

10

Scaling

11 267112 165113 39914 62115 102016 117 0.33%18 12.72%

Number of bridges Heavily DamagedTotal Number of bridges with Total Failure and Heavily Damaged

Earthquake probability (regionally Assumed Probability)Likelihood of service disruption

Total number of bridges in ZoneNumber of bridges not Damaged

Number of M 9.0 in ~300 years

Number of bridges with Total Failure

M9.0 Earthquake

Cascadia Subduction Zone - Oregon

IM456

Please jog your memory and list as many incidents as you can when earthquakes damaged a bridge or otherwise forced a road closure or delay on or under a bridge

Number of Years (Single Event 300 Years)

NCHRP 20-07 (378) Risk AnalysisSheet LD - Earthquake

Likelihood of Service DisruptionWorksheets: Consequences Example

Bridge infrastructure failure can be decomposed into infrastructure cost, human cost, environmental cost, traffic delay cost, as well as economic cost consequences.

Source: Minnesota Department of Transportation. “Economic Impacts of the I-35W Bridge Collapse.” Positively Minnesota Newsletter, Department of Employment and Economic Development, 2008

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1 Bridge ID

2 Forecast year

3 Hazard scenario

Prediction of vehicle and commercial disruption

4 Vehicles requiring alternate routes/day 140,0005 Commercial trucks requiring alternate routes/day 50006 Additional auto travel time 29,0007 Additional commercial truck travel time 203089

Cost of Unavailability

10 Cost Value of additional auto travel time 24700011 Cost value of additional commercial truck travel time 1550012 Travel time cost (TT$) ($/hour) 30.6213 Detour speed (DS) (mph) 4514 Vehicle operating cost (VOC$) ($/mile) 0.20815 Vehicle occupancy (VO) (persons/vehicle) 1.3016 Cost Value of additional operating auto time 12600017 Cost value of additional commercial truck operating time 1200018 Unavailability Cost/Day 400,500

Economic Cost/Day 1130001920 Total Service Disruption Cost 513500

010001

2018

Fatigue

NCHRP 20-07 (378) Risk AnalysisSheet CQ - Cost

Next Steps

• Final proposed guidelines• Define possible implementation approaches

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Questions?

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Thank You

Jeff Westernjeffrey.western@consultingwestern.com

Paul Thompson pdt@pdth.com

Meghann Valeomvaleo@mmvconsult.com

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Western Management and Consulting, LLC

Paul D. Thompson

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Key Findings: Practices Review • States are currently using different methods and models to evaluate risk. In the case

of earthquakes information is relatively well developed in the seismically vulnerable states. The same expertise and capabilities can serve not only in earthquakes, but after other extreme events such as storm surge, wave action, and scour. Databases exist for vehicular impact, floods, fires and other hazards.

• Methods to quantify collision (e.g. over-height trucks) and overload likelihood are currently not well documented. Florida DOT has model of accident risk due to functional deficiencies and histograms of truck height and weight. New York and Florida DOTs have developed methods to assess the likelihood of fatigue damage.

• Florida developed a method to use element level data to compute the likelihood (as a probability) of service disruption due to advanced deterioration. Other states use condition data for this purpose (for example, elements in their worst condition state, or bridges that are structurally deficient due to condition).

• Structural integrity assessment is well established. Network resilience is a more recent practice. While traffic engineers have been focused on this aspect of transportation networks, it is a relatively new concept to structural engineers.

• A number of remote, in-situ, or portable monitoring/damage detection techniques have become available for use in post-event assessment such as sensors, sonar, ground-breaking radar, satellite imagery and unmanned aerial vehicles.

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Implications for MethodologySystems differ in the definition of hazard scenario:

• New York considers three scenarios based on extent of structure damage.• Florida and Minnesota only consider events that interfere with normal traffic flow. • In Florida’s system, the scenario definition differs for different hazards, depending on the

available data and the nature of the hazard. The other systems tend to apply the same criteria across all hazards with less precise definitions.

• Florida and New York explicitly consider the likelihood and consequence of service disruption. Minnesota and the federal sufficiency rating approach do not.

• Florida and New York are also the only two that explicitly consider the likelihood of extreme events.

All systems rely heavily on bridge characteristics that are assessed by inspectors.

All systems apply a multi-objective perspective on consequences: they all consider safety, mobility, and recovery costs in some way, although not always explicitly in the computations.

The Minnesota and New York systems express risk in categories, as does the AASHTO Assessment feature. Florida and the federal sufficiency rating express risk on a continuous scale. The AASHTO system computes utility on a continuous scale.

Performance measures used in benefit/cost prioritization in Florida’s and AASHTO’s systems are expressed on an unbounded scale. The performance measures computed in Minnesota, New York, and the sufficiency rating are on a bounded scale and are not used in benefit/cost analysis.

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Methodology Principles • Be able to accommodate a range of preferences and perspectives

as demonstrated in the various state risk models.

• Be able to address the wide variety of hazards and performance criteria so each agency can select the hazards and criteria of most importance and ignore the rest.

• Behave in a reasonable way to reflect variations in bridge size, utilization, detour distance, difficulty of incident response and recovery, extreme event probability, and other significant variables affecting risk.

• To the greatest extent possible should approximate stable and measurable engineering and economic concepts.

• Be compatible with AASHTOWare BrM and similar bridge management systems that may be developed.

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