Society For Risk Analysis Annual Meeting 2013

Session Schedule & Abstracts


* Disclaimer: All presentations represent the views of the authors, and not the organizations that support their research. Please apply the standard disclaimer that any opinions, findings, and conclusions or recommendations in abstracts, posters, and presentations at the meeting are those of the authors and do not necessarily reflect the views of any other organization or agency. Meeting attendees and authors should be aware that this disclaimer is intended to apply to all abstracts contained in this document. Authors who wish to emphasize this disclaimer should do so in their presentation or poster. In an effort to make the abstracts as concise as possible and easy for meeting participants to read, the abstracts have been formatted such that they exclude references to papers, affiliations, and/or funding sources. Authors who wish to provide attendees with this information should do so in their presentation or poster.

Common abbreviations

M2-I
Symposium: Advances in Risk Models for Infrastructure Management and Investment

Room: Latrobe   10:30 AM- 12:00 PM

Chair(s): Shital Thekdi   sthekdi@richmond.edu

Sponsored by EISG



M2-I.1  10:30  Building an integrated assessment methodology for national infrastructure risk assessment due to climate hazards. Pant R*, Thacker S, Hall JW, Barr S, Alderson D; University of Oxford,University of Oxford,University of Oxford,Newcastle University, Newcastle University   raghav.pant@ouce.ox.ac.uk

Abstract: For modern cities addressing critical infrastructure risk has become very relevant from a safety and security point of view. As seen in recent times, among the different shocks that large-scale infrastructures are exposed to climate hazards have the potential of causing the most widespread disruptions. As such it is important to have an understanding of the risks due to extreme climate events if we plan towards future infrastructure protection and sustainable. In this research we have developed a national infrastructure risk assessment tool that improves our understanding of interdependent infrastructure failures and provides answers to important aspects of damage propagation across infrastructures. The risk assessment tool estimates some key aspects of spatial infrastructure risk which include finding: (1) The scenarios and probabilities of national infrastructure failures; (2) The locations of key vulnerabilities in national infrastructure networks; (3) The implications of interdependent failure propagation; (4) The consequences of national infrastructure failures; (5) The sensitivity of the national infrastructures to multiple climate loading conditions and system states. We provide a demonstration of the risk assessment tool through some initial analysis of interdependent national-scale energy and transport networks risk analysis. The outcomes of such analysis provide important insights into critical infrastructure protection and risk management.

M2-I.2  10:50  Developing a multi-phase, iterative and collaborative decision coordination process for transportation infrastructure management. Andrijcic E.*, Haimes Y.Y.; Rose-Hulman Institute of Technology, University of Virginia   ea2r@virginia.edu

Abstract: The practice of persistent infrastructure underinvestment, coupled with a significant growth in commercial and non-commercial transportation demand, has left the U.S. transportation infrastructure unable to adequately support current and future needs. The lack of political will to allocate the needed funds to bridge infrastructure improvement stems, in part, from the disharmonious goals and objectives among the various stakeholders, and political and other decision makers, as well as the lack of appreciation of the critical interdependencies among the myriad sub-systems of the bridge infrastructure. To address this challenge, we present a multi-phase, iterative and collaborative decision coordination process that is based on the theory of intrinsic meta-modeling via shared state variables. The developed approach enables the harmonization of multiple models representing varied sub-systems and stakeholders’ perspectives. The approach provides decision makers with the ability to better visualize and collaboratively coordinate their shared and conflicting interests with the purpose of achieving public policy solutions for transportation infrastructure that are satisficing to all involved stakeholders, and sustainable over a long planning horizon. We present an illustrative example in which we utilize the meta-modeling coordination to explore the engineering, social, economic, and political implications of insufficient bridge maintenance. We focus on the evolving nature of objectives, interest groups, organizational, political and budgetary baselines, and requirements associated with varied stakeholders, and show that the meta-modeling coordination process enables all stakeholders and decision makers to plan for future emergent changes through collaborative and foresighted efforts. Additionally, we illustrate how the developed process could be utilized to more equally distribute risk ownership among all involved stakeholders.

M2-I.3  11:10  An iterative value of information approach using scenario-based preferences for risk analysis of infrastructure systemsThis is the title. Hamilton MC*, Lambert JH; University of Virginia   mcg7w@virginia.edu

Abstract: Risk analysis is too often applied ad hoc to factors that later turn out to be of little importance to an investment problem at hand. The selection of sources of risk for future analyses ought to be conditioned on knowledge that the risks have a significant influence to priorities of stakeholders. This paper describes integrating three parts of analysis to ensure that risk analysis is focused on significant factors in risk management of large-scale systems: (i) scenario-based preferences analysis combines factors into scenarios that influence priority-setting; (ii) systems analysis with multiple criteria ensures that expertise and concerns of diverse stakeholders are represented; (iii) value of information analysis supports dialogue and negotiation in adaptive iterations. The above steps focus risk and uncertainty analysis towards factors and stakeholder concerns with significant influence to decision-making. This research is unique to combine scenario-based preferences with a value of information philosophy to guide iterative steps of the decision analysis. The combination of factors provides a basis on which to update the investment alternatives, evaluation criteria, and future scenarios in subsequent analyses. The result aids agencies and industry in achieving a more holistic, risk-informed understanding of strategic planning problems. The integration of the three elements is demonstrated on a case study of energy systems of military and industrial installations considering investments in renewable energy, microgrids, and natural gas microturbines, among others. We provide a quantitative demonstration that addresses cost-risk-benefit of several alternatives in multiple iterations of scenario analysis. Scenarios include combinations of future and emergent factors that span technology, climate, economy, regulatory, socio-economic, and others.

M2-I.4  11:30  Robust supply chain investments for disaster preparedness and community resilience: An application to Rio de Janeiro, Brazil. Connelly EB*, Lambert JH, Thekdi SA; University of Virginia, University of Virginia, University of Richmond   ec5vc@virginia.edu

Abstract: Effective disaster preparedness and response requires investment in resilient and agile emergency management systems. Meanwhile there are scarce resources for emergency supply chains and related operations. Resource allocations to these systems must consider multiple criteria and deep uncertainties related to population behaviors, climate change, innovative technologies, wear and tear, extreme events, and others. The methods demonstrated in this paper help to prioritize among emergency supply chain investments by employing an integration of scenario analysis and multi-criteria decision analysis. The results will aid emergency management agencies in maintaining and increasing performance of emergency supply chains and logistics systems. The methods will be applied to disaster reduction initiatives of first- responder agencies in Rio de Janeiro, Brazil, whose overall society and favela populations are vulnerable to landslides, blackouts, radiological events, etc., and will host in the next few years the World Cup and the Olympics.



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