Society For Risk Analysis Annual Meeting 2017

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

Infrastructure Resilience

Room: Salon FG   3:30 pm–5:00 pm

Chair(s): Stanley Levinson

Sponsored by Engineering and Infrastructure Specialty Group

M4-F.1  3:30 pm  Redesigning Resilient Infrastructure Research. Seager TP*; Arizona State University

Abstract: Despite federal policy directives to strengthen the resilience of critical infrastructure systems to extreme weather and other adverse events, several knowledge and governance barriers currently frustrate progress towards policy goals, namely: 1) a lack of awareness of what constitutes resilience, 2) a lack of judgement about how to create resilience, 3) a lack of incentives that motivate resilience, and 4) obstacles that prevent action. I describe each of these barriers in greater detail and provide a catalog of theories for overcoming them. Regarding awareness, I present four different characterizations of resilience as robustness, recovery, graceful extensibility, and sustained adaptability. Integral Theory demonstrates the necessity of integrating multiple investigative perspectives. Resilience is presented as a set of processes, in addition to resources and outcomes. Regarding judgement, theories of human development identify the most critical infrastructure in terms of the services they provide to end users. Regarding incentives, the modes and tools of financial analysis by which investments in resilience infrastructure may be prioritized find two failings: the difficulty of estimating the monetary value of optionality, and the problem of exponential discounting of future cash flows. Regarding obstacles to action, a hierarchy of adaptive actions applicable to physical infrastructure and the essential dimensions of organizational maturity determine how adaptive actions might be initiated. Finally, I discuss the difficulty of education and training for resilient infrastructure systems and propose simulation gaming as an integrative research and education approach for capturing lessons learned from historical catastrophes, play-testing scenarios, sharing knowledge, and training a workforce prepared for the challenges of the post-industrial infrastructure age.

M4-F.3  4:10 pm  Emergent and Future Conditions Disrupting PERT/CPM Schedule Analysis of Infrastructure Systems. Collier ZA*, Lambert JH; University of Virginia

Abstract: Combinations of emergent and future conditions can bring about singular disruptions of project schedules in infrastructure development and management. Existing methods of project management fail to link such disruptions with mission outcomes such as cost, schedule, and quality. This currently limits the efficacy and timeliness of corrective or precautionary actions for interdependent projects with durations of years and expenditures up to billions of US dollars. From a view of risk analysis, this paper will provide understanding of key disruptive conditions for project-activity networks (e.g., PERT/CPM), reprioritizing the constituent activities of projects subject to precedence and other constraints. The approach is critical to guide strategic decision making and system operations to identify and avoid potential deviations from schedule and budgetary targets. The approach will be demonstrated for capacity expansion and operations of a maritime container port with millions of container transactions per year. The demonstration will involve adoption of a schedule analysis, identification of key scenarios and hundreds of candidate emergent and future conditions (technology, economy, demographics, markets, regulation, environment, etc.), and scenario-based preference analysis. The results will characterize the emergent and future conditions that are most and least disruptive to schedule, cost, and technical goals. The paper provides recommendations for revision of associated standards in systems engineering and process operations. The approach is transferable across applications of systems engineering and risk analysis, e.g., environment, health, commerce, regulation, and others.

M4-F.4  4:30 pm  Infrastructure planning under climate change – bridging robustness and probabilistic approaches . Shortridge JE*, Zaitchik BF; Virginia Tech

Abstract: Climate change has the potential to dramatically impact many of our infrastructure systems. Avoiding these impacts will require that infrastructure is built and upgraded with future climate change in mind, particularly in systems with long lifespans that will be operating decades into the future. However, one challenge in incorporating climate change into infrastructure planning is the uncertainty surrounding climate change projections generated by climate models. This uncertainty has been addressed in different ways. For example, some researchers use ensembles of climate models to generate probabilistic climate change projections, but these projections can be highly sensitive to assumptions about model independence and weighting schemes. Because of these issues, other argue that robustness-based approaches to climate adaptation are more appropriate, since they don’t rely on precise probabilistic representation of uncertainty. In this research, we present an alternative approach to infrastructure planning under climate change that leverages methods from both robust decision frameworks and probabilistic climate model ensembles. The Scenario Discovery process is used to search across a multi-dimensional space and identify the climate scenarios most associated with system failure, and a Bayesian statistical model informed by climate model projections is then developed to estimate the probability of those scenarios. This provides an important advancement in that it can incorporate many climate variables instead of just mean temperature and precipitation, and multiple statistical model formulations can be used to account for uncertainty in probabilistic estimates. We demonstrate the methodology using proposed water resources infrastructure in Lake Tana, Ethiopia, where climate model disagreement on changes in future rainfall presents a major challenge for reservoir planning.

M4-F.5  4:50 pm  Current efforts to establish a common methodology and common database for the resilience indicator based assessment. Jovanovic AS*, Oien K; EU-VRi, Steinbeis Advanced Risk Technologies, Germany

Abstract: The resilience of modern societies is largely determined by and dependent on resilience of their critical infrastructures such as energy grids, transportation systems, governmental bodies and water supply. This is clearly recognized by the EU in its policies and research agenda, such as the DRS (Disaster-Resilience) actions and projects safeguarding and securing society, including adapting to climate change. In this context, the issue of “measuring resilience” has an important place and it is tackled primarily by means of indicators. The overall goal of the current research agenda is to improve current approaches by providing an innovative methodology for assessing resilience of critical infrastructure. The EU research project SmartResilience propose a common methodology across all critical infrastructures and all types of hazards or threats based on resilience indicators. The results of the resilience assessment can be used to compare with previous assessment, to provide trends showing how the level of resilience is progressing. Since the calculation is performed on all levels of the model (indicator, issue, phase, threat, critical infrastructures and area/city level), it is also possible to "drill down" and identify the reason for an increase or decrease in resilience compared to the previous assessment. Another use is to compare with other cities, areas or critical infrastructures, i.e. to benchmark against others. The resilience of a city/area or a critical infrastructure can also be assessed by imposing a set of threats (including defined challenges such as interactions and cascading effects), i.e. stress testing the resilience ability of the city/area/critical infrastructure, and compare the results with predefined criteria. The concept presented is practically supported by new tools: the large database of indicators, tools for the assessment of the resilience level, tools for resilience monitoring, big data analysis tools and the advanced visualization tools.

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