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

W2-C
Risk Analysis for System Risk Analysis

Room: Salon C   10:30 am–12:10 pm

Chair(s): Zach Collier   zac4nf@virginia.edu

Sponsored by Decision Analysis and Risk Specialty Group



W2-C.1  10:30 am  How Resilience Analytics Addresses Several Participants Disrupting Priorities for Infrastructure Systems. Almutairi A., Andrews D*, Lambert J.H.; University of Virginia, 151 Engineers Way, Charlottesville, VA 22904    aa2ch@virginia.edu

Abstract: Participants in infrastructure development bring a variety of interests and backgrounds, characterized by complexity, interdependency, interconnectedness, and heterogeneous sources of uncertainty. For a decision framework that involves multiple individuals, the disruptive influences of participants must be taken into account. Recent developments in risk analysis and systems engineering have addressed the influence of scenarios to priorities for systems that involve multiple stakeholders, multiple objectives, and uncertainties in several fields of application. Particular recent work in this topic, however, has neglected to address the influence of the participants, which has been a topic of its own in other literature. This study addresses the need to extend resilience analytics and scenario-based preferences to account for the following requirements. First, it will quantify the influence of the level of participation of multiple participants in a scenario-informed assessment and management model. For a given set of future emergent conditions, a power and interest analysis will be performed to quantify the influence of the level of participation for each participant in the priority setting process. Second, it extends a resilience analytics approach to support planning that is influenced by BOTH scenarios of emergent conditions AND the several participants. This approach classifies future scenarios based on their disruptiveness to the priority setting while taking into account the influence of the participation levels of multiple participants on the priority setting. The methods are demonstrated at major container terminals at the United States that handle several million freight containers per year. The above innovation provides an understanding of what sources of uncertainty matter most and least to priority setting, with a critical new emphasis on accounting for the evolving interests of participants.

W2-C.2  10:50 am  Development of an indicator set for resilience quantification of electricity supply. Gasser P*, Suter J, Cinelli M, Lustenberger P, Wansub K, Spada M, Burgherr P, Hirschberg S, Stojadinovic B; Singapore-ETH Centre   patrick.gasser@frs.ethz.ch

Abstract: As our societies increasingly depend on electricity, security of electricity supply has become a central aspect in research and for policy-makers. The present study consists in an analysis of indicators for the assessment of electricity supply resilience on national levels. Resilience was framed as a combination of four biophysical functions, namely the abilities to (1) resist, (2) restabilize and (3) rebuild after disruptions, and (4) reconfigure the biophysical architecture of a system. Hence, unlike previously published security of supply studies, resilience incorporates post-disruption behaviors. As a case study, twenty-six countries in Europe, Asia and North America were chosen according to their electricity generation mixes, economic development, and geographical location. Through an extensive literature survey, an initial indicator set for resilience quantification was established. Each indicator was then assessed using four criteria, namely relevance, credibility of data, accessibility of data, and applicability and comparability, and assigned to the above-mentioned resilience functions. The final set of indicators was validated through correlation analysis and additional statistical tests such as scale reliability. Results show that indicators to characterize pre-disruption behaviors are more developed than the ones for post-disruption behaviors. The latter are represented by the two resilience functions rebuild and reconfigure. Many indicators, especially for the ability to rebuild, are related to financial and qualified personnel resources. Next to conventional diversity indicators, other indicators relate to the political stability of governments, their effectiveness and corruption levels. The indicator set developed can be used for comprehensive resilience assessment. It can support decision-makers in understanding their overall performance, identifying trade-offs between indicators and improvement strategies to achieve higher electricity supply resilience.

W2-C.3  11:10 am  Optimal Checkpointing of Fault Tolerant Systems subject to Correlated Failure. Bentolhoda Jafary BJ*, Lance Fiondella LF; University of Massachusetts Dartmouth, MA, USA   bjafary@umassd.edu

Abstract: Checkpointing is a technique to backup work at periodic intervals so that if computation fails it will not be necessary to restart from the beginning but will instead be able to restart from the latest checkpoint. Performing checkpointing operations requires time. Therefore, it is necessary to consider the tradeoff between the time to perform checkpointing operations and the time saved when computation restarts at a checkpoint. This paper presents a method to model the impact of correlated failures on a system that performs checkpointing. We map the checkpointing process to a state space model and superimpose a correlated life distribution. Examples illustrate that the model identifies the optimal number of checkpoints despite the negative impact of correlation on system reliability.

W2-C.4  11:30 am  Factored Markov Game Theory for Secure and Resilient Infrastructure Networks. Huang, L LH, Chen, J JC, Zhu, Q QZ*; New York University   qz494@nyu.edu

Abstract: With the integration of modern information and communication technologies (ICTs) into critical infrastructures (CIs) such as 5G networks and the Internet of Things (IoTs), the CIs are becoming vulnerable to cyber threats at the same time improving its connectivity and functionalities. Hence it is essential to understand the risk of ICTs on CIs holistically as a cyber-physical system and design efficient security hardening and optimal resiliency mechanisms to reduce the cyber risks. With limited resources, there is an inherent tradeoff between security and resiliency in the mechanism design. To this end, we establish a game-theoretic framework to capture the system behaviors of the CIs under malicious attacks and the security and resiliency design objectives. We propose the factored Markov game theory to enable a computationally scalable modeling of large-scale infrastructure networks and provide approximate algorithms for designing optimal mechanisms. The proposed theory builds on the factored graphs that exploit the dependency structure of the nodes of CIs and the approximate dynamic programming tools for stochastic Markov games. We use electric power networks and transit networks as examples to illustrate the new design paradigm and show the proactive security and adaptive recovery response at the time of unanticipated attacks.

W2-C.5  11:50 am  Resilience of Food, Energy, and Water Infrastructure for Coastal Cities and Displaced Populations. Hassler ML*, Collier ZA, Bier V, Lambert JH; University of Virginia   madison@virginia.edu

Abstract: Mass relocation of individuals in coastal disasters amplifies stressors to food, energy, water, (FEW) and other infrastructure systems. Critical situations become more devastating and unpredictable in their cascading effects. It is important to identify and monitor the most impactful emergent and future conditions for the interdependent infrastructures. Emergent and future conditions include economics, demographics, environment, technology, regulations, agriculture, disease, population and workforce behaviors, and many others. This paper identifies the combinations of conditions that are most and least disruptive to priorities for investments, assets, policies, locations, and organizations. The paper utilizes methodologies of scenario-based preferences, network modeling, and economic value chains to identify strategies to mitigate the adverse effects of population displacements on infrastructures. The approach addresses the resilience of systems on several time scales. The approach considers interrelated phenomena including energy and resource usage in the food-distribution sector, environmental contamination, congestion of passengers and freight, and continuity of governance and emergency services. The impactful scenarios for FEW systems guide the selection of topics for ongoing and future risk analyses that involve multiple domains of expertise.



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