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

W4-F
Infrastructure: Climate Changes and Extreme Events

Room: Salon FG   3:30 pm–5:10 pm

Chair(s): Benjamin Rachunok   brachuno@purdue.edu

Sponsored by Engineering and Infrastructure Specialty Group



W4-F.1  3:30 pm  Hurricane Power Outage Prediction with Feature Selection Approaches. Shashaani S*, Guikema SD; Umiversity of Michigan   sshashaa@umich.edu

Abstract: Hurricanes are a prominent natural hazard that affects a large portion of the U.S. population. One of their major impacts is power outages. Hurricane-induced power outages can be widespread and prolonged. They both pose substantial inconvenience and exposure the population to other secondary risks. Predicting hurricane power outages facilitates disaster response decision-making by electric power utilities as well as other organizations of critical importance to society such as water systems and emergency response agencies. However since spatial hurricane outage data is largely zero-inflated with a sizable number of explanatory variables, finding statistical models that can provide reliable predictions remains a challenge. We develop a new model that leverages variable selection techniques by using out of bag performance of the predictors for such datasets to guide the search process. We found promising results experimenting on central gulf coast outage data.

W4-F.2  3:50 pm  Characterising and predicting the robustness of coupled power-law networks. Johnson CA*, Flage R, Guikema SD; University of Stavanger and University of Michigan   caroline.a.johnson@uis.no

Abstract: Many networks exhibit a power-law configuration where the number of nodes connected to a node follows a power-law distribution. Such networks are also referred to as scale-free networks. Examples of power-law networks include the Internet, terrorist cells and species relationships. Given the prevalence of power-law networks, the effects of failures or disruptions on the performance of the network is of interest. Previous work has been conducted on the influence of network topology in relation to the effects of random nodal failures. However, this was limited to independent networks. Many networks depend on others to function and thus, the influence of network topology on the effects of random failures on interdependent networks can be explored. The set-up has been extended to coupled networks or interdependent scale-free networks. Failures in the coupled system are simulated and the effects on the system performance were analysed in relation to the network topology. The results are compared with those of the single system set-up to indicate their potential relevance to the design of interdependent networks.

W4-F.3  4:10 pm  Building Resilience into the Water Treatment Process Under a Changing Climate. Camp JS*, Hoover PA; Vanderbilt University   janey.camp@vanderbilt.edu

Abstract: As climate change evolves, many areas are experiencing more intense, short duration rainfall events and extended periods of drought. While much focus has been placed on the changing availability of water resources for agriculture and other uses, little consideration has been given to the changing quality of these water sources under these conditions and the implications for water treatment for human consumption. Dosing of chemicals such as alum and others to ensure high-quality, safe drinking water is likely to change as water availability and quality changes occur under current and future climate trends. We propose that as shifts in climate occur, so will the demands for certain chemical additives to meet public water quality standards and/or expectations. Emperical data on intake water and treatment for 10 years is compared with historical weather data to discern the extent to which these shifts are occurring already in the Middle Tennessee region and preliminary results will be presented along with a forward look at what the future may hold based upon downscaled climate projections for the mid-century.

W4-F.4  4:30 pm  Risk analysis methods in resilience modeling: an overview of homeland security applications. Baroud H*; Vanderbilt University   hiba.baroud@vanderbilt.edu

Abstract: Resilience modeling has received an increased attention in the past few years due to its importance in homeland security applications, more specifically in protecting and enhancing critical infrastructure systems. As a result, there has been a wealth of qualitative, quantitative, conceptual, and applied frameworks developed to address national preparedness and resilience to potential disruptive events. As such applications involve uncertainty, risk analysis concepts significantly influence the development of resilience frameworks, models, and metrics. This paper constitutes an analysis of risk analysis techniques that are used in resilience modeling with a special focus on critical infrastructures preparedness applications. How is risk analysis used in resilience models? How is resilience defined and modeled in the context of risk? This work seeks to identify opportunities and challenges of leveraging foundational risk analysis and previously developed risk analysis methods to enhance resilience modeling efforts and ultimately strengthen national preparedness and resilience to disruptions.

W4-F.5  4:50 pm  Homogeneous-Use Infrastructure Modeling. Rachunok BA*, Nateghi R; Purdue University   brachuno@purdue.edu

Abstract: We rely increasingly on infrastructure to improve and advance our society. This reliance becomes no more apparent than when infrastructure is exposed to catastrophe and fails. The inability to mitigate extreme events which threaten our infrastructure emphasizes the need to develop infrastructure models and methods of analysis which can support decision making in the planning, development, and maintenance of infrastructure systems. Additionally, infrastructure systems are becoming interdependent, ie power infrastructure relies heavily on internet connectivity. This interdependence increases the complexity of infrastructure analysis and is a key field of study. In this work, we introduce a novel framework for the modeling of infrastructure in which use-case is considered and isolated. Homogeneous-use infrastructure modeling is described as a conceptual framework and its performance relative to other infrastructure modeling approaches is reviewed.



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