Monthly Archives: September 2016

New pubs in Sustainable and Resilient Infrastructure

The Analytics Lab has two new publications recently accepted in Sustainable and Resilient Infrastructure.Sustainable and Resilient Infrastructure

Barker, K., J. Lambert, C. Zobel, A. Tapia, J. Ramirez-Marquez, L. McLay, C. Caragea, C. Nicholson. 2016. Defining Resilience Analytics. Accepted for publication in Sustainable and Resilient Infrastructure on September 1, 2016.

Zhang, W. and C. Nicholson. 2016. A multi-objective optimization model for retrofit strategies to mitigate direct economic loss and population dislocation. Accepted for publication in  Sustainable and Resilient Infrastructure on September 19, 2016.

Defining Resilience Analytics

Dr. Nicholson along with Dr. Kash Barker (OU),  Dr. Cornelia Caragea (UNT), Dr. James Lambert (UVA), Dr. Laura McLay (Univ of Wisconsin), Dr. Chris Zobel (Virginia Tech), Dr. Andrea Tapia (Penn State), and Dr. Jose Ramirez-Marquez (Stevens Institute) have collaborated on this perspective article funded by their NSF award.

Abstract: Theory, methodology, and applications of risk analysis contribute to the quantification and management of resilience. For risk analysis, numerous complementary frameworks, guidelines, case studies, etc., are available in the literature. For resilience, the documented applications are sparse relative to numerous untested definitions and concepts. This essay on resilience analytics motivates the methodology, tools, and processes that will achieve resilience of real systems. The paper describes how risk analysts will lead in the modeling, quantification, and management of resilience for a variety of systems subject to future conditions including technologies, economics, environment, health, developing regions, regulations, etc. The paper identifies key gaps where methods innovations are needed, presenting resilience of interdependent infrastructure networks as an example. Descriptive, predictive, and prescriptive analytics are differentiated. A key outcome will be the recognition, adoption, and advancement of resilience analytics by scholars and practitioners of risk analysis.

A multi-objective optimization model for retrofit strategies to mitigate direct economic loss and population dislocation

This work is part of the NIST-funded Center of Excellence in Community Resilience and will be published in a special edition of Sustainable and Resilient Infrastructure focused on some of the initial analysis conducted by the Center.

Abstract: One strategy to mitigate social and economic vulnerabilities of communities to natural disasters is to enhance the current infrastructure underlying the community. Decisions regarding allocation of limited resources to improve infrastructure components are complex and involve various trade-offs. In this study, an efficient multi-objective optimization model is proposed to support decisions regarding building retrofits within a community.
In particular, given a limited budget and a heterogeneous commercial and residential building stock, solutions to the proposed model allow a detailed analysis of the trade-offs between direct economic loss and the competing objective of minimizing immediate population dislocation. The developed mathematical model is informed by earthquake simulation modeling as well as population dislocation modeling from the field of social science. The model is applied to the well-developed virtual city, Centerville, designed collaboratively by a team of engineering experts, economists, and social scientists. Multiple Pareto optimal solutions are computed in the case study and a detailed analysis regarding the various decision strategies is provided.

Sustainable and Resilient Infrastructure is an interdisciplinary journal that focuses on the sustainable development of resilient communities.

Sustainability is defined in relation to the ability of infrastructure to address the needs of the present without sacrificing the ability of future generations to meet their needs.  Resilience is considered in relation to both natural hazards (like earthquakes, tsunami, hurricanes, cyclones, tornado, flooding and drought) and anthropogenic hazards (like human errors and malevolent attacks.)  Resilience is taken to depend both on the performance of the built and modified natural environment and on the contextual characteristics of social, economic and political institutions. Sustainability and resilience are considered both for physical and non-physical infrastructure.

Contributions address pressing societal issues while exploring needed solutions.  Investigating sustainability and resilience from an interdisciplinary perspective, the journal includes original articles, reviews, short communications and case studies in all areas relevant to sustainability and resilience.


Open Faculty Position: Cyber-Physical-Social Systems

Open Faculty Position in ISE

The School of Industrial and Systems Engineering at the University of Oklahoma is recruiting to fill an open tenure-track faculty position to begin in August 2017.  The position should help further our existing core research efforts in Cyber-Physical-Social systems in particular as it relates to the broad field of resilience.  The Analytics Lab @ OU is actively engaged in research in regards to both community resilience and critical resilient interdependent infrastructure systems and processes.

This position will also help support the Data Science and Analytics graduate program in the College of Engineering.   The full position announcement is available as a PDF in the link below.  Here is an excerpt of the position description.  Applicants are encourage to apply by November 1, 2016.

Open Faculty Position

The full position announcement can be found here: ISE Faculty Open Position

The University of Oklahoma is a Carnegie-R1 comprehensive public research university known for excellence in teaching, research, and community engagement, serving the educational, cultural, economic and health-care needs of the state, region, and nation from three campuses: the main campus in Norman, the Health Sciences Center in Oklahoma City, and the Schusterman Center in Tulsa.

OU enrolls over 30,000 students and has more than 2,700 full-time faculty members. Norman is a culturally rich and vibrant town located in the Oklahoma City metro area. With outstanding schools, amenities, and a low cost of living, Norman is a perennial contender on the “Best Places to Live” rankings.

The University of Oklahoma, in compliance with all applicable federal and state laws and regulations, does not discriminate on the basis of race, color, national origin, sex, sexual orientation, genetic information, gender identity, gender expression, age, religion, disability, political beliefs, or status as a veteran in any of its policies, practices, or procedures. The University of Oklahoma, recognizing its obligation to guarantee equal opportunity to all persons in all segments of University life, reaffirms
its commitment to the continuation and expansion of positive programs which reinforce and strengthen its affirmative action policies. This commitment stems not only from compliance with federal and state equal opportunity laws but from a desire to ensure social justice and promote campus diversity. Our commitment to the concept of affirmative action requires sincere and cooperative efforts throughout all levels of our employment structure. We will continue to strive to reach the goals of fair and equal employment opportunities for all.