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Duration:<\/strong>\u00a02017\u20132019<\/p>\nFunding Agency:\u00a0<\/strong>National Science Foundation (#1760258)<\/p>\nFunding Amount:<\/strong>\u00a0$188,873<\/p>\nPI:<\/strong>\u00a0Ali Mostafavi<\/p>\nCo PIs:<\/strong>\u00a0Xia Hu, Bjorn Birgisson, Arnold Vedlitz, Philip Berke<\/p>\nAbstract:<\/strong><\/p>\nCities have a variety of infrastructure systems in place to deal with emergencies and extreme events like hurricanes. The effectiveness and efficiency with which these systems perform is, in part, a function of the severity and characteristics of the specific event relative to the capacities of the individual systems, but also the extent to which these infrastructure systems effectively coordinate. In this Rapid Response Research Grant (RAPID), the Principal Investigators will collect time-sensitive data on the performance of Houston\u2019s flood protection, emergency management, and transportation infrastructure systems and processes in Hurricane Harvey. These data will be used to help identify what inter-organizational planning, communication, and coordination risks exist, what policies and strategies yield network resilience, and which capital investment decisions are optimal. These findings will suggest ways to improve decision-making processes, coordination, and network planning among infrastructure designers and operators, city planners and emergency managers based on better understanding of the underlying interdependencies among infrastructure systems and processes. Hence, the expected results will have significant societal benefits that will help improve public safety and reduce economic losses from extreme weather events.<\/p>\n
The specific tasks to be undertaken are to:<\/p>\n
\n- Map, model, and analyze decision-making processes and human system networks in interdependent infrastructure systems to uncover inter-organizational risks<\/li>\n
- Specify and characterize infrastructure disruptions and cascading failures and their relationships with inter-organizational risks and decision-making processes<\/li>\n
- Examine households? physical and social vulnerabilities influenced by inter-organizational risks and infrastructure disruptions and cascading failures<\/li>\n<\/ol>\n
These tasks will be accomplished through in-depth interviews and participatory workshops with stakeholders and decision-makers (e.g., Flood Control District, Army Corps, City Managers, Infrastructure Engineers, Planners and Utility Companies). Collection of data to assess interdependencies and the subsequent impacts caused by failures in critical infrastructure and a household survey to determine the impacts of infrastructure failures on households in two to three areas in Houston.<\/p>\n\n\t<\/div>\n<\/details>\n\n\n\n\n\n\n\t\n\t\t\n\t\t\t
\n\t\t\t\tStructures of Long-Term Disaster Recovery: Organizational Roles and Collaboration in Six Cities\n\t\t\t<\/span>\n\t\t\t<\/span>\n\t\t<\/div>\n\t<\/summary>\n\n\t\n\t\t
Duration:\u00a0<\/strong>2014\u20132016<\/p>\nFunding Agency:<\/strong>\u00a0National Science Foundation (#1434957)<\/p>\nFunding Amount:<\/strong>\u00a0$221,076<\/p>\nPI:<\/strong>\u00a0Michelle Meyer (Sociology)<\/p>\nCo PIs:<\/strong>\u00a0Walter Gillis Peacock, Shannon Van Zandt, David Bierling, John Cooper Jr.<\/p>\nAbstract:<\/strong><\/p>\nLong-term recovery is the least theorized and studied stage of disasters. Yet, in the past decade, large disasters such as Hurricanes Katrina (2005), Rita (2005), Ike (2008), and Sandy (2012), and smaller but still destructive disasters such as wildfires in Texas (2011) and Colorado (2013), flooding of the Mississippi River (2011), and even technological disasters (West, TX 2013) have left numerous communities struggling with post-disaster planning, unequal and partial recovery outcomes, and recovery efforts that fail to reduce pre-disaster vulnerabilities. Increasing disaster frequencies and impacts mean more communities will struggle, often with little local experience in managing the difficult processes of achieving sustainable and resilient recovery. This research focuses on disaster recovery across different communities to build the knowledge-base and best practices that will help other communities prepare for and plan for disaster recovery. The results of this research will support efforts by local governments and nongovernmental organizations to develop recovery frameworks and plans that will speed disaster recovery and improve fiscal efficiency.<\/p>\n
To accomplish these goals, this research project involves in-depth study and extensive comparative analysis of the structures and networks of groups and organizations involved in disaster recovery efforts across six different communities that recently experienced disasters: Granbury, Texas (2013, tornado), West, Texas (2013, industrial facility explosion), Marion County, Texas (2011, wildfire), Bastrop County, Texas (2011, wildfire), Galveston, Texas (2008, Hurricane Ike), Brownsville, Texas (2008, Hurricane Dolly). Governmental and nongovernmental collaboration during recovery is important, yet which types of collaboration work best for recovery are little understood. Most disaster-related studies on organizational collaboration focus on response and emergency management agencies not on charities and community organizations that work on long-term recovery for two to ten years following a disaster. For each of the case locations, the researchers will conduct in-person interviews with organizational leaders, observe recovery committee and community meetings, document recovery events, and analyze community reconstruction and rehabilitation. This approach will provide rich information that will enable the team to compare and contrast the practices used in the different cases and develop a model of disaster recovery organizational networks. This data will allow the researchers to evaluate the organizational coordination in disaster recovery and describe interactions between various levels of government (local, regional, state, and national). Based on the project outcomes, the researchers will identify promising practices and lessons learned which can be utilized by other communities that are engaged in pre-disaster or post-disaster recovery planning.<\/p>\n\n\t<\/div>\n<\/details>\n\n\n\n\n\n\n\t\n\t\t\n\t\t\t
\n\t\t\t\tREU Site: Studies in Social Inequality and Social Vulnerability\n\t\t\t<\/span>\n\t\t\t<\/span>\n\t\t<\/div>\n\t<\/summary>\n\n\t\n\t\t
Duration:<\/strong>\u00a02014\u20132016<\/p>\nFunding Agency:\u00a0<\/strong>National Science Foundation (#1359240)<\/p>\nFunding Amount:<\/strong>\u00a0$269,997<\/p>\nPI:<\/strong>\u00a0Mark Fossett (Sociology)<\/p>\nCo PIs:<\/strong>\u00a0Walter Gillis Peacock<\/p>\nAbstract:<\/strong><\/p>\nThis Research Experiences for Undergraduates (REU) Sites program at Texas A & M University aims to attract undergraduates to careers in social science research and to increase the participation of talented individuals from under-represented groups (e.g., African Americans and Latinos). The Departments of Sociology (SOCI) and Landscape Architecture and Urban Planning (LAUP) collaborate to host this REU Site that brings undergraduate students majoring in sociology, planning, and related disciplines to participate in an eight-week Summer Institute focusing on Studies of Inequality and Social Vulnerability. The primary student activities are participating in a faculty-supervised research project leading to a research paper and presentation at a professional conference, while supporting activities include a seminar providing grounding in theory, data, and methods relevant for research projects; two research field trips; and workshops on opportunities for graduate education and research careers. The site theme \u201cStudies of Social Inequality and Social Vulnerability\u201d reflects the expertise of the researcher mentors from SOCI & LAUP and is proven effective in attracting applications from African American and Latino students. The eight research mentors have strong research and mentoring credentials and prior experience in overseeing successful NSF REU and SBE programs.<\/p>\n
Students are incorporated into the ongoing research programs of the mentors and assigned individual research projects. Selected examples include: documenting disparities in socioeconomic, residential, and health outcomes by race and poverty-income status; assessing differential vulnerability of social groups to natural and technical hazards; assessing how hazards (e.g., hurricanes and floods) differentially impact ethnic minority, low income, and other vulnerable populations; investigating correlates, causes, and consequences of residential segregation by race and income; conducting historical case studies of the evolution of residential segregation over time in selected cities; and assessing variation in recovery from the impact of hazards. Diversity goals will be served by practices used in prior successful REU Sites. These include working closely with faculty at minority serving universities that have limited STEM student research opportunities to identify promising, motivated students with interests in graduate education and research careers. The proposed REU Site draws on the faculty expertise and institutional resources of two nationally prominent doctoral departments to provide students intensive research experiences based on participating in ongoing research projects, some funded by NSF, relating to social inequality and social vulnerability. Students undertake individual projects directed by faculty mentors and designed to be feasible over the summer institute and within the capabilities of advanced undergraduates. Although the immediate contributions of student projects to science could be modest, the larger intellectual merit is enhancing student research capabilities, understanding of and interest in research, and odds of going on to graduate education and research careers.<\/p>\n\n\t<\/div>\n<\/details>\n\n\n\n\n\n\n\t\n\t\t\n\t\t\t
\n\t\t\t\tRAPID: Technological versus Natural Disasters: Consequences for Early Recovery Planning and Decision-Making at the Community and Household Level\n\t\t\t<\/span>\n\t\t\t<\/span>\n\t\t<\/div>\n\t<\/summary>\n\n\t\n\t\t
Duration:<\/strong>\u00a02013\u20132015<\/p>\nFunding Agency:<\/strong>\u00a0National Science Foundation (#1348070)<\/p>\nFunding Amount:<\/strong>\u00a0$43,893<\/p>\nPI:<\/strong>\u00a0Michelle Meyer<\/p>\nCo PIs:<\/strong>\u00a0Shannon Van Zandt, Walter Gillis Peacock, David Bierling, and John Cooper<\/p>\nAbstract:<\/strong><\/p>\nThe purpose of this Rapid Response Research (RAPID) grant is to explore community and resident post-disaster recovery in two small US towns. Both towns experienced disasters in the spring of 2013, but one town experienced a natural disaster while the other town had a technological disaster. To understand how disaster recovery differs based on the type of disaster, we are comparing the immediate recovery periods in each town. Often researchers compare disaster effects across very different communities or across different time periods. Our research takes advantage of a rare opportunity to compare disaster recovery in communities that are similar in size, location, and cultural traits but faced different disasters at about the same time. We are gathering data from community leaders and residents in both towns to address topics important to disaster recovery, including post-disaster community planning, community-based recovery activities, and residents\u2019 rebuilding or relocating decisions and efforts.<\/p>\n
Although previous research has improved what people know about disasters, how communities recover from them, and what makes communities resilient, there is still a lot to learn. The results of our research will help other communities as they plan for the disasters they face. This research responds directly to efforts by US Federal and state governments to increase the disaster resilience of local communities. Communities across the country face the risk of both types of disaster. Man-made disasters, such as industrial accidents, explosions, or chemical leaks, are a risk for any community that has hazardous facilities located near homes and businesses. Natural disasters, such as tornadoes, floods, hurricanes, and earthquakes, regularly occur across the country. Based on what is learned in this project, recommendations will be made about how other local communities can increase their resilience and be better able to recover from disasters when they do occur.<\/p>\n\n\t<\/div>\n<\/details>\n\n\n\n\n\n\n\t\n\t\t\n\t\t\t
\n\t\t\t\tTexas Census Research Data Center (TXCRDC)\n\t\t\t<\/span>\n\t\t\t<\/span>\n\t\t<\/div>\n\t<\/summary>\n\n\t\n\t\t
Duration:<\/strong>\u00a02011\u20132015<\/p>\nFunding Agency:<\/strong>\u00a0National Science Foundation (#1061410)<\/p>\nFunding Amount:\u00a0<\/strong>$300,000<\/p>\nPI:<\/strong>\u00a0Mark Fossett (Sociology)<\/p>\nCo PIs:<\/strong>\u00a0Dudley Poston (Sociology), Simon Sheather (Statistics), Walter Gillis Peacock (Hazard Reduction and Recovery Center), Rogelio Saenz (UT-San Antonio)<\/p>\nAbstract:<\/strong><\/p>\nThis award provides start-up funding for the establishment of a Research Data Center located in the Texas A&M University Research Park in College Station. A consortium of universities, including Texas A&M University, the Texas A&M University System, the University of Texas at Austin, and Baylor University, will partner with the U.S. Census Bureau to establish and operate the Texas Census Research Data Center (TXCRDC). The TXCRDC will house a secure, state-of-the art computing facility to provide researchers in the surrounding multi-state region access to confidential data files available only through the national network of Census Research Data Centers. By providing access confidential federal data, the TXCRDC will enhance the research capabilities and quality of projects that can be undertaken by researchers in Texas and the surrounding area.<\/p>\n
As one of only a dozen such facilities in the nation, the TXCRDC will serve the needs of a broad, interdisciplinary research community for the purposes of conducting a mix of basic science research and policy research. Research projects conducted in the TXCRDC will involve many dozens of researchers drawn from a variety of scientific disciplines. Projects will address a diverse range of topics including, but not limited to the following: business and management policy; health sciences and health policy; immigration, migration and population distribution and change; urban and regional planning; engineering and social impact analysis; planning for hazards and disasters and assessment of hazards impact and recovery; transportation science and transportation planning and policy; and environmental and energy policies. The center also will provide direct benefits to the federal statistical agencies by enhancing the quality and value of their data and statistical systems.<\/p>\n\n\t<\/div>\n<\/details>\n\n\n\n\n\n\n\t\n\t\t\n\t\t\t
\n\t\t\t\tCollaborative Research: Modeling, Display, and Understanding Uncertainty in Simulations for Policy Decision Making\n\t\t\t<\/span>\n\t\t\t<\/span>\n\t\t<\/div>\n\t<\/summary>\n\n\t\n\t\t
Duration:<\/strong>\u00a0October 2012 \u2013 September 2016<\/p>\nFunding Agency:<\/strong>\u00a0Division of Information & Intelligent Systems (IIS)<\/p>\nFunding Amount:<\/strong>\u00a0$319,125\/4 years<\/p>\nPI:\u00a0<\/strong>Michael Lindell<\/p>\nCo-PI:<\/strong>\u00a0Carla Prater<\/p>\nAbstract:<\/strong><\/p>\nThe goal of this collaborative project (1212806, Ross T. Whitaker, University of Utah; 1212501, Donald H. House, Clemson University; 1212577, Mary Hegarty, University of California-Santa Barbara; 1212790, Michael K. Lindell, Texas A&M University Main Campus) is to establish the computational and cognitive foundations for capturing and conveying the uncertainty associated with predictive simulations, so that software tools for visualizing these forecasts can accurately and effectively present this information about to a wide range of users. Three demonstration applications are closely integrated into the research plan: one in air quality management, a second in wildfire hazard management, and a third in hurricane evacuation management. This project is the first large-scale effort to consider the visualization of uncertainty in a systematic, end-to-end manner, with the goal of developing a general set of principles as well as a set of tools for accurately and effectively conveying the appropriate level of uncertainties for a range of decision-making processes of national importance.<\/p>\n
The primary impact of this work will be methods and tools for conveying the results of predictive simulations and their associated uncertainties, resulting in better informed public policy decisions in situations that rely on such forecasts. Scientific contributions are expected in the areas of simulation and uncertainty quantification, visualization, perception and cognition, and decision making in the presence of uncertainty. Results will be broadly disseminated in a variety of ways across a wide range of academic disciplines and application areas, and will be available at the project Web site (http:\/\/visunc.sci.utah.edu). The multidisciplinary nature of the research and the close integration of the participating research groups will provide a unique educational environment for graduate students and other trainees, while also broadening the participation in computer science beyond traditional boundaries.<\/p>\n\n\t<\/div>\n<\/details>\n\n\n\n\n\n\n\t\n\t\t