Think of it as the civilian equivalent of a war games simulator.” Our objective is to develop computational standards so that social scientists, engineers, economists, doctors, first responders, and everyone else can produce simulators that interact together in a large, all-encompassing simulation of a disaster scenario. But all of the studies are essentially niche studies, belonging in the field of the researchers. “Lots of researchers study disasters, including engineers like me, but also social scientists, economists, doctors, and others. The researchers of this newly funded project are creating a computational framework, using the Flux high performance computing cluster, that will define a set of standards for disaster researchers to use when constructing their models, enabling simulation models to work together.Įl-Tawil explains: “Disaster research is a thriving area because disasters affect so many people worldwide and there is a lot we can do to reduce loss of life and damage to our civil infrastructure.”
Vineet Kamat, Carol Menassa, and Atul Prakash, who will develop the simulation techniques used in the project. On the project team are Jason McCormick, an earthquake engineering expert, Seymour Spence, who has expertise in wind engineering, and Benigno Aguirre, who is a social scientist interested in how people behave during catastrophes. He’s developed 3D models and simulators that show precisely what happens in a building if a particular column or wall is destroyed during an extreme event. Sherif El-Tawil, the lead PI for the project, is a structural engineer interested in how buildings behave, particularly in natural or man-made disasters. Location: Earl Lewis Room, Rackham Building Faculty, staff, and students are welcome to attend. There will also be opportunities for researchers to discuss individualized partnerships with CSCAR and UML to advance specific data-intensive projects.
This event will begin with overview presentations about CSCAR and Library system data services. Many of these services are available free of charge to U-M researchers. This includes consulting, workshops, and training designed to meet basic and advanced needs in data management and analysis, as well as specialized support for areas such as remote sensing and geospatial analyses, and a funding program for dataset acquisitions. As part of the U-M Data Science Initiative, CSCAR and UML are expanding their scopes and adding capacity to support a wide range of research involving data and computation. Representatives of Consulting for Statistics, Computing and Analytics Research ( CSCAR ) and the U-M Library (UML) will give an overview of services that are now available to support data-intensive research on campus. Info Session: Data Science Services at U-M - Nov.
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