Research highlights: A new era in disaster research

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By Bob Brustman, U-M Civil and Environmental Engineering Department

University of Michigan researchers have received a $2.5 million NSF grant to develop a computational model that is hoped to significantly advance natural hazards engineering and disaster science.

Natural hazards engineers study earthquakes, tornadoes, hurricanes, tsunamis, landslides, and other disasters. They work to better understand the causes and effects of these phenomena on cities, homes, and infrastructure and develop strategies to save lives and mitigate damage.

Sherif El-Tawil

Sherif El-Tawil

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. 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.

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. The rest of the team includes. Vineet Kamat, Carol Menassa, and Atul Prakash, who will develop the simulation techniques used in the project.

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.

El-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.”

“Lots of researchers study disasters, including engineers like me, but also social scientists, economists, doctors, and others. But all of the studies are essentially niche studies, belonging in the field of the researchers. 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. Think of it as the civilian equivalent of a war games simulator.”

el-tawil-nsf“Developing this common computational language will allow completely new studies to occur. Someone might look at the effects of an earthquake on a particular town and its citizens and then the subsequent effects of infectious diseases. With a common language, we can really examine the cascading and potentially out-of-control effects that occur during catastrophic events.”

Beyond developing the computational standards, they hope to create something like an app store through which researchers can share their simulation models and foster new collaborations and new areas of research. 

The grant also includes funding for a programmer housed at Advanced Research Computing (ARC) that will become a shared resource for the rest of campus. The Michigan Institute for Computational Discovery and Engineering (MICDE) provided support for the grant submission, and will continue to do so post-award.

The project brings together an experienced team with expertise in engineering, social science, and computer science. Six of the seven core members are from the University of Michigan and the seventh is from the University of Delaware.

Team members:

  • Benigno Aguirre, professor, Disaster Research Center, University of Delaware
  • Sherif El-Tawil, professor, Department of Civil and Environmental Engineering, University of Michigan
  • Vineet Kamat, professor, Department of Civil and Environmental Engineering, University of Michigan
  • Jason McCormick, associate professor, Department of Civil and Environmental Engineering, University of Michigan
  • Carol Menassa, associate professor, Department of Civil and Environmental Engineering, University of Michigan
  • Atul Prakash, professor, Department of Electrical Engineering and Computer Science, University of Michigan
  • Seymour Spence, assistant professor, Department of Civil and Environmental Engineering, University of Michigan

Research highlights: Running climate models in the cloud

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Xianglei Huang

Can cloud computing systems help make climate models easier to run? Assistant research scientist Xiuhong Chen and MICDE affiliated faculty Xianglei Huang, from Climate and Space Sciences and Engineering (CLASP), provide some answers to this question in an upcoming issue of Computers & Geoscience (Vol. 98, Jan. 2017, online publication link:

Teaming up with co-authors Dr. Chaoyi Jiao and Prof. Mark Flanner, also in CLASP, as well as Brock Palen and Todd Raeker from U-M’s Advanced Research Computing – Technology Services (ARC-TS), they compared the reliability and efficiency of Amazon’s Web Service – Elastic Compute 2 (AWS EC2) with U-M’s Flux high performance computing (HPC) cluster in running the Community Earth System Model (CESM), a flagship climate model in the U.S. developed by the National Center for Atmospheric Research.

The team was able to run the CESM in parallel on an AWS EC2 virtual cluster with minimal packaging and code compiling effort, finding that the AWS EC2 can render a parallelization efficiency comparable to Flux, the U-M HPC cluster, when using up to 64 cores. When using more than 64 cores, the communication time between virtual EC2 nodes exceeded the communication time in Flux.

Until now, climate and earth systems simulations had relied on numerical model suites that run on thousands of dedicated HPC cores for hours, days or weeks, depending on the size and scale of each model. Although these HPC resources have the advantage of being supported and maintained by trained IT support staff, making them easier to use them, they are expensive and not readily available to every investigator that needs them.

Furthermore, the systems within reach are sometimes not large enough to run simulations at the desired scales. Commercial cloud systems, on the other hand, are cheaper and accessible to everyone, and have grown significantly in the last few years. One potential drawback of cloud systems is that the user needs to provide and install all the software and the IT expertise needed to run the simulations’ packages.

Chen and Huang’s work represents an important firstxiangleihuangpost2016 step in the use of cloud computing in large-scale climate simulations. Now, cloud computing systems can be considered a viable alternate option to traditional HPC clusters for computational research, potentially allowing researchers to leverage the computational power offered by a cloud environment.

This study was sponsored by the Amazon Climate Initiative through a grant awarded to Prof. Huang. The local simulation in U-M was made possible by a DoE grant awarded to Prof. Huang.

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2015-2016 MICDE Research Snapshot

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Professor Karthik Duraisamy (U-M Aerospace Engineering) demonstrates data-driven turbulence modeling.

The Center for Data-Driven Computational Physics was established as a place to concentrate data-driven modeling research across campus. Its activities are focused on ConFlux, a $3.5M groundbreaking cluster funded by NSF with a unique architecture that connects big-data with traditional HPC clusters. ConFlux went online in April, and several teams are already using it, with five projects participating, totaling more than $3M to advance data-driven modeling. Soon, we expect to announce even more successes that are directly attributable to our pioneering role in this research area. 

The Center for Network and Storage-Enabled Collaborative Computational Science was established to tackle the challenges of extracting scientific results collaboratively from large, distributed or diverse data. This research center is a product of the Open Storage Research Infrastructure (OSiRIS), a $5M multi-institutional NSF investment, and is led by MICDE affiliated  research faculty Shawn McKee.

We hosted 16 internationally known speakers in our seminar series, and had a very successful symposium. With speakers including NSF’s ACI Director Irene Qualters, Tom Hughes from ICES, James Sethian from UC Berkeley, Charbel Farhat from Stanford, and Peter Haas from IBM, these events outlined top priorities in our fields, latest research and computing infrastructure, and increased  awareness of the quality and trend-imposing nature of research activities going on at U-M.


Jim Belak (Lawrence Livermore National Laboratory) delivers a talk titled “Preparing for the Future of Computing: Bridging Scales within the Exascale Materials Co-design Center” as part of MICDE Winter 2016 Seminar Series.

MICDE is coordinating or supporting several large proposal submissions to federal agencies. We offer institutional support and our established educational programs to the faculty teams writing these grants. With the backing of our parent unit, Advanced Research Computing, and their technical and consulting services (ARC-Technology Services, and Consulting for Statistics, Computing and Analytics Research), our proposals have proven stronger by virtue of this support in place behind them.

MICDE also is working with the academic units at U-M to identify compelling new directions for hiring faculty who will drive computational science in the future, and supporting these hiring processes. Many of these blue-sky ideas have come from thematic, faculty-led workshops, which we will continue to organize.

NSF EAGER award to study new information and communication technologies in shared connected vehicles

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social_networkMICDE associate director Siqian Shen (PI) will collaborate with Co-PIs Tawanna Dillahunt and Tanya Rosenblat from U-M School of Information to conduct interdisciplinary research for a newly announced NSF EArly-concept Grant for Exploratory Research (EAGER) project.

The goal is to investigate the feasibility, challenges, and opportunities of deploying shared connected vehicles with new information and communication technologies (ICTs), to deliver goods and services in future smart & connected communities (S&CC). In taking on a living-lab approach, the study will engage industry, non-profit partners, and underserved populations in Detroit throughout each phase of the project.

The end result will be 1) improved mathematical models and efficient algorithms for optimizing resource allocation, supply-demand matching, and barrier-free vehicle & ICT operations in centralized and decentralized vehicle-and-service-sharing (V&SS) systems; 2) an articulation of the types of critical services that have the highest impact and are needed most among underserved communities (e.g., access to better healthcare or jobs).