Award Abstract # 2131111
Natural Hazards Engineering Research Infrastructure: Computational Modeling and Simulation Center 2021-2025

NSF Org: CMMI
Division of Civil, Mechanical, and Manufacturing Innovation
Recipient: REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE
Initial Amendment Date: September 16, 2021
Latest Amendment Date: July 24, 2024
Award Number: 2131111
Award Instrument: Cooperative Agreement
Program Manager: Giovanna Biscontin
gibiscon@nsf.gov
 (703)292-2339
CMMI
 Division of Civil, Mechanical, and Manufacturing Innovation
ENG
 Directorate for Engineering
Start Date: October 1, 2021
End Date: September 30, 2026 (Estimated)
Total Intended Award Amount: $12,750,000.00
Total Awarded Amount to Date: $12,750,000.00
Funds Obligated to Date: FY 2021 = $3,172,476.00
FY 2022 = $3,377,832.00

FY 2023 = $644,936.00

FY 2024 = $5,554,756.00
History of Investigator:
  • Matthew DeJong (Principal Investigator)
    dejong@berkeley.edu
  • Ahsan Kareem (Co-Principal Investigator)
  • Gregory Deierlein (Co-Principal Investigator)
  • Satish Rao (Co-Principal Investigator)
  • Laura Lowes (Co-Principal Investigator)
  • Sanjay Govindjee (Former Principal Investigator)
Recipient Sponsored Research Office: University of California-Berkeley
1608 4TH ST STE 201
BERKELEY
CA  US  94710-1749
(510)643-3891
Sponsor Congressional District: 12
Primary Place of Performance: University of California-Berkeley
CA  US  94710-1749
Primary Place of Performance
Congressional District:
12
Unique Entity Identifier (UEI): GS3YEVSS12N6
Parent UEI:
NSF Program(s): Natural Hazards Engineering Re
Primary Program Source: 01002324DB NSF RESEARCH & RELATED ACTIVIT
01002425DB NSF RESEARCH & RELATED ACTIVIT

01002122DB NSF RESEARCH & RELATED ACTIVIT

01002324DB NSF RESEARCH & RELATED ACTIVIT

01002223DB NSF RESEARCH & RELATED ACTIVIT

01002223DB NSF RESEARCH & RELATED ACTIVIT

01002425DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 151E, 037E, 1057, 043E, 7231, 041E, 040E, 039E, CVIS, 1576, 038E, 036E
Program Element Code(s): 013Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

The Natural Hazards Engineering Research Infrastructure (NHERI) is supported by the National Science Foundation (NSF) as a distributed, multi-user national facility to provide the natural hazards engineering research community with access to research infrastructure that includes earthquake and wind engineering experimental facilities, cyberinfrastructure (CI), computational modeling and simulation tools, high performance computing resources, and research data, as well as education and community outreach activities. Originally funded under program solicitations NSF 14-605 and NSF 15-598, NHERI has operated since 2015 through separate, but coordinated, five-year research infrastructure awards for a Network Coordination Office, CI, Computational Modeling and Simulation Center (SimCenter), and Experimental Facilities, including a post-disaster, rapid response research facility. This award will renew the SimCenter component of NHERI at the University of California, Berkeley, from October 1, 2021, to September 30, 2025, along with its ten partner institutions: Georgia State University, Johns Hopkins University, Stanford University, University of California at Los Angeles, University of California at San Diego, University of Delaware, University of Michigan, University of Notre Dame, University of Southern California, and University of Washington. The SimCenter?s mission is to provide next generation computational modeling and simulation software tools, user support, and educational materials for natural hazards engineering research to simulate the impact of natural hazards, such as earthquakes and windstorms, on buildings, transportation and lifeline systems, and communities. The SimCenter?s software development is motivated by three grand challenges for natural hazards engineering that entail (1) quantifying the damaging characteristics of earthquakes, hurricanes, and other hazards; (2) assessing the physical and social vulnerabilities of civil infrastructure and communities exposed to hazards; and (3) creating technologies and engineering tools to design, construct, retrofit, and operate a multi-hazard resilient and sustainable infrastructure for the nation. The SimCenter will address these challenges through the development of an extensible library of software components and computational workflows that foster multi-disciplinary research collaboration to simulate the impact of natural hazards on communities with unprecedented scale, complexity, and resolution. Education and outreach activities, including a researcher in residence program for visiting faculty, post doctoral scholars, and students; biennial meetings for developers and current and potential users; seminars; workshops; software training bootcamps; community-engaged working groups; and user support, will empower a collaborative workforce to tackle challenges that can inform decision making on planning, design, and deployment of mitigation strategies to create more resilient communities. This award will contribute to NSF's role in the National Earthquake Hazards Reduction Program (NEHRP) and the National Windstorm Impact Reduction Program (NWIRP).

The SimCenter?s software framework is a robust, open-source, extensible, and cloud-based system that will utilize the high-performance computing (HPC) and data management tools provided by NHERI?s DesignSafe CI web portal (https://www.DesignSafe-ci.org). The SimCenter?s computational tools will be designed to integrate modeling and simulation from the source of a hazard through to assessment of its impact and consequences across multiple scales, e.g., from detailed assessment of damage and repair of individual buildings due to a hurricane to regional impacts on recovery of communities. The software will enable modeling of seismic, wind, and hydrodynamic actions, simulating linear and nonlinear dynamic response to these actions, assessing performance, and analyzing networks. The software framework will aid analysis throughout the modeling and simulation process with advanced tools for workflow management, machine-learning-assisted tools for modeling and inventory development, statistical optimization tools for surrogate model development and calibration, and methods for uncertainty quantification. Testbed studies of regional natural hazard scenarios will drive development by identifying key research needs and integrating needed tools. Test data, refined numerical simulations, and user experiences will be used to build skills and confidence in high-resolution computational models. Desktop application interfaces will provide convenient user control to create computational workflows that combine underlying software components and databases. The software tools will enable unparalleled integration and interoperability of applications empowering multi-disciplinary research teams to collaboratively address the three grand challenges using the best HPC available. Information about the SimCenter research and learning tools is available on the SimCenter page on the NHERI web portal (https://simcenter.designsafe-ci.org).

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 18)
Angeles, Karen and Kijewski-Correa, Tracy "Advancing parcel-level hurricane regional loss assessments using open data and the regional resilience determination tool" International Journal of Disaster Risk Reduction , v.95 , 2023 https://doi.org/10.1016/j.ijdrr.2023.103818 Citation Details
Bangalore Satish, A. and Yi, S.-ri and Nair, A.S. and Arduino, P. "Probabilistic Calibration and Prediction of Seismic Soil Liquefaction Using quoFEM" Proceedings of the 4th International Conference on Performance Based Design in Earthquake Geotechnical Engineering (Beijing 2022) , 2022 Citation Details
Banihashemi, MirAmir and Miliziano, Alessandra and Zsarnóczay, Ádám and Wiebe, Lydell and Filiatrault, Andre "Consequences of consequence models: The impact of economies of scale on seismic loss estimates" Earthquake Spectra , 2024 https://doi.org/10.1177/87552930231220001 Citation Details
Bonus, Justin and Spröer, Felix and Winter, Andrew and Arduino, Pedro and Krautwald, Clemens and Motley, Michael and Goseberg, Nils "Tsunami debris motion and loads in a scaled port setting: Comparative analysis of three state-of-the-art numerical methods against experiments" Coastal engineering , v.197 , 2024 Citation Details
Cai, Yunzhu and Wan, Jiawei and Kareem, Ahsan "A new divergence-free synthetic eddy method for generating homogeneous isotropic turbulence with a prescribed energy spectrum" Computers & Fluids , v.253 , 2023 https://doi.org/10.1016/j.compfluid.2023.105788 Citation Details
Duarte, Thays G. and Arunachalam, Srinivasan and Subgranon, Arthriya "Validation and Error Quantification of Data-Informed Stochastic Wind Models for Performance-Based Wind Engineering Applications" , 2023 Citation Details
Gu, Donglian and Kareem, Ahsan and Lu, Xinzheng and Cheng, Qingle "A computational framework for the simulation of wind effects on buildings in a cityscape" Journal of Wind Engineering and Industrial Aerodynamics , v.234 , 2023 https://doi.org/10.1016/j.jweia.2023.105347 Citation Details
Guo, Yunhui and Wang, Chaofeng and Yu, Stella X. and McKenna, Frank and Law, Kincho H. "AdaLN: A Vision Transformer for Multidomain Learning and Predisaster Building Information Extraction from Images" Journal of Computing in Civil Engineering , v.36 , 2022 https://doi.org/10.1061/(ASCE)CP.1943-5487.0001034 Citation Details
Kijewski-Correa, Tracy and Cetiner, Barbaros and Zhong, Kuanshi and Wang, Chaofeng and Zsarnoczay, Adam and Guo, Yunhui and Lochhead, Meredith and McKenna, Frank "Validation of an Augmented Parcel Approach for Hurricane Regional Loss Assessments" Natural Hazards Review , v.24 , 2023 https://doi.org/10.1061/NHREFO.NHENG-1649 Citation Details
Pan, Fei and Jeon, S. and Wang, B. and McKenna, F. and Yu, S.X. "Zero-shot Building Attribute Extraction from Large-Scale Vision and Language Models." , 2024 Citation Details
Satish, AB and Yi, S and Nair, AS and Arduino, P "Probabilistic Calibration and Prediction of Seismic Soil Liquefaction using quoFEM" , v.52 , 2022 Citation Details
(Showing: 1 - 10 of 18)

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