| NSF Org: |
CMMI Division of Civil, Mechanical, and Manufacturing Innovation |
| Recipient: |
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| Initial Amendment Date: | November 2, 2021 |
| Latest Amendment Date: | November 2, 2021 |
| Award Number: | 2053836 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Giovanna Biscontin
gibiscon@nsf.gov (703)292-2339 CMMI Division of Civil, Mechanical, and Manufacturing Innovation ENG Directorate for Engineering |
| Start Date: | November 1, 2021 |
| End Date: | October 31, 2024 (Estimated) |
| Total Intended Award Amount: | $200,000.00 |
| Total Awarded Amount to Date: | $200,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
1850 RESEARCH PARK DR STE 300 DAVIS CA US 95618-6153 (530)754-7700 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
CA US 95618-6134 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | DRRG-Disaster Resilience Res G |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.041 |
ABSTRACT
The ability to reconstruct a seismic wave field in a domain of interest from sparsely-measured seismic ground motion data can help engineers to accurately model potential damage during earthquakes, improve safety, and reduce costs. Realistic seismic ground motions are essential for improving design and assessment of infrastructure by engineers, owners, and regulators. Although a large amount of ground motion data are available from modern sensors (e.g., accelerometers, optical cables, etc.), no established method can reconstruct the full 3 component (3C) incident wave field from the measurements in a three dimensional (3D) near-surface domain. This Disaster Resilience Research Grants (DRRG) project will address this need by developing a new method for reconstructing a full, 3C seismic wave field within a soil/rock volume adjacent to infrastructure from field measurements. The resulting 3C seismic wave field obtained by this approach accounts for local geology and variability, and can be used as a realistic seismic motion input into models of structures and infrastructure to assess their performance during earthquakes.
Current use of one component (1C) motions for horizontal and vertical seismic shaking introduces a number of epistemic, modeling uncertainties into soil-structure interaction analysis. Regional-scale wave models need information about seismic sources, and deep and shallow geology that introduces large epistemic and aleatory, parametric uncertainties in the generated seismic motions. This project will develop a method for resolving these issues and providing accurate, realistic seismic motions that will improve modeling and simulation of earthquake-soil-structure interaction (ESSI) behavior. Consequently, design of infrastructure and lifelines and assessment of their earthquake response will be improved, resulting in increased resilience to seismic loading. The method will be integrated into a public domain program, Real-ESSI simulator (http://real-essi.us). The methodology will be scalable to various types of measurement modes (e.g., full translational 3C, 6C (translational 3C with rotational 3C), vertical-only 1C or the amplitude of full-3C motions measured by accelerometers at discrete locations, surface vibrations measured by vision-based sensors, or 3C motions-along-lines measured by optical cables). An advisory panel will provide feedback on the project to facilitate translation of the research into industrial practice. The PIs will develop online educational material on 'Inverse Modeling for ESSI Systems'. Such educational effort and material will help educate not only students working on this project, but also undergraduate and graduate students worldwide, as well as practicing engineers with interest in modeling of ESSI behavior.
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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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Summary: In this NSF project, we developed a new
method that leverages data from earthquake motion
sensors to recreate in detail how buildings and the
ground are shaken during an earthquake. Namely, the
method serves as a tool that lets us replay the
effects of the earthquake on structures and soil,
showing where and when the strongest shaking
happened. This helps engineers figure out which parts
of a building may have been damaged or failed during
the quake. We proved that the recreated motions
closely match the real ones, even when sensors are
spread out on the ground. However, placing sensors
closer together improves the accuracy of the results.
Intellectual Merit: Our method improves on the
traditional approach to analyzing earthquake effects
in several ways. The traditional method requires
detailed data about the materials in a huge area,
including the origin of an earthquake (i.e., a
hypocenter), which makes it expensive, uncertain, and
inaccurate. In contrast, our method only needs
information about the materials in the building and
nearby ground, making it much simpler, cheaper, and
more accurate. It allows engineers to quickly and
accurately analyze how earthquake waves affected
buildings, foundations, and surrounding soils. This
makes it a practical, low-cost tool for monitoring
earthquake damage to structures and underground
systems using data from just a few sensors placed
around the site.
Broader Impacts: Communities affected by earthquakes
need to recover quickly to resume normal activities.
This project helps improve the post-earthquake
resilience of communities by providing a systematic
method to assess seismic impacts on infrastructure.
Accurate simulations based on sensor data and the
presented method can identify weak points in
buildings and surrounding soils, aiding
decision-makers in planning repairs, allocating
funds, and estimating recovery times for critical
infrastructure like hospitals, highways, and power
plants. The presented algorithm, implemented in the
Real-ESSI simulator, will be a publicly available
tool for analyzing earthquake impacts. It can
automatically process seismic data and reconstruct
structural responses to pinpoint potential damage in
key structures. This will help engineers and
emergency responders prioritize repairs and plan
resources effectively. To promote diversity in
engineering, the PIs trained students and postdocs
from underrepresented groups, including a female
undergraduate, a female postoc, a Latin American
postdoc, and others from traditionally
underrepresented groups, through studies in wave
propagation, inverse problems, and machine learning.
Last Modified: 03/05/2025
Modified by: Boris Jeremic
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