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Collaborative Research: Development of Realistic Seismic Input Motions for Improving the Resilience of Infrastructure to Earthquakes

合作研究：开发真实的地震输入运动以提高基础设施的抗震能力

基本信息

批准号：
2053694
负责人：
Chanseok Jeong
金额：
$ 20万
依托单位：
Central Michigan University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-11-01 至 2024-10-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2053694&HistoricalAwards=false
关键词：
Collaborative Research Development Realistic Seismic

项目摘要

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.

从稀疏测量的地震地面运动数据中重建感兴趣区域中的地震波场的能力可以帮助工程师准确地模拟地震期间的潜在损害，提高安全性，并降低成本。真实的地震地面运动对于改善工程师、业主和监管机构对基础设施的设计和评估至关重要。虽然现代传感器(如加速度计、光缆等)可以获得大量的地面运动数据，但没有一种已建立的方法可以从三维(3D)近表面域中的测量重建完整的3分量(3C)入射波场。这一灾难恢复研究补助金(DRRG)项目将通过开发一种新的方法来满足这一需求，该方法可以根据现场测量在与基础设施相邻的土壤/岩石体积内重建完整的3C地震波场。通过这种方法得到的3C地震波场考虑了局部地质和可变性，可以作为结构和基础设施模型的真实地震运动输入，以评估其在地震中的性能。目前使用的水平和垂直地震动单分量(1C)运动在土-结构相互作用分析中引入了许多认知和建模的不确定性。区域尺度的波动模型需要关于震源的信息，以及在产生的地震运动中引入大的认知和情感、参数不确定性的深浅地质信息。该项目将开发一种方法来解决这些问题，并提供准确、真实的地震运动，这将改进地震-土壤-结构相互作用(ESSI)行为的建模和模拟。因此，基础设施和生命线的设计及其对地震反应的评估将得到改进，从而提高对地震荷载的复原力。该方法将被集成到一个公共领域程序Real-ESSI模拟器(http://real-essi.us).该方法将可扩展到各种类型的测量模式(例如，全平移3C、6C(具有旋转3C的平移3C)、仅垂直1C或由离散位置的加速计测量的全3C运动的幅度、由基于视觉的传感器测量的表面振动、或由光缆沿直线测量的3C运动)。一个咨询小组将就该项目提供反馈，以促进将研究转化为工业实践。PIS将开发关于“ESSI系统的逆向建模”的在线教育材料。这样的教育努力和材料不仅有助于教育参与该项目的学生，也有助于教育世界各地的本科生和研究生，以及对ESSI行为建模感兴趣的实践工程师。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。