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Improved Methods for Imaging Fault Rupture: Dynamic Rupture Modeling and Optimal Use of Diverse Data

Improved Methods for Imaging Fault Rupture: Dynamic Rupture Modeling and Optimal Use of Diverse Data
故障破裂成像的改进方法:动态破裂建模和各种数据的优化使用
批准号:
9614168
负责人:
Gregory Beroza
金额:
$16.61万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1997
资助国家:
美国
项目状态:
已结题
起止时间:
1997-03-01 至 2001-02-28

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中文摘要
翻译
9614168 Beroza这项研究是为了开发新的技术,通过对有限断层反问题的动态方法来成像和理解断层破裂。有限故障反问题本质上是欠定的,因此不是唯一的。平滑约束通常是任意的,通常用于稳定解。动态破裂模拟将稳定化参数建立在物理基础上。研究的重点将集中在1)解决动态参数的有限故障逆问题和2)发展一种方法来适当地考虑波形反演中的数据、模型和建模的不确定性。这项研究是国家减少地震灾害计划的一部分。***
英文摘要
9614168 Beroza This research is to develop new techniques for imaging and understanding fault rupture by means of a dynamic approach to the finite-fault inverse problem. The finite-fault inverse problem is inherently under-determined and hence non-unique. Smoothing constraints, often arbitrary, are usually applied to stabilize the solution. Dynamic rupture modeling puts the stabilization parameters on a physical basis. The research will focus on 1) solving the finite-fault inverse problem of dynamic parameters and 2) developing a method to properly account for data, model, and modeling uncertainty in waveform inversion. This research is a component of the National Earthquake Hazard Reduction Program. ***
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Seafloor Fiber Optic Array in Monterey Bay (SEAFOAM)
  • 批准号:
    2023301
  • 项目类别:
    Standard Grant
  • 资助金额:
    $66.62万
  • 财政年份:
    2020
  • 负责人:
    Gregory Beroza
  • 依托单位:
Collaborative Research: Mining Seismic Wavefields
  • 批准号:
    1818579
  • 项目类别:
    Standard Grant
  • 资助金额:
    $12.41万
  • 财政年份:
    2018
  • 负责人:
    Gregory Beroza
  • 依托单位:
The Second Cargese School on Earthquakes - Participant Support
  • 批准号:
    1743284
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.2万
  • 财政年份:
    2017
  • 负责人:
    Gregory Beroza
  • 依托单位:
Collaborative Research: Mining Seismic Wavefields
  • 批准号:
    1551462
  • 项目类别:
    Standard Grant
  • 资助金额:
    $28.66万
  • 财政年份:
    2016
  • 负责人:
    Gregory Beroza
  • 依托单位:
国内基金
海外基金
Computational Methods for Analyzing Toponome Data