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Collaborative Research: Characterization of Random Fields and their Impact on the Mechanics of Geosystems at Multiple Scales

Collaborative Research: Characterization of Random Fields and their Impact on the Mechanics of Geosystems at Multiple Scales
合作研究:随机场的表征及其对多尺度地球系统力学的影响
批准号:
0727121
负责人:
Jack Baker
金额:
$9.24万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-09-01 至 2010-03-31

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中文摘要
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英文摘要
In this research, the multi-scale nature of soil behavior is explicitly accounted for by obtaining the mechanical response of geosystems using an accurate multi-scale hierarchical computational framework. It is well known that the behavior of particulate media, such as sands, is encoded at the granular-scale and hence methods for up-scaling such behavior across relevant scales of interest?from granular-scale (~1mm) to field-scale (1m)?are needed to attain a more accurate prediction of soil behavior. Multi-scale analysis is especially important under extreme conditions such as strain localization, penetration or liquefaction, where the classical constitutive description may no longer apply. Several unanswered questions illustrate the importance of studying such phenomena: What material parameterizations are most appropriate at various scales? What are the relevant scales needed for an accurate material description? What are the impacts of uncertainties and inhomogeneities on field-scale behavior? A probabilistic framework across multiple scales is needed to answer these questions and to consistently compute the behavior of the material across scales. In an unprecedented fashion, probabilistic models for soil porosity are developed at multiple scales, using experimental results from X-Ray computed tomography to study spatial correlation down to the millimeter scale. From a computational standpoint, the multi-scale framework is demonstrated using well-established models for sands. In this hierarchical approach, a more accurate material description?at finer scales?is pursued only in the presence of strong inhomogeneities, either material or imposed (e.g. by deformations). The hierarchical approach is based on passing the macroscopic deformation down to the finer scale(s) and then returning more accurate, averaged stresses. Monte Carlo simulation is used to generate material properties in a hierarchical manner, so that fine scale material data can be obtained whenever necessary, conditional upon previously simulated coarse scale data. These modeling approaches will be developed and then used in several parametric and validation studies to bring insight to practical problems where multi-scale effects are important. Multi-scale modeling opens the door to develop design-specific engineering systems with desirable qualities or properties, and will allow scientists and engineers to better understand the role of finer scales on the behavior of complex geotechnical systems.
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Assessing Urban Post-Earthquake Community Recovery to Inform Pre-Disaster Planning
  • 批准号:
    2053014
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.94万
  • 财政年份:
    2021
  • 负责人:
    Jack Baker
  • 依托单位:
Planning Grant: Engineering Research Center for Data for Socio-Physical Extreme Event Resilience (Data-SPEER)
  • 批准号:
    1840435
  • 项目类别:
    Standard Grant
  • 资助金额:
    $10.0万
  • 财政年份:
    2018
  • 负责人:
    Jack Baker
  • 依托单位:
CAREER: Assessment of Infrastructure Risk Under Natural Disasters in a Multiscale Probabilistic Framework
  • 批准号:
    0952402
  • 项目类别:
    Standard Grant
  • 资助金额:
    $40.35万
  • 财政年份:
    2010
  • 负责人:
    Jack Baker
  • 依托单位:
A Comprehensive Approach for Incorporating the Effects of Near-Fault Directivity into Design Criteria
  • 批准号:
    0726684
  • 项目类别:
    Standard Grant
  • 资助金额:
    $25.0万
  • 财政年份:
    2008
  • 负责人:
    Jack Baker
  • 依托单位:
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
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Cell Research (细胞研究)