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: Stanford University
• 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
• 起止时间: 2007-09-01 至 2010-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0727121&HistoricalAwards=false
• 关键词: Collaborative; Research; Characterization; Random; Fields

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.

在这项研究中，土壤行为的多尺度性质明确占通过获得地质系统的机械响应，使用一个准确的多尺度层次计算框架。这是众所周知的，颗粒介质，如沙子，的行为是在颗粒尺度上编码，因此，在相关的利益尺度上放大这种行为的方法？从颗粒尺度（~ 1 mm）到现场尺度（1 m）？以获得更准确的土壤行为预测。在应变局部化、渗透或液化等极端条件下，多尺度分析尤其重要，因为经典的本构描述可能不再适用。几个尚未解答的问题说明了研究此类现象的重要性：在各种尺度下，什么材料参数化最合适？准确描述材料所需的相关尺度是什么？不确定性和不均匀性对场尺度行为的影响是什么？需要一个跨多个尺度的概率框架来回答这些问题，并一致地计算跨尺度材料的行为。在一个前所未有的方式，土壤孔隙度的概率模型在多个尺度上开发，使用X射线计算机断层扫描的实验结果，研究空间相关性下降到毫米尺度。从计算的角度来看，多尺度框架证明了使用完善的模型砂。在这种分层的方法中，更准确的材料描述？在更精细的尺度上？仅在存在强不均匀性的情况下进行，无论是材料的还是强加的（例如通过变形）。分层方法基于将宏观变形向下传递到更精细的尺度，然后返回更准确的平均应力。蒙特卡罗模拟用于以分层方式生成材料属性，以便在必要时可以根据先前模拟的粗尺度数据获得细尺度材料数据。这些建模方法将被开发，然后在几个参数和验证研究中使用，以深入了解多尺度效应很重要的实际问题。多尺度建模为开发具有理想质量或特性的特定设计工程系统打开了大门，并将使科学家和工程师能够更好地了解更精细尺度对复杂岩土系统行为的作用。