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，通过使用准确的多尺度分层计算框架获得地理系统的机械响应，可以明确解释土壤行为的多尺度性质。众所周知，颗粒培养基的行为（例如沙子）是在颗粒尺度上编码的，因此是在相关尺度上对这种行为提高这种行为的方法？ 1M）？是否需要更准确地预测土壤行为。在极端条件下，例如应变定位，穿透或液化，多尺度分析尤为重要，而经典的本构描述可能不再适用。几个未解决的问题说明了研究这种现象的重要性：在各种尺度上，哪些物质参数化最合适？准确的材料描述需要什么相关尺度？不确定性和不均匀性对现场尺度行为的影响是什么？需要跨多个尺度的概率框架来回答这些问题并始终如一地计算跨量表的材料的行为。以前所未有的方式，使用X射线计算机断层扫描的实验结果，以多个尺度开发了土壤孔隙率的概率模型，从而研究空间相关性至毫米量表。从计算的角度来看，使用良好的沙子模型证明了多尺度框架。在这种层次结构方法中，更准确的材料描述？在更细的尺度上？仅在材料或施加的强烈不均匀性的情况下才能追求（例如，变形）。分层方法基于将宏观变形传递到更细的尺度，然后返回更准确的平均应力。 Monte Carlo模拟用于以层次的方式生成材料属性，因此在必要时可以根据先前模拟的粗尺度数据来获得精细的规模材料数据。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，以对多尺度效果很重要的实际问题进行洞察力。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，并将允许科学家和工程师更好地理解更精细的尺度对复杂岩土技术系统的行为的作用。