Development of Algorithms for the Quantification and Simulation of Three-Dimensional Microstructure in Granular Materials

该奖项支持的研究旨在开发一套体视学算法，以便从实验室测试的样品的计算机断层扫描(CT)结果中稳健地量化颗粒土壤的三维结构。这些算法将允许在多个尺度上明确地描述样品中的固体和空隙空间。这种方法对于测量、描述、量化和建模颗粒材料的结构的方式具有潜在的变革性。当这些算法与现有的颗粒形状量化和模拟方法相结合时，将允许从实验室测量中提取前所未有的大量信息，如果需要，还可以用于离散的数值模拟。目前，用于颗粒材料微观结构研究的实验方法和数值方法之间存在着严重的脱节。实验方法依赖于在实验室中观察真实材料的响应，而数值方法通常应用于理想化的颗粒组装，但能够快速重复测试和连续监测作为边界变形函数的微观结构。然而，目前还没有一个强有力和一致的程序来在多个范围内将这两个研究战略联系起来。用于量化真实样品中微结构的相同算法可以用于指导DEM模拟的颗粒组件的生成，以便它们在结构和统计上与实验室测量的颗粒组件相似。这套算法对岩土工程和其他需要以类似分辨率表征微结构的领域的研究人员来说是有价值的，例如石油工程、材料加工、复合材料、陶瓷和一些消费品。虽然目前文献中存在一些单独的算法，但这些算法通常是在专有(和不同的)平台上开发的，通常不会广泛分发。值得注意的是，这些不同的方法还没有在单个相干数据集上被综合，以允许比较结果、推断更高阶行为或实现当执行单个微结构的多个表征时可能产生的任何计算效率。因此，拟议算法的开发和传播可能会产生重大的更广泛的影响。此外，拟议的工作将为项目团队中的学生提供有价值的培训，并使他们掌握一套可移植到各种问题的技能。

The research supported by this award is directed toward the development of a suite of stereological algorithms to allow for the robust quantification of the three-dimensional structure of granular soils from the results of computed tomography (CT) scans of specimens tested in the laboratory. These algorithms will allow for the unambiguous description of the solids and void space at multiple scales within the specimen. Such an approach is potentially transformative with respect to the manner in which the structure of granular materials are measured, described, quantified, and modeled. These algorithms, when coupled with existing approaches to the quantification and simulation of particle shapes, will allow for unprecedented amounts of information to be extracted from laboratory measurements and, if desired, used for discrete numerical simulations. There is currently a significant disconnect between the experimental and numerical approaches that are exploited for the study of granular material microstructure. An experimental approach relies upon observation of the response of real materials in the laboratory while a numerical approach is typically applied to an idealized assembly of particles but is capable of rapid replicate tests and continuous monitoring of microstructure as a function of boundary deformation. However, there is not currently a robust and consistent procedure for linking the two research strategies across multiple scales. The same algorithms used to quantify microstructure in real specimens can be used to guide the generation of granular assemblies for DEM simulations such that they are structurally and statistically similar to those measured in the laboratory. This suite of algorithms will be valuable to researchers in geotechnical engineering and other fields where characterization of microstructure at similar resolutions is necessary: e.g., petroleum engineering, materials processing, composite materials, ceramics, and some consumer goods. While some individual algorithms currently exist in the literature, these have often been developed on proprietary (and varying) platforms and are generally not widely distributed. Significantly, these disparate approaches have not been synthesized across a single coherent data set to allow for comparison of results, inference of higher-order behavior, or realization of any computational efficiencies that may arise when performing multiple characterizations of a single microstructure. Thus, development and dissemination of the proposed algorithms may have significant broader impacts. In addition, the proposed work will provide valuable training to the students working on the project team and equip them with a set of skills that is portable to a variety of problems.