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立体学算法，以便根据实验室测试样品的计算机断层扫描（CT）结果对颗粒土的三维结构进行稳健的量化。这些算法将允许在试样内的多个尺度的固体和空隙空间的明确描述。这种方法对于颗粒材料的结构被测量、描述、量化和建模的方式具有潜在的变革性。当这些算法与现有的粒子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明显的脱节。实验方法依赖于对实验室中真实材料响应的观察，而数值方法通常应用于理想的颗粒组合，但能够快速重复测试和连续监测微观结构作为边界变形的函数。然而，目前还没有一个健全和一致的程序，将两种研究策略跨多个尺度联系起来。用于量化真实样品微观结构的相同算法可用于指导生成DEM模拟的颗粒组合，使其在结构和统计上与实验室中测量的相似。这套算法对岩土工程和其他需要以类似分辨率表征微观结构的领域的研究人员很有价值，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（和各种）平台上开发的，并且通常没有广泛分发。值得注意的是，这些不同的方法并没有在单个连贯的数据集上进行综合，以允许结果的比较，高阶行为的推断，或实现在执行单个微观结构的多个特征时可能出现的任何计算效率。因此，提出的算法的发展和传播可能会产生重大的更广泛的影响。此外，拟议的工作将为在项目团队中工作的学生提供有价值的培训，并为他们提供一套可用于解决各种问题的技能。

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.