Particle scale mechanisms influence the mechanical behaviour of geomaterials. A better understanding of soil micromechanics will help develop more accurate constitutive models and, by extension, safer and more economic geotechnical design. Sand-grained soils have been widely studied at the particle scale using X-ray Computed tomography and this has revealed important micromechanical behaviour of sands. Clays are least understood and studied at the particle scale. As technology rapidly progresses, to understand clay kinematics, a particle kinematic algorithm to match plate shaped (platy) particles will be required. Current algorithms developed for the matching of quartz and carbonate sand particles may not be suitable, since particle attributes that are strong discriminators of round particles may be less unique on platy particles, due to their extremely small c-axis and the reduced image resolution associated with their smaller size. This study presents, particle tracking of kaolin sample using mica markers and provides a platy soil particle matching algorithm for evaluating platy particle kinematics. After testing a range of alternative particle attributes, it was observed that a combination of particle major axis length, intermediate axis length, and perimeter was a good discriminant of the platy mica particles studied. On this basis, we developed PLATYMATCH, an optimised platy particle matching algorithm that considers a minimised combined normalised error of unique particle attributes within a defined search volume space. The algorithm was implemented such that particle attributes were compared in parallel, rather than sequentially, to avoid filtering out a potential particle match based on a single non-unique attribute. PLATYMATCH was then successfully validated using a compressed mica soil sample.

粒子尺度机制影响土工材料的力学行为。更好地了解土壤微观力学将有助于开发更准确的本构模型，进而实现更安全、更经济的岩土工程设计。已经使用 X 射线计算机断层扫描在颗粒尺度上对沙粒土壤进行了广泛的研究，这揭示了沙子的重要微观力学行为。在颗粒尺度上对粘土的了解和研究最少。随着技术的快速进步，为了理解粘土运动学，需要一种粒子运动学算法来匹配板状（板状）粒子。当前为匹配石英和碳酸盐砂颗粒而开发的算法可能不适合，因为作为圆形颗粒强鉴别器的颗粒属性在片状颗粒上可能不那么独特，由于它们的 c 轴非常小，并且由于其较小的尺寸而降低了图像分辨率。本研究提出了使用云母标记对高岭土样品进行颗粒跟踪，并提供了一种用于评估片状颗粒运动学的片状土壤颗粒匹配算法。在测试了一系列替代粒子属性后，观察到粒子长轴长度、中间轴长度和周长的组合是所研究的板状云母粒子的良好判别器。在此基础上，我们开发了 PLATYMATCH，这是一种优化的板状粒子匹配算法，它考虑了定义的搜索体积空间内唯一粒子属性的最小组合归一化误差。该算法的实现是并行比较粒子属性，而不是顺序比较，以避免基于单个非唯一属性过滤掉潜在的粒子匹配。然后使用压缩的云母土壤样品成功验证了 PLATYMATCH。