Stochastic particle models for the quantification of relationships between structural characteristics and mechanical properties to predict particle breakage behaviour

随机颗粒模型，用于量化结构特征和机械性能之间的关系，以预测颗粒破碎行为

• 批准号: 238651683
• 负责人: Professor Dr. Volker Schmidt
• 金额: --
• 依托单位: Institut für Stochastik
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2013
• 资助国家: 德国
• 起止时间: 2012-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/238651683?language=en
• 关键词: Stochastic; particle; models; quantification; relationships

In the proposed project we develop parametric material models that quantitatively capture dependencies between disperse structural characteristics and mechanical properties. These models depend on the material properties and generalize the property function by H. Rumpf. The aim of this approach is to estimate the material-dependent parameters that influence breakage behaviour, while the effect of process-dependent stress has to be separated. Based on these data, breakage probabilities and breakage functions are derived. Furthermore, these are implemented into a breakage module inside the software framework in order to make the results available for other projects of the SPP 1679.For systematic investigations of the effect of material properties and structural characteristics of agglomerates on their mechanical behaviour, a stochastic particle model is used to generate 3D microstructures, which are then used as input to DEM simulations. DEM simulations are performed in cooperation with the work group of Prof. Heinrich. The stochastic particle model facilitates the generation of tailored microstructures with given structural characteristics. Because as many realizations as needed can be simulated, this is an ideal tool to generate a database large enough for statistical inference. Structural segmentation of 3D image data of various agglomerates ensures that the microstructures under investigation are realistic. In the first funding period, we analyse the mechanical behaviour of agglomerates under compressive normal load. A first joint article has been submitted where the effect of the size distribution of primary particles is explored. In the second funding period, the behaviour under dynamical load will be studied and the results will be used to describe particle breakage. The parametric material models, or more precisely, the disperse properties captured in these models, are chosen accordingly. The material models for the aggregated description of solids are specified by parametric multivariate probability distributions, which are constructed based on so-called copulas. This approach allows us to capture various disperse properties simultaneously, e.g., particle size, particle shape, inner porosity, together with mechanical properties like e.g. breakage energies. Therefore, mechanical properties can be predicted by evaluating conditional distributions. The model-based description of breakage probabilities and breakage functions incorporates these results as well as the given (process-dependent) particle stress. This provides the link to the partner groups that consider particle breakage in their apparatus/process descriptions. In cooperation with the Z project, we will specify and implement a "breakage module" suitable for the software system developed in the SPP 1679.

在拟议的项目中，我们开发参数化材料模型，定量捕捉分散的结构特征和力学性能之间的依赖关系。这些模型依赖于材料的性质，并将性质函数推广为H。滚这种方法的目的是估计的材料依赖的参数，影响破碎行为，而过程依赖的应力的影响必须分开。基于这些数据，破损概率和破损函数的推导。此外，这些都被实现到一个破碎模块内的软件框架，以使结果可用于其他项目的SPP 1679。为了系统的研究的影响，材料性能和结构特征的团聚体对他们的机械行为，随机颗粒模型被用来生成3D微观结构，然后被用作输入DEM模拟。DEM模拟与Heinrich教授的工作组合作进行。随机粒子模型有利于生成具有给定结构特征的定制微结构。由于可以模拟所需的尽可能多的实现，因此这是生成足够大的数据库以进行统计推断的理想工具。各种团聚体的3D图像数据的结构分割确保了所研究的微观结构是真实的。在第一个资助期间，我们分析了压缩法向载荷下团聚体的力学行为。已提交第一个联合文章，其中探讨了初级颗粒的尺寸分布的影响。在第二个供资期间，将研究动态载荷下的行为，研究结果将用于描述颗粒破碎。相应地选择参数材料模型，或者更准确地说，在这些模型中捕获的分散特性。用于固体的聚集描述的材料模型由基于所谓的copula构造的参数多元概率分布指定。这种方法使我们能够同时捕获各种分散特性，例如，颗粒尺寸、颗粒形状、内部孔隙率以及机械性能，例如断裂能。因此，可以通过评估条件分布来预测机械性能。破碎概率和破碎函数的基于模型的描述结合了这些结果以及给定的（依赖于过程的）颗粒应力。这提供了与在其设备/工艺描述中考虑颗粒破碎的伙伴组的链接。在与Z项目的合作中，我们将指定并实现一个适用于SPP 1679中开发的软件系统的“断裂模块”。