SidyW - Simulation of dynamical resistances during the operation of construction and conveying machines

多种货物的搬运是许多建筑和输送机器的任务。术语“良好”在这里通常代表在建筑机械的实际工作过程中或在连续输送机上的常规运输期间移动的颗粒材料。机器和货物的相互作用是工作和运输过程的特征。对更高能效、更长产品生命周期和更高成本压力的日益增长的需求引发并推动了高效跨域仿真方法的发展。由于建筑机械和输送机械通常是小批量生产或作为独特的样品生产，因此生产和测试原型是非常不经济的，因此对这种仿真工具的需求得到了加强。由于这些原因，近年来，作为产品开发工具的机械过程仿真的使用显著增加。因此，颗粒力学过程通常用离散单元法（DEM）模拟，其材料参数必须在广泛的校准过程中确定。校准是通过比较实验研究的结果与具有不同参数的模拟系列。这被称为逆参数确定。到目前为止，大多数校准都是用目标来考虑颗粒材料的真实流动行为。这是不够的，一个现实的前瞻性的负载分析。因此，本项目的目的是开发一种方法的DEM模型的自动参数化，可用于模拟动态阻力在移动的施工设备和运输机械。这是对过程载荷和运动阻力进行现实评估所缺少的环节，可以对此类机床进行基于仿真的前瞻性分析。研究的主要部分一方面需要开发高效的优化系统，另一方面需要开发用于结果提取和后处理的工具和方法。所谓的优化系统包括解决优化问题所需的所有组件（初始化、优化算法、目标函数值计算等）。为此，研究了智能初始化和多目标评价的新方法。作为优化算法，将使用人工神经网络和基于元模型的方法。校准将通过相对简单的校准测试来完成，而校准模型的验证将通过比较模拟结果和大规模实验的实验数据来完成。

The handling of a manifold of goods is the task of many construction and conveying machines. The term 'good' stands here generally for granular materials that are moved during the actual working process of the construction machine or the regular transport on continuous conveyors. The interaction of machine and good characterizes the working and transport process.The increasing need for more energy efficiency, longer product life cycles and raised cost pressure initiates and drives the development of efficient cross-domain simulation methods. This desire for such simulation tools is reinforced by the fact that construction and conveying machines are often produced in small series or as unique specimen so that producing and testing prototypes is very uneconomical.For these reasons, the use of machine-process-simulations, as a tool of product development, has increased significantly in recent years. Particle-mechanical processes are thereby usually simulated with the Discrete Element Method (DEM), whose material parameters have to be determined in extensive calibration procedures. Calibration is done by comparing the results of experimental studies with those of a simulation series with varying parameters. This is called inverse parameter determination. So far most calibration is done with the target to consider a realistic flow behavior of granular materials. This is not sufficient for a realistic prospective load analysis.The aim of this project is therefore the development of a method for the automated parameterization of DEM models which can be applied for the simulation of dynamical resistances in mobile construction equipment and conveying machines. This is the missing link for a realistic assessment of process loads and motion resistances and enables simulation-based prospective analysis of such machines.The main part of research is required by developing an efficient optimization system on the one side and tools and methods for result extraction and post-processing on the other side. The so called optimization system includes all components which are needed to solve an optimization problem (initialization, optimization algorithm, objective function value calculation, etc.). Therefore, new approaches of intelligent initialization as well as the evaluation of multi-criteria objectives are studied. As optimization algorithms artificial neural networks and metamodel-based methods will be used. The calibration will be done by help of relatively simple calibration tests, while the validation of the calibrated models will be done by comparing simulation results and experimental data from large-scale experiments.