权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

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

SidyW - 模拟建筑和输送机械运行期间的动态阻力

基本信息

批准号：
320146379
负责人：
Professor Dr.-Ing. Andrè Katterfeld
金额：
--
依托单位：
Institut für Logistik und Materialflusstechnik (ILM)
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2016
资助国家：
德国
起止时间：
2015-12-31 至 2018-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/320146379?language=en
关键词：
SidyW Simulation dynamical resistances during

项目摘要

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.

搬运大量货物是许多建筑和运输机械的任务。这里的“好”一词一般指的是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过程中移动的颗粒状材料。机器与机器的相互作用是工作和运输过程的特征，对更高的能效、更长的产品生命周期和更高的成本压力的日益增长的需求引发并推动了高效跨域模拟方法的发展。由于建筑和运输机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。出于这些原因，近年来，作为产品开发工具的机器工艺模拟的使用显著增加。因此，颗粒力学过程的模拟通常采用离散单元法(DEM)，其材料参数必须通过大量的标定过程来确定。校准是通过将实验研究的结果与变参数的模拟系列的结果进行比较来完成的。这称为逆参数确定。到目前为止，大多数校准都是针对目标进行的，以考虑颗粒材料的真实流动行为。因此，本项目的目的是开发一种自动参数化DEM模型的方法，该方法可应用于移动施工设备和运输机械中的动态阻力模拟。这是对工艺载荷和运动阻力进行真实评估的缺失环节，并使基于模拟的前瞻性分析成为可能。研究的主要部分一方面需要开发一个高效的优化系统，另一方面需要开发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。