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Prediction models for calculating bolted connections using data mining techniques and the finite element method

机译:使用数据挖掘技术和有限元方法计算螺栓连接的预测模型

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This paper describes a method based on a combination of Finite Element Method (FEM) and Data Mining (DM) techniques to set up prediction models that can be used to calculate bolted connections. Based on the results of a finite element (FE) model validated by tests, a number of FE simulations is developed, varying the most significant parameters (thickness, bolt diameter, friction, etc.). The results of these simulations are used to generate a database which can then be used to create prediction models. The process centres on selecting the best technique from a set of DM and artificial intelligence (AI) algorithms to find the models which provide the most generally applicable solutions to the problem.rnThis method, combining FE models with prediction techniques, is highly useful for the specific case of bolted connections, because it enables results to be obtained almost in real time with only slight prediction errors. This makes it an excellent tool for optimising the design of such connections.
机译:本文介绍了一种基于有限元方法(FEM)和数据挖掘(DM)技术相结合的方法,以建立可用于计算螺栓连接的预测模型。根据经过测试验证的有限元(FE)模型的结果,开发了许多有限元模拟,其中改变了最重要的参数(厚度,螺栓直径,摩擦力等)。这些模拟的结果用于生成数据库,然后该数据库可用于创建预测模型。该过程的重点是从DM和人工智能(AI)算法集中选择最佳技术,以找到能够为该问题提供最通用解决方案的模型。这种方法将有限元模型与预测技术结合在一起,对于解决问题非常有用。螺栓连接的特定情况,因为它可以几乎实时地获得结果,而预测误差很小。这使其成为优化此类连接设计的出色工具。

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