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Reduced Model Approximation Approach Using Model Updating Methodologies

机译:使用模型更新方法减少模型近似方法

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Model reduction has been performed for several decades to allow for correlation of an analytical model to experimental data at a reduced number of points; however, traditional approaches have limitations. Static stiffness matrix reduction methods (e.g.,Guyan) may not accurately capture the system dynamics, while techniques based on mode shapes [e.g.,the system equivalent reduction expansion process (SEREP)] may experience rank deficiency issues. A new model reduction approach presented herein addresses these limitations by combining the accuracy of SEREP with the full-rank attributes of Guyan reduction. The advantages of the presented methodology over traditional reduction techniques are showcased via analytical studies on a cantilevered beam and general plate-type structure. (C) 2018 American Society of Civil Engineers.
机译:已经执行了数十年的模型减少,以允许分析模型在减少的点数下与实验数据相关; 然而,传统方法有局限性。 静态刚度矩阵减少方法(例如,Guyan)可能无法准确捕获系统动态,而基于模式形状的技术[例如,系统等效减少扩展过程(Serep)]可能会经历排名缺陷问题。 通过将SEREP的准确性与Guyan减少的全级别属性相结合,通过组合来解决这些限制的新的模型还原方法。 通过对悬臂梁和一般板式结构的分析研究展示了对传统减少技术的所呈现的方法的优点。 (c)2018年美国土木工程师协会。

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