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System identification-guided basis selection for reduced-order nonlinear response analysis

机译:系统识别指导的基序选择,用于降阶非线性响应分析

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Reduced-order nonlinear simulation is often times the only computationally efficient means of calculating the extended time response of large and complex structures under severe dynamic loading. This is because the structure may respond in a geometrically nonlinear manner, making the computational expense of direct numerical integration in physical degrees of freedom prohibitive. As for any type of modal reduction scheme, the quality of the reduced-order solution is dictated by the modal basis selection. The techniques for modal basis selection currently employed for nonlinear simulation are ad hoc and are strongly influenced by the analyst's subjective judgment. This work develops a reliable and rigorous procedure through which an efficient modal basis can be chosen. The method employs proper orthogonal decomposition to identify nonlinear system dynamics, and the modal assurance criterion to relate proper orthogonal modes to the normal modes that are eventually used as the basis functions. The method is successfully applied to the analysis of a planar beam and a shallow arch over a wide range of nonlinear dynamic response regimes. The error associated with the reduced-order simulation is quantified and related to the computational cost. Published by Elsevier Ltd.
机译:降阶非线性仿真通常是在大型动态载荷下计算大型复杂结构的扩展时间响应的唯一有效计算手段。这是因为结构可能以几何非线性方式响应,从而使直接数字积分在物理自由度上的计算开销变得无法接受。对于任何类型的模态归约方案,降阶解的质量取决于模态基础选择。当前用于非线性仿真的模态基础选择技术是临时性的,并且受到分析师的主观判断的强烈影响。这项工作制定了可靠而严格的程序,通过该程序可以选择有效的模态基础。该方法采用适当的正交分解来识别非线性系统动力学,并使用模态保证准则将适当的正交模式与最终用作基础函数的正常模式相关联。该方法已成功地应用于在广泛的非线性动力响应范围内的平面梁和浅拱的分析。量化与降阶模拟相关的误差并将其与计算成本相关。由Elsevier Ltd.发布

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