论文标题

惯性救济问题参数解决方案的非感性降低订单模型

Nonintrusive reduced order model for parametric solutions of inertia relief problems

论文作者

Cavaliere, F., Zlotnik, S., Sevilla, R., Larrayoz, X., Diez, P.

论文摘要

惯性缓解技术被行业广泛使用,并产生平衡的负载,可以分析不受限制的系统,而无需诉诸更昂贵的完整动态分析。这项工作的主要目的是开发一个计算框架,以解决IR和适当的广义分解(PGD)方法解决不受约束的参数结构问题。首先,在材料和几何参数的参数设置中制定了IR方法。然后开发了使用封装的PGD套件的减少订单模型来解决参数IR问题,从而规避了所谓的维度诅咒。只有一个离线计算,提出的PGD-IR方案提供了一个计算VadeMecum,其中包含用于预定义参数范围的所有可能解决方案。所提出的方法是无引人注目的,因此可以与商业FE套餐集成。使用三维测试用例和更复杂的工业测试案例显示了开发技术的适用性和潜力。第一个示例用于突出该方案的数值属性,而第二个示例则在更复杂的设置中演示了潜力,并显示了将所提出的框架集成在商业FE包中的可能性。此外,最后一个示例显示了在多目标优化设置中使用广义解决方案的可能性。

The Inertia Relief (IR) technique is widely used by industry and produces equilibrated loads allowing to analyze unconstrained systems without resorting to the more expensive full dynamic analysis. The main goal of this work is to develop a computational framework for the solution of unconstrained parametric structural problems with IR and the Proper Generalized Decomposition (PGD) method. First, the IR method is formulated in a parametric setting for both material and geometric parameters. A reduced order model using the encapsulated PGD suite is then developed to solve the parametric IR problem, circumventing the so-called curse of dimensionality. With just one offline computation, the proposed PGD-IR scheme provides a computational vademecum that contains all the possible solutions for a pre-defined range of the parameters. The proposed approach is nonintrusive and it is therefore possible to be integrated with commercial FE packages. The applicability and potential of the developed technique is shown using a three dimensional test case and a more complex industrial test case. The first example is used to highlight the numerical properties of the scheme, whereas the second example demonstrates the potential in a more complex setting and it shows the possibility to integrate the proposed framework within a commercial FE package. In addition, the last example shows the possibility to use the generalized solution in a multi-objective optimization setting.

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