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Boundary Element Modeling for Simulation and Optimization of Three-Temperature Anisotropic Micropolar Magneto-thermoviscoelastic Problems in Porous Smart Structures Using NURBS and Genetic Algorithm
International Journal of Thermophysics ( IF 2.2 ) Pub Date : 2021-01-13 , DOI: 10.1007/s10765-020-02777-7
M. A. Fahmy , S. Shaw , S. Mondal , A. E. Abouelregal , Kh. Lotfy , I. A. Kudinov , A. H. Soliman

The main objective of the present paper is to propose a new boundary element modeling technique for simulation and optimization of three-temperature micropolar magneto-thermoviscoelastic problems in anisotropic porous smart structures, where we implemented the genetic algorithm (GA), as a method of optimization based on the free form deformation (FFD) methodology to improve the performance of our proposed technique. Two numerical examples are presented herein, in order to prove that the proposed technique is able to optimize the shape of the domains with minimum computational effort. A nonuniform rational B-spline curve (NURBS) has been introduced to define the optimum boundary where it decreases the number of control points and offers a new degree of versatility in the design of various different shapes. The profiles of the items considered shall be represented by the FFD methodology. The location vectors of the FFD control points are known to be the genes, and then the chromosomes for the profiles are determined by the gene sequence. The population is made up of several chromosomes individuals, where the fitness functions of individuals are assessed using BEM. The numerical results are depicted graphical forms to show the effects of viscosity and magnetic fields on the three temperatures, displacement components, microrotation components, pore pressure, electric potential, and thermal stress components. The validity, accuracy, and computational efficiency of the proposed BEM technique were demonstrated by comparing our BEM-obtained results with the corresponding results of normal mode analysis method (NMAM), finite difference method (FDM), and finite element method (FEM).

中文翻译:

使用 NURBS 和遗传算法模拟和优化多孔智能结构中的三温度各向异性微极磁热粘弹性问题的边界元建模

本文的主要目的是提出一种新的边界元建模技术,用于模拟和优化各向异性多孔智能结构中的三温度微极磁热粘弹性问题,其中我们实施了遗传算法 (GA),作为优化方法基于自由形式变形(FFD)方法来提高我们提出的技术的性能。这里提供了两个数值示例,以证明所提出的技术能够以最少的计算工作优化域的形状。引入了非均匀有理 B 样条曲线 (NURBS) 来定义最佳边界,它减少了控制点的数量,并在各种不同形状的设计中提供了新的多功能性。所考虑项目的概况应由 FFD 方法表示。已知FFD控制点的位置向量是基因,然后由基因序列确定剖面的染色体。种群由几个染色体个体组成,其中个体的适应度函数使用边界元法进行评估。数值结果以图形形式表示,以显示粘度和磁场对三个温度、位移分量、微旋转分量、孔隙压力、电势和热应力分量的影响。通过将我们的边界元法获得的结果与正态模式分析法 (NMAM)、有限差分法 (FDM) 的相应结果进行比较,证明了所提出的边界元法技术的有效性、准确性和计算效率。
更新日期:2021-01-13
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