Miller Bartosz, Ziemiański Leonard
Faculty of Civil and Environmental Engineering and Architecture, Rzeszów University of Technology, al. Powstańców Warszawy 12, 35-959 Rzeszów, Poland.
Materials (Basel). 2020 Nov 28;13(23):5414. doi: 10.3390/ma13235414.
The paper presents the optimization of stacking sequence (the lamination angles in subsequent composite layers) of the composite cylinder in order to simultaneously maximize the values of the first natural frequency f1 and the first buckling force Pcr. The optimization problem involves either two objective functions or one which combines both problems using a coefficient whose optimal value is also being searched for. The main idea of the paper is the application of two neural network metamodels which substitute very time- and resource-consuming Finite Element (FE) calculations. The metamodels are created separately through a novel iterative procedure, using examples obtained through Finite Element Method (FEM). The metamodels, once ready, are able to assess the values of f1 and Pcr instantly and thus enable the application of nature-inspired Genetic Algorithm (GA) minimization with reasonable calculation times. Obviously, the maxima of f1 and Pcr may be located in different points of the design parameters (i.e., lamination angles) space, the considered optimization task is to find a solution for which both f1 and Pcr simultaneously reach values as close to their maxima as possible. All the investigated optimization examples are repeated several times and basic statistical analysis of the results is presented.
本文介绍了复合圆柱堆叠顺序（后续复合层中的层合角）的优化，以便同时最大化第一固有频率f1和第一屈曲力Pcr的值。优化问题涉及两个目标函数，或者一个使用系数将两个问题结合起来的目标函数，该系数的最优值也在寻找中。本文的主要思想是应用两个神经网络元模型来替代非常耗时且耗费资源的有限元（FE）计算。元模型通过一种新颖的迭代过程分别创建，使用通过有限元方法（FEM）获得的示例。元模型一旦准备好，就能立即评估f1和Pcr的值，从而能够在合理的计算时间内应用受自然启发的遗传算法（GA）进行最小化。显然，f1和Pcr的最大值可能位于设计参数（即层合角）空间的不同点，所考虑的优化任务是找到一个解决方案，使f1和Pcr同时达到尽可能接近其最大值的值。所有研究的优化示例都重复进行了几次，并给出了结果的基本统计分析。
