基于正交试验方法的大型有面外支撑杆X撑结构的屈曲分析和优化设计

BUCKLING ANALYSIS AND OPTIMAL DESIGN OF LARGE-SCALE XBRACE STRUCTURE WITH OUT-OF-PLANE SUPPORT BARS BASED ON ORTHOGONAL TEST METHOD

基于非线性屈曲有限元模型,该文结合正交试验和多因素方差分析方法研究了大型有面外支撑杆X撑结构的稳定性,并采用非线性曲面回归和BP神经网络机器学习对结构进行了优化设计,获得了临界屈曲系数预测模型,为复杂的高度非线性问题提供了一种解决思路。具体而言,搭建了支持表格形式自动化模拟的ANSYS和SOLIDWORKS联合仿真有限元模型,在充分考虑几何设计参数和边界条件的基础上进行了显著性正交试验和多因素方差分析,从中筛选出了主要影响因素并确定了优化设计自变量。然后,以显著性分析为指导进行了优化设计正交试验,利用非线性曲面回归方法和BP神经网络机器学习方法完成了结构优化设计。研究发现:面内支撑几何参数对结构稳定性的影响更为显著,其中临界屈曲载荷对面内支撑管径的变化最为敏感;另外,面外支撑会增加面内支撑的刚度,且节点位置会显著影响整体结构的稳定性;同时,载荷比的影响也很大,拉力会改善结构稳定性。针对新型复杂结构和初期优化设计,该文提供了一种基于数据驱动的高效优化设计方法。

Based on the nonlinear flexural finite element model,the stability of the X-braced structure with out-of-plane support was investigated combined orthogonal test and analysis of variance(ANOVA),and nonlinear surface regression and neural network method were used for optimal design,which provided a way for the design of complex nonlinear structures.Specifically,finite element models supporting automated simulations in tabular form were constructed using ANSYS and SOLIDWORKS.The effects of geometric parameters and boundary conditions were fully considered,and factors with important influence were identified by significance orthogonal test and analysis of variance.Then,orthogonal test for optimal design was conducted followed by the structural optimal design using nonlinear regression and BP neural network.The study found that the influence of the in-plane support geometric parameters was greater than that of the out-of-plane support,where a larger diameter of the in-plane support tube led to a more stable structure.In addition,the out-of-plane support can effectively improve the structural stiffness,while the junction position will have great influence on the stability.Finally,the load ratio affected buckling and the tension increased the stability.This paper provided a data-driven optimization design approach in preliminary design.