基于多线性材料硬化的向量式有限元C型薄壁型钢屈曲分析OA北大核心CSTPCD
Buckling Analysis of C-type Thin-walled Steel with Vector Form Intrinsic Finite Element Based on Multi-linear Material Hardening
C型薄壁型钢在实际工程中较常见,在力的作用下容易发生屈曲失效.传统有限元法预测结构屈曲变形已经有一套较为成熟的方案,但程序较烦琐.基于向量式有限元(VFIFE)方法编制了三角形壳单元的 For-tran计算程序.通过 Matlab软件编写前处理与后处理程序,将计算结果与经典的双曲壳屈曲计算结果对比,考察其正确性.考虑几何非线性问题与材料非线性问题,引入多线性材料硬化模型,计算了不同尺寸的 C型薄壁型钢在轴压荷载下的屈曲特性.根据位移-轴力曲线判断屈曲荷载,通过后处理程序绘制出屈曲发生后的变形,并与现有的试验结果对比.结果表明:引入多线性材料硬化模型的向量式有限元方法能够较好地预测结构屈曲荷载以及屈曲变形,为预测结构的屈曲变形提供一种新的、可靠参考.
C-shaped thin-walled steel is quite common in practical engineering and is prone to buckling failure under the action of force.The traditional finite element method has a mature scheme for predicting structural buckling,but the proce-dure is complicated.Based on the vector form intrinsic finite element(VFIFE)method,a Fortran calculation program for triangular shell element is developed.The pre-processing and post-processing programs are written in Matlab,and the cal-culation results are compared with those of classical hyperbolic shell buckling to check their correctness.Considering geo-metric non-linearity and material non-linearity,a multi-linear material hardening model is introduced to calculate the buck-ling characteristics of C-type thin-walled steel with different sizes under axial load.The buckling load is determined by the displace axial force curve,and the deformation after buckling is plotted by the post-processing program and compared with the existing test results.The results show that the VFIFE method with multi-linear material hardening model can predict the buckling load and buckling mode of the structure well,which provides a new and reliable reference for predicting the buck-ling behavior of the structure.
孙子涵;陈朝晖;宋春草;马文亮
华北水利水电大学,河南 郑州 450046烟台市政府投资工程建设服务中心,山东 烟台 264003郑州工商学院,河南 郑州 451400
土木建筑
向量式有限元结构屈曲多线性材料硬化模型后屈曲
vector form intrinsic finite elementstructural bucklingmulti-linear material hardening modelpost-buckling
《华北水利水电大学学报(自然科学版)》 2024 (006)
74-80 / 7
国家自然科学基金项目(11402090);河南省水利厅科技攻关项目(GG202050);华北水利水电大学博士研究生创新基金(NCWUBC202228).
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