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Buckling of moderately thick arbitrarily shaped plates with intermediate point supports using a simple hp-cloud method

机译:使用简单的HP云法,具有中间点支持的中等厚的任意形状板的屈曲

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摘要

This paper presents the simple hp-cloud meshless method for the stability analysis of moderately thick plates with various shapes subjected to uniaxial and biaxial in-plane compressive and pure shear loads. To allow the effect of transverse shear deformation on the critical buckling load of the plate, the Mindlin's plate theory is employed. Simple hp-cloud method is applied for constructing the cloud shape functions and for discretization of the domain. Shepard functions are also used for the partition of unity and complete polynomials are utilized for the enrichment functions part. The simple hp-cloud method has Kronecker delta property, so contrary to most of meshless methods the essential boundary conditions can be imposed directly. Constructing the stiffness and geometry matrices leads to an eigenvalue problem that should be solved to determine the critical buckling load of the plate. Numerical results are verified against the results reported elsewhere to illustrate the accuracy and effectiveness of the present method. To show the applications of simple hp-cloud method in the buckling analysis of moderately thick plates, local buckling coefficients of various shapes of plates, rectangular, skew, trapezoidal, triangular, circular, semi-circular, hexagonal and general shape with different boundary conditions are determined. Also, local buckling coefficients of plates with point supports and intermediate support are calculated. (C) 2017 Elsevier Inc. All rights reserved.
机译:本文介绍了具有中等厚板的简单HP云网状方法,其各种形状经受单轴和双轴在面内压缩和纯剪切载荷的各种形状。为了允许横向剪切变形对板的关键屈曲负荷的影响,采用了Minglin的板理论。应用简单的HP-Cloud方法用于构建云形功能和域的离散化。 Shepard功能也用于统一的分区,并且完全多项式用于富集功能部分。简单的HP-Cloud方法具有Kronecker Delta属性,与大多数无网格方法相反,可以直接施加必要的边界条件。构造刚度和几何矩阵导致应解决的特征值问题,以确定板的临界屈曲负荷。根据其他地方报告的结果验证了数值结果,以说明本方法的准确性和有效性。为了展示简单的HP云法在适度厚板屈曲分析中的应用,局部屈曲系数的板块,矩形,偏斜,梯形,三角形,圆形,半圆形,六边形和一般形状,具有不同的边界条件确定。而且,计算具有点支撑和中间支撑的板的局部屈曲系数。 (c)2017年Elsevier Inc.保留所有权利。

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