Adaptive Load Incremental Step in Large Increment Method for Elastoplastic Problems

Author:

Cui Baorang,Zhang JingxiuORCID,Ma YongORCID

Abstract

As a force-based finite element method (FEM), large increment method (LIM) shows unique advantages in material nonlinearity problems. In LIM for material nonlinearity analysis, adaptive load incremental step is a fundamental step for its successful application. In this work, a strategy to automatically refine the load incremental step is proposed in the framework of LIM. The adaptive load incremental step is an iterative process based on the whole loading process, and the location and number of post-refined incremental steps are determined by the posteriori error of energy on the pre-refined incremental steps. Furthermore, the iterative results from the pre-refined incremental steps can be utilized as the initial value to calculate the result for the post-refined incremental steps, which would significantly improve the computational accuracy and efficiency. The strategy is demonstrated using a two-dimensional example with a bilinear hardening material model under cyclic loading, which verifies the accuracy and efficiency of the strategy in LIM. Compared with the displacement-based FEM, which relies upon a step-by-step incremental approach stemming from flow theory, the adaptive load incremental step based on the whole loading process of LIM can avoid the cumulative errors caused by step-by-step in global stage and can quantify the accuracy of results. This work provides a guidance for the practical application of LIM in nonlinear problems.

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3