A Modeling Method for Finite Element Analysis of Corroded Steel Structures with Random Pitting Damage
Author(s): |
Shenghui Zeng
Song Gu Songbo Ren Ying Gu Chao Kong Liqiong Yang |
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Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 27 October 2022, n. 11, v. 12 |
Page(s): | 1793 |
DOI: | 10.3390/buildings12111793 |
Abstract: |
Aiming at simulating the surface morphology of corroded steel and providing a modeling method with higher accuracy, the accelerated corrosion test was used to obtain six groups of corroded specimens, and then applied to stochastic finite element analysis (FEA) for studying the mechanical behavior of corroded steel. The pitting parameters (the depth, width, and diameter–depth ratio) of all specimens were investigated and statistically analyzed. Considering the irregularity of corroded surface, the random pitting model (RPM) was established based on the secondary development of ABAQUS. Moreover, the rough surface meshing method (RSMM) was subsequently proposed to optimize the element quality of the FEA model. At last, the modeling method was applied to investigate the bearing capacity of corroded steel beams. The results indicate that, firstly, the pitting parameters of all specimens obeyed log-normal distribution, and their logarithmic mean values grew with increase in corrosion time. The corroded surface the RPM can reproduce the evolution behaviors of a corroded surface with higher accuracy. In addition, the FEA model of corroded steel structures can be meshed easily into hexahedron elements by using the RSMM and effectively optimizing the number and quality of elements. By comparing with other test results, the calculation results of the FEA model of steel beams established by using the modeling method proposed in this study demonstrate a good accuracy in mechanical behavior analysis. The modeling method provides further support for the study of mechanical properties of corroded steel structures. |
Copyright: | © 2022 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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10700111 - Published on:
10/12/2022 - Last updated on:
10/05/2023