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Achieving Higher Levels of Crack Simulation with the Improved Adaptive Static Condensation Method

Author(s):



Medium: journal article
Language(s): English
Published in: Buildings, , n. 3, v. 14
Page(s): 648
DOI: 10.3390/buildings14030648
Abstract:

Accurately simulating concrete cracking in large-dimensional structures is a challenging task. To address this issue, an adaptive static condensation (ASC) method has been developed that has demonstrated effectiveness in localized nonlinearities. The ASC method aims to concentrate computational efforts solely on the damaged area, which may evolve due to crack initiation or propagation. However, the efficiency of the ASC method may be limited as it is based on a non-evolving mesh. To overcome this limitation, a novel approach is proposed in this study, which utilizes an evolutionary mesh with mesh refinement. The proposed approach employs a fine mesh solely in the activated and evolving domain of interest. The ASC method with mesh refinement is demonstrated on a notched bending beam, indicating that the accuracy of the ASC is maintained while providing an additional gain in computational time. Furthermore, a reinforced concrete vessel subjected to internal pressure is considered, and it is shown that this new approach results in a significant improvement in computational time, with a 14-fold improvement compared to a 5-fold improvement without mesh refinement. This study demonstrates that the proposed improvement on the ASC method allows for finer discretization in the zones of interest that were previously inaccessible with the nominal ASC method or a direct numerical simulation strategy.

Copyright: © 2024 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.

  • About this
    data sheet
  • Reference-ID
    10773864
  • Published on:
    29/04/2024
  • Last updated on:
    05/06/2024
 
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