Parameter inverse of fiber‐cement matrix interface cohesive model based on <scp>PSO</scp> algorithm
Abstract The toughening effect of fibers on cement‐based composite materials mainly depends on the bonding performance of the interface transition zone. At present, interface units based on cohesive zone models (CZM) have gradually become an effective method for studying material layering. Therefore, the accurate acquisition of CZM parameters has an important influence on the reliability of bond performance evaluation. The load–displacement data information was obtained through the fiber pull‐out test. The CZM was introduced to simulate the interface layer between the fiber and the cement matrix, and the CZM parameters were determined based on the particle swarm optimization (PSO) inverse. Numerical simulation and test results indicate that the PSO algorithm has better conversion and optimization ability than the genetic algorithm (GA) and simulated annealing algorithm (SA). The peak load gradually increases with the depth of fiber burial, but the toughness index shows a trend of increasing first and then decreasing. When the fiber burial length is 20 mm, the toughness index is optimal at 0.38. In addition, the load–displacement data simulated using inverse parameters are close to the test results. Compared with the forward model, it improves the simulation accuracy of the local debonding stage and reduces the error by 50%.
Authors
- Yuan Qin (ORCID: https://orcid.org/0000-0002-3515-1066)
- Xianwei Zhang (ORCID: https://orcid.org/0000-0002-0283-4493)
- Heng Zhou (ORCID: https://orcid.org/0000-0001-8790-5870)
- Wenzhe Ji
- Jinge Liu
Institutions
- PowerChina (China) (CN)
- Xi'an University of Technology (CN)
- China Power Engineering Consulting Group (China) (CN)
Publication Details
- Journal
- Structural Concrete
- Published
- 2025-05-20
- DOI
- https://doi.org/10.1002/suco.70148
- Citations
- 1
- Primary Topic
- Mechanical Behavior of Composites
- Type
- article
- Field-Weighted Citation Impact
- 0.86
Funders
- National Natural Science Foundation of China