Determination of the Ultimate Bearing Capacity of a Single Barrette Wall using FEA and Cubic Nonlinear Regression
Received: 6 September 2024 | Revised: 1 November 2024 | Accepted: 3 November 2024 | Online: 29 November 2024
Corresponding author: Tuan Anh Nguyen
Abstract
This study analyzes the mechanical behavior of barrette walls under various load levels, a critical issue in the design and construction of structures subjected to large loads. The primary objective of the research is to determine the nonlinear relationship between load and settlement of barrette walls, as well as to assess the maximum load-bearing capacity of the walls under diverse loading conditions. The finite element analysis method was employed to simulate the detailed interaction between the barrette wall and the soil, combined with cubic and linear regression analysis techniques to establish the model of the relationship between load and settlement displacement. The research results reveal a nonlinear relationship between load and settlement of the wall, with an inflection point occurring at a load level of approximately 12,000 kN, where the change in settlement becomes more pronounced. The cubic regression equation achieved a coefficient of determination R² = 0.999, demonstrating the high accuracy of the model. The maximum load-bearing capacity of the barrette wall was determined to be 15,745.59 kN, providing a clear scientific basis for evaluating the load-bearing capacity of structures. The conclusions from this study affirm the importance of using finite element simulations in soil mechanics analysis and the design of structures subjected to large loads. The achieved results not only enhance understanding of the behavior of Barrette walls but also contribute to the development of new technical solutions and design methods, with the potential for wide application in the construction and geotechnical engineering sectors.
Keywords:
finite element analysis, ultimate capacity, barrette wall, cubic nonlinear regressionDownloads
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Copyright (c) 2024 Truong Xuan Dang, Phuong Tuan Nguyen, Luan Nhat Vo, Hoa Van Vu Tran, Tuan Anh Nguyen
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