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ARTICLE

A Boundary-Type Meshless Method for Traction Identification in Two-Dimensional Anisotropic Elasticity and Investigating the Effective Parameters

Mohammad-Rahim Hematiyan^*

School of Mechanical Engineering, Shiraz University, Shiraz, 71936, Iran

* Corresponding Author: Mohammad-Rahim Hematiyan. Email:

(This article belongs to the Special Issue: Advanced Computational Modeling and Simulations for Engineering Structures and Multifunctional Materials: Bridging Theory and Practice)

Computers, Materials & Continua 2025, 82(2), 3069-3090. https://doi.org/10.32604/cmc.2025.060067

Received 23 October 2024; Accepted 26 December 2024; Issue published 17 February 2025

Abstract

The identification of the traction acting on a portion of the surface of an anisotropic solid is very important in structural health monitoring and optimal design of structures. The traction can be determined using inverse methods in which displacement or strain measurements are taken at several points on the body. This paper presents an inverse method based on the method of fundamental solutions for the traction identification problem in two-dimensional anisotropic elasticity. The method of fundamental solutions is an efficient boundary-type meshless method widely used for analyzing various problems. Since the problem is linear, the sensitivity analysis is simply performed by solving the corresponding direct problem several times with different loads. The effects of important parameters such as the number of measurement data, the position of the measurement points, the amount of measurement error, and the type of measurement, i.e., displacement or strain, on the results are also investigated. The results obtained show that the presented inverse method is suitable for the problem of traction identification. It can be concluded from the results that the use of strain measurements in the inverse analysis leads to more accurate results than the use of displacement measurements. It is also found that measurement points closer to the boundary with unknown traction provide more reliable solutions. Additionally, it is found that increasing the number of measurement points increases the accuracy of the inverse solution. However, in cases with a large number of measurement points, further increasing the number of measurement data has little effect on the results.

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Keywords

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