Improving the performance of damage repair in thin-walled structures with analytical data and machine learning algorithms

Shaikh, Abdul Aabid and Raheman, Md Abdul and Hrairi, Meftah and Baig, Muneer (2024) Improving the performance of damage repair in thin-walled structures with analytical data and machine learning algorithms. Frattura ed Integrita Strutturale, 18 (68). pp. 310-324. E-ISSN 1971-8993

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Abstract

In the last four decades, bonded composite repair has proven to be an effective method for addressing crack damage propagation. On the other hand, machine learning (ML) has made it possible to employ a variety of approaches for mechanical and aerospace problems and such significant approach is the repair mechanism and hence ML algorithms used to enhance in the present work. The current work investigates the effect of the single-sided composite patch bonded on a thin plate under plane stress conditions. An analytical model was formulated for a single-sided composite patch repair using linear elastic fracture mechanics and Rose's analytical modelling. From the analytical model, the stress intensity factors (SIF) were calculated by varying all possible parameters of the model. Next, ML algorithms were selected, and comparative studies were conducted for the best possible performance and to identify the parametric effects on optimum SIF. Also, the analytical model is validated with existing work, and it shows good agreement with less than 10% error. This study is particularly important for designing the single-sided composite patch repair method based on analytical modelling. Also, it is important to compare ML algorithms with analytical solutions in regression applications.

Item Type:	Article (Journal)
Uncontrolled Keywords:	Bonded composite repair, Cracks, Reinforced patch, Analytical model; Machine learning
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA349 Mechanics of engineering. Applied mechanics T Technology > TA Engineering (General). Civil engineering (General) > TA630 Structural engineering (General) T Technology > TJ Mechanical engineering and machinery > TJ212 Control engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering Kulliyyah of Engineering > Department of Mechanical Engineering
Depositing User:	Prof. Dr. Meftah Hrairi
Date Deposited:	01 Apr 2024 15:10
Last Modified:	01 Apr 2024 15:10
URI:	http://irep.iium.edu.my/id/eprint/111676

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