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Aircraft Structural Integrity Assessment through Computational Intelligence Techniques

RamanaM. Pidaparti1
1 Department of Mechanical Engineering, Virginia Commonwealth University, Richmond, VA 23284. E-mail: rmpidaparti@vcu.edu

Structural Durability & Health Monitoring 2006, 2(3), 131-148. https://doi.org/10.3970/sdhm.2006.002.131

Abstract

This paper provides an overview of the computational intelligence methods developed for the structural integrity assessment of aging aircraft structures. Computational intelligence techniques reviewed include artificial neural networks, inverse neural network mapping, wavelet based image processing methods, genetic algorithms, spectral element methods, and particle swarm optimization. Multi-site damage, corrosion, and corrosion-fatigue damage in aging aircraft is specifically discussed. Results obtained from selected computational intelligence methods are presented and compared to the existing alternate solutions and experimental data. The results presented illustrate the applicability of computational intelligence methods for assessing the structural integrity of aging aircraft structures and materials.

Keywords

Corrosion, Multi-site Damage, Fatigue, Structural Integrity, Computational Intelligence, Particle Swarm Optimization, Wavelets

Cite This Article

Pidaparti, R. (2006). Aircraft Structural Integrity Assessment through Computational Intelligence Techniques. Structural Durability & Health Monitoring, 2(3), 131–148.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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