Hybrid genetic algorithm for elimination of severe stress concentration in railhead ends

Zong, Nannan & Dhanasekar, Manicka (2013) Hybrid genetic algorithm for elimination of severe stress concentration in railhead ends. Journal of Computing in Civil Engineering.

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This paper presents a computational method for eliminating severe stress concentration at the unsupported railhead ends in rail joints through innovative shape optimization of the contact zone, which is complex due to near field nonlinear contact. With a view to minimizing the computational efforts, hybrid genetic algorithm method coupled with parametric finite element has been developed and compared with the traditional genetic algorithm (GA). The shape of railhead top surface where the wheel contacts nonlinearly was optimized using the hybridized GA method. Comparative study of the optimal result and the search efficiency between the traditional and hybrid GA methods has shown that the hybridized GA provides the optimal shape in fewer computational cycles without losing accuracy. The method will be beneficial to solving complex engineering problems involving contact nonlinearity.

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1 citations in Scopus
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ID Code: 70341
Item Type: Journal Article
Refereed: Yes
Keywords: Hybridized Genetic Algorithm, Shape Optimization, Wheel-railhead Contact, Rail Edge Stress
DOI: 10.1061/(ASCE)CP.1943-5487.0000374
ISSN: 1943-5487
Divisions: Current > Schools > School of Civil Engineering & Built Environment
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 by the American Society of Civil Engineers
Deposited On: 22 Apr 2014 01:43
Last Modified: 20 Oct 2014 23:49

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