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Détail de l'auteur
Auteur Jenny T. Ng
Documents disponibles écrits par cet auteur
Affiner la rechercheOptimization of pile groups using hybrid genetic algorithms / Chan, C. M. in Journal of geotechnical and geoenvironmental engineering, Vol. 135 N° 4 (Avril 2009)
[article]
in Journal of geotechnical and geoenvironmental engineering > Vol. 135 N° 4 (Avril 2009) . - pp. 497–505
Titre : Optimization of pile groups using hybrid genetic algorithms Type de document : texte imprimé Auteurs : Chan, C. M., Auteur ; Zhang, L. M., Auteur ; Jenny T. Ng, Auteur Année de publication : 2009 Article en page(s) : pp. 497–505 Note générale : Geotechnical and geoenvironmental engineering Langues : Anglais (eng) Mots-clés : Pile foundations Pile caps Pile groups Algorithms Optimization Limit states Résumé : This paper presents an automated optimal design method using a hybrid genetic algorithm for pile group foundation design. The design process is a sizing and topology optimization for pile foundations. The objective is to minimize the material volume of the foundation taking the configuration, number, and cross-sectional dimensions of the piles as well as the thickness of the pile cap as design variables. A local search operator by the fully stressed design (FSD) approach is incorporated into a genetic algorithm (GA) to tackle two major shortcomings of a GA, namely, large computation effort in searching the optimum design and poor local search capability. The effectiveness and capability of the proposed algorithm are first illustrated by a five by five pile group subjected to different loading conditions. The proposed optimization algorithm is then applied to a large-scale foundation project to demonstrate the practicality of the algorithm. The proposed hybrid genetic algorithm successfully minimizes the volume of material consumption and the result matches the engineering expectation. The FSD operator has great improvement on both design quality and convergence rate. Challenges encountered in the application of optimization techniques to design of pile groups consisting of hundreds of piles are discussed. En ligne : http://ascelibrary.org/doi/abs/10.1061/%28ASCE%291090-0241%282009%29135%3A4%2849 [...] [article] Optimization of pile groups using hybrid genetic algorithms [texte imprimé] / Chan, C. M., Auteur ; Zhang, L. M., Auteur ; Jenny T. Ng, Auteur . - 2009 . - pp. 497–505.
Geotechnical and geoenvironmental engineering
Langues : Anglais (eng)
in Journal of geotechnical and geoenvironmental engineering > Vol. 135 N° 4 (Avril 2009) . - pp. 497–505
Mots-clés : Pile foundations Pile caps Pile groups Algorithms Optimization Limit states Résumé : This paper presents an automated optimal design method using a hybrid genetic algorithm for pile group foundation design. The design process is a sizing and topology optimization for pile foundations. The objective is to minimize the material volume of the foundation taking the configuration, number, and cross-sectional dimensions of the piles as well as the thickness of the pile cap as design variables. A local search operator by the fully stressed design (FSD) approach is incorporated into a genetic algorithm (GA) to tackle two major shortcomings of a GA, namely, large computation effort in searching the optimum design and poor local search capability. The effectiveness and capability of the proposed algorithm are first illustrated by a five by five pile group subjected to different loading conditions. The proposed optimization algorithm is then applied to a large-scale foundation project to demonstrate the practicality of the algorithm. The proposed hybrid genetic algorithm successfully minimizes the volume of material consumption and the result matches the engineering expectation. The FSD operator has great improvement on both design quality and convergence rate. Challenges encountered in the application of optimization techniques to design of pile groups consisting of hundreds of piles are discussed. En ligne : http://ascelibrary.org/doi/abs/10.1061/%28ASCE%291090-0241%282009%29135%3A4%2849 [...]