Similarity Measuring Approuch for Engineering Materials Selection

Auteurs : Doreswamy, M. N. Vanajakshi

International Journal of Computational Intelligence Systems (IJCIS), Vol.3, Issue 1, April 2010, pp.115-122. (ISSN: 1875-6883)

Résumé : Advanced engineering materials design involves the exploration of massive multidimensional feature spaces, the correlation of materials properties and the processing parameters derived from disparate sources. The search for alternative materials or processing property strategies, whether through analytical, experimental or simulation approaches, has been a slow and arduous task, punctuated by infrequent and often expected discoveries. A few systematic efforts have been made to analyze the trends in data as a basis for classifications and predictions. This is particularly due to the lack of large amounts of organized data and more importantly the challenging of shifting through them in a timely and efficient manner. The application of recent advances in Data Mining on materials informatics is the state of art of computational and experimental approaches for materials discovery. In this paper similarity based engineering materials selection model is proposed and implemented to select engineering materials based on the composite materials constraints. The result reviewed from this model is sustainable for effective decision making in advanced engineering materials design applications.

Soumis à arXiv le 02 Jan. 2013

Explorez l'arbre d'article

Cliquez sur les nœuds de l'arborescence pour être redirigé vers un article donné et accéder à leurs résumés et assistant virtuel

Accédez également à nos Résumés, ou posez des questions sur cet article à notre Assistant IA.

Beta

Recherchez des articles similaires (en version bêta)

En cliquant sur le bouton ci-dessus, notre algorithme compare le titre et le résumé de cet article à tous les articles de la même catégorie arXiv que nous avons résumés, et trouve les plus proches. Vous pouvez le relancer de temps en temps : les résultats s'améliorent à mesure que notre base grandit.