Soft computing techniques in advancement of structural metals

Abstract

Current trends in the progress of technology demand availability of materials resources ahead of the advancing fronts of the application areas. During the last couple of decades, significant progress has been made in computational and experimental design of materials. Among the potential computational techniques, soft computing stands in distinction due to the inherent flexibility in capturing the complexity of the problem in global scale. Since 1990s remarkable success has been achieved in soft computing activities in different facets of materials science and engineering. Extensive efforts have been devoted in design of metals and alloys based on composition-process-microstructure-property correlation. The present review aims to address the contribution of soft computing in the field of structural metals and alloys including processing and joining. The critical issues concerning applicability of particular techniques in specific materials problem have been particularly emphasised encompassing the scope of integrating the gradual progress in different techniques in hybrid and tandem framework to address greater complexities in larger length and time scale. Attempt has also been made to emphasise on the evolution of newer knowledge and materials through soft computing activities. Finally, the potential of soft computing techniques in futuristic design approaches has been critically enumerated.

Imprecise knowledge based design and development of titanium alloys for prosthetic applications

“…single crystal elastic constants of Mg-Li alloys using density functional theory (DFT) [23], semiconductor spintronics [24], and Pb(Sc0.5Nb0.5)O3 perovskite alloy [25] etc. However, informatics-based design using computational intelligence techniques have been successfully used for designing Ti alloys [26][27] and other materials [28][29][30]. Informatics based materials design strategies try to extract the inherent correlation within data and utilize the information for designing novel materials [31].…”

In silico Design of High Strength Aluminium Alloy Using Multi-objective GA

“…Computational approaches for designing the alloys makes the development process easier [3]. Here computational intelligence techniques come into picture as it has the ability to handle problems non-linear, complex systems as in cases of metals and alloys [4]. Genetic algorithm (GA) [5,6] has been successfully employed for designing novel materials [7][8][9][10].…”

An Informatics Based Approach to Reduce the Grain Size of Cast Hadfield Steel

“…Useful and novel information extracted from this available data, could be utilized for the designing of new composition or processing for developing new material with improved performance [5]. The scheme of materials informatics could be implemented using concepts of statistics and/or computational intelligence based tools [6][7][8], viz. artificial neural network (ANN) [9,10], fuzzy logic [11][12][13][14], rough sets (RS) [15][16][17][18], and evolutionary algorithms [7,19,20].…”