Artificial neural network model is developed for the prediction of phase transformation of
steel from austenite, and thus construction of the continuous cooling transformation (CCT) …

Simulation of creep curves using data obtained from a limited number of short-time creep
tests is helpful for predicting the long-time creep life of materials by extrapolation techniques …

A genetic algorithm (GA) based optimization of the composite desirability of the tensile
properties of thermomechanically processed high strength low alloy (HSLA) steel plates is …

Modification of the architecture of the artificial neural network is done to accommodate the
information available from the knowledge base in the field of materials science for …

We investigated various numerical methods including a physical-based empirical equation,
linear regression, shallow neural network, and deep learning approaches, to compare their …

Abstract High Entropy Alloys (HEAs) are constituted by at least five elements and can even
increase to seven or eight different elements. Due to high entropy of mixing, the solid …

Ionic polymer metal composites (IPMC) are an emerging class of electro-active polymers,
which are used as sensors and actuators in soft robots. In this study, the methodology of …

Multi-objective optimization is employed using genetic algorithm, for designing novel age-
hardenable aluminium alloy with improved properties. Data on the mechanical properties of …

Magnesium alloys are advantageous for their low specific gravity and a high strength-to-
weight ratio. These properties make the alloys find their utilization in different domain like …

The effect of composition and process parameters on the mechanical properties of high-
strength low-alloy (HSLA) steels is modeled by the application of fuzzy systems viz. Sugeno …