Work

A machine learning based prediction of elasto-plastic response of a short fiber reinforced polymer (SFRP) composite

Year: 2023

Type: article

Abstract: Several homogenization techniques are available in the literature to compute the mechanical response of the short fiber-reinforced polymer (SFRP) composites. However, in some cases, the complex modeling of the SFRP makes it computationally expensive. In this study, an artificial neural network (ANN) is developed to predict the elasto-plastic response of an SFRP. The datasets for training the ANN model are obtained from Mori-Tanaka mean-field homogenization using the commercial software Digimat. The elasto-plastic response predicted by the ANN model is compared with the experimental results and with different homogenization schemes reported in the literature. Additionally, the effect of significant parameters on the response of the SFRP is extensively studied using the ANN model.

Source: Modelling and Simulation in Materials Science and Engineering

DOI: 10.1088/1361-651x/aced5a

Authors: Subrat Kumar Maharana, Ganesh Soni, Mira Mitra

Institutions: Indian Institute of Technology Kharagpur, Hexagon (United Kingdom)

Language: English

Topic: Composite Material Mechanics

Subfield: Mechanics of Materials

Field: Engineering

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W4385568616

FWCI: 0.996

Cites: 46

Cited by: 10

Related to: 10