Real time inverse solution of the composites' cure heat transfer problem under uncertainty

Date

2019-12-09

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Taylor & Francis

Department

Type

Article

ISSN

1741-5977

Format

Free to read from

Citation

Tifkitsis K, Skordos AA. (2020) Real time inverse solution of the composites' cure heat transfer problem under uncertainty. Inverse Problems in Science and Engineering, Volume 28, Issue 7, 2020, pp. 1011-1030

Abstract

This paper addresses the development of an inversion scheme based on Markov Chain Monte Carlo integrating process modelling with monitoring data for the real-time probabilistic estimation of unknown stochastic input parameters such as heat transfer coefficient and resin thermal conductivity and process outcomes during the manufacture of fibrous composites materials. Kriging was utilized to build an efficient surrogate model of the composite curing process based on finite element modelling. The utilization of an inverse scheme with real-time temperature monitoring driving the estimation of process parameters during manufacture results in real-time probabilistic prediction of process outcomes.

Description

Software Description

Software Language

Github

Keywords

Composites manufacturing, Curing, Uncertainty estimation, Inverse analysis, Markov Chain Monte Carlo

DOI

Rights

Attribution-NonCommercial 4.0 International

Relationships

Relationships

Supplements

Funder/s