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@inproceedings{Wang:2016:3/032042,
author = {Wang, A and Zheng, Y and Liu, J and El, Fakir O and Masen, M and Wang, L},
doi = {3/032042},
pages = {032042--032042},
publisher = {IOP Publishing},
title = {Knowledge Based Cloud FE simulation – data-driven material characterization guidelines for the hot stamping of aluminium alloys},
url = {http://dx.doi.org/10.1088/1742-6596/734/3/032042},
year = {2016}
}
TY - CPAPER
AB - The Knowledge Based Cloud FEA (KBC-FEA) simulation technique allows multi-objective FE simulations to be conducted on a cloud-computing environment, which effectively reduces computation time and expands the capability of FE simulation software. In this paper, a novel functional module was developed for the data mining of experimentally verified FE simulation results for metal forming processes obtained from KBC-FE. Through this functional module, the thermo-mechanical characteristics of a metal forming process were deduced, enabling a systematic and data-driven guideline for mechanical property characterization to be developed, which will directly guide the material tests for a metal forming process towards the most efficient and effective scheme. Successful application of this data-driven guideline would reduce the efforts for material characterization, leading to the development of more accurate material models, which in turn enhance the accuracy of FE simulations.
AU - Wang,A
AU - Zheng,Y
AU - Liu,J
AU - El,Fakir O
AU - Masen,M
AU - Wang,L
DO - 3/032042
EP - 032042
PB - IOP Publishing
PY - 2016///
SN - 1742-6588
SP - 032042
TI - Knowledge Based Cloud FE simulation – data-driven material characterization guidelines for the hot stamping of aluminium alloys
UR - http://dx.doi.org/10.1088/1742-6596/734/3/032042
UR - http://hdl.handle.net/10044/1/37439
ER -