MaterialModeler—From experimental raw data to a material model
Author(s) -
T. Benkert,
Christoph Hartmann,
M. Eder,
F. Speckmaier,
Wolfram Volk
Publication year - 2019
Publication title -
softwarex
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.528
H-Index - 21
ISSN - 2352-7110
DOI - 10.1016/j.softx.2019.100249
Subject(s) - computer science , software , raw data , process (computing) , closing (real estate) , experimental data , sheet metal , code (set theory) , field (mathematics) , data mining , programming language , mechanical engineering , set (abstract data type) , engineering , statistics , mathematics , political science , pure mathematics , law
To perform the numerical analysis of metal forming processes, material models are needed. These models are based on experiments such as the tensile test. To generate a material model from experimental results, the test data must be analyzed, possibly smoothed, fitted by mathematical approaches and exported in the format of the simulation software. Currently this is achieved using proprietary software, self-programmed code or spreadsheets. The software MaterialModeler is aimed at closing the gap between the data generated in experiments and simulation software to improve the quality of material models, especially in respect of complex to model materials. Simultaneously, the error rate compared to the current manual process is decreased and every step from the experimental raw data to the material model is reproducible. MaterialModeler has been developed in the field of sheet metal forming, but it should easily be possible to extend its use to other disciplines.
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