Minimum Area Discrepancy Method (MADM) Python Executables

Christophe Bastien; Jesper Christensen

Minimum Area Discrepancy Method (MADM) Python Executables

Christophe Bastien (Developer), Jesper Christensen

Research output: Practice-Based and Non-textual Research › Software

Abstract

Latest version of MADM (Win64), which stands for “Minimum Area Discrepancy Method (MADM)”.

This computer method is suited for research and industry

This new application has two major and unique benefits:
1) Correlate CAE models against Force vs Displacement signals (i.e. against a mean/median, lower corridor (+1 or 2 standard deviations) and upper corridor (+1 or 2 standard deviations)).
2) Improve the final CORA selection process.

The download link provides the computer programme with GUI aned BATCH modes.

Original language	English
Publication status	Published - 28 Jan 2022

Keywords

Automotive engineering Materials
Automotive safety Engineering
Biomechanical Engineering
minimum area discrepancy method

ASJC Scopus subject areas

Automotive Engineering

Access to Document

https://figshare.com/articles/software/Minimum_Area_Discrepancy_Method_MADM_Python_Executables/19085963Licence: CC BY

1 Oral presentation

A Numerical Framework to Improve Computer Model Correlation
Bastien, C. (Speaker), Diederich, A. (Speaker), Christensen, J. (Speaker) & Ghaleb, S. (Speaker)
22 Jun 2022
Activity: Talk or presentation › Oral presentation

1 Article

Improving Correlation Accuracy of Crashworthiness Applications by Combining the CORA and MADM Methods
Bastien, C., Diederich, A., Christensen, J. & Ghaleb, S., Dec 2022, In: Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 236, 14, p. 3192-3200 9 p.
Research output: Contribution to journal › Article › peer-review

Open Access
File
4 Citations (Scopus)

333 Downloads (Pure)

Cite this

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title = "Minimum Area Discrepancy Method (MADM) Python Executables",

abstract = "Latest version of MADM (Win64), which stands for “Minimum Area Discrepancy Method (MADM)”.This computer method is suited for research and industryThis new application has two major and unique benefits:1) Correlate CAE models against Force vs Displacement signals (i.e. against a mean/median, lower corridor (+1 or 2 standard deviations) and upper corridor (+1 or 2 standard deviations)).2) Improve the final CORA selection process.The download link provides the computer programme with GUI aned BATCH modes.",

keywords = "Automotive engineering Materials, Automotive safety Engineering, Biomechanical Engineering, minimum area discrepancy method",

author = "Christophe Bastien and Jesper Christensen",

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N2 - Latest version of MADM (Win64), which stands for “Minimum Area Discrepancy Method (MADM)”.This computer method is suited for research and industryThis new application has two major and unique benefits:1) Correlate CAE models against Force vs Displacement signals (i.e. against a mean/median, lower corridor (+1 or 2 standard deviations) and upper corridor (+1 or 2 standard deviations)).2) Improve the final CORA selection process.The download link provides the computer programme with GUI aned BATCH modes.

AB - Latest version of MADM (Win64), which stands for “Minimum Area Discrepancy Method (MADM)”.This computer method is suited for research and industryThis new application has two major and unique benefits:1) Correlate CAE models against Force vs Displacement signals (i.e. against a mean/median, lower corridor (+1 or 2 standard deviations) and upper corridor (+1 or 2 standard deviations)).2) Improve the final CORA selection process.The download link provides the computer programme with GUI aned BATCH modes.

KW - Automotive engineering Materials

KW - Automotive safety Engineering

KW - Biomechanical Engineering

KW - minimum area discrepancy method

M3 - Software

ER -

Minimum Area Discrepancy Method (MADM) Python Executables

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Activities

A Numerical Framework to Improve Computer Model Correlation

Research output

Improving Correlation Accuracy of Crashworthiness Applications by Combining the CORA and MADM Methods

Cite this