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A minimum area discrepancy method (MADM) for force displacement response correlation.

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A new Minimum Area Discrepancy Method (MADM) objectively evaluates Force versus Deflection (FvD) signals in simulations. This method improves crashworthiness and biomechanics model correlation by quantifying the discrepancy between numerical and physical test data.

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Area of Science:

  • * Computational Mechanics
  • * Biomechanics
  • * Crashworthiness Engineering

Background:

  • * Computer Aided Engineering (CAE) necessitates accurate numerical model evaluation.
  • * Existing metrics like CORA evaluate parameter vs. time data, but lack a method for Force vs. Deflection (FvD) signals.
  • * FvD signals are crucial in biomechanics and crashworthiness applications.

Purpose of the Study:

  • * To introduce the Minimum Area Discrepancy Method (MADM) for objectively evaluating FvD signal correlation.
  • * To validate MADM using a Finite Element (FE) chest model against Post Mortem Human Subject (PMHS) data.
  • * To demonstrate MADM's utility in optimizing numerical models for better correlation.

Main Methods:

  • * Calculation of parameter 'R' representing the area between numerical and average physical test responses.
  • * Normalization of 'R' between 0 and 1 to derive the MADM correlation rating.
  • * Validation using a 1D FE chest model under impact, comparing against PMHS data and optimizing parameters.

Main Results:

  • * The MADM method provides an objective correlation rating for FvD signals.
  • * Validation demonstrated MADM's effectiveness in assessing and improving a chest model's response.
  • * Optimization using MADM identified parameter values yielding a significantly improved model fit.

Conclusions:

  • * MADM is a novel, unique, and user-friendly method for evaluating FvD correlation.
  • * It addresses a critical gap in objectively assessing simulation accuracy for FvD data.
  • * MADM facilitates enhanced correlation between numerical models and physical experiments in biomechanics and crashworthiness.