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A Probabilistic Approach to Assessing and Predicting the Failure of Notched Components.

Miguel Muñiz-Calvente1, Lucas Venta-Viñuela1, Adrián Álvarez-Vázquez1

  • 1Department of Construction and Manufacturing Engineering, University of Oviedo, Campus de Viesques, 33203 Gijón, Spain.

Materials (Basel, Switzerland)
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PubMed
Summary
This summary is machine-generated.

This study introduces a probabilistic model using the generalized local method (GLM) to predict material failure. This approach ensures reliable component design by establishing a transferable primary failure cumulative distribution function (PFCDF).

Keywords:
Notch effectgeneralised local modelprobability of failure

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Area of Science:

  • Materials Science and Engineering
  • Mechanical Engineering
  • Probabilistic Mechanics

Background:

  • Evaluating strength in notched components requires robust probabilistic models.
  • Existing methods often lack transferability across different test conditions and geometries.
  • Material characterization needs to account for inherent statistical variability.

Purpose of the Study:

  • To develop and validate a probabilistic model for evaluating strength results in notched components.
  • To derive a transferable material property, the primary failure cumulative distribution function (PFCDF), using the generalized local method (GLM).
  • To confirm the applicability of the GLM methodology for reliable component design.

Main Methods:

  • Application of the generalized local method (GLM) to derive the primary failure cumulative distribution function (PFCDF).
  • Experimental characterization program using EPOLAM 2025 epoxy resin specimens with three different notch geometries.
  • Two assessment scenarios: individual sample analysis with cross-failure predictions and a joint assessment of all samples.

Main Results:

  • Individual sample assessments showed some discrepancies in cross-failure predictions, attributed to statistical variability and limited sample size.
  • A joint assessment of all three samples yielded a unique PFCDF, confirming the GLM's reliability.
  • The joint assessment verified the suitability of the driving force and confirmed the transferability of the material characterization.

Conclusions:

  • The generalized local method (GLM) provides a reliable framework for deriving a transferable primary failure cumulative distribution function (PFCDF).
  • Joint assessment of multiple specimen geometries enhances the accuracy and reliability of material strength predictions.
  • The developed methodology ensures transferability in component design, improving material characterization effectiveness.