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Related Concept Videos

Elastic Strain Energy for Shearing Stresses01:20

Elastic Strain Energy for Shearing Stresses

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As discussed in previous lessons, strain energy in a material is the energy stored when it is elastically deformed, a concept crucial in materials science and mechanical engineering. This energy results from the internal work done against the cohesive forces within the material. When a material undergoes shearing stress and corresponding shearing strain, the strain energy density, which is the energy stored per unit volume, is calculated. Within the elastic limit, where the stress is...
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Residual Stresses01:26

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Residual stresses reside in a structure even after removing the original stress inducer. This phenomenon often arises from varied plastic deformations across different parts of a structure. Consider a rod stretched beyond its yield point. It will not regain its original length due to permanent deformation. Even after load removal, the rod does not entirely lose stress because of uneven plastic deformations, resulting in residual stresses. The computation of these stresses in structures is...
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In the study of elastoplastic members subjected to bending moments, understanding the loading and unloading phases is crucial for assessing material behavior and structural integrity. During the loading phase, as the bending moment increases, the material initially responds elastically, adhering to Hooke's Law, where stress is directly proportional to strain. When the load exceeds the yield strength, plastic deformation occurs, resulting in permanent strain and deformation that remains even...
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Stresses under Combined Loadings01:23

Stresses under Combined Loadings

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When analyzing a bent tube with a circular cross-section subjected to multiple forces, it is crucial to determine the stress distribution in order to maintain structural integrity under varied load conditions.
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Bending of Members Made of Several Materials01:11

Bending of Members Made of Several Materials

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In analyzing a structural member composed of two different materials with identical cross-sectional areas, it is crucial to understand how their distinct elastic properties affect the member's response under load. The analysis involves assessing stress and strain distributions using the transformed section concept, which accounts for variations in material properties.
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Dynamic Modulus of Elasticity of Concrete01:16

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Multiscale Uncertainty Quantification of Woven Composite Structures by Dual-Correlation Sampling for Stochastic

Guangmeng Yang1, Sinan Xiao2, Chi Hou3

  • 1Jihua Laboratory, Foshan 528200, China.

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|October 16, 2025
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Summary

This study introduces a multiscale uncertainty quantification framework for woven composites. It accurately predicts structural performance and damage by capturing material property correlations, unlike traditional methods.

Keywords:
multiscale simulationmultivariate random fieldprobabilistic distributionspatial correlationuncertainty quantificationwoven composites

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Area of Science:

  • Materials Science
  • Mechanical Engineering
  • Computational Science

Background:

  • Woven composites exhibit uncertainties from material properties to geometry, affecting structural performance.
  • These uncertainties cause spatial correlations, leading to variable strength and damage patterns.

Purpose of the Study:

  • To develop a multiscale uncertainty quantification framework for woven composites.
  • To accurately propagate uncertainties from microscale to macroscale, considering spatial correlations.

Main Methods:

  • Proposed a novel dual-correlation sampling approach based on multivariate random field (MRF) theory.
  • Simultaneously captured spatial autocorrelation and cross-correlation for realistic material property representation.
  • Validated the framework using in-plane tensile tests on woven composite structures.

Main Results:

  • The dual-correlation sampling approach accurately predicted probabilistic mechanical responses and damage morphology.
  • Demonstrated superior accuracy compared to traditional independent sampling methods.
  • Highlighted the importance of capturing spatial correlations for reliable predictions.

Conclusions:

  • The developed framework provides a robust method for uncertainty quantification in woven composites.
  • Findings enhance structural reliability assessment and risk management in engineering.
  • Emphasized the limitations of ignoring spatial correlations in composite material modeling.