Modeling Inelastic Responses Using Constrained Reactive Mixtures
Gerard A Ateshian1, Clark T Hung2, Jeffrey A Weiss3
1Columbia University, Department of Mechanical Engineering, 10027, New York, New York, United States.
Summary
This study introduces constrained reactive mixture theories for modeling inelastic solid material responses, utilizing observable variables instead of hidden internal state variables for enhanced accuracy.
Area of Science:
- Solid Mechanics
- Materials Science
- Continuum Mechanics
Background:
- Traditional models for inelastic responses in solids rely on internal state variable theory.
- This approach often involves hidden variables and complex evolution equations.
- Existing methods may not fully capture the complexities of material behavior under various conditions.
Purpose of the Study:
- To present an alternative foundational approach for modeling inelastic responses in solids.
- To develop theories based on observable state variables, moving away from hidden internal state variables.
- To extend the application from cartilage tissue engineering to general solid materials.
Main Methods:
- Formulation of constrained reactive mixture theories.
- Modeling multiple solid generations co-existing within a mixture.
- Utilizing observable state variables like deformation gradient and referential mass concentrations.
- Governing the evolution of mass concentrations via the axiom of mass balance.
Main Results:
- Demonstrated a framework where multiple solid generations coexist with shared velocity but distinct reference configurations.
- Developed a formulation that relies solely on observable state variables.
- Provided an alternative to classical internal state variable theories for inelastic responses.
- Showcased applicability to damage mechanics, viscoelasticity, plasticity, and elasto-plastic damage.
Conclusions:
- The constrained reactive mixture theory offers a robust alternative for modeling inelastic solid behaviors.
- This approach simplifies modeling by avoiding hidden internal state variables.
- The framework is grounded in the classical theory of mixtures, providing a solid theoretical foundation.
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