4.5 Article

A theory of anisotropic healing and damage mechanics of materials

出版社

ROYAL SOC
DOI: 10.1098/rspa.2011.0326

关键词

plasticity; continuum damage-healing mechanics; polymers; self-healing materials; thermodynamic framework

资金

  1. NSF [CMMI0900064, HRD0932300]
  2. National Research Foundation of Korea
  3. Directorate For Engineering
  4. Div Of Civil, Mechanical, & Manufact Inn [0900064] Funding Source: National Science Foundation

向作者/读者索取更多资源

Self-healing smart materials have emerged into the research arena and have been deployed in industrial and biomedical applications, in which the modelling techniques and predicting schemes are crucial for designers to optimize these smart materials. In practice, plastic deformation is coupled with damage and healing in these systems, which necessitates a coupled formulation for characterization. The thermodynamics of inelastic deformation, damage and healing processes are incorporated here to establish the coupled constitutive equations for healing materials. This thermodynamic consistent formulation provides the designers with the ability to predict the irregular inelastic deformation of glassy polymers and damage and healing patterns for a highly anisotropic self-healing system. Moreover, the lack of a physically consistent method to measure and calibrate the healing process in the literature is addressed here. Within the continuum damage mechanics (CDM) framework, the physics of damage and healing processes is used to introduce the healing effect into the CDM concept and a set of two new anisotropic damage-healing variables are derived. These novel damage-healing variables together with the proposed thermodynamic consistent coupled theory constitute a well-structured method for accurately predicting the degradation and healing mechanisms in material systems. The inelastic and damage response for a shape memory polymer-based self-healing system is captured herein. While the healing experimental results are limited in the literature, the proposed theory provides the mathematical competency to capture the most nonlinear responses.

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