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Shape memory alloy sensory particles for damage detection: Experiments, analysis, and design studies

Author(s):


Medium: journal article
Language(s): English
Published in: Structural Health Monitoring, , n. 4, v. 17
Page(s): 777-814
DOI: 10.1177/1475921717721194
Abstract:

Developing novel techniques for monitoring structural integrity has become an important area of research in the aerospace community. One new technique exploits the stress-induced phase transformation behavior in shape memory alloy particles embedded in a structure. By monitoring changes in the mechanical and/or electromagnetic behavior of such particles, the formation or propagation of fatigue cracks in the vicinity of these particles can be detected. This work demonstrates sensory particle response to local structural damage using finite element modeling for the first time. Using an optimization method to minimize the difference between experimentally measured strain and simulated results, a good approximation of sensory particle properties can be determined and the strong sensory response of the transforming particle demonstrated. To illustrate an application of this method, a multi-scale finite element model of sensory particles embedded in the root rib of an aircraft wing is then considered. In particular, this unique model utilizes substructure modeling to maintain computational efficiency while relating globally applied loads to local structural response, allowing for the consideration of predicted particle response to crack propagation during wing loading. The effect of particle position relative to the crack tip on particle sensory response is assessed. Finally, this work demonstrates how sensory particles can be used to approximate the location of structural damage by interpolating a stress field based on the responses of multiple sensory particles in the vicinity of a propagating crack.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1177/1475921717721194.
  • About this
    data sheet
  • Reference-ID
    10562103
  • Published on:
    11/02/2021
  • Last updated on:
    19/02/2021
 
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