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Student Examines Material
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Dr. Dimitris Lagoudas and Dr. Ibrahim Karaman

SMAs exhibit coupled responses to stimuli (thermo-mechanical, magneto-mechanical, and fluid-morphing solid couplings) that make them extremely useful for a wide variety of engineering applications, such as small actuators or sensors. However, efficient design of SMA-based systems that achieve optimum performance requires the ability to simulate and analyze active responses at both the local and system levels. Our team has been developing and improving an engineering design framework that allows for automated, iterative design optimization of fabricated systems. This framework employs numerical implementations of continuum approaches, such as non-linear finite element analysis, that make it possible to directly simulate active responses at both the local and system levels (Fig. 2).

Research Plan:
The REU student will help to develop and implement user material subroutines for in-house composite analysis codes, allowing customized capabilities to model behavior of SMAs. Bridging of scales from the micro- to the macro-scales will be performed using the methods of micro-mechanics such as the Mori-Tanaka and self-consistent schemes, with which the research team is highly experienced. Material properties used to calibrate all models will be derived from carefully performed experiments designed to quantify both mechanical and coupled (e.g., thermo-mechanical, magneto-mechanical) responses. Results will be validated through characterization of the materials using specialized equipment, including low-pressure grips, contact-free deformation measurement techniques, and environmental chambers. Results will be passed back to the simulation processes management framework for determination of additional optimization studies. As the student learns to use the analysis tools and becomes more independent, he/she will have the opportunity to conduct initial analysis and validation of a specific candidate design, gaining experience in the experimentally validated analysis and iterative optimization of active, passive, and multifunctional components, especially for aerospace systems.