Shape-Memory Alloys and Effects: Types, Functions, Modeling, and Applications

Abstract

The most salient feature of modeling work in the area of smart materials is its great diversity. Materials considered as smart span a staggeringly wide range. Smart materials run the gamut from the inorganic, monolithic crystalline materials, to the organic, polymeric, semi crystalline ones. Composites, polycrys¬talline materials, hydrated gels, magneto strictive/ferromagnetic tagged composites, electrochromic materials, etc. to mention but a few, further expand the range of smart materials to be modeled. The complexity that arises from this great variety of material types is compounded with the wide range of interesting properties they display. Finally, the question of the time and the length of scales at which the modeling is to be implemented adds an extra level of complexity to the field: Even when applied to the very same material and the very same property, it frequently happens that different smart material modelers (i) look at the material at vastly different spatial or temporal scales, (ii) use completely unrelated modeling techniques, and (iii) even come to conclusions and modeling results, which can be unrelated for all practical purposes.