Strategies for modelling and optimization of bi-stable composite laminates actuated by embedded Shape Memory Alloy wires

Imparting controllable flexural rigidity into a material system is one of the key motivations for the design of intelligent materials for structural applications. In this direction, shape memory alloy (SMA) reinforced polymer composites have enormous potentials for active shape and vibration control of systems related to aerospace, automobile, and energy harvesting applications. The primary motivation of reinforcing SMA wires into a composite is to actively change the composite stiffness or elasticity through thermo-mechanical as well as electrical/magnetic stimulation. The SMA -reinforced hybrid composites are found to be able to adapt their shape, which may also improve the specific strength, vibration damping, and self-healing capability by utilizing shape memory effect and pseudoelastic behavior of the SMA. In this paper, we intend to provide a comprehensive review of all SMA -reinforced composites available today in the open literature and a critical assessment of the technology. Currently, shape memory alloys in the form of long fibers (wires), ribbons, short fibers, and particles are used for hybridizing the reinforcements in composites. Continuous SMA fiber embedded composites are generally used for shape control of structures. However, it has difficulty in obtaining suitable interfacial characteristics required for actuation. The discontinuous SMA embedded composites have scope for modifying such active properties. The work presented here gives an overview of the concepts of design, development, and modeling of continuous and discontinuous shape memory alloy embedded composites for advanced smart composites.

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“…Bi-stable composite laminates Shape morphing in aerospace structures, wind turbines, automobiles [25].…”

Section: Research Area Utilitymentioning

confidence: 99%

“…Hence, the incremental constitutive equation for short fiber SMA elastic matrix composite can be drafted by substituting equation (26) and equation (27) into equation equation (25) as follows.…”

Section: Matrixmentioning

confidence: 99%