The influence of loading during cold shape formation on the amount of shape recovery in NiTi alloys
ABSTRACT The long-term stability of the shape memory effect is critical for ensuring repeatability in shape memory alloy (SMA) based actuation devices. It is well known that the degradation in shape recoverability originates mainly from the generation of a permanent strain and its accumulation over repeated cyclical operations. Such strains should be minimized and the recoverable strain maximized. This requires a detailed understanding of the deformation behaviour of SMAs under loading, heating and cooling. This study investigates how the application of loading under different representative heating and cooling paths between martensite and austenite (loading paths) influences the deformation behaviour and the amount of shape memory achievable in a NiTi SMA. The deformation behaviour differs, depending on the magnitude of the applied load and especially the material phase of SMA under which the external load is applied. During the formation of martensite upon cooling, deformation occurs with great ease and much larger recoverable strains at the same level of external loading are achieved than in full martensite and austenite, while during the heating process for reverse transformation, even a small deformation arising from the formation of stress induced martensite is liable to introduce a permanent strain. A detailed analysis and an interpretation of these phenomena are presented.
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ABSTRACT: In this paper the two-way shape memory effect (TWSME) of a Ni–51 at.% Ti alloy is investigated and a numerical model is developed, which allows real time simulations of its hysteretic behaviour strain versus temperature. The two-way shape memory effect (TWSME) was induced through a proper thermo-mechanical training, carried out at an increasing number of training cycles and for two values of training deformation. The TWSME was measured under different applied stresses and the hysteretic behaviour in the strain–temperature response was recorded. In order to evaluate the thermal stability of the hysteresis loops the material was subjected to many cycles, by repeated heating and cooling, between Af (austenite finish temperature) and Mf (martensite finish temperature). The numerical method is based on a phenomenological approach and was developed in a Matlab® function, which calculates the model parameters from a set of experimental data, and a Simulink® model, which is efficient enough for use in real time applications. The accuracy of the proposed model was analysed through systematic comparisons between experimental measurements and numerical predictions.Smart Materials and Structures 04/2007; 16(3):771. · 2.02 Impact Factor
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ABSTRACT: The creation of an effective two-way shape memory alloy (TWSMA) requires appropriate heat treatment and optimal training considerations. In particular, the training method used plays a key role. This work investigates different training methods for producing NiTi TWSMA wires with the hot shape of an arc and the cold shape of a straight line. These methods are shape memory cycling, constrained cycling of deformed martensite, pseudoelastic cycling and combined shape memory and pseudoelastic cycling. In order to give a meaningful evaluation of their performance that is relevant to training TWSMA for practical applications, these training methods are assessed in terms of maximum two-way strain, changes in the original hot shape together with the transformation temperatures after the training process, and the effective production of the cold shape. It was found that only the combined shape memory and pseudoelastic cycling provides an effective training method for creating NiTi TWSMA with a non-uniaxial two-way shape change. The undesirable side effects of training are that the NiTi TWSMA wire loses partial memory of the original hot shape and its transformation temperatures shift to lower values. There also exists an optimal number of training cycles, and possibly an optimal training load for obtaining the best cold shape memory and the greatest two-way recoverable strain. These findings give future directions to advance the training technology for TWSMA.Smart Materials and Structures 01/2007; · 2.02 Impact Factor