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دانلود رایکان مقاله انگلیسی ISI با موضوع ارزیابی عملکرد یک سیستم جداسازی پایه از نوع متحرک با یک دستگاه آلیاژ حافظه دار NiTi

عنوان فارسی مقاله:

ارزیابی عملکرد یک سیستم جداسازی پایه از نوع متحرک با یک دستگاه آلیاژ حافظه دار NiTi که اثرات دما را در نظر می گیرد

عنوان انگلیسی مقاله:

Evaluation of the performance of a sliding-type base isolation system with a NiTi shape memory alloy device considering temperature effects

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2. Modeling superelastic shape memory alloys

The inherent complexity of superelastic behavior of SMAs makes modeling behavior of the material challenging. Many researchers have studied to develop constitutive models that can reproduce complex stress–strain relationship of SMAs [29–32]. However, most of these studies aim to model quasi-static material response and neglect rate- and/or temperature-dependent behavior of SMAs [33]. Since SMAs will be exposed to dynamic effects and temperature changes when they are used for seismic control of bridges, it is important to consider the dependence of the mechanical response of SMAs on the high loading rate and temperature. However, considering the loading rate and/or temperature effects makes SMA constitutive models complicated and numerically expensive to implement into simulations. 

In this study, a neuro-fuzzy technique is used to develop a simple, accurate, and computationally efficient model for simulating the superelastic behavior of NiTi shape memory alloys. Here, a brief discussion of the neuro-fuzzy model is given, yet a detailed description of the model can be found in [34].

Fuzzy logic and neural networks are among the soft computing technologies that have been widely used in engineering applications in past decades. The combination of these methods results in intelligent systems that possess the strengths of each technique. The adaptive neuro-fuzzy inference system (ANFIS) is such a hybrid system that allows a fuzzy model to learn its parameters using neural network strategies [35]