Browsing by Author "Rahmati, Amir Hossein"
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Item Application of Machine Learning in Failure Prediction of Brazed-Aluminum Based Heat Exchangers(2019-05) Rahmati, Amir Hossein; Sharma, Pradeep; Kulkarni, Yashashree; Nakshatrala, Kalyana BabuBrazed aluminum plate-fin heat exchangers (BAHX), extensively used by the natural gas liquid recovery and gas processing industry, are subject to a uniquely stressful and harsh environment that involves large thermal stresses due to steady-state and transient thermal loads, mechanical loads, contaminants, corrosion and exposure to low temperatures. Despite careful design for unlimited life, several pre-mature failures in different natural gas processing plants have been happened which has resulted in significant loss of revenue and serious life threats. In this work, we used finite element analysis to explain potential reasons for failure occurred at two failed BAHX. Since this kind of modeling has limited utility and a stronger tool for prediction of failure has to be developed, we train an artificial neural network which can predict failure by distinguishing between healthy operating conditions and unhealthy operating conditions. An excellent accuracy was obtained for the current available dataset. However, since available dataset was extremely limited, we believe training should be performed on a much larger dataset to have reliable results.Item Deformation, Light, Electrical and Magnetic Fields in Soft Matter(2022-05-11) Rahmati, Amir Hossein; Sharma, Pradeep; Kulkarni, Yashashree; Nakshatrala, Kalyana Babu; Baxevanis, Theocharis; Joshi, Shailendra P.One of the holy grails of soft multifunctional materials is to design a material that is simultaneously capable of (i) large deformation under the application of a moderate external stimuli such as an electric or magnetic field and (ii) generating appreciable electric field under the application of moderate forces. Such soft materials enable applications that range from sensors, actuators, artificial muscles, self-powered biomedical devices, soft robotics to energy harvesting. In this dissertation, we focus on three different aspects of the design of soft multifunctional materials: (1) Use of immobile embedded charges (called electrets) to obtain an emergent piezoelectric or flexoelectric response in a soft material Specifically, we show the underlying mechanisms for the weak apparent piezoelectric effect in flexure mode of electret beams and how to appropriately design such structures for energy harvesting applications. (2) Imagine a material that will produce electricity via a contactless, wireless signal. Further, we hope that this material is capable of large deformation reminiscent of soft robots. This would all be possible if soft magnetoelectric materials were available; paving the way for applications such as remote drug delivery, wireless energy harvesting, multiple state memories among others. Here, for the first time, using the concept of hard magnetic soft matter in combination with electrets, we design and create a soft magnetoelectric material that exhibits an extremely strong, self-biased magnetoelectric effect. Further, using programmable pattern of deposition of magnetic dipoles and charges, we report a giant magnetoelectric coefficient in an ultra-soft deformable material that retains its strength even under infinitesimal external fields and at low frequencies. (3) Liquid crystal elastomers are an interesting class of soft materials that combine the elasticity of rubber with the ordered structure and mobility of liquid crystals. In this work, we present a nonlinear theory to couple mechanics, electrical fields and light in nematic liquid crystal elastomers. In particular, we incorporate the effect of photomechanical coupling and flexoelectricity.