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A Novel Method for Thermoelectric Generator Based on Neural Network

Computers, Materials & Continua 2022年第10期73卷 2115-2133页

作者： Mohammad Saraireh A.M.Maqableh Manar Jaradat Omar A.Saraereh Mechanical Engineering Department Faculty of EngineeringMutah UniversityKarak61710Jordan Electromechanical Engineering Department Luminus Technical University CollegeAmman11118Jordan Department of Computer Engineering Faculty of EngineeringThe Hashemite UniversityZarqa13133Jordan Department of Electrical Engineering Faculty of EngineeringThe Hashemite UniversityZarqa13133Jordan

The growing need for renewable energy and zero carbon dioxide emissions has fueled the development of thermoelectric generators with improved power generating capability.Along with the endeavor to develop thermoelectric materials with greater figures of merit,the geometrical and structural optimization of thermoelectric generators is equally critical for maximum power output and efficiency.Green energy strategies that are constantly updated are a viable option for addressing the global energy issue while also protecting the environment.There have been significant focuses on the development of thermoelectric modules for a range of solar,automotive,military,and aerospace applications in recent years due to various advantages including as low vibration,great reliability and durability,and the absence of moving components.In order to enhance the system performance of the thermoelectric generator,an artificial neural network(ANN)based algorithm is proposed.Furthermore,to achieve high efficiency and system stability,a buck converter is designed and deployed.Simulation and experimental findings demonstrate that the suggested method is viable and available,and that it is almost similar to the real value in the steady state with the least power losses,making it ideal for vehicle exhaust thermoelectric generator applications.Furthermore,the proposed hybrid algorithm has a high reference value for the development of a dependable and efficient car exhaust thermoelectric generating system.

关键词： Thermoelectric system thermodynamics electromechanics rotational factors neural networks

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Fibroblast proliferation alters cardiac excitation conduction and contraction： a computational study

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2014年第3期15卷 225-242页

作者： He-qing ZHAN Ling XI Guo-fa SHOU Yun-liang ZANG Feng LIU Stuart CROZIER Department of Biomedical Engineering Zhejiang University Hangzhou 310027 China School of Information Technology and Electrical Engineering the University of Queensland Brisbane QLD 4072 Australia

In this study, the effects of cardiac fibroblast proliferation on cardiac electric excitation conduction and mechanical contraction were investigated using a proposed integrated myocardial-fibroblastic electromechanical model. At the cellular level, models of the human ventricular myocyte and fibroblast were modified to incorporate a model of cardiac mechanical contraction and cooperativity mechanisms. Cellular electromechanical coupling was realized with a calcium buffer. At the tissue level, electrical excitation conduction was coupled to an elastic mechanics model in which the finite difference method (FDM) was used to solve electrical excitation equations, and the finite element method (FEM) was used to solve mechanics equations. The electromechanical properties of the proposed integrated model were investigated in one or two dimensions under normal and ischemic pathological conditions. Fibroblast proliferation slowed wave propagation, induced a conduction block, decreased strains in the fibroblast proliferous tissue, and increased dispersions in depolarization, repolarization, and action potential duration (APD). It also distorted the wave-front, leading to the initiation and maintenance of re-entry, and resulted in a sustained contraction in the proliferous areas. This study demonstrated the important role that fibroblast proliferation plays in modulating cardiac electromechanical behaviour and which should be considered in planning future heart-modeling studies.

关键词： Cardiac model electromechanics Fibroblast proliferation Q66 R540.4

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Electroaeroelastic Modeling and Analysis for Flow Energy Piezoelectric Harvester

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Transactions of Nanjing University of Aeronautics and Astronautics 2017年第1期34卷 9-14页

作者： Zhang Jiantao Wu Song Shu Chang Li Chaodong School of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200072P.R.China

An electroaeroelastic model for wind energy harvesting using piezoelectric generators is presented.The flow field is mapped in detail.The force which the fluid flow exerts on the generator is formulated.The output voltage levels generated from the mechanical strain within the piezoelectric elements are determined.An analytical model is developed with consideration of the interactions between the fluid,solid and electric.Various analytical results are obtained,such as flow velocity contour and pressure contour for the flow,moving trajectories,stress contour and output voltage of the harvester.A prototype is fabricated and tested.The simulation result is close to the experimental result.The model developed in this paper can predict the performance and behavior of different energy harvesters.And it also can be used as a design tool for optimizing the performance of the harvester.

关键词： wind energy harvester piezoelectric aeroelasticity electromechanics

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