2022 - Research.com Rising Star of Science Award
Amin Shahsavar spends much of his time researching Nanofluid, Thermal conductivity, Composite material, Heat transfer and Viscosity. Amin Shahsavar combines subjects such as Non-Newtonian fluid, Pressure drop and Reynolds number with his study of Nanofluid. His studies examine the connections between Reynolds number and genetics, as well as such issues in Heat transfer coefficient, with regards to Working fluid.
His Thermal conductivity research includes themes of Chemical engineering and Carbon nanotube. Amin Shahsavar conducts interdisciplinary study in the fields of Composite material and Ferrofluid through his works. His Heat transfer research incorporates elements of Heat exchanger and Thermal.
The scientist’s investigation covers issues in Nanofluid, Heat transfer, Mechanics, Thermal and Composite material. His Nanofluid research is multidisciplinary, relying on both Pressure drop, Heat exchanger, Thermal conductivity and Reynolds number. His biological study spans a wide range of topics, including Nusselt number and Laminar flow.
His work on Natural convection, Non-Newtonian fluid and Flow as part of general Mechanics research is often related to Enclosure, thus linking different fields of science. His study in Thermal is interdisciplinary in nature, drawing from both Thermal wheel, Heat recovery ventilation, Nuclear engineering, Automotive engineering and Exergy. The study incorporates disciplines such as Phase-change material, Coolant and Thermal energy storage in addition to Composite material.
Amin Shahsavar mainly focuses on Nanofluid, Thermal, Mechanics, Exergy and Heat exchanger. His Nanofluid study improves the overall literature in Heat transfer. His work in Mechanics tackles topics such as Heat sink which are related to areas like Wake, Fluid dynamics and Numerical analysis.
The Exergy study combines topics in areas such as Nuclear engineering, Tube, Volumetric flow rate and Volume. His Heat exchanger research is multidisciplinary, incorporating elements of Artificial neural network and Hybrid system. Within one scientific family, Amin Shahsavar focuses on topics pertaining to Thermal energy under Thermal wheel, and may sometimes address concerns connected to Thermal conductivity, Active cooling, Thermal energy storage, Passive cooling and Composite material.
His main research concerns Nanofluid, Mechanics, Thermal, Non-Newtonian fluid and Pressure drop. Amin Shahsavar combines subjects such as Flow, Volume, Laminar flow, Partial differential equation and Entropy with his study of Nanofluid. His work deals with themes such as Nuclear engineering, Volumetric flow rate, Exergy, Exergy efficiency and Tube, which intersect with Volume.
His studies in Laminar flow integrate themes in fields like Heat exchanger and Heat transfer. His research in Partial differential equation intersects with topics in Entropy production, Work, Convective heat transfer and Nonlinear system. His Entropy research integrates issues from Hydrothermal circulation and Flow.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Experimental investigation and modeling of a direct-coupled PV/T air collector
A. Shahsavar;M. Ameri.
Solar Energy (2010)
A review of melting and freezing processes of PCM/nano-PCM and their application in energy storage
Sara Rostami;Masoud Afrand;Amin Shahsavar;M. Sheikholeslami.
Energy (2020)
Heat transfer reduction in buildings by embedding phase change material in multi-layer walls: Effects of repositioning, thermophysical properties and thickness of PCM
Z.X. Li;Z.X. Li;Abdullah A.A.A. Al-Rashed;Mahfouz Rostamzadeh;Rasool Kalbasi.
Energy Conversion and Management (2019)
A novel comprehensive experimental study concerned synthesizes and prepare liquid paraffin-Fe3O4 mixture to develop models for both thermal conductivity & viscosity: A new approach of GMDH type of neural network
Amin Shahsavar;Shoaib Khanmohammadi;Arash Karimipour;Marjan Goodarzi.
International Journal of Heat and Mass Transfer (2019)
Experimental investigation and develop ANNs by introducing the suitable architectures and training algorithms supported by sensitivity analysis: Measure thermal conductivity and viscosity for liquid paraffin based nanofluid containing Al2O3 nanoparticles
Amin Shahsavar;Shoaib Khanmohammadi;Davood Toghraie;Hamze Salihepour.
Journal of Molecular Liquids (2019)
Impact of variable fluid properties on forced convection of Fe3O4/CNT/water hybrid nanofluid in a double-pipe mini-channel heat exchanger
Amin Shahsavar;Ali Godini;Pouyan Talebizadeh Sardari;Davood Toghraie.
Journal of Thermal Analysis and Calorimetry (2019)
Experimental investigation on laminar forced convective heat transfer of ferrofluid loaded with carbon nanotubes under constant and alternating magnetic fields
A. Shahsavar;A. Shahsavar;M. Saghafian;M.R. Salimpour;M.B. Shafii.
Experimental Thermal and Fluid Science (2016)
Free convection heat transfer and entropy generation analysis of water-Fe3O4/CNT hybrid nanofluid in a concentric annulus
Amin Shahsavar;Pouyan Talebizadeh Sardari;D. Toghraie.
International Journal of Numerical Methods for Heat & Fluid Flow (2019)
An experimental study on the effect of ultrasonication on thermal conductivity of ferrofluid loaded with carbon nanotubes
A. Shahsavar;M.R. Salimpour;M. Saghafian;M.B. Shafii.
Thermochimica Acta (2015)
Prediction of energetic performance of a building integrated photovoltaic/thermal system thorough artificial neural network and hybrid particle swarm optimization models
Abdulwahab A. Alnaqi;Hossein Moayedi;Amin Shahsavar;Truong Khang Nguyen.
Energy Conversion and Management (2019)
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