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Arash Karimipour
Researcher at Islamic Azad University
Publications - 313
Citations - 14751
Arash Karimipour is an academic researcher from Islamic Azad University. The author has contributed to research in topics: Nanofluid & Heat transfer. The author has an hindex of 65, co-authored 257 publications receiving 10833 citations. Previous affiliations of Arash Karimipour include Virginia Tech College of Natural Resources and Environment & University of Sistan and Baluchestan.
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Minimize pressure drop and maximize heat transfer coefficient by the new proposed multi-objective optimization/statistical model composed of “ANN + Genetic Algorithm” based on empirical data of CuO/paraffin nanofluid in a pipe
Seyed Amin Bagherzadeh,Mohsen Tahmasebi Sulgani,V. Nikkhah,Mehrdad Bahrami,Arash Karimipour,Yu Jiang +5 more
TL;DR: In this article, a new multi-objective optimization model composed of the artificial neural network (ANN) and the genetic algorithm (GA) methods based on the empirical thermo-physical characteristics of CuO/liquid paraffin nanofluid flow in a pipe is presented for the first time.
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Prediction of the interaction between HIV viruses and Human Serum Albumin (HSA) molecules using an equilibrium dynamics simulation program for application in bio medical science
Aliakbar Karimipour,Arash Karimipour,Nitasha Adavoodi Jolfaei,Maboud Hekmatifar,Davood Toghraie,Roozbeh Sabetvand,Sara Rostami +6 more
TL;DR: In this paper, a molecular dynamics simulation based on Newton's law was used to predict the destruction of HSA structure by the HIV virus with atomic, the authors showed that the presence of temperature is an important factor in HAS protein and HIV virus mutual interaction.
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Application of rotating circular obstacles in improving ferrofluid heat transfer in an enclosure saturated with porous medium subjected to a magnetic field
TL;DR: In this paper, the authors evaluated the heat transfer rate and fluid flow in an enclosure with rotating circular obstacles and found that different temperature cases of the obstacles and their direction play an essential role in the flow and heat transfer.
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Performance of joined artificial neural network and genetic algorithm to study the effect of temperature and mass fraction of nanoparticles dispersed in ethanol
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Lattice Boltzmann method with heat flux boundary condition applied to mixed convection in inclined lid driven cavity
TL;DR: In this paper, a double population thermal Lattice Boltzmann method is applied to simulate a mixed convective heat transfer in a two-dimensional rectangular inclined driven cavity, and the results show that heat transfer rate increases as increases the inclination angle, but this effect is significant for higher Richardson numbers, when buoyancy forces dominate the problem.