What is he best known for?
The fields of study he is best known for:
- Thermodynamics
- Mechanical engineering
- Heat transfer
His primary areas of investigation include Nanofluid, Heat transfer, Mechanics, Thermodynamics and Thermal.
His Nanofluid research is multidisciplinary, relying on both Heat exchanger, Composite material and Heat sink.
His research in Heat transfer intersects with topics in Fluid dynamics, Pressure drop and Reynolds number.
His research integrates issues of Heat transfer coefficient and Heat transfer enhancement in his study of Pressure drop.
As a part of the same scientific study, Mehdi Bahiraei usually deals with the Thermodynamics, concentrating on Ethylene glycol and frequently concerns with Homogenization.
His work on Parabolic trough as part of general Thermal research is frequently linked to State and Performance enhancement, thereby connecting diverse disciplines of science.
His most cited work include:
- Thermal conductivity modeling of MgO/EG nanofluids using experimental data and artificial neural network (188 citations)
- Flow and heat transfer characteristics of magnetic nanofluids: A review (184 citations)
- Recent research contributions concerning use of nanofluids in heat exchangers: A critical review (123 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Nanofluid, Heat transfer, Mechanics, Reynolds number and Heat transfer coefficient.
His Nanofluid research incorporates elements of Heat exchanger, Pressure drop and Composite material.
His work deals with themes such as Bejan number, Laminar flow and Heat sink, which intersect with Heat transfer.
His Mechanics research integrates issues from Volume fraction and Mixing.
His work on Nusselt number is typically connected to Particle as part of general Reynolds number study, connecting several disciplines of science.
His work in the fields of Concentric tube heat exchanger overlaps with other areas such as Magnetic pressure.
He most often published in these fields:
- Nanofluid (87.43%)
- Heat transfer (57.49%)
- Mechanics (40.72%)
What were the highlights of his more recent work (between 2019-2021)?
- Nanofluid (87.43%)
- Mechanics (40.72%)
- Heat transfer (57.49%)
In recent papers he was focusing on the following fields of study:
Mehdi Bahiraei focuses on Nanofluid, Mechanics, Heat transfer, Reynolds number and Artificial neural network.
His Nanofluid study combines topics from a wide range of disciplines, such as Heat exchanger, Heat transfer coefficient and Volume fraction, Composite material.
The various areas that Mehdi Bahiraei examines in his Heat transfer coefficient study include Thermal resistance, Laminar flow and Boundary layer.
His studies deal with areas such as Conical surface and Mixing as well as Mechanics.
The Heat transfer study combines topics in areas such as Turbulence, Microchannel, Mass fraction and Heat sink.
While the research belongs to areas of Reynolds number, Mehdi Bahiraei spends his time largely on the problem of Pressure drop, intersecting his research to questions surrounding Micro heat exchanger, Shell and tube heat exchanger, Shell and Baffle.
Between 2019 and 2021, his most popular works were:
- Employing artificial bee colony and particle swarm techniques for optimizing a neural network in prediction of heating and cooling loads of residential buildings (56 citations)
- Hybridizing four wise neural-metaheuristic paradigms in predicting soil shear strength (14 citations)
- Using neural network optimized by imperialist competition method and genetic algorithm to predict water productivity of a nanofluid-based solar still equipped with thermoelectric modules (13 citations)
In his most recent research, the most cited papers focused on:
- Thermodynamics
- Mechanical engineering
- Mechanics
His primary areas of study are Nanofluid, Artificial neural network, Mechanics, Perceptron and Exergy efficiency.
His Nanofluid study is within the categories of Heat transfer and Thermal.
As a member of one scientific family, Mehdi Bahiraei mostly works in the field of Artificial neural network, focusing on Metaheuristic and, on occasion, Salp swarm algorithm and Shuffled frog leaping algorithm.
His work on Natural convection as part of general Mechanics research is often related to Rib cage, thus linking different fields of science.
His biological study spans a wide range of topics, including Algorithm, Glazing and Cooling load.
His work carried out in the field of Coaxial brings together such families of science as Heat transfer coefficient, Entropy and Thermodynamics.
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