What is he best known for?
The fields of study he is best known for:
- Thermodynamics
- Mechanics
- Heat transfer
His primary areas of investigation include Mechanics, Thermodynamics, Heat transfer, Nanofluid and Mass transfer.
His Mechanics research incorporates elements of Magnetohydrodynamic drive, Magnetohydrodynamics and Classical mechanics.
He performs integrative Thermodynamics and Chemistry research in his work.
Naramgari Sandeep regularly links together related areas like Thermal radiation in his Heat transfer studies.
His Nanofluid research is multidisciplinary, incorporating elements of Volume fraction, Thermal conductivity, Convective heat transfer and Buoyancy.
His Mass transfer research incorporates elements of Carreau fluid and Dissipation.
His most cited work include:
- Heat and mass transfer in magnetohydrodynamic Casson fluid over an exponentially permeable stretching surface (97 citations)
- Heat and mass transfer in MHD non-Newtonian bio-convection flow over a rotating cone/plate with cross diffusion (96 citations)
- Effect of aligned magnetic field on liquid thin film flow of magnetic-nanofluids embedded with graphene nanoparticles (92 citations)
What are the main themes of his work throughout his whole career to date?
Naramgari Sandeep mostly deals with Mechanics, Thermodynamics, Nanofluid, Heat transfer and Chemistry.
The various areas that Naramgari Sandeep examines in his Mechanics study include Magnetohydrodynamic drive and Classical mechanics.
He usually deals with Thermodynamics and limits it to topics linked to Magnetohydrodynamics and Slip and Flow.
His Nanofluid research incorporates themes from Volume fraction, Thermal conductivity, Composite material and Thermal radiation.
His Heat transfer study deals with Thermal intersecting with Cross diffusion.
His Mass transfer study integrates concerns from other disciplines, such as Fluid dynamics, Newtonian fluid and Churchill–Bernstein equation.
He most often published in these fields:
- Mechanics (75.00%)
- Thermodynamics (52.50%)
- Nanofluid (48.33%)
What were the highlights of his more recent work (between 2017-2019)?
- Mechanics (75.00%)
- Magnetohydrodynamics (30.83%)
- Flow (28.33%)
In recent papers he was focusing on the following fields of study:
Naramgari Sandeep mainly investigates Mechanics, Magnetohydrodynamics, Flow, Heat transfer and Nanofluid.
His studies deal with areas such as Surface, Casson fluid and Thermal radiation as well as Mechanics.
His Thermal radiation study combines topics in areas such as Péclet number, Hall effect and Boundary layer.
His research integrates issues of Eckert number, Thermal conductivity and Shooting method in his study of Heat transfer.
He is studying Thermophoresis, which is a component of Nanofluid.
His Fluid dynamics course of study focuses on Non-Newtonian fluid and Mass transfer.
Between 2017 and 2019, his most popular works were:
- Scrutinization of the effects of Grashof number on the flow of different fluids driven by convection over various surfaces (76 citations)
- Impact of Non-linear Radiation on MHD Non-aligned Stagnation Point Flow of Micropolar Fluid Over a Convective Surface (43 citations)
- Impact of Brownian motion and thermophoresis on bioconvective flow of nanoliquids past a variable thickness surface with slip effects (32 citations)
In his most recent research, the most cited papers focused on:
- Thermodynamics
- Mechanics
- Fluid dynamics
Naramgari Sandeep spends much of his time researching Mechanics, Magnetohydrodynamics, Convection, Radiation and Stagnation point flow.
His work in Combined forced and natural convection and Parasitic drag is related to Mechanics.
His studies in Combined forced and natural convection integrate themes in fields like Sherwood number, Stanton number, Bejan number and Buoyancy.
His Parasitic drag study combines topics from a wide range of disciplines, such as Nanofluid, Thermophoresis, Mass transfer and Heat sink.
His Heat sink study frequently intersects with other fields, such as Slip.
His research on Convection frequently links to adjacent areas such as Surface.
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.
