What is he best known for?
The fields of study he is best known for:
- Thermodynamics
- Mechanics
- Mechanical engineering
Danesh K. Tafti mainly investigates Mechanics, Reynolds number, Turbulence, Heat transfer and Thermodynamics.
His Mechanics research incorporates themes from Solver and Simulation.
His biological study spans a wide range of topics, including Flow separation, Louver and Classical mechanics.
His research integrates issues of Navier–Stokes equations and Laminar flow in his study of Turbulence.
The study incorporates disciplines such as Hydraulic diameter, Turbine blade, Internal flow, Duct and Meteorology in addition to Heat transfer.
His work investigates the relationship between Thermodynamics and topics such as Fin that intersect with problems in Length scale, Flow, Heat exchanger, Drag and Parasitic drag.
His most cited work include:
- Optimal control and simulation of multidimensional crystallization processes (142 citations)
- High-Resolution Simulation of Multidimensional Crystal Growth (130 citations)
- Study of discrete test filters and finite difference approximations for the dynamic subgrid‐scale stress model (103 citations)
What are the main themes of his work throughout his whole career to date?
Danesh K. Tafti focuses on Mechanics, Reynolds number, Heat transfer, Turbulence and Large eddy simulation.
His work carried out in the field of Mechanics brings together such families of science as Duct, Thermodynamics and Classical mechanics.
As a member of one scientific family, Danesh K. Tafti mostly works in the field of Reynolds number, focusing on Turbine blade and, on occasion, Internal flow.
His studies deal with areas such as Secondary flow, Meteorology, Fin and Mean flow as well as Heat transfer.
His work deals with themes such as Dimple, Laminar flow and Boundary layer, which intersect with Turbulence.
His research investigates the link between Large eddy simulation and topics such as Coolant that cross with problems in Composite material.
He most often published in these fields:
- Mechanics (66.26%)
- Reynolds number (36.21%)
- Heat transfer (34.57%)
What were the highlights of his more recent work (between 2018-2021)?
- Mechanics (66.26%)
- Drag (5.76%)
- Heat transfer (34.57%)
In recent papers he was focusing on the following fields of study:
Danesh K. Tafti mainly focuses on Mechanics, Drag, Heat transfer, Reynolds number and Thrust.
His work on Turbulence and Trailing edge as part of general Mechanics research is frequently linked to Immersed boundary method and Order of magnitude, thereby connecting diverse disciplines of science.
His Drag research includes elements of Artificial neural network, Test data generation, Machine learning, Artificial intelligence and Leading edge.
His Heat transfer research is multidisciplinary, incorporating elements of Fluidized bed, Thermal conduction, CFD-DEM and Immersed tube.
His work in Reynolds number tackles topics such as Suspension which are related to areas like Orientation and Ellipsoid.
Danesh K. Tafti interconnects Kinematics, Aerodynamics, Vortex, Flapping and Centripetal force in the investigation of issues within Thrust.
Between 2018 and 2021, his most popular works were:
- A supervised machine learning approach for predicting variable drag forces on spherical particles in suspension (13 citations)
- Development of drag correlation for suspensions of ellipsoidal particles (4 citations)
- Physics-Guided Deep Learning for Drag Force Prediction in Dense Fluid-Particulate Systems. (3 citations)
In his most recent research, the most cited papers focused on:
- Thermodynamics
- Mechanics
- Mechanical engineering
Danesh K. Tafti spends much of his time researching Drag, Mechanics, Artificial neural network, Machine learning and Artificial intelligence.
His Drag research includes elements of Suspension and Reynolds number.
His research integrates issues of Point particle and Work in his study of Suspension.
His Reynolds number study combines topics from a wide range of disciplines, such as Orientation, Aspect ratio, Representation, Spherical geometry and Ellipsoid.
Danesh K. Tafti is studying Turbulence, which is a component of Mechanics.
His study in the field of Deep learning is also linked to topics like Context.
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