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Amirreza Rouhi

Senior Lecturer

School of Science & Technology

Staff Group(s)
Engineering

Role

Amirreza Rouhi is a Senior Lecturer in Mechanical Engineering in the School of Science and Technology at Nottingham Trent University. His research area is Computational Thermo-Fluid Dynamics. Specifically, high-fidelity simulation and modelling of turbulent flows in various applications, including rough-wall turbulent flows, rotating flows, thermal convection and blood flows.

Career overview

Amirreza received his PhD degree from Queen's University of Canada in 2017. His PhD research was on turbulence modelling. He was part of the team that developed a new subfilter (subgrid) scale stress model for large-eddy simulation (LES). The model has been employed to study complex applications, such as flow over filamentous canopies, flow around ground vehicle, hydrogen combustion in nuclear vessels and nozzle flows. He later joined the Fluid Mechanics Research Group at the University of Melbourne as a Postdoctoral Fellow. In concert with his experimental colleagues, he studied various fundamental flow physics including turbulent flow over heterogeneous rough surfaces, centrifugal convection, heat transfer augmentation and active flow control. He also has research experience in blood flows and geophysical flows. For his research, Amirreza has received several awards, including:

Amirreza was involved in developing and delivering several Thermofluids modules at Queen's University, including Fluid Mechanics, Computational Fluid Dynamics (CFD) and Thermodynamics. For his teaching, he has received several departmental and university wide awards, including:

Research areas

Turbulent flow past a step change in surface roughness. Engineers and meteorologists have developed models for evenly distributed rough surfaces. However, the majority of turbulent flows are affected by abrupt changes in surface roughness, e.g. the ocean water passing over the biofouling patches on ship hulls or atmospheric wind across the coastlines. In these cases, the set of empirical rules for evenly distributed roughness (Moody chart and equivalent sand-grain roughness) offer little insight into the complex physics of spatially varying (heterogeneous) roughness. There are many questions in this subject that require investigation, such as how the flow direction with respect to the step change alters the flow physics? how much the flow departs from equilibrium? how reliable are the modelling assumptions (e.g. log-law or Monin-Obukhov theory)?

Centrifugal buoyancy driven convection. Several important configurations in nature and industry are simultaneously exposed to rotation and thermal convection: Earth’s outer core, mid-latitude atmosphere and compressor cavity. To study these phenomena, engineers and geophysicists consider a rotating cylindrical shell with inner cold core and outer hot wall, known as centrifugal buoyancy driven convection. Due to rotation and temperature gradient, the system is exposed to two forces: centrifugal force and Coriolis force. The interaction between these forces results in various regimes, from classical Rayleigh–Bénard convection to the geostrophic regime. These regimes are of interest to the geophysical, turbomachinery and fundamental physics communities.

Subfilter-scale stress modelling for large-eddy simulation. Large-eddy simulation (LES) is the state-of-the-art computational fluid dynamics (CFD) technique to study practical flows. It resolves the large energy-carrying flow scales and parameterises the small computationally-demanding scales. Therefore, it saves the computational cost by at least an order of magnitude compared to high-fidelity techniques, i.e direct numerical simulation (DNS). Additionally, the modelling error in LES is substantially lower than low-fidelity techniques, namely Reynolds-Averaged Navier Stokes (RANS). Since LES is a scale resolving technique, it also allows us to study flow physics. Up until the early 2000s, due to the computational limitations, industry was mainly using RANS. However, since the first LES by Deardorff (1970), the computer power has increased by seven orders of magnitude and industry is transitioning from RANS to LES. Despite substantial advances in LES modelling, there remain challenges, among which is relating the filter width to the grid size, i.e. linking the subfilter motions (as a physical process) to a non-physical parameter (grid size). This carries several disadvantages, such as sub-optimal filter width distribution, i.e. large filter width (grid size) when turbulent scales are small, or amplification of numerical errors in complex flows with local grid refinement.

External activity

Refereeing for scientific journals:

  • Journal of Fluid Mechanics
  • Journal of Turbulence
  • Flow Turbulence and Combustion
  • Applied Mathematical Modelling
  • Journal of Hydraulic Research
  • Applied Ocean Research

Publications

M. Samie, W. Baars, A. Rouhi, P. Schlatter, R. Örlü, I. Marusic & N. Hutchins, “Near wall coherence in wall-bounded flows and implications for flow control”, Int. J. Heat Fluid Flow, Vol 86, 108683, (2020), https://doi.org/10.1016/j.ijheatfluidflow.2020.108683

A. Rouhi, D. Chung & N. Hutchins, “Direct numerical simulation of open-channel flow over smooth-to-rough and rough-to-smooth step changes”, J. Fluid Mech., Vol 866, 450-486, (2019), https://doi.org/10.1017/jfm.2019.84

A. Rouhi, D. Chung & N. Hutchins “Roughness and Reynolds number effects on the flow past a rough-to-smooth step change”, Progress in Turbulence VIII. Springer, 2018. https://doi.org/10.1007/978-3-030-22196-6_13

B. Geurts, A. Rouhi & U. Piomelli, “Recent progress on reliability assessment of large-eddy simulation”, J. Fluids Struct., Vol 91, 102615 (2019), https://doi.org/10.1016/j.jfluidstructs.2019.03.008

M. Li, C. M. de Silva, A. Rouhi, R. Baidya, D. Chung, I. Marusic & N. Hutchins, “Recovery of the wall-shear stress to equilibrium flow conditions after a rough-to-smooth step-change in turbulent boundary layers”, J. Fluid Mech., Vol 872, 472-491, (2019), https://doi.org/10.1017/jfm.2019.351

J. G. Wong, G. A. Rosi, A. Rouhi & D. E. Rival, “Coupling temporal and spatial gradient information in high density Lagrangian measurements”, Exp. Fluids, Vol 59, 64, (2017), https://doi.org/10.1007/s00348-017-2427-6

A. Rouhi, U. Piomelli & B. Geurts, “Dynamic subfilter-scale stress model for large-eddy simulations”, Phys. Rev. Fluids, Vol 1, 044401, (2016), https://doi.org/10.1103/PhysRevFluids.1.044401

A. Jabbari, A. Rouhi & L. Boegman, “Evaluation of the structure function method to compute turbulent dissipation within boundary layers using numerical simulations”, J. Geophys. Res.: Oceans, Vol 121, 5888-5897, (2016), https://doi.org/10.1002/2015JC011608

U. Piomelli, A. Rouhi & B. Geurts, “A grid-independent length scale for large eddy simulations”, J. Fluid Mech., Vol 766, 499-527, (2015), https://doi.org/10.1017/jfm.2015.29

A. Rouhi, U. Piomelli & P. Vlachos, “Numerical investigation of pulsatile flow in endovascular stents”, Phys. Fluids, Vol. 25, (2013), https://doi.org/10.1063/1.4821618

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