Ehsan Roohi mainly works on novel and intelligent collision models in the direct simulation Monte Carlo (DSMC) technique framework to make the rarefied flow simulations more accurate and less time-consuming [3]. The collision process is the most sophisticated part of DSMC, which is treated probabilistically [4]. He has demonstrated the shortcomings of conventional collision models [5] and has been developing innovative intermolecular collision paradigms in the framework of the DSMC. In 2015, he improved the “Simplified Bernoulli” trial (SBT) collision model [6] by introducing an intelligent version, [7] and he was the lead developer of a new collision model called the “Generalized Bernoulli” trial (GBT) scheme in 2018 [8].
In 2022, he developed another model, the “Symmetrized and Simplified Bernoulli” trial (SSBT) scheme, [9] that has improved performance compared to previous ones. In the same year, Stefan Stefanov and he suggested a hybrid collision scheme on transient adaptive subcells to treat various types of rarefied gas flows at the hypersonic regime [10]. He has been developing numerical tools to perform simulations of hypersonic space re-entry vehicles, waveriders, and propulsion of arrays of small-scale satellites much faster with high reliability [11]. During his research career, he contributed to developing the very first open-source DSMC code in the framework of OpenFOAM, i.e., dsmcFoam [12]. His next plan is to incorporate physics-informed machine learning and deep learning methods into ab-inito collision models for hypersonic and non-equilibrium flow simulations. He also works on designing next-generation micro-scale pumps and propulsion systems that exploit heat losses and produce propulsion force and flow motion without requiring pressure gradients. This is done using DSMC simulations and is now extended using machine learning. A thin vane immersed in a rarefied gas with a temperature gradient across its surfaces will produce a force that tends to move the vane from the hot side to the cold side. This is the Crookes radiometer. He has been creating and developing novel concepts in thermal ratchet (rather than using the vanes) pumps and propulsion systems using either an intelligent selection of wall reflection properties or surface morphologies [13].
He was the first to demonstrate that the working mechanism of ratchet pumps and propulsion systems is based on radiometric forces [14]. He was the first researcher to use these pumps for rarefied gas species separation [15]. This topic is exciting in MEMS/NEMS (Micro/nano-electro-mechanical systems) and aerospace communities and impacts technological developments in both fields. The former seeks extra-small scale pumps for miniaturized devices, while the latter is interested in propulsion systems for space applications, like thrust production for space vehicles and orbit control of lightweight satellites.
In addition to his research in rarefied gas dynamics, he works on bio-inspired techniques to mitigate the destructive impacts of cavitation on the performance of hydraulic machinery. He recently worked on wavy leading hydrofoils inspired by a particular Humpback whale species [16]. He showed that the cavitation weakens on the modified geometry, delaying the stall. He also used hybrid surface wettability to control the devastating effects of cavitation [17].
Additionally, he works on novel subgrid-scale (SGS) models in the large eddy simulation (LES) approach for turbulent flows. For the first time, various modern SGS, such as modulated gradient (MG) and anisotropic minimum dissipation (AMD) models, were considered, modified, and implemented in the OpenFOAM framework [18],[19].
Scopus Profile: https://www.scopus.com/authid/detail.uri?authorId=24471770600
Scholar Profile: https://scholar.google.com/citations?hl=en&user=AWKLce4AAAAJ&view_op=list_works&sortby=pubdate
SSBT collision model in predicting the flow field around a hypersonic cylinder, from Roohi’s work in Physics of Fluids, 2015.
Shock wave structure around the hypersonic biconic geometry, from the Roohi’s work with Stefanov and Goshayeshi, Journal of Computational Physics, 2015.
Cavitation around a sphere: Boundary layer separation point (≈96◦) and cavity inception point (≈76◦); velocity vectors are plotted over the mean water volume fraction contour for fluid with the formation of the cavity at a cavitation number of σ=0.45, from Pendar and Roohi’s work in International Journal of Multiphase Flow, 2018.
Supercavitating flows around a hydrofoil at a cavitation number of σ=0.4, from Mousavi and Roohi’s work in Journal of the Taiwan Institute of Chemical Engineers, 2023.
Vortex shedding in a rarefied flow behind a cylinder, European Journal of Mechanics – B/Fluids, 2017.
Vortex shedding in a rarefied flow behind a cylinder, , European Journal of Mechanics – B/Fluids, 2017.
Normalized Turbulent Kinetic Energy around a cavitating Pitching-Plunging hydrofoil, from the Alavi and Roohi’s work, Physics of Fluids, 2023.
Cavitation around a wavy leading edge hydrofoil, from Pendar and Roohi’s work published in the International Journal of Multiphase Flow, 2020.
Cavitation around a sphere, Ocean Engineering, 2019.
3. ^ “Direct simulation Monte Carlo”.
4. ^ Roohi, Ehsan; Stefanov, Stefan (2016). “Collision partner selection schemes in DSMC: From micro/Nano flows to hypersonic flows”. Physics Reports. 656: 1–38. Bibcode:2016PhR…656….1R. doi:10.1016/j.physrep.2016.08.002.
5. ^ Akhlaghi, Hassan; Roohi, Ehsan; Stefanov, Stefan (2018). “On the consequences of successively repeated collisions in no-time-counter collision scheme in DSMC”. Computers & Fluids. 161: 23–32. doi:10.1016/j.compfluid.2017.11.005.
6. ^ Stefanov, Stefan K. (January 25, 2011). “On DSMC Calculations of Rarefied Gas Flows with Small Number of Particles in Cells”. SIAM Journal on Scientific Computing. 33 (2): 677–702. Bibcode:2011SJSC…33..677S. doi:10.1137/090751864 – via CrossRef.
7. ^ https://pubs.aip.org/aip/pof/article-abstract/27/10/107104/314632/A-novel-simplified-Bernoulli-trials-collision?redirectedFrom=fulltext
8. ^ Roohi, Ehsan; Stefanov, Stefan; Shoja-Sani, Ahmad; Ejraei, Hossein (2018). “A generalized form of the Bernoulli Trial collision scheme in DSMC: Derivation and evaluation”. Journal of Computational Physics. 354: 476–492. Bibcode:2018JCoPh.354..476R. doi:10.1016/j.jcp.2017.10.033.
9. ^ https://pubs.aip.org/aip/pof/article-abstract/34/1/012010/2845513/A-symmetrized-and-simplified-Bernoulli-trial
10. ^ https://pubs.aip.org/aip/pof/article-abstract/34/9/092003/2844541/A-novel-transient-adaptive-subcell-algorithm-with?redirectedFrom=fulltext
11. ^ Goshayeshi, Bijan; Roohi, Ehsan; Stefanov, Stefan (2015). “DSMC simulation of hypersonic flows using an improved SBT-TAS technique”. Journal of Computational Physics. 303: 28–44. Bibcode:2015JCoPh.303…28G. doi:10.1016/j.jcp.2015.09.027.
12. ^ Scanlon, T.J.; Roohi, E.; White, C.; Darbandi, M.; Reese, J.M. (2010). “An open source, parallel DSMC code for rarefied gas flows in arbitrary geometries”. Computers & Fluids. 39 (10): 2078–2089. doi:10.1016/j.compfluid.2010.07.014.
13. ^ https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/radiometric-flow-in-periodically-patterned-channels-fluid-physics-and-improved-configurations/DA76621385D7DF0C3824B8D3F215FE13
14. ^ https://www.nature.com/articles/srep41412
15. ^ https://www.sciencedirect.com/science/article/abs/pii/S0735193320305881
16. ^ https://www.sciencedirect.com/science/article/abs/pii/S0301932220305243
17. ^ https://www.sciencedirect.com/science/article/abs/pii/S1876107023001578
18. ^ https://www.tandfonline.com/doi/abs/10.1080/14685248.2018.1483078
19. ^ https://www.sciencedirect.com/science/article/abs/pii/S0045793018309368