17 papers · 1 filter
Task-preserving neural segmentation of overlapping shocks and vortex cores in compressible flows
Ehsan Roohi
Shock fronts and vortex cores often coexist and overlap in compressible flows, where walls, wakes and shear layers also produce strong gradients. Refining a network to detect one s…
Transport fidelity and domain of validity of compact Gaussian kinetic representations for rarefied flows
Ehsan Roohi
Compact representations of rarefied flows must retain nonequilibrium transport information while identifying their range of validity. We investigate a common localized-Gaussian str…
What does anti-Fourier heat-flux agreement validate? Observability of the fourth-order closure state in a rarefied lid-driven cavity
Ehsan Roohi
Cold-to-hot heat transfer is a conspicuous non-equilibrium feature of rarefied cavity flows and is often used to judge whether a continuum closure captures higher-order transport.…
Noise-separated evidence for a slow collective displacement in a rarefied hypersonic bow-shock layer
Ahmad Shoja-sani, Ehsan Roohi
Time-resolved direct simulation Monte Carlo (DSMC) fields are used to test whether a detached rarefied hypersonic bow shock contains a slow collective displacement that can be sepa…
Cross-stream pressure support and the limits of scalar relaxation in rarefied Poiseuille flow
Omid Ejtehadi, Ehsan Roohi
The weak wall-normal pressure variation in pressure-driven rarefied Poiseuille flow is a stringent test of higher-order constitutive models: it is almost invisible in the total-pre…
Gaussian kinetic representations of rarefied nonequilibrium flows
Ehsan Roohi
Compact representations of rarefied flows must preserve kinetic observables, not only smooth macroscopic fields. We introduce Gaussian kinetic representations for discrete velocity…
Machine learning for rarefied gas transport in vacuum and micro/nano systems: promise, pitfalls, and a verification agenda
Ehsan Roohi
Machine learning is beginning to influence rarefied-gas modeling at multiple levels, including equation-solving, operator learning, learned collision physics, moment closures, dire…
Bulk-to-Wall Observability in Rarefied Hypersonic Flow: Moment Limits and Incident Half-Range Sufficiency
Elyas Lekzian, Ehsan Roohi
Wall traction in a rarefied gas is a half-range functional of molecules arriving at and leaving a surface, whereas hybrid solvers, moment methods, and learned wall models often tra…
Anti-Fourier heat flux does not certify the fourth-order closure state of a rarefied cavity
Ehsan Roohi
Cold-to-hot heat transfer in rarefied cavities is usually treated as a signature of Fourier-law failure. Here it is used to ask whether a correct anti-Fourier heat-flux field certi…
Tail observability and fourth-order closure recovery in physics-informed neural networks for Bhatnagar-Gross-Krook normal shocks
Ehsan Roohi
Closure-level accuracy in neural kinetic shock solvers is not guaranteed by accurate density, velocity and temperature profiles, because the relevant observables are velocity-weigh…
Prescribed Wall-Heat-Flux Control of Blockage and Impulse in a Rarefied Micro-Nozzle
Amirmehran Mahdavi, Ehsan Roohi
Prescribed wall heat flux provides an active route for controlling rarefied micro-nozzle flows, but its effect is governed by the coupled wall--bulk thermal response rather than by…
Rarefaction-induced inflation and similarity breakdown of hypersonic bow shocks over a circular cylinder
Ehsan Roohi, Ahmad Shoja-Sani
Rarefied hypersonic bow shocks over blunt bodies inflate as the Knudsen number increases, but it remains unclear whether this inflation is a simple shift and broadening of one comm…
Shock-Centered Low-Rank Structure and Neural-Operator Representation of Rarefied Micro-Nozzle Flows
Ehsan Roohi, Amirmehran Mahdavi
We examine the structure of Direct Simulation Monte Carlo (DSMC)-resolved internal compression layers in rarefied micro-nozzle flows and show that their apparent parametric complex…
Resolving Cryogenic and Hypersonic Rarefied Flows via Deep Learning-Accelerated Lennard-Jones DSMC
Ahmad Shoja Sani, Ehsan Roohi, Stefan Stefanov
Integrating the physically realistic Lennard--Jones (LJ) potential into Direct Simulation Monte Carlo (DSMC) remains challenging because the long-range potential complicates collis…
AI-Accelerated Operator Learning Framework for Rarefied Microflows
Ehsan Roohi
The high computational cost of kinetic solvers such as DSMC remains a major challenge in rarefied flow simulations. This work presents a unified framework combining deep neural net…
Deep Learning Surrogates for Gas Dynamics: A Physics-Informed Pedagogical Approach
Ehsan Roohi
Compressible flow problems are characterized by highly nonlinear, implicit, and often transcendental governing equations. In undergraduate gas dynamics education, solving these equ…
Passive Cavitation Mitigation on Hydrofoils via Porous Media: A Comparative Study of LES and RANS Models
Ali Alavi, Maziyar Ghasemnezhad, Ali Sangtarash +1
This study numerically investigates the use of porous media as a passive strategy for mitigating cavitation on a NACA 66 (MOD) hydrofoil subjected to unsteady two-phase flow.