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20022026
most citedSparsity-promoting dynamic mode decomposition

911 citations · 1.4k across the 22 of their papers we have counts for

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16 papers · 1 filter

physics.flu-dyn2026

Data-driven modeling of hypersonic flows in chemical non-equilibrium with catalytic surfaces

Konstantinos Sarras, Louis Walpot, Thierry Magin +2

Hypersonic flows involve extreme thermochemical non-equilibrium, where strong energy dissipation leads to tightly coupled chemical reactions, radiation, and energy exchange. In thi…

physics.flu-dyn2023★ 4 cited

Linear stability of Poiseuille flow over a steady spanwise Stokes layer

Daniele Massaro, Fulvio Martinelli, Peter J. Schmid +1

The temporal linear stability of plane Poiseuille flow modified by spanwise forcing applied at the walls is considered. The forcing consists of a stationary streamwise distribution…

physics.flu-dyn2022★ 1 cited

Development of a high-fidelity computational tool for chemically reacting hypersonic flow simulations

Athanasios T. Margaritis, Clément Scherding, Olaf Marxen +2

In this paper, we present a methodology to achieve high-fidelity simulations of chemically reacting hypersonic flows and demonstrate our numerical solver's capabilities on a select…

physics.flu-dyn2022

Data-driven framework for input/output lookup tables reduction: Application to hypersonic flows in chemical non-equilibrium

Clément Scherding, Georgios Rigas, Denis Sipp +2

In this paper, we present a novel model-agnostic machine learning technique to extract a reduced thermochemical model for reacting hypersonic flows simulation. A first simulation g…

physics.flu-dyn2021★ 23 cited

Mixing by stirring: optimizing shapes and strategies

Maximilian F. Eggl, Peter J. Schmid

The mixing of binary fluids by stirrers is a commonplace procedure in many industrial and natural settings, and mixing efficiency directly translates into more homogeneous final pr…

physics.flu-dyn2020★ 13 cited

A gradient-based framework for maximizing mixing in binary fluids

Maximilian F. Eggl, Peter J. Schmid

A computational framework based on nonlinear direct-adjoint looping is presented for optimizing mixing strategies for binary fluid systems. The governing equations are the nonlinea…