Zobrazeno 1 - 10
of 508
pro vyhledávání: '"Schmid, P. J."'
Model reduction is a key technology for large-scale physical systems in science and engineering, as it brings behavior expressed in many degrees of freedom to a more manageable size that subsequently allows control, optimization, and analysis with mu
Externí odkaz:
http://arxiv.org/abs/2411.08071
Publikováno v:
J. Fluid Mech. 999 (2024) A43
We study the effect of acceleration and deceleration on the stability of channel flows. To do so, we derive an exact solution for laminar profiles of channel flows with arbitrary, time-varying wall motion and pressure gradient. This solution then all
Externí odkaz:
http://arxiv.org/abs/2312.12701
Many engineering applications rely on the evaluation of expensive, non-linear high-dimensional functions. In this paper, we propose the RONAALP algorithm (Reduced Order Nonlinear Approximation with Active Learning Procedure) to incrementally learn a
Externí odkaz:
http://arxiv.org/abs/2311.10550
The Koopman operator presents an attractive approach to achieve global linearization of nonlinear systems, making it a valuable method for simplifying the understanding of complex dynamics. While data-driven methodologies have exhibited promise in ap
Externí odkaz:
http://arxiv.org/abs/2310.10745
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 of spanwise velocity that generates a steady transversal Stokes layer
Externí odkaz:
http://arxiv.org/abs/2308.11525
Leveraging recent work on data-driven methods for constructing a finite state space Markov process from dynamical systems, we address two problems for obtaining further reduced statistical representations. The first problem is to extract the most sal
Externí odkaz:
http://arxiv.org/abs/2308.10864
Autor:
Margaritis, Athanasios T., Scherding, Clément, Marxen, Olaf, Schmid, Peter J., Sayadi, Taraneh
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 selection of configurations. The numerical tools are developed based on prev
Externí odkaz:
http://arxiv.org/abs/2210.05547
Publikováno v:
Physical Review Fluids, 8(2023), 023201
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 gathers all relevant thermodynamic states and the corresponding gas pro
Externí odkaz:
http://arxiv.org/abs/2210.04269
Publikováno v:
46th AIAA Fluid Dynamics Conference Proceedings, AIAA 2016-3805, 2016
In the context of adjoint-based optimization, nonlinear conservation laws pose significant problems regarding the existence and uniqueness of both direct and adjoint solutions, as well as the well-posedness of the problem for sensitivity analysis and
Externí odkaz:
http://arxiv.org/abs/2209.03270
Autor:
Eggl, Maximilian F., Schmid, Peter J.
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 products, more enriched compounds, and often substantial economic saving
Externí odkaz:
http://arxiv.org/abs/2108.07064