关注
Martin Schmelzer
Martin Schmelzer
TU Delft, PhD Student
在 tudelft.nl 的电子邮件经过验证
标题
引用次数
引用次数
年份
Discovery of algebraic Reynolds-stress models using sparse symbolic regression
M Schmelzer, RP Dwight, P Cinnella
Flow, Turbulence and Combustion 104 (2), 579-603, 2020
1962020
Bayesian predictions of Reynolds-averaged Navier–Stokes uncertainties using maximum a posteriori estimates
WN Edeling, M Schmelzer, RP Dwight, P Cinnella
AIAA Journal 56 (5), 2018-2029, 2018
282018
Bayesian Predictions of Reynolds-Averaged Navier–Stokes Uncertainties Using Maximum a Posteriori Estimates
P CINNELLA, M Schmelzer, WN EDELING
American Institute of Aeronautics and Astronautics (AIAA), 2018
282018
Customized data-driven RANS closures for bi-fidelity LES-RANS optimization
Y Zhang, RP Dwight, M Schmelzer, JF Gomez, S Hickel, Z Han
arXiv preprint arXiv:2004.03003, 2020
142020
Machine learning of algebraic stress models using deterministic symbolic regression
M Schmelzer, RP Dwight, P Cinnella
preprint, 2019
102019
Stochastic turbulence modeling in RANS simulations via multilevel Monte Carlo
P Kumar, M Schmelzer, RP Dwight
Computers & Fluids 201, 104420, 2020
82020
Data-driven deterministic symbolic regression of nonlinear stress-strain relation for rans turbulence modelling
M Schmelzer, R Dwight, P Cinnella
2018 Fluid Dynamics Conference, 2900, 2018
62018
Symbolic Regression of Algebraic Stress-Strain Relation for RANS Turbulence Closure
M Schmelzer, RP Dwight, P Cinnella
2*
Estimation of Model Error Using Bayesian Model-Scenario Averaging with Maximum a Posterori-Estimates
M Schmelzer, RP Dwight, W Edeling, P Cinnella
Uncertainty Management for Robust Industrial Design in Aeronautics, 53-69, 2019
2019
Uncertainties Identification and Quantification
D Büche, S Klostermann, M Schmelzer
Uncertainty Management for Robust Industrial Design in Aeronautics, 679-686, 2019
2019
系统目前无法执行此操作,请稍后再试。
文章 1–10