Turbulence modeling in the age of data
Data from experiments and direct simulations of turbulence have historically been used to
calibrate simple engineering models such as those based on the Reynolds-averaged Navier …
calibrate simple engineering models such as those based on the Reynolds-averaged Navier …
Structure and dynamics of highly turbulent premixed combustion
Turbulent premixed combustion involves simultaneous and mutually interacting fluid,
chemical, and transport phenomena spanning a wide range of spatial and temporal scales …
chemical, and transport phenomena spanning a wide range of spatial and temporal scales …
An interpretable framework of data-driven turbulence modeling using deep neural networks
Reynolds-averaged Navier–Stokes simulations represent a cost-effective option for practical
engineering applications, but are facing ever-growing demands for more accurate …
engineering applications, but are facing ever-growing demands for more accurate …
Reynolds-averaged Navier–Stokes equations with explicit data-driven Reynolds stress closure can be ill-conditioned
Reynolds-averaged Navier–Stokes (RANS) simulations with turbulence closure models
continue to play important roles in industrial flow simulations. However, the commonly used …
continue to play important roles in industrial flow simulations. However, the commonly used …
基于组合神经网络的雷诺平均湍流模型多次修正方法
张珍， 叶舒然， 岳杰顺， 王一伟， 黄晨光 - 力学学报, 2021 - lxxb.cstam.org.cn
求解雷诺平均(Reynolds-averaged Navier-Stokes, RANS) 方程依然是工程应用中有效且实用
的方法, 但对雷诺应力建模的不确定性会导致该方法的预测精度具有很大差异 …
的方法, 但对雷诺应力建模的不确定性会导致该方法的预测精度具有很大差异 …
Neural network models for the anisotropic Reynolds stress tensor in turbulent channel flow
Reynolds-averaged Navier-Stokes (RANS) equations are presently one of the most popular
models for simulating turbulence. Performing RANS simulation requires additional …
models for simulating turbulence. Performing RANS simulation requires additional …
Learning nonlocal constitutive models with neural networks
Constitutive and closure models play important roles in computational mechanics and
computational physics in general. Classical constitutive models for solid and fluid materials …
computational physics in general. Classical constitutive models for solid and fluid materials …
[HTML][HTML] An iterative data-driven turbulence modeling framework based on Reynolds stress representation
Data-driven turbulence modeling studies have reached such a stage that the basic
framework is settled, but several essential issues remain that strongly affect the …
framework is settled, but several essential issues remain that strongly affect the …
A predictive surrogate model for hemodynamics and structural prediction in abdominal aorta for different physiological conditions
X Tang, CJ Wu - Computer Methods and Programs in Biomedicine, 2024 - Elsevier
Background and objective This study investigates the application of a Predictive Surrogate
Model (PSM) for the prediction of the fluid and solid variables in the abdominal aorta by …
Model (PSM) for the prediction of the fluid and solid variables in the abdominal aorta by …
Tempered fractional LES modeling
M Samiee, A Akhavan-Safaei… - Journal of Fluid …, 2022 - cambridge.org
The presence of non-local interactions and intermittent signals in the homogeneous
isotropic turbulence grant multi-point statistical functions a key role in formulating a new …
isotropic turbulence grant multi-point statistical functions a key role in formulating a new …