Machine-Learning-Augmented Predictive Modeling of Turbulent Separated Flows over Airfoils-Reference-Cited by-同舟云学术

Machine-Learning-Augmented Predictive Modeling of Turbulent Separated Flows over Airfoils

Published:2017-07 Issue:7 Volume:55 Page:2215-2227
ISSN:0001-1452
Container-title:AIAA Journal
language:en
Short-container-title:AIAA Journal

Author:

Singh Anand Pratap¹,Medida Shivaji²,Duraisamy Karthik¹

Affiliation:

1. University of Michigan, Ann Arbor, Michigan 48104

2. Altair Engineering, Inc., Sunnyvale, California 94086

Funder

National Aeronautics and Space Administration

Publisher

American Institute of Aeronautics and Astronautics (AIAA)

Subject

Aerospace Engineering

Link

https://arc.aiaa.org/doi/pdf/10.2514/1.J055595

Reference58 articles.

1. SlotnickJ.KhodadoustJ.AlonsoJ.DarmofalD.GroppW.LurieE.MavriplisD. “CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences,” NASA Langley Research Center, NASA/CR 2014-218178, Hampton, VA, 2013.

2. Contribution to single-point closure Reynolds-stress modelling of inhomogeneous flow

3. Towards a rational model for the triple velocity correlations of turbulence

4. Velocity/Pressure-Gradient Correlations in a FORANS Approach to Turbulence Modeling

Cited by 297 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Non-unique machine learning mapping in data-driven Reynolds-averaged turbulence models;Physics of Fluids;2024-09-01

2. Experimental Data-Driven Flow Field Prediction for Compressor Cascade based on Deep Learning and ℓ1 Regularization;Journal of Thermal Science;2024-08-08

3. Merging experiment data and simulation data for parameter identification of shaft seal;Measurement;2024-08

4. Application of artificial intelligence in turbomachinery aerodynamics: progresses and challenges;Artificial Intelligence Review;2024-07-30

5. Addressing performance improvement of a neural network model for Reynolds-averaged Navier–Stokes solutions with high wake formation;Engineering Computations;2024-07-30