Turbulence and CFD Models.

https://unige.it/en/off.f/2019/ins/36793

Additional material

In this page you will find additional material to be used during the course (articles, external links, additonal Python and Matlab scripts, source code to programs, additional notes, and so on).

Additional notes and presentations

Introduction to Computational Fluid Dynamics: Governing equations, turbulence modeling introduction, and finite volume distretization basics. This is a work in progress, but you can use it to get a basic introduction to the Finite Volume Method (FVM).

Quick and dirty introduction to index notation. This is a short introduction to index notation using operators that commonly appears in the governing equations of fluid dynamics.

IVBP problem in CFD. Brief overview on the information required to conduct CFD simulations (initial conditions and boundary conditions).

Art and Turbulence. As difficult as turbulence is to understand from a statistical, numerical, experimental, or theoretical point of view, artists have used paint strokes to depict the way it looks.

CFD and turbulence joke. Which turbulence model should I use?

Useful articles

J. Slotnick, A. Khodadoust, J. Alonso, D. Darmofal, W. Gropp, E. Lurie, D. Mavriplis. CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences. NASA/CR-2014-218178, March 2014. Click here to download

W. J. McCroskey. A Critical Assessment of Wind Tunnel Results for the NACA 0012 Airfoil. NASA TM 100019, October 1987. Click here to download

C. L. Ladson. Effects of Independent Variation of Mach and Reynolds Numbers on the Low-Speed Aerodynamic Characteristics of the NACA 0012 Airfoil Section. NASA TM 4074, October 1988. Click here to download

N. Mansour, J. Kim, P. Moin. Reynolds-Stress and Dissipation Rate Budgets in a Turbulent Channel Flow. NASA TM 101399. 1988. Click here to download

S. Kim. A Near-Wall Turbulence Model and its Application to Fully Developed Turbulent Channel and Pipe Flows. NASA TM 89451. 1987. Click here to download

P. Spalart. Direct simulation of a turbulent boundary layer up to Re_theta= 1410. NASA TM 89407. 1986. Click here to download

D. B. Spalding A Single Formula for the “Law of the Wall. NASA TM 89407. J. Appl. Mech. Sep 1961, 28(3):455-458. Click here to download

J. Kim, P. Moin, R. Moser. Turbulence statistics in fully developed channel flow at low Reynolds number. Journal of Fluid Mechanics, 177, 133-166. 1987. Click here to download

B. Launder, D. Spalding. The Numerical Computation of Turbulent Flows. NASA TM 89451. Computer Methods in Applied Mechanics and Engineering. Volume 3, Issue 2, March 1974, Pages 269-289. Click here to download

J. Callaham, J. Kutz, B. Brunton, S. Brunton. Learning dominant physical processes with data-driven balance models. https://arxiv.org/abs/2001.10019. January 2020. Click here to download

P. Spalart, M. Strelets. Turbulence Prediction in Aerospace CFD: Reality and the Vision 2030 Roadmap. Advanced Modeling & Simulation (AMS) Seminar Series. NASA Ames Research Center, September 12th, 2019. Click here to download

H. Xiao. Physics-Informed Machine Learning for Predictive Turbulence Modeling:Status, Perspectives, and Case Studies. Machine Learning Technologies and Their Applications to Scientific and Engineering Domains Workshop, August 17, 2016. Click here to download

X. Liu, F. Thomas, R. Nelson. Measurement of the Turbulence Kinetic Energy Budget of a Turbulent Planar Wake Flow in Pressure Gradients. NASA Langley Research Center, Technical Report NAG1-1878. Click here to download

P. Moin, C. Hamman, G. Iaccarino. Turbulence: V&V and UQ Analysis of a Multi-scale Complex System. Center for Turbulence Research Stanford University. Click here to download the presentation Click here to download the notes

P. Durbin. Some Recent Developments in Turbulence Closure Modeling. Annual Review of Fluid Mechanics. Vol. 50:77-103, Jan. 2018. Click here to download

P. Durbin. Limiters and Wall Treatments in Applied Turbulence Modeling. Fluid Dynamics Reasearch. Vol. 41(1):012203, 2009. Click here to download

J. Bardina, P. Huang, T. Coakley. Turbulence Modeling Validation, Testing, and Development. NASA Ames Research Center, Technical Memorandum 110446. Click here to download

Useful links

Johns Hopkins Turbulence Databases

http://turbulence.pha.jhu.edu/

http://turbulence.idies.jhu.edu/cutout/

NASA Langley Research Center - Turbulence Modeling Resource

https://turbmodels.larc.nasa.gov/

Data-driven Reynolds stress modeling with physics-informed machine learning

https://github.com/xiaoh/turbulence-modeling-PIML

Uncertainty Quantification of RANS Data-Driven Turbulence Modeling

https://github.com/cics-nd/rans-uncertainty

Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations

https://ge.in.tum.de/publications/2018-deep-flow-pred/

UMich/NASA Symposium on Advances in Turbulence Modeling

http://turbgate.engin.umich.edu/symposium/

Learning dominant physical processes with data-driven balance models

https://github.com/dynamicslab/dominant-balance

Data Driven Science & Engineering. Machine Learning, Dynamical Systems and Control

http://www.databookuw.com/

Turbulence: V&V and UQ Analysis of a Multi-scale Complex System.

https://www.youtube.com/watch?v=ga8cRzyKkxA

email: joel.guerrero@unige.it