Presentation of anisotropy properties of turbulence, invariants versus eigenvalue approaches
By S. Banerjee, R. Krahl, Franz Durst, C. Zenger. 2007
293 citations recorded by the source corpus.
Subfields: Computational Mechanics, Environmental Engineering, Mechanical Engineering
View Paper: https://www.semanticscholar.org/paper/f934db55018cee28eb75b905504109256597f805
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Mechanics
- Heng Xiao
- Karthik Duraisamy
- Paola Cinnella
- Jin-Long Wu
- Jian-Xun Wang
- Sanjiva K. Lele
- Soshi Kawai
- Rui Sun
In Environmental Engineering
- Heng Xiao
- Jin-Long Wu
- Paola Cinnella
- Jian-Xun Wang
- Rui Sun
- Karthik Duraisamy
- N. Nguyen
- Sanjiva K. Lele
In Mechanical Engineering
Citations in the corpus
- Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier-Stokes simulations: A data-driven, physics-informed Bayesian approach (2015, background): “Figure 2: Mapping between Barycentric coordinates and natural coordinates, transforming the Barycentric triangle that encloses all physically realizable states [16, 28] to a square via standard finite element shape functions (detailed in Appendix A).”
- Physics-informed machine learning approach for augmenting turbulence models: A comprehensive framework (2017, unknown): “[8] and [44].”
- Flow physics and RANS modelling of oblique shock/turbulent boundary layer interaction (2013, methodology): “Thus, to better visualize the effect of anisotropy in the Reynolds stress tensor, the barycentric mapping technique proposed by Banerjee et al. (2007) is utilized.”
- Physics-informed machine learning approach for reconstructing Reynolds stress modeling discrepancies based on DNS data (2016, methodology): “[33] proposed an improved formulation in which the eigenvalues of the anisotropy tensor are mapped to Barycentric coordinates as opposed to the variants II and III as in the Lumley triangle.”
- Quantification of model uncertainty in RANS simulations: A review (2018, background): “Transformation of the eigenvalues leads to invariants that can be mapped to the well-known Lumley triangle [129] or the recently proposed barycentric triangle [130], both of which provide a map for all realizable states of turbulence.”