The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Presentation of anisotropy properties of turbulence, invariants versus eigenvalue approaches
Abstract
In the literature, anisotropy-invariant maps are being proposed to represent a domain within which all realizable Reynolds stress invariants must lie. It is shown that the representation proposed by Lumley and Newman has disadvantages owing to the fact that the anisotropy invariants (II, III) are nonlinear functions of stresses. In the current work, it is proposed to use an equivalent linear representation of the anisotropy invariants in terms of eigenvalues. A barycentric map, based on the convex combination of scalar metrics dependent on eigenvalues, is proposed to provide a non-distorted visual representation of anisotropy in turbulent quantities. This barycentric map provides the possibility of viewing the normalized Reynolds stress and any anisotropic stress tensor. Additionally the barycentric map provides the possibility of quantifying the weighting for any point inside it, in terms of the limiting states (one-component, two-component, three-component). The mathematical basis for the barycentric map is derived using the spectral decomposition theorem for second-order tensors. In this way, an analytical proof is provided that all turbulence lies along the boundaries or inside the barycentric map. It is proved that the barycentric map and the anisotropy-invariant map in terms of (II, III) are one-to-one uniquely interdependent, and as a result satisfies the requirement of realizability.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Turbulence statistics in fully developed channel flow at low Reynolds number
Kim, J., Moin, P., & Moser, R. (1987) · Journal of Fluid Mechanics · doi:10.1017/s0022112087000892 · Cited by 4,873
Computational Modeling of Turbulent Flows
Lumley, J. L. (1979) · Advances in Applied Mechanics · doi:10.1016/s0065-2156(08)70266-7 · Cited by 1,232
The return to isotropy of homogeneous turbulence
Lumley, J. L., & Newman, G. R. (1977) · Journal of Fluid Mechanics · doi:10.1017/s0022112077000585 · Cited by 787
Some characteristics of small-scale turbulence in a turbulent duct flow
Antonia, R. A., Kim, J., & Browne, L. W. B. (1991) · Journal of Fluid Mechanics · doi:10.1017/s0022112091000526 · Cited by 173
Cited by
Wang, J.-X., Wu, J.-L., & Xiao, H. (2017) · Physical Review Fluids · doi:10.1103/physrevfluids.2.034603 · Cited by 737
RANS turbulence model development using CFD-driven machine learning
Zhao, Y., Akolekar, H. D., Weatheritt, J., Michelassi, V., & Sandberg, R. D. (2020) · Journal of Computational Physics · doi:10.1016/j.jcp.2020.109413 · Cited by 303
Metadata
- Authors
- Banerjee, S., Krahl, R., Durst, F., & Zenger, C.
- Venue
- Journal of Turbulence
- Publisher
- Informa UK Limited
- Published
- 2007-01
- Volume
- 8
- Pages
- N32
- ISSN
- 1468-5248 (ISSN-L)
- OpenAlex
- W1968024513
- Cited by
- 279
- References
- 4
- FWCI
- 1.54
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Presentation of anisotropy properties of turbulence, invariants versus eigenvalue approaches. https://app.cochat.ai/papers/10.1080/14685240701506896
- The paper
- Banerjee, S., Krahl, R., Durst, F., & Zenger, C. (2007). Presentation of anisotropy properties of turbulence, invariants versus eigenvalue approaches. Journal of Turbulence. https://doi.org/10.1080/14685240701506896
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.