Exploration of digital-filter and forward-stepwise synthetic turbulence generators and an improvement for their skewness-kurtosis
Exploration of digital-filter and forward-stepwise synthetic turbulence generators and an improvement for their skewness-kurtosis
The performance of four synthetic turbulence generators which represent the majority of capabilities of i: digital-filter-based (DFM) and ii: forward-stepwise-based (FSM) generator categories is evaluated prior to transferring generator outputs into computational fluid dynamics simulations. In addition, a cheap-to-run and easy-to-code piecewise closed-form function that transforms onespatial- point skewness-kurtosis of a synthetic time-series to a target value is derived and presented. The main purpose of the study is to support model users in their decision process for choosing the most convenient type and their understanding of the models, and to extend the Gaussian nature of these models into non-Gaussianity for the first time. These have been carried out through a systematic exploration of model parameters-stages, which was observed absent in the literature. The evaluation test-bed contains three benchmarks, each of which focuses on an isolated aspect of turbulent flows: i: decaying homogeneous isotropic turbulence, ii: homogeneous shear turbulence and iii: plane channel flow with smooth walls. Results obtained reveal that: (i) the original DFM provides the highest level of reconstruction for input one-spatial-point second-order correlation tensors and two-spatial/temporal-point correlation functions; (ii) FSM yields the best trade-off between the computational cost and the level of reconstruction; (iii) the use of exponential-form correlation functions as a model approximation is more advisable than that of Gaussian-form, as the former removes the premature, sharp, flow-type-independent drop in power spectra observed for the latter; (iv) the proposed non-Gaussian functionality reconstructs the target skewness-kurtosis pairs of the test-bed flows virtually without altering their already-embedded statistics; (v) the Lund transformation changes existing statistics only in statistically inhomogeneous lateral directions of a flow when anisotropic Reynolds stresses are present; and (vi) a spatial variation of correlation functions on turbulence generation plane improves the overall reconstruction fidelity in terms of correlation functions and power spectra.
443-466
Bercin, Kutalmis
4b298947-d222-4a1a-878d-4c71079ebef2
Xie, Zheng-Tong
98ced75d-5617-4c2d-b20f-7038c54f4ff0
Turnock, Stephen
d6442f5c-d9af-4fdb-8406-7c79a92b26ce
30 August 2018
Bercin, Kutalmis
4b298947-d222-4a1a-878d-4c71079ebef2
Xie, Zheng-Tong
98ced75d-5617-4c2d-b20f-7038c54f4ff0
Turnock, Stephen
d6442f5c-d9af-4fdb-8406-7c79a92b26ce
Bercin, Kutalmis, Xie, Zheng-Tong and Turnock, Stephen
(2018)
Exploration of digital-filter and forward-stepwise synthetic turbulence generators and an improvement for their skewness-kurtosis.
Computers & Fluids, 172, .
(doi:10.1016/j.compfluid.2018.03.070).
Abstract
The performance of four synthetic turbulence generators which represent the majority of capabilities of i: digital-filter-based (DFM) and ii: forward-stepwise-based (FSM) generator categories is evaluated prior to transferring generator outputs into computational fluid dynamics simulations. In addition, a cheap-to-run and easy-to-code piecewise closed-form function that transforms onespatial- point skewness-kurtosis of a synthetic time-series to a target value is derived and presented. The main purpose of the study is to support model users in their decision process for choosing the most convenient type and their understanding of the models, and to extend the Gaussian nature of these models into non-Gaussianity for the first time. These have been carried out through a systematic exploration of model parameters-stages, which was observed absent in the literature. The evaluation test-bed contains three benchmarks, each of which focuses on an isolated aspect of turbulent flows: i: decaying homogeneous isotropic turbulence, ii: homogeneous shear turbulence and iii: plane channel flow with smooth walls. Results obtained reveal that: (i) the original DFM provides the highest level of reconstruction for input one-spatial-point second-order correlation tensors and two-spatial/temporal-point correlation functions; (ii) FSM yields the best trade-off between the computational cost and the level of reconstruction; (iii) the use of exponential-form correlation functions as a model approximation is more advisable than that of Gaussian-form, as the former removes the premature, sharp, flow-type-independent drop in power spectra observed for the latter; (iv) the proposed non-Gaussian functionality reconstructs the target skewness-kurtosis pairs of the test-bed flows virtually without altering their already-embedded statistics; (v) the Lund transformation changes existing statistics only in statistically inhomogeneous lateral directions of a flow when anisotropic Reynolds stresses are present; and (vi) a spatial variation of correlation functions on turbulence generation plane improves the overall reconstruction fidelity in terms of correlation functions and power spectra.
Text
CnF2018
- Accepted Manuscript
More information
Accepted/In Press date: 28 March 2018
e-pub ahead of print date: 29 March 2018
Published date: 30 August 2018
Identifiers
Local EPrints ID: 414706
URI: http://eprints.soton.ac.uk/id/eprint/414706
ISSN: 0045-7930
PURE UUID: 644f5b0f-0c98-4c3f-90fd-1996d8b845e8
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Date deposited: 06 Oct 2017 16:31
Last modified: 16 Mar 2024 05:48
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