The University of Southampton
University of Southampton Institutional Repository

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
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.
0045-7930
443-466
Bercin, Kutalmis
4b298947-d222-4a1a-878d-4c71079ebef2
Xie, Zheng-Tong
98ced75d-5617-4c2d-b20f-7038c54f4ff0
Turnock, Stephen
d6442f5c-d9af-4fdb-8406-7c79a92b26ce
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, 443-466. (doi:10.1016/j.compfluid.2018.03.070).

Record type: Article

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
Download (4MB)
Text
submitted version
Restricted to Repository staff only
Request a copy

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
ORCID for Zheng-Tong Xie: ORCID iD orcid.org/0000-0002-8119-7532
ORCID for Stephen Turnock: ORCID iD orcid.org/0000-0001-6288-0400

Catalogue record

Date deposited: 06 Oct 2017 16:31
Last modified: 16 Mar 2024 05:48

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×