Mohsen Talei
University of Melbourne
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Publication
Featured researches published by Mohsen Talei.
aiaa ceas aeroacoustics conference | 2007
Mohsen Talei; Michael J. Brear; Franck Nicoud; Daniel J. Bodony; Alexis Giauque
This paper presents a study of hot and cold turbulent jets by using the exact and linearised ‘disturbance energy corollaries’ proposed by Myers. Myers’ energy corollaries are first extended to allow examination of results from Large Eddy Simulations (LES) around a turbulent base flow, via inclusion of additional disturbance energy flux and source terms. The budget of these extended forms of Myers’ energy corollaries are then closed on selected LES results from Bodony & Lele. It is argued that Myers’ exact disturbance energy flux should become the classical acoustic energy flux in the far-field surrounding a jet issuing into a quiescent domain. Thus, the volume integral of the exact disturbance energy source terms can be considered as related to the sources of far-field sound, although no information on the direction of the generated sound can be obtained using this approach. Moreover, this decomposition does not separate the radiating and non-radiating portions of the sources at a point in space. These claims are partially demonstrated in this paper, with closure of the disturbance energy budget showing that vortical, entropic and ‘unresolved scale’ source terms are the only significant source terms in this problem. For fixed acoustic Mach number above 0.7, the entropic source term dominates the vortical term for hot jets, which is in keeping with results from other studies on heated jets using acoustic analogies.
Journal of Computational Physics | 2018
Matthias Schoepplein; Jack Weatheritt; Richard D. Sandberg; Mohsen Talei; M. Klein
Abstract Recently the concept of Gene Expression Programming (GEP) has been introduced with very encouraging results for the purpose of modelling the unclosed tensors in the context of RANS (Reynolds Averaged Navier–Stokes) turbulence modelling. This paper extends the previous framework to modelling subgrid stresses (SGS) in the context of Large Eddy Simulation (LES). In order to achieve this goal the GEP algorithm was coupled with an external multiprocessor postprocessing tool that evaluates a cost function based on a-priori analysis of explicitly filtered DNS data of turbulent premixed planar flames. Although LES of combustion systems is becoming increasingly popular, the closures for sub-grid scale (SGS) stresses have mostly been derived assuming constant density flows. However, it has been shown recently that depending on the relative strength of heat release and turbulence, counter-gradient transport can occur for the stress tensor if the isotropic part is not properly accounted for. The focus of this work is not to put forward a particular new model but to demonstrate that evolutionary algorithms can successfully be used in the framework of LES modelling. To achieve this purpose the GEP software is used for modelling the deviatoric stress, the trace of the SGS tensor and the stress tensor itself. Although the functional form of the model was not imposed, the evolutionary algorithm did find a well known model from the literature with even the model constants comparable to values reported in the literature.
Journal of Fluid Mechanics | 2012
Michael J. Brear; Frank Nicoud; Mohsen Talei; Alexis Giauque; Evatt R. Hawkes
Journal of Fluid Mechanics | 2011
Mohsen Talei; Michael J. Brear; Evatt R. Hawkes
Proceedings of the Combustion Institute | 2015
Alex Krisman; Evatt R. Hawkes; Mohsen Talei; Ankit Bhagatwala; Jacqueline H. Chen
Combustion and Flame | 2012
Mohsen Talei; Michael J. Brear; Evatt R. Hawkes
Combustion and Flame | 2016
Alex Krisman; Evatt R. Hawkes; Mohsen Talei; Ankit Bhagatwala; Jacqueline H. Chen
Proceedings of the Combustion Institute | 2015
Mohsen Talei; Evatt R. Hawkes
Proceedings of the Combustion Institute | 2017
Alex Krisman; Evatt R. Hawkes; Mohsen Talei; Ankit Bhagatwala; Jacqueline H. Chen
Journal of Fluid Mechanics | 2015
Shahram Karami; Evatt R. Hawkes; Mohsen Talei; Jacqueline H. Chen