Moosavifard, Arezoo (2024)
Investigating the Aeroacoustic Performance of the Partially Averaged Navier-Stokes Method.
Technische Universität Darmstadt
doi: 10.26083/tuprints-00026644
Ph.D. Thesis, Primary publication, Publisher's Version
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Item Type: | Ph.D. Thesis | ||||
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Type of entry: | Primary publication | ||||
Title: | Investigating the Aeroacoustic Performance of the Partially Averaged Navier-Stokes Method | ||||
Language: | English | ||||
Referees: | Schäfer, Prof. Dr. Michael ; Jakirlic, Apl. Prof. Suad | ||||
Date: | 26 March 2024 | ||||
Place of Publication: | Darmstadt | ||||
Collation: | xiv, 115 Seiten | ||||
Date of oral examination: | 31 January 2024 | ||||
DOI: | 10.26083/tuprints-00026644 | ||||
Abstract: | Aeroacoustics is the field of research dedicated to studying the generation and propagation of sound resulting from the interaction of unsteady flows with solid structures, such as aircraft and automobiles. As the demand for quieter vehicles continues to rise and the negative impacts of noise pollution on human well-being become more evident, it is crucial to develop accurate and efficient methods for predicting and controlling aerodynamic noise. Computational Aeroacoustics (CAA), which unites theoretical and computational techniques, has emerged as a powerful approach to effectively address these challenges. The success of CAA relies heavily on Computational Fluid Dynamics (CFD), a numerical simulation method for studying fluid flow and its characteristics. Given the intricate interplay between unsteady flows and solid structures, it is essential to employ reliable CFD methods that capture the underlying flow dynamics and its acoustic consequences with precision. Turbulence, a common occurrence in real-world flows, plays a vital role in sound generation by inducing fluctuations and instabilities that contribute to aerodynamic noise. Among various CFD methods, Reynolds-Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) are widely utilized for simulating turbulent flows. However, RANS models, while computationally efficient, have limitations in accurately capturing unsteady flow phenomena critical for aeroacoustic predictions. On the other hand, LES provides a more accurate representation of unsteady flow features, but its practical application is constrained by substantial computational resource requirements. To address the limitations of RANS and LES, researchers have developed hybrid LES/RANS methods that seek to balance computational cost and accuracy by utilizing the strengths of both approaches. One prominent hybrid method is the Partially-Averaged Navier-Stokes (PANS) method, which offers a compromise between computational efficiency and the ability to capture unsteady flow phenomena. By incorporating dynamic resolution parameters and suitable turbulence models, such as the k − ϵ − ζ − f model equation, the PANS method aims to provide a more accurate representation of flow and its acoustic characteristics. This research focuses on investigating the aeroacoustic performance of the SSV-PANS method, a specific variant of the PANS method, by comparing it to a reference LES. The assessment considers both computational accuracy and costs. The research employs a hybrid approach, decomposing fluid variables into incompressible hydrodynamic and compressible perturbation equations to enable the study of aerodynamic noise. The SSV-PANS method is used to compute aeroacoustic sources from the incompressible flow field. To validate the accuracy and computational efficiency of the SSV-PANS method, extensive analyses are conducted on the flow around a circular cylinder and an Ahmed body—renowned benchmark cases in Computational Fluid Dynamics (CFD). Results obtained using the SSV-PANS method are compared against those obtained from LES as well as experimental measurements. By advancing the understanding and capabilities of CAA methods through the evaluation of the SSV-PANS method, this research contributes to the development of quieter vehicles with reduced noise emissions. Improving the accuracy and efficiency of computational methods facilitates the optimization of vehicle designs, enabling effective noise pollution mitigation and the creation of sustainable and healthier communities. |
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Status: | Publisher's Version | ||||
URN: | urn:nbn:de:tuda-tuprints-266446 | ||||
Classification DDC: | 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering | ||||
Divisions: | 16 Department of Mechanical Engineering > Institute of Numerical Methods in Mechanical Engineering (FNB) 16 Department of Mechanical Engineering > Institute of Numerical Methods in Mechanical Engineering (FNB) > Numerics |
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Date Deposited: | 26 Mar 2024 13:27 | ||||
Last Modified: | 02 Apr 2024 10:48 | ||||
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/26644 | ||||
PPN: | 516676938 | ||||
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