{"title":"改进燃气轮机叶片的湍流建模:解决流动过渡和停滞点异常的新方法","authors":"Ali Akbar Shahbazi , Vahid Esfahanian","doi":"10.1016/j.jcp.2024.113499","DOIUrl":null,"url":null,"abstract":"<div><div>Accurate prediction of temperature and Heat Transfer Coefficient (HTC) distributions over gas turbine blades is crucial for the design process and life assessment of these components. Numerical studies of flow over gas turbine blades face significant challenges in accurately simulating two complex phenomena: (1) the transition of flow from laminar to turbulent, and (2) stagnation point flow at the leading edge. Many turbulence models tend to overpredict the temperature on turbine blades, leading to incorrect identification of hot-spot regions and, consequently, erroneous estimations of blade life. This paper investigates the performance of various turbulence models in simulating flow and heat transfer over gas turbine vanes. The study includes three full turbulence models, i.e., Spalart-Allmaras (SA), Shear Stress Transport <span><math><mi>k</mi><mo>−</mo><mi>ω</mi></math></span> (SST-kw), and <span><math><msup><mrow><mi>v</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>−</mo><mi>f</mi></math></span> (V2F), as well as two transitional models, i.e., Transition SST (Trans-SST) and <span><math><mi>k</mi><mo>−</mo><msub><mrow><mi>k</mi></mrow><mrow><mi>L</mi></mrow></msub><mo>−</mo><mi>ω</mi></math></span> (k-kl-w). Simulation results indicate that the <span><math><msup><mrow><mi>v</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>−</mo><mi>f</mi></math></span>, Trans-SST, and <span><math><mi>k</mi><mo>−</mo><msub><mrow><mi>k</mi></mrow><mrow><mi>L</mi></mrow></msub><mo>−</mo><mi>ω</mi></math></span> models can detect flow transition. However, the transition length and onset location predicted by the Trans-SST and <span><math><mi>k</mi><mo>−</mo><msub><mrow><mi>k</mi></mrow><mrow><mi>L</mi></mrow></msub><mo>−</mo><mi>ω</mi></math></span> models do not align with experimental data. Conversely, the <span><math><msup><mrow><mi>v</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>−</mo><mi>f</mi></math></span> model suffers from over-predictions at the leading edge due to stagnation point anomaly. To address these issues and due to capacities of the V2F model, this study proposes two modifications to enhance the performance of the V2F model. First, the production term of turbulent kinetic energy is redefined to mitigate the stagnation point anomaly. Second, the model is recalibrated to improve the prediction of flow transition. The new model, named the Production Modified V2F (PMV2F) model, shows promising results in predicting temperature and heat transfer coefficients.</div></div>","PeriodicalId":352,"journal":{"name":"Journal of Computational Physics","volume":"520 ","pages":"Article 113499"},"PeriodicalIF":3.8000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improving turbulence modeling for gas turbine blades: A novel approach to address flow transition and stagnation point anomalies\",\"authors\":\"Ali Akbar Shahbazi , Vahid Esfahanian\",\"doi\":\"10.1016/j.jcp.2024.113499\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Accurate prediction of temperature and Heat Transfer Coefficient (HTC) distributions over gas turbine blades is crucial for the design process and life assessment of these components. Numerical studies of flow over gas turbine blades face significant challenges in accurately simulating two complex phenomena: (1) the transition of flow from laminar to turbulent, and (2) stagnation point flow at the leading edge. Many turbulence models tend to overpredict the temperature on turbine blades, leading to incorrect identification of hot-spot regions and, consequently, erroneous estimations of blade life. This paper investigates the performance of various turbulence models in simulating flow and heat transfer over gas turbine vanes. The study includes three full turbulence models, i.e., Spalart-Allmaras (SA), Shear Stress Transport <span><math><mi>k</mi><mo>−</mo><mi>ω</mi></math></span> (SST-kw), and <span><math><msup><mrow><mi>v</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>−</mo><mi>f</mi></math></span> (V2F), as well as two transitional models, i.e., Transition SST (Trans-SST) and <span><math><mi>k</mi><mo>−</mo><msub><mrow><mi>k</mi></mrow><mrow><mi>L</mi></mrow></msub><mo>−</mo><mi>ω</mi></math></span> (k-kl-w). Simulation results indicate that the <span><math><msup><mrow><mi>v</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>−</mo><mi>f</mi></math></span>, Trans-SST, and <span><math><mi>k</mi><mo>−</mo><msub><mrow><mi>k</mi></mrow><mrow><mi>L</mi></mrow></msub><mo>−</mo><mi>ω</mi></math></span> models can detect flow transition. However, the transition length and onset location predicted by the Trans-SST and <span><math><mi>k</mi><mo>−</mo><msub><mrow><mi>k</mi></mrow><mrow><mi>L</mi></mrow></msub><mo>−</mo><mi>ω</mi></math></span> models do not align with experimental data. Conversely, the <span><math><msup><mrow><mi>v</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>−</mo><mi>f</mi></math></span> model suffers from over-predictions at the leading edge due to stagnation point anomaly. To address these issues and due to capacities of the V2F model, this study proposes two modifications to enhance the performance of the V2F model. First, the production term of turbulent kinetic energy is redefined to mitigate the stagnation point anomaly. Second, the model is recalibrated to improve the prediction of flow transition. The new model, named the Production Modified V2F (PMV2F) model, shows promising results in predicting temperature and heat transfer coefficients.</div></div>\",\"PeriodicalId\":352,\"journal\":{\"name\":\"Journal of Computational Physics\",\"volume\":\"520 \",\"pages\":\"Article 113499\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational Physics\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0021999124007472\",\"RegionNum\":2,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Physics","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0021999124007472","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Improving turbulence modeling for gas turbine blades: A novel approach to address flow transition and stagnation point anomalies
Accurate prediction of temperature and Heat Transfer Coefficient (HTC) distributions over gas turbine blades is crucial for the design process and life assessment of these components. Numerical studies of flow over gas turbine blades face significant challenges in accurately simulating two complex phenomena: (1) the transition of flow from laminar to turbulent, and (2) stagnation point flow at the leading edge. Many turbulence models tend to overpredict the temperature on turbine blades, leading to incorrect identification of hot-spot regions and, consequently, erroneous estimations of blade life. This paper investigates the performance of various turbulence models in simulating flow and heat transfer over gas turbine vanes. The study includes three full turbulence models, i.e., Spalart-Allmaras (SA), Shear Stress Transport (SST-kw), and (V2F), as well as two transitional models, i.e., Transition SST (Trans-SST) and (k-kl-w). Simulation results indicate that the , Trans-SST, and models can detect flow transition. However, the transition length and onset location predicted by the Trans-SST and models do not align with experimental data. Conversely, the model suffers from over-predictions at the leading edge due to stagnation point anomaly. To address these issues and due to capacities of the V2F model, this study proposes two modifications to enhance the performance of the V2F model. First, the production term of turbulent kinetic energy is redefined to mitigate the stagnation point anomaly. Second, the model is recalibrated to improve the prediction of flow transition. The new model, named the Production Modified V2F (PMV2F) model, shows promising results in predicting temperature and heat transfer coefficients.
期刊介绍:
Journal of Computational Physics thoroughly treats the computational aspects of physical problems, presenting techniques for the numerical solution of mathematical equations arising in all areas of physics. The journal seeks to emphasize methods that cross disciplinary boundaries.
The Journal of Computational Physics also publishes short notes of 4 pages or less (including figures, tables, and references but excluding title pages). Letters to the Editor commenting on articles already published in this Journal will also be considered. Neither notes nor letters should have an abstract.