Biblio

Found 25 results
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Conference Paper
Rosenzweig M, Giaccherini S, Pinelli L, Kozul M, Sandberg R, Marconcini M, Pacciani R.  2023.  Best-Practice Guidelines for High-Fidelity Simulations Based on Detailed Analysis of a Highly-Loaded Low-Pressure Turbine Cascade. ASME Turbo Expo 2023 Turbomachinery Technical Conference and Exposition. 13B: Turbomachinery
GT2023-102697
Fang Y, Zhao Y, Akolekar HD, Ooi ASH, Sandberg R, Pacciani R, Marconcini M.  2023.  A Data-Driven Approach for Generalizing the Laminar Kinetic Energy Model for Separation and Bypass Transition in Low- and High-Pressure Turbines. ASME Turbo Expo 2023 Turbomachinery Technical Conference and Exposition. 13C: Turbomachinery
GT2023-102902
Rosenzweig M, Kozul M, Sandberg R, Marconcini M, Pacciani R.  2023.  High-Fidelity Simulations and Rans Analysis of a Low-Pressure Turbine Cascade in a Spanwise-Diverging Gas Path - End-Wall Flow Analysis and Loss Generation Mechanisms. ASME Turbo Expo 2023 Turbomachinery Technical Conference and Exposition. 13B: Turbomachinery
GT2023-101039
Metti L, Marconcini M, Salvadori S, Misul DAnna, Rosafio N, Lopes G, Lavagnoli S, Fang Y, Sandberg R, Pacciani R.  2025.  The Impact of Transition and Turbulence Modelling on the SPLEEN High-Speed Low-Pressure Turbine Cascade. ASME Turbo Expo 2025 Turbomachinery Technical Conference and Exposition. 10: Turbomachinery:V010T30A019.
GT2025-153288. Recommended for publication on ASME J. Turbomach.
Pacciani R, Marconcini M, Arnone A, Bertini F, Spano E, Rosa Taddei S, Sandberg R.  2023.  Improvements in the Prediction of Steady and Unsteady Transition and Mixing in Low Pressure Turbines by Means of Machine-Learnt Closures. ASME Turbo Expo 2023 Turbomachinery Technical Conference and Exposition. 13B: Turbomachinery
GT2023-102985 Accepted for publication on ASME J. Turbomach. TURBO-23-1186
Akolekar H, Zhao Y, Sandberg R, Pacciani R.  2020.  Integration of Machine Learning and Computational Fluid Dynamics to Develop Turbulence Models for Improved Turbine Wake Mixing Prediction. ASME Turbo Expo 2020 Turbomachinery Technical Conference and Exposition. 2C: Turbomachinery:10.
paper GT2020-14732
Akolekar H, Waschkowski F, Sandberg R, Pacciani R, Zhao Y.  2022.  Multi-Objective Development of Machine-Learnt Closures for Fully Integrated Transition and Wake Mixing Predictions in Low Pressure Turbines. ASME Turbo Expo 2022 Turbomachinery Technical Conference and Exposition. Volume 10C: Turbomachinery
ASME paper GT2022-81091
Rosenzweig M, Kozul M, Sandberg R, Giannini G, Pacciani R, Marconcini M, Arnone A.  2025.  Numerical Design of Experiments for Repeating Low-Pressure Turbine Stages Part 1: Computational Opportunities and Methodology. ASME Turbo Expo 2025 Turbomachinery Technical Conference and Exposition. 11: Turbomachinery:V011T32A014.
GT2025-152583. Recommended for publication on ASME J. Turbomach.
Rosenzweig M, Kozul M, Sandberg R, Giannini G, Pacciani R, Marconcini M, Arnone A, Spano E, Bertini F.  2025.  Numerical Design of Experiments for Repeating Low-Pressure Turbine Stages Part 2: Effect of Reynolds Number on Different Blade Geometries. ASME Turbo Expo 2025 Turbomachinery Technical Conference and Exposition. 11: Turbomachinery:V011T32A024.
GT2025-153512. Recommended for publication on ASME J. Turbomach.
Conference Proceedings
Fang Y, Rosenzweig M, Reissmann M, Pacciani R, Marconcini M, Bertini F, Sandberg R.  2025.  Data-Driven Enhancements to Transition and Turbulence Modeling Under Varying Pressure Gradients and Unsteadiness Effects. 15th International ERCOFTAC Symposium on Engineering Turbulence Modelling and Measurements (ETMM15).
Fang Y, Reissmann M, Pacciani R, Zhao Y, Ooi A, Marconcini M, Akolekar H, Sandberg R.  2024.  Exploiting a Transformer Architecture to Simultaneous Development of Transition and Turbulence Models for Turbine Flow Predictions. ASME Turbo Expo 2024 Turbomachinery Technical Conference and Exposition. Volume 12C: Turbomachinery:V12CT32A023.
GT2024-125550
Pichler R, Zhao Y, Sandberg R, Michelassi V, Pacciani R, Marconcini M, Arnone A.  2018.  LES and RANS Analysis of the End-Wall Flow in a Linear LPT Cascade: Part I — Flow and Secondary Vorticity Fields Under Varying Inlet Condition. ASME Turbo Expo 2018: Turbine Technical Conference and Exposition. Volume 2B: Turbomachinery:pp.V02BT41A020;11pages.
paper GT2018-76233
Marconcini M, Pacciani R, Arnone A, Michelassi V, Pichler R, Zhao Y, Sandberg R.  2018.  LES and RANS analysis of the end-wall flow in a linear LPT cascade with variable inlet conditions, Part II: Loss generation. ASME Turbo Expo 2018: Turbine Technical Conference and Exposition. Volume 2B: Turbomachinery:pp.V02BT41A024;11pages.
paper GT2018-76450
Gu Y, Fang Y, Akolekar HD, Pacciani R, Marconcini M, Ooi ASH, Sandberg R.  2025.  Machine-Learning Strategies for Transition/Turbulence Modelling for Low-Pressure Turbines With Unsteady Inflow Conditions. 17th International Symposium on Unsteady Aerodynamics Aeroacoustics and Aeroelasticity of Turbomachines ISUAAAT17.
Journal Article
Pacciani R, Marconcini M, Bertini F, Rosa Taddei S, Spano E, Zhao Y, Akolekar H, Sandberg R, Arnone A.  2021.  Assessment of Machine-Learned Turbulence Models Trained for Improved Wake-Mixing in Low Pressure Turbine Flows. Energies. 14(24):8327.
Fang Y, Zhao Y, Akolekar HD, Ooi ASH, Sandberg R, Pacciani R, Marconcini M.  2024.  A Data-Driven Approach for Generalizing the Laminar Kinetic Energy Model for Separation and Bypass Transition in Low- and High-Pressure Turbines. ASME J. Turbomach.. 146(9):091005.
TURBO-23-1139
Metti L, Marconcini M, Salvadori S, Misul DAnna, Rosafio N, Lopes G, Lavagnoli S, Fang Y, Sandberg R, Pacciani R.  2026.  The Impact of Transition and Turbulence Modeling on the SPLEEN High-Speed Low-Pressure Turbine Cascade. ASME J Turbomach. 148(2):021011.
Pacciani R, Marconcini M, Arnone A, Bertini F, Spano E, Rosa Taddei S, Sandberg R.  2024.  Improvements in the Prediction of Steady and Unsteady Transition and Mixing in Low Pressure Turbines by Means of Machine-Learnt Closures. ASME J. Turbomach.. 146(5):051009.
Akolekar H, Zhao Y, Sandberg R, Pacciani R.  2021.  Integration of Machine Learning and Computational Fluid Dynamics to Develop Turbulence Models for Improved Low-Pressure Turbine Wake Mixing Prediction. ASME J. Turbomach.. 143(12):121001.
Marconcini M, Pacciani R, Arnone A, Michelassi V, Pichler R, Zhao Y, Sandberg R.  2019.  Large Eddy Simulation and RANS Analysis of the End-Wall Flow in a Linear Low-Pressure-Turbine Cascade - Part II: Loss Generation. ASME Journal of Turbomachinery. 141(5):051004(9pages).
Pichler R, Zhao Y, Sandberg R, Michelassi V, Pacciani R, Marconcini M, Arnone A.  2019.  Large-Eddy Simulation and RANS Analysis of the End-Wall Flow in a Linear Low-Pressure Turbine Cascade, Part I: Flow and Secondary Vorticity Fields Under Varying Inlet Condition. ASME Journal of Turbomachinery. 141(12):121005(10pages).
Rosenzweig M, Kozul M, Sandberg R, Giannini G, Pacciani R, Marconcini M, Arnone A, Spano E, Bertini F.  2026.  Numerical Design of Experiments for Repeating Low-Pressure Turbine Stages Part 2: Effect of Reynolds Number on Different Blade Geometries. ASME J Turbomach.
Rosenzweig M, Kozul M, Sandberg R, Giannini G, Pacciani R, Marconcini M, Arnone A.  2026.  Numerical Design of Experiments for Repeating Low-Pressure Turbine Stages Part 1: Computational Opportunities and Methodology. ASME J Turbomach.
Pacciani R, Fang Y, Metti L, Marconcini M, Sandberg R.  2025.  A Reformulation of the Laminar Kinetic Energy Model to Enable Multi-Mode Transition Predictions.. Flow, Turbulence and Combustion. 114(1):81-116.
Akolekar H, Waschkowski F, Zhao Y, Pacciani R, Sandberg R.  2021.  Transition Modeling for Low Pressure Turbines Using Computational Fluid Dynamics Driven Machine Learning. Energies. 14(15):4680.