Biblio

Fang Y, Zhao Y, Akolekar HD, Ooi ASH, Sandberg RD, 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

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.

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

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.

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.

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.

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 RD, 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.

Fang Y, Reissmann M, Pacciani R, Zhao Y, Ooi ASH, Marconcini M, Akolekar HD, Sandberg RD.  Submitted.  Exploiting a Transformer Architecture to Simultaneous Development of Transition and Turbulence Models for Turbine Flow Predictions. ASME J Turbomach.

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).

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.