Biblio

Rosenzweig M, Kozul M, Sandberg RD, 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.

Rosenzweig M, Kozul M, Sandberg RD, 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.

Pacciani R, Fang Y, Metti L, Marconcini M, Sandberg RD.  2025.  A Reformulation of the Laminar Kinetic Energy Model to Enable Multi-Mode Transition Predictions.. Flow, Turbulence and Combustion. 114(1):81-116.

Pinelli L, Malcaus M, Giannini G, Marconcini M.  2025.  Some Experiences About the RANS Modeling of UHBR Fan: The Case of ECL5/CATANA. 16th European Turbomachinery Conference ETC16.

Bandini A, Bettini C, Peruzzi L, Caretta M, Canelli C, Marconcini M, Pinelli L, Arnone A.  2025.  Targeting Full-Hydrogen Operation on Industrial-Scale Gas Turbines: Impact of Unconventional Fuels on Turbine Module Performance and Aeromechanics. ASME J Turbomach. 147(7):071008.

Bandini A, Bettini C, Peruzzi L, Caretta M, Canelli C, Marconcini M, Pinelli L, Arnone A.  2025.  Targeting Full-Hydrogen Operation on Industrial-Scale Gas Turbines: Impact of Unconventional Fuels on Turbine Module Performance and Aeromechanics. ASME J Turbomach. 147(7):071008.

Pela A, Marconcini M, Agnolucci A, Belardini E, Grimaldi A, Toni L, Valente R, Arnone A.  2025.  Towards the Automatic Generation of Transonic Centrifugal Impellers by Deep Learning and Feature Importance Techniques. ASME Turbo Expo 2025 Turbomachinery Technical Conference and Exposition.

Bottarelli T, Fanfani M, Nesi P, Pinelli L.  2025.  Using Physics-Informed Neural Networks for Solving Navier-Stokes Equations in Complex Scenarios. Engineering Applications of Artificial Intelligence. 148:110347.

Fang Y, Rosenzweig M, Reissmann M, Pacciani R, Marconcini M, Bertini F, Sandberg RD.  In Press.  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 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.

Giannini G, Pinelli L, Pacciani R, Arnone A, Bertini F, Spano E, Marconcini M.  Submitted.  The Impact of Modeling Assumptions on the Hot Spots Convection Within a Cooled High-Pressure Turbine Stage. Aerospace Science and Technology.

Giannini G, Pinelli L, Pacciani R, Arnone A, Bertini F, Spano E, Marconcini M.  Submitted.  The Impact of Modeling Assumptions on the Hot Spots Convection Within a Cooled High-Pressure Turbine Stage. Aerospace Science and Technology.

Pinelli L, Malcaus M, Giannini G, Marconcini M.  Submitted.  Some Experiences About the RANS Modeling of UHBR Fan: The Case of ECL5/CATANA. Int. J. Turbomach. Propuls. Power..