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Proceedings Papers

Investigation of the Map Width Improvement in a Radially Reduced Diffuser Design Concept for a Centrifugal Compressor

Laura McLaughlin, Stephen Spence, Daniel Rusch, Charles Stuart, Marco Geron, Kwok Kai So, Magnus Fischer
Proc. ASME. GT2022, Volume 10B: Turbomachinery — Axial Flow Turbine Aerodynamics; Deposition, Erosion, Fouling, and Icing; Radial Turbomachinery Aerodynamics, V10BT35A002, June 13–17, 2022
Paper No: GT2022-78684
DOI: https://doi.org/10.1115/GT2022-78684
View Paper titled, Investigation of the Map Width Improvement in a Radially Reduced Diffuser Design Concept for a Centrifugal Compressor
Click here to open pdf in another window PDF for Investigation of the Map Width Improvement in a Radially Reduced Diffuser Design Concept for a Centrifugal Compressor
Topics: Compressors, Computational fluid dynamics, Design, Diffusers
Proceedings Papers

Assessment of Low Engine Order Excitation of a Contaminated Turbocharger Radial Turbine Stage Using a Nozzle Ring Only Computational Model

Michaela R. Beierl, Damian M. Vogt, Magnus Fischer, Tobias R. Müller, Kwok Kai So
Proc. ASME. GT2022, Volume 10B: Turbomachinery — Axial Flow Turbine Aerodynamics; Deposition, Erosion, Fouling, and Icing; Radial Turbomachinery Aerodynamics, V10BT35A013, June 13–17, 2022
Paper No: GT2022-82452
DOI: https://doi.org/10.1115/GT2022-82452
View Paper titled, Assessment of Low Engine Order Excitation of a Contaminated Turbocharger Radial Turbine Stage Using a Nozzle Ring Only Computational Model
Click here to open pdf in another window PDF for Assessment of Low Engine Order Excitation of a Contaminated Turbocharger Radial Turbine Stage Using a Nozzle Ring Only Computational Model
Topics: Computer simulation, Engines, Excitation, Nozzles, Turbines, Turbochargers, High cycle fatigue, Blades, Combustion, Contamination
Proceedings Papers

Machine-Learning Assisted Optimization of Generalized K-Omega (GEKO) Turbulence Model Parameters for Turbocharger Radial Compressor

Patrick Amstad, Kwok Kai So, Magnus Fischer
Proc. ASME. GT2022, Volume 10D: Turbomachinery — Multidisciplinary Design Approaches, Optimization, and Uncertainty Quantification; Turbomachinery General Interest; Unsteady Flows in Turbomachinery, V10DT34A002, June 13–17, 2022
Paper No: GT2022-78306
DOI: https://doi.org/10.1115/GT2022-78306
View Paper titled, Machine-Learning Assisted Optimization of Generalized K-Omega (GEKO) Turbulence Model Parameters for Turbocharger Radial Compressor
Click here to open pdf in another window PDF for Machine-Learning Assisted Optimization of Generalized K-Omega (GEKO) Turbulence Model Parameters for Turbocharger Radial Compressor
Topics: Compressors, Machine learning, Optimization, Turbochargers, Turbulence, Artificial neural networks, Diffusers, Errors, Flow (Dynamics), Pressure
Journal Articles

Assessment of Low Engine Order Excitation of a Contaminated Turbocharger Radial Turbine Stage Using a Nozzle Ring Only Computational Model

Michaela R. Beierl, Damian M. Vogt, Magnus Fischer, Tobias R. Müller, Kwok Kai So
Journal: Journal of Turbomachinery
Article Type: Research Papers
J. Turbomach. January 2023, 145(1): 011011.
Paper No: TURBO-22-1158
DOI: https://doi.org/10.1115/1.4055499
Published Online: October 7, 2022
View Article titled, Assessment of Low Engine Order Excitation of a Contaminated Turbocharger Radial Turbine Stage Using a Nozzle Ring Only Computational Model
Click here to open pdf in another window PDF for Assessment of Low Engine Order Excitation of a Contaminated Turbocharger Radial Turbine Stage Using a Nozzle Ring Only Computational Model
Topics: Blades, Excitation, Nozzles, Turbines, Engines, Rotors, Computational fluid dynamics, Simulation, Turbochargers, Contamination