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Richard Ahlfeld
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Proceedings Papers

Using Autoencoders and Output Consolidation to Improve Machine Learning Models for Turbomachinery Applications

Julie Pongetti, Timoleon Kipouros, Marc Emmanuelli, Richard Ahlfeld, Shahrokh Shahpar
Proc. ASME. GT2021, Volume 2D: Turbomachinery — Multidisciplinary Design Approaches, Optimization, and Uncertainty Quantification; Radial Turbomachinery Aerodynamics; Unsteady Flows in Turbomachinery, V02DT36A018, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-60158
https://doi.org/10.1115/GT2021-60158
View Paper titled, Using Autoencoders and Output Consolidation to Improve Machine Learning Models for Turbomachinery Applications
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Topics: Machine learning, Turbomachinery, Optimization, Blades, Compressors, Design, Engineering simulation, Flow (Dynamics), Fluid dynamics, Simulation
Proceedings Papers

Uncertainty Quantification Analysis of Back Facing Steps Film Cooling Configurations

Eiji Sakai, Meng Bai, Richard Ahlfeld, Francesco Montomoli
Proc. ASME. GT2018, Volume 5A: Heat Transfer, V05AT12A009, June 11–15, 2018
Publisher: American Society of Mechanical Engineers
Paper No: GT2018-75686
https://doi.org/10.1115/GT2018-75686
View Paper titled, Uncertainty Quantification Analysis of Back Facing Steps Film Cooling Configurations
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Topics: Film cooling, Uncertainty quantification, Engineering simulation, Simulation, Uncertainty, Approximation, Chaos, Coolants, Cooling, Eddies (Fluid dynamics)
Journal Articles

Autonomous Uncertainty Quantification for Discontinuous Models Using Multivariate Padé Approximations

Richard Ahlfeld, Francesco Montomoli, Mauro Carnevale, Simone Salvadori
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research-Article
J. Turbomach. April 2018, 140(4): 041004.
Paper No: TURBO-17-1062
https://doi.org/10.1115/1.4038826
Published Online: January 23, 2018
View Article titled, Autonomous Uncertainty Quantification for Discontinuous Models Using Multivariate Padé Approximations
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Topics: Approximation, Computational fluid dynamics, Errors, Shock (Mechanics), Uncertainty quantification, Film cooling, Polynomials
Journal Articles

Uncertainty Quantification of Leakages in a Multistage Simulation and Comparison With Experiments

Cosimo Maria Mazzoni, Richard Ahlfeld, Budimir Rosic, Francesco Montomoli
Journal: Journal of Fluids Engineering
Publisher: ASME
Article Type: Research-Article
J. Fluids Eng. February 2018, 140(2): 021110.
Paper No: FE-16-1554
https://doi.org/10.1115/1.4037983
Published Online: November 3, 2017
View Article titled, Uncertainty Quantification of Leakages in a Multistage Simulation and Comparison With Experiments
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Topics: Blades, Clearances (Engineering), Flow (Dynamics), Leakage, Pressure, Rotors, Simulation, Stators, Turbines, Uncertainty quantification
Journal Articles

A Single Formulation for Uncertainty Propagation in Turbomachinery: SAMBA PC

Richard Ahlfeld, Francesco Montomoli
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research-Article
J. Turbomach. November 2017, 139(11): 111007.
Paper No: TURBO-16-1184
https://doi.org/10.1115/1.4037362
Published Online: August 23, 2017
View Article titled, A Single Formulation for Uncertainty Propagation in Turbomachinery: SAMBA PC
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Topics: Algorithms, Approximation, Computational fluid dynamics, Diffusers, Errors, Fittings, Gas turbines, Manufacturing, Polynomials, Simulation
Proceedings Papers

An Autonomous Uncertainty Quantification Method for the Digital Age: Transonic Flow Simulations Using Multivariate Padé Approximations

Richard Ahlfeld, Mauro Carnevale, Simone Salvadori, Francesco Montomoli
Proc. ASME. GT2017, Volume 2C: Turbomachinery, V02CT47A023, June 26–30, 2017
Publisher: American Society of Mechanical Engineers
Paper No: GT2017-64968
https://doi.org/10.1115/GT2017-64968
View Paper titled, An Autonomous Uncertainty Quantification Method for the Digital Age: Transonic Flow Simulations Using Multivariate Padé Approximations
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Topics: Approximation, Engineering simulation, Simulation, Transonic flow, Uncertainty quantification, Computational fluid dynamics, Errors, Reliability, Algorithms, Chaos
Proceedings Papers

A Single Formulation for Uncertainty Propagation in Turbomachinery: SAMBA PC

Richard Ahlfeld, Francesco Montomoli
Proc. ASME. GT2016, Volume 2C: Turbomachinery, V02CT45A007, June 13–17, 2016
Publisher: American Society of Mechanical Engineers
Paper No: GT2016-56573
https://doi.org/10.1115/GT2016-56573
View Paper titled, A Single Formulation for Uncertainty Propagation in Turbomachinery: SAMBA PC
Open the PDF for A Single Formulation for Uncertainty Propagation in Turbomachinery: SAMBA PC in another window
Topics: Turbomachinery, Uncertainty, Simulation, Polynomials, Uncertainty quantification, Chaos, Errors, Fittings, Algorithms, Approximation