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Proceedings Papers

Bayesian Data Assimilation in Cold Flow Experiments on an Industrial Thermoacoustic Rig

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Jingquan Zheng, André Fischer, Claus Lahiri, Matthew Yoko, Matthew Juniper
Proc. ASME. GT2024, Volume 3A: Combustion, Fuels, and Emissions, V03AT04A018, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-122656
https://doi.org/10.1115/GT2024-122656
View Paper titled, Bayesian Data Assimilation in Cold Flow Experiments on an Industrial Thermoacoustic Rig
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Topics: Flow (Dynamics), Acoustics, Combustion chambers, Emissions, Geometry, Network models, Optimization, Physics, Probability, Uncertainty
Proceedings Papers

A Comparison of Flat and Hierarchical Structures in Aircraft Engine Fault Classification Algorithms

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Igor Loboda, Juan Luis Pérez-Ruiz, Iván González Castillo, Sergiy Yepifanov
Proc. ASME. GT2024, Volume 4: Controls, Diagnostics, and Instrumentation, V004T05A053, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-129597
https://doi.org/10.1115/GT2024-129597
View Paper titled, A Comparison of Flat and Hierarchical Structures in Aircraft Engine Fault Classification Algorithms
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Topics: Aircraft engines, Algorithms, Gas turbines, Engines, Monitoring systems, Artificial neural networks, Construction, Feature extraction, Machine learning, Pattern recognition
Proceedings Papers

Risk Assessment and Probabilistic Projection of IN706 Gas Turbine Rotor

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John Scheibel, Huawei Shi, Robert Dewey
Proc. ASME. GT2024, Volume 6: Education; Electric Power; Energy Storage; Fans and Blowers, V006T08A004, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-125009
https://doi.org/10.1115/GT2024-125009
View Paper titled, Risk Assessment and Probabilistic Projection of IN706 Gas Turbine Rotor
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Topics: Gas turbines, Risk assessment, Rotors, Creep, Durability, Failure mode and effects analysis, Inspection, Design, Disks, Failure
Proceedings Papers

Possibilities of Applying Machine Learning Techniques for Probabilistic Analysis in a Turbine Blade-Disk Interface

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Elmira Emmrich, Md Tarekul Islam, Matthias Voigt, Lukas Bruder, Julian von Lautz, Ronald Mailach
Proc. ASME. GT2024, Volume 10B: Structures and Dynamics — Fatigue, Fracture, and Life Prediction; Probabilistic Methods; Rotordynamics; Structural Mechanics and Vibration, V10BT25A002, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-122477
https://doi.org/10.1115/GT2024-122477
View Paper titled, Possibilities of Applying Machine Learning Techniques for Probabilistic Analysis in a Turbine Blade-Disk Interface
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Topics: Blades, Disks, Machine learning, Metamodeling, Turbines, Deep neural networks, Design, Finite element model, Failure, Finite element analysis
Proceedings Papers

Model Order Determination for Modal Parameter Estimation: Application to a Composite Fan Stage

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Corentin Jorajuria, Claude Gibert, Cécile Esteves, Fabrice Thouverez
Proc. ASME. GT2024, Volume 10B: Structures and Dynamics — Fatigue, Fracture, and Life Prediction; Probabilistic Methods; Rotordynamics; Structural Mechanics and Vibration, V10BT27A021, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-126685
https://doi.org/10.1115/GT2024-126685
View Paper titled, Model Order Determination for Modal Parameter Estimation: Application to a Composite Fan Stage
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Topics: Aeronautics, Bladed disks, Composite materials, Engines, Modal analysis, Parameter estimation, Turbojets, Computer simulation, Testing, Damping
Proceedings Papers

Integrating Location-Specific Non-Destructive Inspection Simulation With Probabilistic Damage Tolerance Assessment

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Michael P. Enright, Yasin Zaman, Fabrice Foucher, Sebastien Lonné, Philippe Dubois, Stephane Leberre, Pierre Calmon
Proc. ASME. GT2024, Volume 10B: Structures and Dynamics — Fatigue, Fracture, and Life Prediction; Probabilistic Methods; Rotordynamics; Structural Mechanics and Vibration, V10BT25A007, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-129117
https://doi.org/10.1115/GT2024-129117
View Paper titled, Integrating Location-Specific Non-Destructive Inspection Simulation With Probabilistic Damage Tolerance Assessment
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Topics: Damage, Inspection, Nondestructive evaluation, Probability, Simulation
Proceedings Papers

A Proposed Framework for Minimizing Starts and Extending Maintenance Intervals Through Optimized Scheduling With Mixed Integer Programming

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Cody W. Allen
Proc. ASME. GT2023, Volume 9: Microturbines, Turbochargers, and Small Turbomachines; Oil and Gas Applications, V009T19A008, June 26–30, 2023
Publisher: American Society of Mechanical Engineers
Paper No: GT2023-102032
https://doi.org/10.1115/GT2023-102032
View Paper titled, A Proposed Framework for Minimizing Starts and Extending Maintenance Intervals Through Optimized Scheduling With Mixed Integer Programming
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Topics: Integer programming, Maintenance, Optimization, Computation, Machinery, Reliability, Carbon, Emissions, Energy generation, Engines
Proceedings Papers

High Altitude Relight Performance of Hydrogen-Air Micromix Combustion Systems

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Nicholas C. W. Treleaven, Stefano Puggelli, Renaud Mercier, Julien Leparoux, Xiaoxiao Sun, Bobby Sethi
Proc. ASME. GT2023, Volume 3B: Combustion, Fuels, and Emissions, V03BT04A063, June 26–30, 2023
Publisher: American Society of Mechanical Engineers
Paper No: GT2023-103970
https://doi.org/10.1115/GT2023-103970
View Paper titled, High Altitude Relight Performance of Hydrogen-Air Micromix Combustion Systems
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Topics: Combustion systems, Hydrogen, Ignition, Chemistry, Ejectors, Flames, Fuels, Combustion chambers, Probability, Aircraft
Proceedings Papers

Learning RANS Model Parameters From LES Using Bayesian Inference

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Santosh Hemchandra, Anindya Datta, Matthew P. Juniper
Proc. ASME. GT2023, Volume 3A: Combustion, Fuels, and Emissions, V03AT04A051, June 26–30, 2023
Publisher: American Society of Mechanical Engineers
Paper No: GT2023-102159
https://doi.org/10.1115/GT2023-102159
View Paper titled, Learning RANS Model Parameters From LES Using Bayesian Inference
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Topics: Reynolds-averaged Navier–Stokes equations, Flow (Dynamics), Design, Turbulence, Combustion, Eddies (Fluid dynamics), Energy dissipation, Engineering design, Engineering simulation, Flames
Proceedings Papers

A Probabilistic Method for Predicting Particle-Blade Impact Kinematics in Turbomachinery

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D. Klaoudatos, N. Bojdo, A. Filippone, S. Covey-Crump, M. Jones, A. Pawley
Proc. ASME. GT2022, Volume 10B: Turbomachinery — Axial Flow Turbine Aerodynamics; Deposition, Erosion, Fouling, and Icing; Radial Turbomachinery Aerodynamics, V10BT31A006, June 13–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-80389
https://doi.org/10.1115/GT2022-80389
View Paper titled, A Probabilistic Method for Predicting Particle-Blade Impact Kinematics in Turbomachinery
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Topics: Blades, Kinematics, Particulate matter, Turbomachinery, Compressors, Particle collisions, Rotors, Kinetic energy, Probability, Chords (Trusses)
Proceedings Papers

Impact of Epistemic Uncertainty on Performance Parameters of Compressor Blades

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Andriy Prots, Lukas Schlüter, Matthias Voigt, Ronald Mailach, Marcus Meyer
Proc. ASME. GT2022, Volume 10D: Turbomachinery — Multidisciplinary Design Approaches, Optimization, and Uncertainty Quantification; Turbomachinery General Interest; Unsteady Flows in Turbomachinery, V10DT34A015, June 13–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-82579
https://doi.org/10.1115/GT2022-82579
View Paper titled, Impact of Epistemic Uncertainty on Performance Parameters of Compressor Blades
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Topics: Blades, Compressors, Uncertainty, Density, Optical measurement, Probability, Chords (Trusses), Design, Gaussian distribution, Manufacturing
Proceedings Papers

A Stochastic and Bayesian Inference Toolchain for Uncertainty and Risk Quantification of Rare Autoignition Events in DLE Premixers

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Sajjad Yousefian, Gilles Bourque, Sandeep Jella, Philippe Versailles, Rory F. D. Monaghan
Proc. ASME. GT2022, Volume 3B: Combustion, Fuels, and Emissions, V03BT04A055, June 13–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-83667
https://doi.org/10.1115/GT2022-83667
View Paper titled, A Stochastic and Bayesian Inference Toolchain for Uncertainty and Risk Quantification of Rare Autoignition Events in DLE Premixers
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Topics: Risk, Uncertainty, Particle filtering (numerical methods), Combustion systems, Computational fluid dynamics, Emissions, Methane, Modeling, Temperature, Temperature distribution
Proceedings Papers

Modeling of Flashback With Different Blends of CH4 and H2 by Using Finite Rate Chemistry With Large Eddy Simulation

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Ishan Verma, Rakesh Yadav, Naseem Ansari, Stefano Orsino, Shaoping Li, Pravin Nakod
Proc. ASME. GT2022, Volume 3B: Combustion, Fuels, and Emissions, V03BT04A026, June 13–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-82601
https://doi.org/10.1115/GT2022-82601
View Paper titled, Modeling of Flashback With Different Blends of CH4 and H2 by Using Finite Rate Chemistry With Large Eddy Simulation
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Topics: Chemistry, Combustion, Hydrogen, Large eddy simulation, Methane, Modeling, Combustion chambers, Engineering simulation, Simulation, Boundary layers
Proceedings Papers

A Probabilistic Framework for Minimum Low Cycle Fatigue Life Prediction

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Michael P. Enright, Jonathan P. Moody, Yasin Zaman, James C. Sobotka, R. Craig McClung
Proc. ASME. GT2022, Volume 8B: Structures and Dynamics — Probabilistic Methods; Rotordynamics; Structural Mechanics and Vibration, V08BT25A001, June 13–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-80220
https://doi.org/10.1115/GT2022-80220
View Paper titled, A Probabilistic Framework for Minimum Low Cycle Fatigue Life Prediction
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Topics: Low cycle fatigue, Damage, Fatigue, Fracture (Materials), Gas turbines, Photodynamic therapy, Aircraft, Cycles, Density, Probability
Proceedings Papers

Uncertainty Quantification of a Jet Engine Performance Model Under Scarce Data Availability

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Norbert Ludwig, Giulia Antinori, Marco Daub, Fabian Duddeck
Proc. ASME. GT2021, Volume 2D: Turbomachinery — Multidisciplinary Design Approaches, Optimization, and Uncertainty Quantification; Radial Turbomachinery Aerodynamics; Unsteady Flows in Turbomachinery, V02DT36A006, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-58604
https://doi.org/10.1115/GT2021-58604
View Paper titled, Uncertainty Quantification of a Jet Engine Performance Model Under Scarce Data Availability
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Topics: Jet engines, Uncertainty quantification, Manufacturing, Uncertainty, Design, Flow (Dynamics), Probability, Gaussian distribution, Robustness
Proceedings Papers

Investigations on the Aerothermal Performance Uncertainty Quantification of the Turbine Blade Squealer Tip

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Ming Huang, Zhigang Li, Jun Li, Liming Song
Proc. ASME. GT2021, Volume 2D: Turbomachinery — Multidisciplinary Design Approaches, Optimization, and Uncertainty Quantification; Radial Turbomachinery Aerodynamics; Unsteady Flows in Turbomachinery, V02DT36A008, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-59033
https://doi.org/10.1115/GT2021-59033
View Paper titled, Investigations on the Aerothermal Performance Uncertainty Quantification of the Turbine Blade Squealer Tip
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Topics: Turbine blades, Uncertainty quantification, Design, Uncertainty, Geometry, Heat transfer, Rotors, Clearances (Engineering), Film cooling, Heat flux
Proceedings Papers

NOx Emission Modelling for Lean Premixed Industrial Combustors With a Diffusion Pilot Burner

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Johann Moritz Reumschüssel, Jakob G. R. von Saldern, Thomas Ludwig Kaiser, Thoralf Reichel, Jan Paul Beuth, Bernhard Ćosić, Franklin Genin, Kilian Oberleithner, Christian Oliver Paschereit
Proc. ASME. GT2021, Volume 3A: Combustion, Fuels, and Emissions, V03AT04A035, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-59071
https://doi.org/10.1115/GT2021-59071
View Paper titled, NOx Emission Modelling for Lean Premixed Industrial Combustors With a Diffusion Pilot Burner
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Topics: Combustion chambers, Diffusion (Physics), Emissions, Modeling, Nitrogen oxides, Flames, Fuels, Combustion, Chemistry, Combustion systems
Proceedings Papers

Reducing Uncertainty in the Onset of Combustion Instabilities Using Dynamic Pressure Information and Bayesian Neural Networks

Open Access

Michael McCartney, Ushnish Sengupta, Matthew Juniper
Proc. ASME. GT2021, Volume 3B: Combustion, Fuels, and Emissions, V03BT04A042, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-60283
https://doi.org/10.1115/GT2021-60283
View Paper titled, Reducing Uncertainty in the Onset of Combustion Instabilities Using Dynamic Pressure Information and Bayesian Neural Networks
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Topics: Artificial neural networks, Combustion, Pressure, Uncertainty, Hidden variables, Combustion chambers, Combustion systems, Emissions, Errors, Wall temperature
Proceedings Papers

Thermoacoustic Instabilities of Hydrogen-Enriched Partially Premixed Flames in a Swirl Combustor

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Y. Gong, D. Fredrich, A. J. Marquis, W. P. Jones, I. Boxx
Proc. ASME. GT2021, Volume 3B: Combustion, Fuels, and Emissions, V03BT04A023, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-60009
https://doi.org/10.1115/GT2021-60009
View Paper titled, Thermoacoustic Instabilities of Hydrogen-Enriched Partially Premixed Flames in a Swirl Combustor
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Topics: Combustion chambers, Flames, Hydrogen, Chemistry, Combustion, Oscillations, Chemical reactions, Density, Dynamics (Mechanics), Feedback
Proceedings Papers

Micromechanical Modeling Tension-Compression Fatigue Hysteresis Loops Model of Fiber-Reinforced Ceramic-Matrix Composites Considering Fibers Failure

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Longbiao Li
Proc. ASME. GT2021, Volume 6: Ceramics and Ceramic Composites; Coal, Biomass, Hydrogen, and Alternative Fuels; Microturbines, Turbochargers, and Small Turbomachines, V006T02A002, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-58485
https://doi.org/10.1115/GT2021-58485
View Paper titled, Micromechanical Modeling Tension-Compression Fatigue Hysteresis Loops Model of Fiber-Reinforced Ceramic-Matrix Composites Considering Fibers Failure
Open the PDF for Micromechanical Modeling Tension-Compression Fatigue Hysteresis Loops Model of Fiber-Reinforced Ceramic-Matrix Composites Considering Fibers Failure in another window
Topics: Ceramics, Composite materials, Compression, Failure, Fatigue, Fibers, Modeling, Tension, Stress, Ceramic matrix composites