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Machine learning for Advanced Gas turbine Injection SysTems to Enhance combustoR performance.

Deliverables

Modelling of acoustically absorbing liners.

Modelling of acoustically absorbing liners.

Comparison of different machine learning algorithms.

Comparison of different machine learning algorithms.

Application of machine learning in CFD.

Application of machine learning in CFD.

Summer school: Thermo-acoustics and combustion dynamics in aero gas turbine engines

Thermo-acoustics and combustion dynamics in aero gas turbine engines

Workshop C

Entrepreneurship, ethics, intellectual property rights and management

Workshop B

CFD for spray flame simulations

Workshop A

Machine Learning, Combustion and Acoustics in aero engine combustors

Data Management Plan (DMP)

Mandatory deliverable as consortium decided not to opt out of the pilot on open research.

Publications

Data Assimilation Using Heteroscedastic Bayesian Neural Network Ensembles for Reduced-Order Flame Models

Author(s): Maximilian L. Croci, Ushnish Sengupta, Matthew P. Juniper
Published in: Computational Science – ICCS 2021 - 21st International Conference, Krakow, Poland, June 16–18, 2021, Proceedings, Part V, Issue 12746, 2021, Page(s) 408-419
DOI: 10.1007/978-3-030-77977-1_33

Real-time parameter inference in reduced-order flame models with heteroscedastic Bayesian neural network ensembles

Author(s): Sengupta, Ushnish; Croci, Maximilian L.; Juniper, Matthew P.
Published in: Issue 1, 2021

Thermoacoustic stabilization of combustors with gradient-augmented Bayesian optimization and adjoint models

Author(s): Ushnish Sengupta1 and Matthew P. Juniper1
Published in: 2021

Numerical design of Luenberger observers for nonlinear systems

Author(s): L. C. Ramos, F. D. Meglio, V. Morgenthaler, L. F. Figueira da Silva, P. Bernard
Published in: 2020 IEEE Conference on Decision and Control (CDC), 2020

Fusing model ensembles and observations together with Bayesian neural networks

Author(s): Amos, Matt ; Sengupta, Ushnish ; Hosking, Scott ; Young, Paul
Published in: 2021

Forecasting Thermoacoustic Instabilities in Liquid Propellant Rocket Engines Using Multimodal Bayesian Deep Learning

Author(s): Ushnish Senguptaa, G ̈unther Waxenegger-Wilfingb, Jan Martinb,Justin Hardib, Matthew P. Junipera,∗
Published in: Fluid Dynamics (physics.flu-dyn); Computational Engineering, Finance, and Science (cs.CE); Machine Learning (cs.LG), 2021

Online Detection of Combustion Instabilities Using Supervised Machine Learning

Author(s): Michael McCartney, Wolfgang Polifke
Published in: Proceedings of the ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition, 2020
DOI: 10.1115/gt2020-14834

Comparison of Machine Learning Algorithms in the Interpolation and Extrapolation of Flame Describing Functions

Author(s): Michael McCartney, Matthias Haeringer, Wolfgang Polifke
Published in: Volume 4B: Combustion, Fuels, and Emissions, Issue GT 2019, Anual, 2019
DOI: 10.1115/gt2019-91319

A model to study spontaneous oscillations in a lean premixed combustor using non-linear analysis

Author(s): Sara Navarro Arredondo, Jim Kok
Published in: Proceedings of the 26th International Congress on Sound and Vibration, Issue 26, 2019

Numerical Study Of A Swirl Atomized Spray Response To Acoustic Perturbations.

Author(s): Alireza Ghasemi, J.B.W. Kok
Published in: Proceedings of the 26th International Congress on Sound and Vibration, Issue 26, 2019

Bayesian machine learning for the prognosis of combustion instabilities from noise

Author(s): Ushnish Sengupta Carl Rasmussen Matthew Juniper
Published in: Proceedings of the ASME 2020 Turbomachinery Technical Conference Exposition, 2020
DOI: 10.31224/osf.io/ysgp4

Real-time parameter inference in reduced-order flame models with heteroscedastic Bayesian neural network ensembles

Author(s): Ushnish Sengupta, Maximilian L. Croci, Matthew P. Juniper
Published in: 2020

Comparison of Machine Learning Algorithms in the Interpolation and Extrapolation of Flame Describing Functions

Author(s): Michael McCartney, Matthias Haeringer, Wolfgang Polifke
Published in: Volume 4B: Combustion, Fuels, and Emissions, 2019
DOI: 10.1115/gt2019-91319

Real-time parameter inference of nonlinear bluff-body-stabilized flame models using Bayesian neural network ensembles

Author(s): Maximilian L. Croci1 2, Ushnish Sengupta1 and Matthew P. Juniper1
Published in: 2021

Numerical design of Luenberger observers for nonlinear systems

Author(s): Louise da C. Ramos, Florent Di Meglio, Valery Morgenthaler, Luis F. Figueira da Silva, Pauline Bernard
Published in: 2020 59th IEEE Conference on Decision and Control (CDC), 2020, Page(s) 5435-5442
DOI: 10.1109/cdc42340.2020.9304163

Reduced Order Models Applied to Laminar Diffusion Flames

Author(s): N. L. M. B. Junqueira, L. F. Figueira da Silva, L. C. Ramos
Published in: 2020 Brazilian Congress of Thermal Sciences and Engineering, Online., 2020

Reduced Order Model of Laminar Premixed Inverted Conical Flames

Author(s): Louise da Costa Ramos, Florent Di Meglio, Luis Fernando F. Da Silva, Valery Morgenthaler
Published in: AIAA Scitech 2020 Forum, 2020
DOI: 10.2514/6.2020-0416

Estimating Both Reflection Coefficients of 2×2 Linear Hyperbolic Systems with Single Boundary Measurement

Author(s): Nils Christian A. Wilhelmsen, Florent Di Meglio
Published in: 2020 59th IEEE Conference on Decision and Control (CDC), 2020, Page(s) 658-665
DOI: 10.1109/cdc42340.2020.9304413

Assimilation of Experimental Data to Create a Quantitatively Accurate Reduced-Order Thermoacoustic Model

Author(s): Francesco Garita; Hans Yu; Matthew P. Juniper
Published in: Issue 4, 2021, ISSN 1528-8919
DOI: 10.31224/osf.io/8bmaz

Ongoing Development of Non-reflective Boundary Conditions for Euler and Navier-Stokes Equations via the Discontinuous Galerkin Framework

Author(s): Edmond Shehadi, Edwin van der Weide
Published in: AIAA Scitech 2021 Forum, 2021
DOI: 10.2514/6.2021-1660

ASSIMILATION OF EXPERIMENTAL DATA TO CREATE A QUANTITATIVELY-ACCURATE REDUCED ORDER THERMOACOUSTIC MODEL

Author(s): Garita, F., Yu, H., & Juniper, M.
Published in: Proceedings of the ASME Turbo Expo 2020: Turbine Technical Conference and Exposition, 2020

Improved color-gradient method for lattice Boltzmann modeling of two-phase flows

Author(s): T. Lafarge; P. Boivin; N. Odier; B. Cuenot
Published in: EISSN: 1089-7666, Issue 1, 2021, ISSN 1527-2435
DOI: 10.1063/5.0061638

Static mesh adaptation for reliable large eddy simulation of turbulent reacting flows

Author(s): P. W. Agostinelli; B. Rochette; D. Laera; J. Dombard; B. Cuenot; L. Gicquel
Published in: Crossref, Issue 5, 2021, ISSN 1527-2435
DOI: 10.1063/5.0040719

Influence of an Oscillating Airflow on the PrefilmingAirblast Atomization Process

Author(s): Thomas Christou Björn Stelzner Nikolaos Zarzalis
Published in: Atomization and Sprays, 2021, ISSN 1936-2684
DOI: 10.1615/atomizspr.2021034553

Modeling of the nonlinear flame response of a Bunsen-type flame via multi-layer perceptron

Author(s): Nilam Tathawadekar, Nguyen Anh Khoa Doan, Camilo F. Silva, Nils Thuerey
Published in: Proceedings of the Combustion Institute, 2020, ISSN 1540-7489
DOI: 10.1016/j.proci.2020.07.115

Numerical study of multicomponent spray flame propagation

Author(s): Varun Shastry Quentin Cazeres Bastien Rochette Eleonore Riber Bénédicte Cuenot
Published in: Proceedings of the Combustion Institute, 2019, ISSN 1540-7489
DOI: 10.1016/j.proci.2020.07.090

Impact of wall heat transfer in Large Eddy Simulation of flame dynamics in a swirled combustion chamber

Author(s): P.W.Agostinelli D.Laera I.Boxx L.Gicquel T.Poinsotd
Published in: Combustion and Flame, 2021, ISSN 0010-2180
DOI: 10.1016/j.combustflame.2021.111728

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

Author(s): Michael McCartney, Ushnish Sengupta, Matthew Juniper
Published in: Journal of Engineering for Gas Turbines and Power, 2021, ISSN 0742-4795
DOI: 10.1115/1.4052145

Comparison of Machine Learning Algorithms in the Interpolation and Extrapolation of Flame Describing Functions

Author(s): Michael McCartney, Matthias Haeringer, Wolfgang Polifke
Published in: Journal of Engineering for Gas Turbines and Power, Issue 142/6, 2020, ISSN 0742-4795
DOI: 10.1115/1.4045516

An Observer for the Electrically Heated Vertical Rijke Tube with Nonlinear Heat Release

Author(s): Nils Christian A. Wilhelmsen, Florent Di Meglio
Published in: IFAC-PapersOnLine, Issue 53/2, 2020, Page(s) 4181-4188, ISSN 2405-8963
DOI: 10.1016/j.ifacol.2020.12.2461

Early detection of thermoacoustic instabilities in a cryogenic rocket thrust chamber using combustion noise features and machine learning

Author(s): Günther Waxenegger-Wilfing, Ushnish Sengupta, Jan Martin, Wolfgang Armbruster, Justin Hardi, Matthew Juniper, Michael Oschwald
Published in: Chaos: An Interdisciplinary Journal of Nonlinear Science, Issue 31/6, 2021, Page(s) 063128, ISSN 1054-1500
DOI: 10.1063/5.0038817

Ensembling geophysical models with Bayesian Neural Networks

Author(s): Ushnish Sengupta, Matt Amos, J. Scott Hosking, Carl Edward Rasmussen, Matthew Juniper, Paul J. Young
Published in: Advances in Neural Information Processing Systems (NeurIPS) 2020, 2020