Classification and computation of extreme events in turbulent combustion
M Hassanaly, V Raman - Progress in Energy and Combustion Science, 2021 - Elsevier
In the design of practical combustion systems, ensuring safety and reliability is an important
requirement. For instance, reliably avoiding lean blowout, flame flashback or inlet unstart is …
requirement. For instance, reliably avoiding lean blowout, flame flashback or inlet unstart is …
Challenges for turbulent combustion
AR Masri - Proceedings of the Combustion Institute, 2021 - Elsevier
Turbulent combustion will remain central to the next generation of combustion devices that
are likely to employ blends of renewable and fossil fuels, transitioning eventually to …
are likely to employ blends of renewable and fossil fuels, transitioning eventually to …
Multiscale graph neural network autoencoders for interpretable scientific machine learning
The goal of this work is to address two limitations in autoencoder-based models: latent
space interpretability and compatibility with unstructured meshes. This is accomplished here …
space interpretability and compatibility with unstructured meshes. This is accomplished here …
Data-driven classification and modeling of combustion regimes in detonation waves
A data-driven approach to classify combustion regimes in detonation waves is implemented,
and a procedure for domain-localized source term modeling based on these classifications …
and a procedure for domain-localized source term modeling based on these classifications …
A generative adversarial network (GAN) approach to creating synthetic flame images from experimental data
Modern diagnostic tools in turbulent combustion allow for highly-resolved measurements of
reacting flows; however, they tend to generate massive data-sets, rendering conventional …
reacting flows; however, they tend to generate massive data-sets, rendering conventional …
[HTML][HTML] 3d convolutional selective autoencoder for instability detection in combustion systems
T Gangopadhyay, V Ramanan, A Akintayo, PK Boor… - Energy and AI, 2021 - Elsevier
While analytical solutions of critical (phase) transitions in dynamical systems are abundant
for simple nonlinear systems, such analysis remains intractable for real-life dynamical …
for simple nonlinear systems, such analysis remains intractable for real-life dynamical …
Using machine learning to construct velocity fields from OH-PLIF images
This work utilizes data-driven methods to morph a series of time-resolved experimental OH-
PLIF images into corresponding three-component planar PIV fields in the closed domain of a …
PLIF images into corresponding three-component planar PIV fields in the closed domain of a …
Influence of operating conditions on flow field dynamics and soot formation in an aero-engine model combustor
M Grader, P Gerlinger - Combustion and Flame, 2023 - Elsevier
Large-eddy simulations of a sooting aero-engine model combustor are performed for three
operating points. They are analyzed to investigate the influence of secondary air injection …
operating points. They are analyzed to investigate the influence of secondary air injection …
Data-driven reduction and decomposition with time-axis clustering
A new approach for modal decomposition through re-interpretation of unsteady dynamics,
termed time-axis clustering, is developed in this work and is demonstrated on an …
termed time-axis clustering, is developed in this work and is demonstrated on an …
Data-based analysis of multimodal partial cavity shedding dynamics
Time-resolved X-ray densitometry void fraction measurements and accompanying acoustic
emissions have revealed that partial cavity shedding on a hydrofoil can be multimodal, with …
emissions have revealed that partial cavity shedding on a hydrofoil can be multimodal, with …