Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion | Paper Citation Record

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This paper cites Introduction to combustion, volume 287.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Introduction to combustion, volume 287

Reference 1

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This paper cites Combustion.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Combustion

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This paper cites Theoretical and numerical combustion.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Theoretical and numerical combustion

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This paper cites Combustion.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Combustion

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This paper cites Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

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This paper cites Physics-informed machine learning.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Physics-informed machine learning

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This paper cites Scientific machine learning through physics–informed neu- ral networks: Where we are and what’s next.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Scientific machine learning through physics–informed neu- ral networks: Where we are and what’s next

Reference 7

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This paper cites A physics-informed deep convolutional neural network for simulating and predicting transient darcy flows in heterogeneous reservoirs without labeled data.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion A physics-informed deep convolutional neural network for simulating and predicting transient darcy flows in heterogeneous reservoirs without labeled data

Reference 8

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Observation ca5dd97a-bff9-42c1-a6c2-cc49e30a55ef · outbound

This paper cites Physics informed integral neural network for dynamic modelling of solvent-based post-combustion co2 capture process.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Physics informed integral neural network for dynamic modelling of solvent-based post-combustion co2 capture process

Reference 9

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This paper cites Model predictive control of diesel engine emissions based on neural network modeling.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Model predictive control of diesel engine emissions based on neural network modeling

Reference 10

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Observation aa3d7699-3239-4955-ae69-a3fc94123e5b · outbound

This paper cites Crk-pinn: A physics-informed neural net- work for solving combustion reaction kinetics ordinary differential equations.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Crk-pinn: A physics-informed neural net- work for solving combustion reaction kinetics ordinary differential equations

Reference 11

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This paper cites Exploring surface reaction mech- anism using a surface reaction neural network framework.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Exploring surface reaction mech- anism using a surface reaction neural network framework

Reference 12

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Observation a13c04db-07f4-4c6c-9e9d-788173a014d1 · outbound

This paper cites Ppinn: Parareal physics-informed neural network for time-dependent pdes.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Ppinn: Parareal physics-informed neural network for time-dependent pdes

Reference 13

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Observation 4a0f9031-99b5-4dd4-a1e7-8b421f062999 · outbound

This paper cites An adaptive sampling method based on expected improvement function and residual gradient in pinns.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion An adaptive sampling method based on expected improvement function and residual gradient in pinns

Reference 14

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Observation 025a4ab2-c439-4a45-ab1d-06e6f3c8e2ae · outbound

This paper cites Physics-informed neural net- works for turbulent combustion: Toward extracting more statistics and closure from point multiscalar measurements.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Physics-informed neural net- works for turbulent combustion: Toward extracting more statistics and closure from point multiscalar measurements

Reference 15

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This paper cites Physics-informed neural network for solving a one-dimensional solid mechanics problem.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Physics-informed neural network for solving a one-dimensional solid mechanics problem

Reference 16

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Observation f58280c0-6235-4852-b4ca-61a6a5151854 · outbound

This paper cites Physics-informed neural network solver for numerical analysis in geoengineering.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Physics-informed neural network solver for numerical analysis in geoengineering

Reference 17

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This paper cites Understanding physics-informed neural networks: techniques, applications, trends, and challenges.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Understanding physics-informed neural networks: techniques, applications, trends, and challenges

Reference 18

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This paper cites Finite volume method network for the acceleration of unsteady computational fluid dynamics: Non-reacting and reacting flows.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Finite volume method network for the acceleration of unsteady computational fluid dynamics: Non-reacting and reacting flows

Reference 19

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This paper cites Flamepinn-1d: Physics-informed neural networks to solve forward and inverse problems of 1d laminar flames.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Flamepinn-1d: Physics-informed neural networks to solve forward and inverse problems of 1d laminar flames

Reference 20

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Observation 917b7cda-b5ff-4874-8336-d1685a721ad3 · outbound

This paper cites Exploring Physics-Informed Neural Networks: From Fundamentals to Applications in Complex Systems.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Exploring Physics-Informed Neural Networks: From Fundamentals to Applications in Complex Systems

Reference 21

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Observation 18597b0c-4a8e-4ff5-b7bb-ef0989d8ce0d · outbound

This paper cites On the Generalization of PINNs outside the training domain and the Hyperparameters influencing it.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion On the Generalization of PINNs outside the training domain and the Hyperparameters influencing it

Reference 22

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Observation b6b8a128-b3dc-4207-b5ae-343694b6ba82 · outbound

This paper cites Exploring physics-informed neural networks for the generalized nonlinear sine-gordon equation.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Exploring physics-informed neural networks for the generalized nonlinear sine-gordon equation

Reference 23

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Observation 7ea40232-e09f-489c-a364-17587b4f42df · outbound

This paper cites Generalization of PINNs for various boundary and initial conditions.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Generalization of PINNs for various boundary and initial conditions

Reference 24

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Observation 86c2264d-b5ae-4233-9807-90594debccd2 · outbound

This paper cites Estimates on the generalization error of physics-informed neural networks for approximating pdes.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Estimates on the generalization error of physics-informed neural networks for approximating pdes

Reference 25

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This paper cites Physics- informed neural networks for inverse problems in supersonic flows.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Physics- informed neural networks for inverse problems in supersonic flows

Reference 26

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This paper cites The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks

Reference 27

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This paper cites Investigating and Mitigating Failure Modes in Physics-informed Neural Networks (PINNs).

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Investigating and Mitigating Failure Modes in Physics-informed Neural Networks (PINNs)

Reference 28

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Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Approximation of Large Stiff Acausal Models

Reference 29

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Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Tackling the curse of dimensionality with physics-informed neural networks

Reference 30

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This paper cites On the importance of the mathematical formulation to get pinns working.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion On the importance of the mathematical formulation to get pinns working

Reference 31

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Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Locally adaptive ac- tivation functions with slope recovery for deep and physics-informed neural networks

Reference 32

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Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Auto-PINN: Understanding and Optimizing Physics-Informed Neural Architecture

Reference 33

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This paper cites Separable physics-informed neural networks.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Separable physics-informed neural networks

Reference 34

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This paper cites Robust Regression with Highly Corrupted Data via Physics Informed Neural Networks.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Robust Regression with Highly Corrupted Data via Physics Informed Neural Networks

Reference 35

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Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Physics-informed neural networks with unknown measurement noise

Reference 36

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This paper cites On the Preprocessing of Physics-informed Neural Networks: How to Better Utilize Data in Fluid Mechanics.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion On the Preprocessing of Physics-informed Neural Networks: How to Better Utilize Data in Fluid Mechanics

Reference 37

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Observation eb848fe0-81b5-44ba-bab0-95bca5842bc2 · outbound

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Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Cleaner combustion

Reference 38

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Observation 5813fd88-0362-4415-b1ed-1230383214db · outbound

This paper cites What fuel properties enable higher thermal eﬀiciency in spark- ignited engines? Progress in Energy and Combustion Science , 82:100876, 2021.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion What fuel properties enable higher thermal eﬀiciency in spark- ignited engines? Progress in Energy and Combustion Science , 82:100876, 2021

Reference 39

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This paper cites On the effects of adding syngas to an ammonia-mild combustion regime—a computational study of the reaction zone structure.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion On the effects of adding syngas to an ammonia-mild combustion regime—a computational study of the reaction zone structure

Reference 40

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Observation 234d12eb-8b5e-469d-a9de-f462d3526452 · outbound

This paper cites A comprehensive investigation of acoustic power level in a moderate or intense low oxygen dilution in a jet-in-hot-coflow under various working conditions.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion A comprehensive investigation of acoustic power level in a moderate or intense low oxygen dilution in a jet-in-hot-coflow under various working conditions

Reference 41

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Observation 32e609b4-f986-44ad-92a4-075607377e6c · outbound

This paper cites On the effects of nh3 addition to a reacting mixture of h2/ch4 under mild combustion regime: Numerical modeling with a modified edc combus- tion model.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion On the effects of nh3 addition to a reacting mixture of h2/ch4 under mild combustion regime: Numerical modeling with a modified edc combus- tion model

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.459617Z

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Observation 6251a638-521d-456d-975e-0aca4fb47ce8 · outbound

This paper cites Sustainable energy transition for renewable and low carbon grid electricity generation and supply.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Sustainable energy transition for renewable and low carbon grid electricity generation and supply

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.446483Z

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Observation 3008405b-a92c-495e-b48d-5696581e9f0a · outbound

This paper cites Fuels of the Future for Renewable Energy Sources (Ammonia, Biofuels, Hydrogen).

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Fuels of the Future for Renewable Energy Sources (Ammonia, Biofuels, Hydrogen)

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-08-04T21:21:41.445911Z

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Observation 0a23fef7-6676-4d51-a517-aac9477bfa38 · outbound

This paper cites A review on alternative fuels in future energy system.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion A review on alternative fuels in future energy system

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.433947Z

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Observation ce1d4df2-1a07-47fb-ac96-6cc1ea254351 · outbound

This paper cites Impact of hydrogen on the environment.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Impact of hydrogen on the environment

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.421135Z

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Observation 43853430-3483-4d27-8657-368d87fe5f0a · outbound

This paper cites Hydrogen combustion, production, and applications: A review.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Hydrogen combustion, production, and applications: A review

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.408043Z

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Observation da362f7e-df64-4eb9-95f0-6fa61ccf8c1f · outbound

This paper cites Low nox-lpg staged combustion double swirl flames.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Low nox-lpg staged combustion double swirl flames

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.394777Z

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Observation 8a9b1eae-6b7d-4e62-8dd4-e72e6d67dd84 · outbound

This paper cites On the effects of fractal geometry on reacting and nonreacting flows in a low- swirl burner: A numerical study with large-eddy simulation.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion On the effects of fractal geometry on reacting and nonreacting flows in a low- swirl burner: A numerical study with large-eddy simulation

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.381878Z

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Observation f66f420d-43e5-4161-ad00-6b980e46d711 · outbound

This paper cites Moderate or intense low-oxygen dilution combustion of methane diluted by co2 and n2.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Moderate or intense low-oxygen dilution combustion of methane diluted by co2 and n2

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.368256Z

Source-reported events for the cited work

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Observation 7a52536f-59b0-4bcf-ae81-a8598e6bbee9 · outbound

This paper cites Ammonia combustion and emissions in practical applications: a review.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Ammonia combustion and emissions in practical applications: a review

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.353967Z

Source-reported events for the cited work

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Observation 71c0a6a8-612f-4772-b53d-634a432c4b67 · outbound

This paper cites Ammonia combustion in furnaces: A review.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Ammonia combustion in furnaces: A review

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.341682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0c0cc619-b560-4ec3-8e34-2ef6216988c5 · outbound

This paper cites Science and technology of ammonia combustion.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Science and technology of ammonia combustion

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.328745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 941e2167-a2dc-43a4-af77-80d712e0f16b · outbound

This paper cites A review on ammonia blends combustion for industrial applications.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion A review on ammonia blends combustion for industrial applications

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.315274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e155564a-5799-4c5f-b5af-0a9d36a91c1a · outbound

This paper cites Green synthetic fuels: Renewable routes for the conversion of non-fossil feedstocks into gaseous fuels and their end uses.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Green synthetic fuels: Renewable routes for the conversion of non-fossil feedstocks into gaseous fuels and their end uses

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.302327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 68152a00-84a1-429c-bc0b-023eac47a80e · outbound

This paper cites Biofuels an alternative to traditional fossil fuels: A comprehensive review.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Biofuels an alternative to traditional fossil fuels: A comprehensive review

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.289067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6e7d7b29-ef45-42e4-832b-e77adb996dc4 · outbound

This paper cites Biofuels: An alternative to conventional fuel and energy source.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Biofuels: An alternative to conventional fuel and energy source

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.274967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3ce84889-fbfb-4ff5-ae73-5876635a392f · outbound

This paper cites The feasibility of synthetic fuels in renewable energy systems.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion The feasibility of synthetic fuels in renewable energy systems

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.261525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3c521827-5b61-456a-bfb5-733f76a087da · outbound

This paper cites Fossil fuels and alternative fuels.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Fossil fuels and alternative fuels

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.248723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ded6b25e-347e-4e18-bcfb-9064abb0edeb · outbound

This paper cites Oxy-fuel combustion technology: current status, applications, and trends.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Oxy-fuel combustion technology: current status, applications, and trends

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.235380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 19a346db-fc8b-4816-929f-ee48a2bf5b48 · outbound

This paper cites Oxy-fuel combustion of solid fuels.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Oxy-fuel combustion of solid fuels

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.223005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d0c67437-cc45-41cc-97e2-89c8881a72a9 · outbound

This paper cites Oxy-fuel coal combustion—a review of the current state-of-the-art.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Oxy-fuel coal combustion—a review of the current state-of-the-art

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.209539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5b55973b-51f9-43a5-b726-a782f6cf07c8 · outbound

This paper cites Oxyfuel combustion for clean energy applications.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Oxyfuel combustion for clean energy applications

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.195941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 981df9f1-34c0-4ddc-925d-abe6e8b6c6c2 · outbound

This paper cites Technological, economic, and emission analysis of the oxy-combustion process.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Technological, economic, and emission analysis of the oxy-combustion process

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.182948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d876b51e-e835-4f6d-a680-025e075176ac · outbound

This paper cites Flame stretch effects on partially premixed flames.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Flame stretch effects on partially premixed flames

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.170947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f61f56c6-db8f-4906-bb4f-c4582a23a391 · outbound

This paper cites Flame dynamics.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Flame dynamics

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.158013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4fe8994c-ab1d-4f6a-ba0c-a722fe45f603 · outbound

This paper cites Large eddy simulation of the effects of radiative heat loss on combustion instability prediction.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Large eddy simulation of the effects of radiative heat loss on combustion instability prediction

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.145049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation adfdad1f-c438-428a-8731-2fe0cff8e5d1 · outbound

This paper cites Turbulent flows.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Turbulent flows

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.118936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3ac2ea68-300d-4692-b739-949dfdd35801 · outbound

This paper cites A pinn-deeponet framework for extracting turbulent combustion closure from multiscalar measurements.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion A pinn-deeponet framework for extracting turbulent combustion closure from multiscalar measurements

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.106725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0be61313-e112-415f-9d12-98e375c71835 · outbound

This paper cites Learning thermoa- coustic interactions in combustors using a physics-informed neural network.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Learning thermoa- coustic interactions in combustors using a physics-informed neural network

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.094309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 89cdcc10-20a9-406c-b70b-106c734defd1 · outbound

This paper cites Predicting bifurcation and amplitude death characteristics of thermoacoustic instabilities from pinns-derived van der pol oscillators.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Predicting bifurcation and amplitude death characteristics of thermoacoustic instabilities from pinns-derived van der pol oscillators

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.081116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 329202cd-6458-4fd6-95f1-bb8a049a8739 · outbound

This paper cites Efficient nonlinear flame response modeling for propulsion thermoacoustic analysis using limited numerical data.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Efficient nonlinear flame response modeling for propulsion thermoacoustic analysis using limited numerical data

Reference 73

Resolution: verified exact; local_arxiv, observed 2026-08-04T21:21:41.417407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 962dc3a4-579c-4e42-b842-1d1ec3f49c1c · outbound

This paper cites Physics-Informed Deep Learning to Reduce the Bias in Joint Prediction of Nitrogen Oxides.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Physics-Informed Deep Learning to Reduce the Bias in Joint Prediction of Nitrogen Oxides

Reference 74

Resolution: verified exact; local_arxiv, observed 2026-08-04T21:21:41.388557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 15f1c058-3ea1-4a2e-b6fd-8c0ee66ebbeb · outbound

This paper cites Physics-based deep learning reveals rising heating demand heightens air pollution in Norwegian cities.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Physics-based deep learning reveals rising heating demand heightens air pollution in Norwegian cities

Reference 75

Resolution: verified exact; local_arxiv, observed 2026-08-04T21:21:41.360959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cf5cfd21-7311-47fc-8fa5-7fd1dd3cc79a · outbound

This paper cites A physics-informed neural net- work that considers monotonic relationships for predicting nox emissions from coal-fired boilers.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion A physics-informed neural net- work that considers monotonic relationships for predicting nox emissions from coal-fired boilers

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.067547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e990a7ca-76e9-4294-b7de-9010bdb213a8 · outbound

This paper cites Reconstructing soot fields in acoustically forced laminar sooting flames using physics-informed machine learn- ing models.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Reconstructing soot fields in acoustically forced laminar sooting flames using physics-informed machine learn- ing models

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.055140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation aff9b60b-156d-4c50-9848-3eb53393d276 · outbound

This paper cites Soot temperature and volume fraction field predictions via line-of-sight soot integral radiation equation informed neural networks in laminar sooting flames.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Soot temperature and volume fraction field predictions via line-of-sight soot integral radiation equation informed neural networks in laminar sooting flames

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.042701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 31139aaf-ae12-4b9d-9328-6f0dbedac02f · outbound

This paper cites Accelerating the Chemical Kinetics Calculations in Combustion Simulations Using Physics Informed Neural Networks.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Accelerating the Chemical Kinetics Calculations in Combustion Simulations Using Physics Informed Neural Networks

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.030362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f3dd1db6-db32-4b9c-87ce-bab95a0ef6de · outbound

This paper cites Co+ oh→ co 2+ h: The relative reaction rate of five co isotopologues.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Co+ oh→ co 2+ h: The relative reaction rate of five co isotopologues

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.017476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d0feee4c-2ed3-4364-a3f5-1d01707c7a32 · outbound

This paper cites Instability behaviors and suppression of the unsteady autoignited turbulent jet flame in hot coflow.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Instability behaviors and suppression of the unsteady autoignited turbulent jet flame in hot coflow

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.004736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c94740f9-6318-4f92-8704-6389ceff99e6 · outbound

This paper cites Heat release rate responses in self-excited thermoacoustic instabilities of tangential swirling non-premixed flames.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Heat release rate responses in self-excited thermoacoustic instabilities of tangential swirling non-premixed flames

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:43.991648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ec8c2780-96c4-4417-bb03-04e4adbaf78d · outbound

This paper cites Combustion driven oscillations in gas turbines.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Combustion driven oscillations in gas turbines

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:43.977869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f150dad0-1ec8-45e8-8f3d-551e0e4c07be · outbound

This paper cites Machine learning for thermoacoustics.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Machine learning for thermoacoustics

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:43.965662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation de217de3-a59e-4f0d-bb6d-0d695877df6c · outbound

This paper cites Flame dynamics and unsteady heat release rate of self-excited azimuthal modes in an annular combustor.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Flame dynamics and unsteady heat release rate of self-excited azimuthal modes in an annular combustor

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:43.952037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation dbdb6e03-6189-4780-bfc0-e3fd7baf5e5b · outbound

This paper cites Experimental investigation on the route to vortex-acoustic lock-in phenomenon in bluff body stabilized combustors.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Experimental investigation on the route to vortex-acoustic lock-in phenomenon in bluff body stabilized combustors

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:43.938382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 59f5bf49-e056-4a16-964d-6f003fd69344 · outbound

This paper cites an unresolved cited work.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Unresolved cited work

Reference 87

Resolution: unresolved; raw_fallback, observed 2026-08-04T21:21:43.924771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bd9d1047-d512-41f2-8854-4b11d81be87d · outbound

This paper cites Experimental investigation of high- frequency combustion instabilities in liquid rocket engine.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Experimental investigation of high- frequency combustion instabilities in liquid rocket engine

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:43.911779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6c80c093-e282-4e94-8c37-145ae87ec81a · outbound

This paper cites Surrogate modeling for bayesian inverse problems based on physics-informed neural networks.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Surrogate modeling for bayesian inverse problems based on physics-informed neural networks

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:43.898478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 492c1bba-5d2c-42c2-943d-c23bf600148b · outbound

This paper cites Neural network pid control for combustion instability.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Neural network pid control for combustion instability

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:43.883773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation aa947542-8a1d-4861-a0b3-60e6e4f636b4 · outbound

This paper cites Conservative physics- informed neural networks on discrete domains for conservation laws: Applications to forward and inverse problems.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Conservative physics- informed neural networks on discrete domains for conservation laws: Applications to forward and inverse problems

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:43.869800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation aec831e2-6981-49ff-a3a2-5b911dacd3b3 · outbound

This paper cites Assimilation of experimental data to create a quantitatively accurate reduced-order thermoacoustic model.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Assimilation of experimental data to create a quantitatively accurate reduced-order thermoacoustic model

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:43.767127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c6632520-3537-4130-bb28-a83ed55d9677 · outbound

This paper cites Generating a physics-based quantitatively- accurate model of an electrically-heated rijke tube with bayesian inference.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Generating a physics-based quantitatively- accurate model of an electrically-heated rijke tube with bayesian inference

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:43.572238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9e9450dc-15fb-4780-8943-20e60c7b96f0 · outbound

This paper cites Premixed ammonia/hydrogen swirl combustion under rich fuel conditions for gas turbines operation.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Premixed ammonia/hydrogen swirl combustion under rich fuel conditions for gas turbines operation

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:43.425797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c9ecf042-370a-43a3-b187-5e6c1e23e5be · outbound

This paper cites A physics-informed neural network based simulation tool for reacting flow with multicomponent reactants.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion A physics-informed neural network based simulation tool for reacting flow with multicomponent reactants

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:43.282271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0580eb1d-1048-4479-8866-33f19a54ad2e · outbound

This paper cites The application of physics-informed machine learning in multiphysics modeling in chemical engineering.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion The application of physics-informed machine learning in multiphysics modeling in chemical engineering

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:43.190876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f9e3faed-62db-4f95-9181-95832dd1b112 · outbound

This paper cites Phelan, and Paolo Barucca.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Phelan, and Paolo Barucca

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:43.039456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 30dce071-f130-4088-b8c0-3a58186606fb · outbound

This paper cites Mpc-guided, data-driven fuzzy controller synthesis.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Mpc-guided, data-driven fuzzy controller synthesis

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:42.881434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 39ff1c24-f51c-4f39-a010-038a7f04a586 · outbound

This paper cites From pinns to pikans: Re- cent advances in physics-informed machine learning.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion From pinns to pikans: Re- cent advances in physics-informed machine learning

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:42.728414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0a785a8e-cc19-4345-8756-bc83f9fc2cef · outbound

This paper cites Physics-informed neural networks coupled with flamelet/progress variable model for solv- ing combustion physics considering detailed reaction mechanism.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Physics-informed neural networks coupled with flamelet/progress variable model for solv- ing combustion physics considering detailed reaction mechanism

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T21:21:44.131697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7fa4f484-ae4c-4608-8770-eff641b85874 · outbound

This paper cites Reduced-PINN: An Integration-Based Physics-Informed Neural Networks for Stiff ODEs.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Reduced-PINN: An Integration-Based Physics-Informed Neural Networks for Stiff ODEs

Reference 101

Resolution: verified exact; local_arxiv, observed 2026-08-04T21:21:41.340020Z

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