Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions | Paper Citation Record

Observation 4ff44100-23fa-4862-8b5c-a66da91c07e2 · outbound

This paper cites Analysis of Development Trends for Rotating Detonation Engines Based on Experimental Studies.Aerospace, 11(7):570, July 2024.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Analysis of Development Trends for Rotating Detonation Engines Based on Experimental Studies.Aerospace, 11(7):570, July 2024

Reference 1

Resolution: malformed identifier; raw_fallback, observed 2026-05-19T13:23:07.186863Z

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Observation 6c8aba90-edde-4d30-b45f-bcff4013597d · outbound

This paper cites Detonative propulsion.Proceedings of the Combustion Institute, 34(1):125–158.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Detonative propulsion.Proceedings of the Combustion Institute, 34(1):125–158

Reference 2

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.894181Z

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Observation 8617f634-9b8c-4208-86d3-a5481d315590 · outbound

This paper cites Heister, John Smallwood, Alexis Harroun, Kevin Dille, Ariana Martinez, and Nathan Ballintyn.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Heister, John Smallwood, Alexis Harroun, Kevin Dille, Ariana Martinez, and Nathan Ballintyn

Reference 3

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.916211Z

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Observation 24520f8f-0434-44a7-8290-a030cd53f8be · outbound

This paper cites Braun, Frank K.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Braun, Frank K

Reference 4

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.882537Z

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Observation 929a3f13-34bf-4bd7-afb6-db50c35008de · outbound

This paper cites an unresolved cited work.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Unresolved cited work

Reference 5

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.919234Z

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Observation be2afa08-af62-4c61-af45-89143de9405e · outbound

This paper cites Nonidealities in Rotating Detonation Engines.Annual Review of Fluid Mechanics, 55(V olume 55, 2023):639–674, January 2023.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Nonidealities in Rotating Detonation Engines.Annual Review of Fluid Mechanics, 55(V olume 55, 2023):639–674, January 2023

Reference 6

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.878484Z

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Observation 8f34213a-efc0-4089-88b1-d834b4535da0 · outbound

This paper cites Space Flight Demonstration of Rotating Detonation Engine Using Sounding Rocket S-520-31.Journal of Spacecraft and Rockets, 60(1):273–285, January 2023.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Space Flight Demonstration of Rotating Detonation Engine Using Sounding Rocket S-520-31.Journal of Spacecraft and Rockets, 60(1):273–285, January 2023

Reference 7

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.941835Z

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Observation 1f92fd0a-0aca-4955-8c61-8c68cec78211 · outbound

This paper cites Development of Gasturbine with Detonation Chamber.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Development of Gasturbine with Detonation Chamber

Reference 8

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.968211Z

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Observation 479cc330-850c-4af2-9801-cc9d6e7fa29b · outbound

This paper cites Thermodynamic analysis of a gas turbine engine with a rotating detonation combustor.Applied Energy, 195:247–256, June 2017.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Thermodynamic analysis of a gas turbine engine with a rotating detonation combustor.Applied Energy, 195:247–256, June 2017

Reference 9

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.886795Z

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Observation 5b890b82-4077-4fa0-82cc-eee454a1deed · outbound

This paper cites The feasibility of mode control in rotating detonation engine.Applied Thermal Engineering, 129:1538–1550, January 2018.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions The feasibility of mode control in rotating detonation engine.Applied Thermal Engineering, 129:1538–1550, January 2018

Reference 10

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.897881Z

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Observation 969efa63-d4af-4020-82f4-15d368f35207 · outbound

This paper cites an unresolved cited work.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Unresolved cited work

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:45:19.964969Z

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Observation 9035d2b6-86c9-47f0-8ab5-1e77aff43b12 · outbound

This paper cites An active direction control method in rotating detonation combustor.International Journal of Hydrogen Energy, 47(55):23427–23443, June 2022.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions An active direction control method in rotating detonation combustor.International Journal of Hydrogen Energy, 47(55):23427–23443, June 2022

Reference 12

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.912910Z

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Observation 695551f4-3edb-4a61-9bb4-36707cf50d7b · outbound

This paper cites Investigation of counter-rotating shock wave and wave direction control of hollow rotating detonation engine with Laval nozzle.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Investigation of counter-rotating shock wave and wave direction control of hollow rotating detonation engine with Laval nozzle

Reference 13

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.095522Z

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Observation ed3a6b5a-0578-401c-9a6d-ab371b211140 · outbound

This paper cites A review on deep reinforcement learning for fluid mechanics.Computers & Fluids, 225:104973, July 2021.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions A review on deep reinforcement learning for fluid mechanics.Computers & Fluids, 225:104973, July 2021

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:45:20.117879Z

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Observation 7e0249b3-16cd-41f0-a4e5-b0b888b14b32 · outbound

This paper cites Vignon, J.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Vignon, J

Reference 15

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.131424Z

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Observation 5ed78784-a9b3-471e-8128-ca7badbb46de · outbound

This paper cites an unresolved cited work.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Unresolved cited work

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:45:20.077354Z

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Observation ad5563e1-12ed-4cc9-a382-830f00bf8989 · outbound

This paper cites Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow control.Journal of Fluid Mechanics, 865:281–302, April 2019.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow control.Journal of Fluid Mechanics, 865:281–302, April 2019

Reference 17

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.088954Z

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Observation 34f92314-f28f-4f45-8b5b-941bd35c3a7b · outbound

This paper cites Robust active flow control over a range of Reynolds numbers using an artificial neural network trained through deep reinforcement learning.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Robust active flow control over a range of Reynolds numbers using an artificial neural network trained through deep reinforcement learning

Reference 18

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.101573Z

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Observation 68310305-f335-4fa5-8880-ca19179bb5fd · outbound

This paper cites Applying deep reinforcement learning to active flow control in weakly turbulent conditions.Physics of Fluids, 33(3):037121, March 2021.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Applying deep reinforcement learning to active flow control in weakly turbulent conditions.Physics of Fluids, 33(3):037121, March 2021

Reference 19

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.134707Z

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Observation bc1fd802-256a-42e9-acec-74bdb1618513 · outbound

This paper cites an unresolved cited work.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Unresolved cited work

Reference 20

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.084588Z

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Observation 6843bbe5-cc70-43bb-80cd-67d533fed8b8 · outbound

This paper cites an unresolved cited work.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-05-19T13:23:07.160226Z

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Observation 57053986-80c7-43ee-8ca5-6c3b784d56e5 · outbound

This paper cites doi: 10.1063/5.0171188.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions doi: 10.1063/5.0171188

Reference 22

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.153866Z

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Observation a8c4b7ca-4016-4826-92bd-9a6a04d6ea78 · outbound

This paper cites Active flow control of square cylinder adaptive to wind direction using deep reinforcement learning.Physical Review Fluids, 9(9):094607, September 2024.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Active flow control of square cylinder adaptive to wind direction using deep reinforcement learning.Physical Review Fluids, 9(9):094607, September 2024

Reference 23

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.124486Z

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Observation 1b70b323-b429-441f-82d8-0e026fd0dcbb · outbound

This paper cites Active Flow Control for Drag Reduction Through Multi-agent Reinforcement Learning on a Turbulent Cylinder at $$Re_D=3900$$.Flow, Turbulence and Combustion, March 2025.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Active Flow Control for Drag Reduction Through Multi-agent Reinforcement Learning on a Turbulent Cylinder at $$Re_D=3900$$.Flow, Turbulence and Combustion, March 2025

Reference 24

Resolution: malformed identifier; raw_fallback, observed 2026-05-19T13:23:07.163871Z

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Observation 051fce1f-551d-4480-b288-e908ad9fb221 · outbound

This paper cites Deep reinforcement learning for turbulent drag reduction in channel flows.The European Physical Journal E, 46(4):27, April 2023.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Deep reinforcement learning for turbulent drag reduction in channel flows.The European Physical Journal E, 46(4):27, April 2023

Reference 25

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.127864Z

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correction dated 2023-06-29. Source: crossref record 10.1140/epje/s10189-023-00304-8->10.1140/epje/s10189-023-00285-8:correction, observed 2026-07-11T03:01:38.904603+00:00. This notice travels one citation hop only.

Observation 3a0283d1-1250-43fd-8d8f-15a67c36d393 · outbound

This paper cites Reinforcement learning of control strategies for reducing skin friction drag in a fully developed turbulent channel flow.Journal of Fluid Mechanics, 960:A30, April 2023.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Reinforcement learning of control strategies for reducing skin friction drag in a fully developed turbulent channel flow.Journal of Fluid Mechanics, 960:A30, April 2023

Reference 26

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.987452Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 28ff1a54-3231-4308-9589-f475d45ee988 · outbound

This paper cites Reinforcement-learning-based control of turbulent channel flows at high Reynolds numbers.Journal of Fluid Mechanics, 1006:A12, March 2025.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Reinforcement-learning-based control of turbulent channel flows at high Reynolds numbers.Journal of Fluid Mechanics, 1006:A12, March 2025

Reference 27

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.979842Z

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Observation 9aacd036-f2df-4cd8-b5e5-79a8fdf20d22 · outbound

This paper cites Deep reinforcement learning for active flow control in a turbulent separation bubble.Nature Communications, 16(1):1422, February.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Deep reinforcement learning for active flow control in a turbulent separation bubble.Nature Communications, 16(1):1422, February

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T13:23:07.168025Z

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Observation d8cd4886-fb65-4592-a32f-a56ab6b00c01 · outbound

This paper cites doi: 10.1038/s41467-025-56408-6.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions doi: 10.1038/s41467-025-56408-6

Reference 29

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.996774Z

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correction dated 2025-04-24. Source: crossref record 10.1038/s41467-025-57534-x->10.1038/s41467-025-56408-6:correction, observed 2026-07-11T02:59:09.107198+00:00. This notice travels one citation hop only.

Observation 495ec82b-dd87-412b-b875-769603df2db3 · outbound

This paper cites Controlling Rayleigh–Bénard convection via reinforcement learning.Journal of Turbulence, 21(9-10):585–605, October 2020.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Controlling Rayleigh–Bénard convection via reinforcement learning.Journal of Turbulence, 21(9-10):585–605, October 2020

Reference 30

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T11:45:20.006329Z

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Observation 3875485e-dd88-4968-b52c-f50bc10c320a · outbound

This paper cites an unresolved cited work.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Unresolved cited work

Reference 31

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.011195Z

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Observation 79bbcd5a-0f81-4a51-bedf-af112f3292ba · outbound

This paper cites Effective control of two-dimensional Rayleigh–Bénard convection: Invariant multi-agent reinforcement learning is all you need.Physics of Fluids, 35(6):065146, June 2023.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Effective control of two-dimensional Rayleigh–Bénard convection: Invariant multi-agent reinforcement learning is all you need.Physics of Fluids, 35(6):065146, June 2023

Reference 32

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.976181Z

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Observation 12d3df83-1d38-439f-9a84-d8a671d7086e · outbound

This paper cites Multi-agent Reinforcement Learning for the Control of Three-Dimensional Rayleigh–Bénard Convection.Flow, Turbulence and Combustion, 115(3):1319–1355, September 2025.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Multi-agent Reinforcement Learning for the Control of Three-Dimensional Rayleigh–Bénard Convection.Flow, Turbulence and Combustion, 115(3):1319–1355, September 2025

Reference 33

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.023522Z

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Observation 13addb9d-8536-4c92-bf7f-3c525a0a9fe5 · outbound

This paper cites meMIA: Multilevel Ensemble Membership Inference Attack.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions meMIA: Multilevel Ensemble Membership Inference Attack

Reference 34

Resolution: malformed identifier; doi_truncated, observed 2026-05-10T11:45:19.990929Z

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Observation a4693543-7b1d-4717-8694-605bcd4abeb0 · outbound

This paper cites Navigation in a simplified urban flow through deep rein- forcement learning.Journal of Computational Physics, 538:114194, October 2025.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Navigation in a simplified urban flow through deep rein- forcement learning.Journal of Computational Physics, 538:114194, October 2025

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:45:20.017783Z

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Observation ea8c41cb-8ee8-4d43-a6ce-580f2f9d6ee4 · outbound

This paper cites A Reinforcement Learning Approach for Transient Control of Liquid Rocket Engines.IEEE Transactions on Aerospace and Electronic Systems, 57(5):2938–2952, October 2021.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions A Reinforcement Learning Approach for Transient Control of Liquid Rocket Engines.IEEE Transactions on Aerospace and Electronic Systems, 57(5):2938–2952, October 2021

Reference 36

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.071649Z

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Observation 1a078b31-d2e3-4673-90d0-78eb142c14a1 · outbound

This paper cites Deep reinforcement learning-based active flow control for a tall building.Physics of Fluids, 37(4):045132, April 2025.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Deep reinforcement learning-based active flow control for a tall building.Physics of Fluids, 37(4):045132, April 2025

Reference 37

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.971718Z

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Observation ffdd47d1-ba40-4c3e-8c5a-a47eb1f767aa · outbound

This paper cites Intelligent control of structural vibrations based on deep reinforcement learning.Journal of Infrastructure Intelligence and Resilience, 4(2):100136, June 2025.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Intelligent control of structural vibrations based on deep reinforcement learning.Journal of Infrastructure Intelligence and Resilience, 4(2):100136, June 2025

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:45:19.947276Z

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Observation 265b4a7d-c1e7-4499-a512-f3ce6aa1dc1d · outbound

This paper cites Flow Control in Wings and Discovery of Novel Approaches via Deep Reinforcement Learning.Fluids, 7(2):62, February 2022.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Flow Control in Wings and Discovery of Novel Approaches via Deep Reinforcement Learning.Fluids, 7(2):62, February 2022

Reference 39

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.901574Z

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Observation ac766d22-fef8-47e5-9ed7-4aa3dd25a3f4 · outbound

This paper cites Deep reinforcement learning based synthetic jet control on disturbed flow over airfoil.Physics of Fluids, 34(3):033606, March 2022.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Deep reinforcement learning based synthetic jet control on disturbed flow over airfoil.Physics of Fluids, 34(3):033606, March 2022

Reference 40

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.955352Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1c857e06-e48e-44a8-94c4-c278b440d8e6 · outbound

This paper cites Renn and Morteza Gharib.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Renn and Morteza Gharib

Reference 41

Resolution: malformed identifier; raw_fallback, observed 2026-05-19T13:23:07.151849Z

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Observation 96753b4c-4787-4b57-8f67-2e0dcd5cb9b0 · outbound

This paper cites Deep-reinforcement-learning-based separation control in a two-dimensional airfoil.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Deep-reinforcement-learning-based separation control in a two-dimensional airfoil

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:45:19.960150Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0db0b128-1e41-4cbd-9d99-1d037f8ef635 · outbound

This paper cites Robust flow control and optimal sensor placement using deep reinforcement learning.Journal of Fluid Mechanics, 913:A25, April 2021.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Robust flow control and optimal sensor placement using deep reinforcement learning.Journal of Fluid Mechanics, 913:A25, April 2021

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:45:19.929089Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 74637c04-7ba7-4a9f-90ea-9c02009c7d3f · outbound

This paper cites an unresolved cited work.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Unresolved cited work

Reference 44

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.951131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 95ef0c01-624a-4597-9208-b9918261af15 · outbound

This paper cites Triantafyllou, and George Em Karniadakis.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Triantafyllou, and George Em Karniadakis

Reference 45

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.890209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 66582868-61ad-4b48-b722-a8b41c8e2305 · outbound

This paper cites an unresolved cited work.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Unresolved cited work

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:45:19.934734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 348e33b3-1fd2-41f6-adde-da3bcbb14b1b · outbound

This paper cites Accelerating deep reinforcement learning strategies of flow control through a multi-environment approach.Physics of Fluids, 31(9):094105, September 2019.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Accelerating deep reinforcement learning strategies of flow control through a multi-environment approach.Physics of Fluids, 31(9):094105, September 2019

Reference 47

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.909082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 65c545bb-ef27-4767-a3e7-835083f3c56c · outbound

This paper cites The Journal of Chemical Physics 132(21), 214102 (2010).

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions The Journal of Chemical Physics 132(21), 214102 (2010)

Reference 48

Resolution: malformed identifier; doi_truncated, observed 2026-05-10T11:45:19.904906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 90676edf-146a-4c5a-992e-9abb27a40a5b · outbound

This paper cites an unresolved cited work.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Unresolved cited work

Reference 49

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.922868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b268b52e-5f46-4691-a723-545e77d734d8 · outbound

This paper cites Closed-loop supersonic flow control with a high-speed experimental deep reinforcement learning framework.Journal of Fluid Mechanics, 1009:A3, April 2025.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Closed-loop supersonic flow control with a high-speed experimental deep reinforcement learning framework.Journal of Fluid Mechanics, 1009:A3, April 2025

Reference 50

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.938088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e88e73c1-58e8-4f03-ad47-3344c4ddabf6 · outbound

This paper cites Deep reinforcement learning control of supersonic cavity flow using a pulsed-arc plasma actuator matrix.Journal of Fluid Mechanics, 1029:A38, February.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Deep reinforcement learning control of supersonic cavity flow using a pulsed-arc plasma actuator matrix.Journal of Fluid Mechanics, 1029:A38, February

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T13:23:07.156291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6bd05603-9490-442a-8e11-b8d2ee093813 · outbound

This paper cites doi: 10.1017/jfm.2026.11212.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions doi: 10.1017/jfm.2026.11212

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:45:20.146836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 82ccc652-4799-4948-8c18-e756b138816b · outbound

This paper cites Nathan Kutz.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Nathan Kutz

Reference 53

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.141443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 001868f4-e592-476e-8255-c3a1538c87f5 · outbound

This paper cites Towards the ultimate conservative difference scheme III.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Towards the ultimate conservative difference scheme III

Reference 54

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.150383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7158c94c-b515-4d20-9ba5-d0b70a3929cd · outbound

This paper cites Efficient implementation of essentially non-oscillatory shock-capturing schemes.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Efficient implementation of essentially non-oscillatory shock-capturing schemes

Reference 55

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.108133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 279b39e0-e735-468c-b8e8-43b728e12287 · outbound

This paper cites doi:10.5334/jors.151 , urldate =.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions doi:10.5334/jors.151 , urldate =

Reference 56

Resolution: metadata mismatch; doi, observed 2026-05-10T11:45:20.105215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2bdc0d4e-03ca-4c8e-8e9e-05dd9d826cba · outbound

This paper cites Bezanson , author A.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Bezanson , author A

Reference 57

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.138373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9a0a89ec-de30-4a29-bbe3-2ad3223b2842 · outbound

This paper cites an unresolved cited work.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Unresolved cited work

Reference 58

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.098578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 627aff99-ad9c-4704-9fdc-98517a7d8075 · outbound

This paper cites Nathan Kutz.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Nathan Kutz

Reference 59

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.081475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1c605c3e-67b6-4311-ae24-75f41356f5b2 · outbound

This paper cites Rotating Detonation Wave Propulsion: Experimental Challenges, Modeling, and Engine Concepts (Invited).

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Rotating Detonation Wave Propulsion: Experimental Challenges, Modeling, and Engine Concepts (Invited)

Reference 60

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.121115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4d9c0e2e-fc82-40a2-8360-7b6f7fa5323d · outbound

This paper cites an unresolved cited work.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Unresolved cited work

Reference 61

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.092490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0811cb7d-4156-4da8-b710-5ef18e1de152 · outbound

This paper cites Sutton and Andrew G.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Sutton and Andrew G

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T13:23:07.180645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e809d062-83ad-42a1-a653-97781b93e47a · outbound

This paper cites Proximal Policy Optimization Algorithms.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Proximal Policy Optimization Algorithms

Reference 63

Resolution: metadata mismatch; local_arxiv, observed 2026-05-10T11:45:20.112573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ae609ac6-d3a5-465d-bf44-f0bfed4901cc · outbound

This paper cites A Survey of Temporal Credit Assignment in Deep Reinforcement Learning.Transactions on Machine Learning Research, December 2023.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions A Survey of Temporal Credit Assignment in Deep Reinforcement Learning.Transactions on Machine Learning Research, December 2023

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T13:23:07.174536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2cb2ff76-3f51-42f0-a098-36d0fe547b8e · outbound

This paper cites Bridging RL Theory and Practice with the Effective Horizon.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Bridging RL Theory and Practice with the Effective Horizon

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T13:23:07.177791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 81a617f7-2089-47fa-b02e-31ec6690771f · outbound

This paper cites Stable- Baselines3: Reliable Reinforcement Learning Implementations.Journal of Machine Learning Research, 22(268): 1–8.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Stable- Baselines3: Reliable Reinforcement Learning Implementations.Journal of Machine Learning Research, 22(268): 1–8

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T13:23:07.183702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a2d6e138-48a6-4e7a-aa18-e05ffd9963a9 · outbound

This paper cites Privacy-preserving and uncertainty-aware federated trajectory prediction for connected autonomous vehicles.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Privacy-preserving and uncertainty-aware federated trajectory prediction for connected autonomous vehicles

Reference 67

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T11:45:20.067630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 11e4b941-553a-4ca1-9a8c-c99b804125df · outbound

This paper cites Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T13:23:07.171325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6266d45e-d287-4c07-b4c7-a7f9da98ff1f · outbound

This paper cites Sutton, Doina Precup, and Satinder Singh.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Sutton, Doina Precup, and Satinder Singh

Reference 69

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.054215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c3f2fdf9-afb9-4ec9-80de-9d7da7ff816b · outbound

This paper cites Invariant control strategies for active flow control using graph neural networks.Computers & Fluids, 303:106854, December 2025.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Invariant control strategies for active flow control using graph neural networks.Computers & Fluids, 303:106854, December 2025

Reference 70

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:45:20.060837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a4dd0ef5-2ab5-4427-8672-bb1ff2f97767 · outbound

This paper cites Nathan Kutz.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions Nathan Kutz

Reference 71

Resolution: verified exact; doi, observed 2026-05-10T11:45:19.983724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c0c60eb4-0203-4b97-914e-0f7c707c7168 · outbound

This paper cites DRL_RDE_data.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions DRL_RDE_data

Reference 72

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.031410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3730464f-6ec4-4f04-8408-5615839b632c · outbound

This paper cites KristianHolme/DRL_RDE_paper_code.

Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions KristianHolme/DRL_RDE_paper_code

Reference 73

Resolution: verified exact; doi, observed 2026-05-10T11:45:20.026977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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