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Record W4317568584 · doi:10.2514/6.2023-0171

Validation of a Density Base Navier-Stokes solver simulating the startup deflagration to detonation process of Rotating Detonation Engine (RDE)

2023· article· en· W4317568584 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAIAA SCITECH 2023 Forum · 2023
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsComputational fluid dynamicsSolverDetonationTurbulenceCombustion chamberAerospace engineeringCombustorDeflagrationMechanical engineeringFluentCombustionEngineeringMechanicsComputer sciencePhysicsExplosive materialChemistry

Abstract

fetched live from OpenAlex

View Video Presentation: https://doi.org/10.2514/6.2023-0171.vid Validation of a Density Based Navier-Stokes solver simulating the start-up deflagration to detonation process of Rotating Detonation Engine (RDE) Bruce Crawford Ansys Inc., 2600 Ansys Dr, Canonsburg, PA 15317 USA Ishan Verma Ansys Pune, Vari Tech Park, India Stefano Orsino Ansys Inc., 10 Cavendish Court, Lebanon NH, 03766, USA Jean-Sebastien Cagnone Ansys Canada Ltd., 1000 Sherbrooke Street West, Montreal QC, H3A 3G4 Canada Modeling pressure gain combustion systems, in-particular rotating detonation engines (RDE), has been a growing area of interest in academia and industry for the last decade. The main application for RDEs is in rocket motors and gas-turbine combustors. Following this industry trend, there has been a push to expand the capabilities of the Ansys Fluent CFD solver, especially in its high-speed Density Based Navier-Stokes solver (DBNS), to improve the modeling and design of new RDE systems. High-fidelity CFD simulations can provide invaluable insights into the high-speed flow mixing and combustion processes in a typical RDE combustor. These CFD simulations require physical models that can predict physical phenomena such as compressibility, turbulence, and chemical non-equilibrium. Implementing new enhancements towards chemical non-equilibrium (combustion) and turbulence combustion interaction models has been done to meet the requirement of predictive high-speed reactive flow simulations. The present work shows the validation of the newly implemented capabilities and physical model of Ansys Fluent for RDEs. The computational domain is based on the experiments from AFRL/NETL RDE, and the validation of CFD simulations is done with the experimental results. Three different mesh resolutions using Poly-Hexcore Mosaic mesh topology are evaluated, showing the performance of the RDE modeling. Additionally, the system demonstrates the computationally efficient modeling capabilities offered by the direct source chemistry solver with a global mechanism and various chemistry solvers using detailed chemistry kinetic mechanisms for higher fidelity combustion modeling. The validation cases presented here use the spectrum of turbulence models to validate RDE operating conditions by using realizable k-epsilon, k-omega Shear Stress Transport (SST), and Large Eddy Simulations (LES).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.263
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it