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Record W4317651314 · doi:10.2514/6.2023-2528

Validation of the Density Based Navier-Stokes solver simulating the combustion process of different Scramjets combustors

2023· article· en· W4317651314 on OpenAlex
Bruce G. Crawford, Jayson C. Small, Liwei Zhang, Shaoping Li, Valerio Viti, Jean-Sébastian Cagnone

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
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsnot available
Fundersnot available
KeywordsScramjetCombustorAerospace engineeringPropulsionRamjetComputational fluid dynamicsCombustionSolverAerodynamicsTurbulenceSupersonic speedMechanical engineeringComputer scienceEngineeringMechanicsPhysicsChemistry

Abstract

fetched live from OpenAlex

View Video Presentation: https://doi.org/10.2514/6.2023-2528.vid Validation of the Density-Based Navier-Stokes solver simulating the combustion process of different scramjet combustors Bruce Crawford Ansys Inc., 2600 Ansys Dr, Canonsburg, PA 15317 USA Jayson Small , Liwei Zhang Aerodynamics Research Center, The University of Texas at Arlington, Arlington, TX 76019, USA Valerio Viti , Shaoping Li Ansys Inc., 10 Cavendish Court, Lebanon NH, 03766, USA Jean-Sebastien Cagnone Ansys Canada Ltd., 1000 Sherbrooke Street West, Montreal QC, H3A 3G4 Canada With the recent rise in interest in new hypersonic propulsion systems, there has been a push to expand Ansys Fluent CFD high-speed Density-Based Navier-Stokes (DBNS) solver capabilities to model these complex systems. The goal of the improvement is to be able to simulate the combustion process inside scramjet engines with a high level of accuracy and in a streamlined and efficient way . High-fidelity numerical simulations can provide invaluable insights on the high-speed flow mixing and combustion processes of scramjet motors as well as detailed temperature and heat flux distribution through the vehicle propulsion system. In order to achieve the desired fidelity, these numerical simulations need to include physical models that can predict phenomena such as compressibility, turbulence, and chemical non-equilibrium. Several new and enhanced chemical non-equilibrium and turbulence-combustion interaction models have been introduced to meet the need for improved accuracy by the community. The current work presents three validation studies of scramjet combustion cases. The three cases selected are representative of different combustor configurations and fuels and they are: the Burrows-Kurkov combustor, the DLR supersonic combustor, and the NASA HIFiRE 2 Scramjet combustor. Each of the three geometries is meshed using Ansys meshing tools, creating 2D, 3D hexahedral, and 3D Fluent Poly-Hexcore Mosaic meshes. Four combustion models available in Ansys Fluent CFD high-speed solver are validated for each of the validation studies. Three of these combustion models considered are typically used for laminar chemistry solution, nominally the React to Equilibrium (RTE), Direct source method (DSM), and Stiff Chemistry (ODE) solvers. The fourth combustion model is typically used for cases with turbulence/combustion interaction (TCI), and that is the Eddy Dissipation Concept (EDC) PaSR model. All validation cases presented use the K-Omega SST turbulence model to simulate the flow turbulence.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.026
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.230
Teacher spread0.221 · 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