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Record W3157561093 · doi:10.22055/jacm.2021.35491.2665

Two-Dimensional Numerical Study of the Transient Flow Conditions in Complete Shock Tunnel

2021· article· en· W3157561093 on OpenAlexaff
Ali M. Mohsen, Mohd Zamri Yusoff, Hakim S. Sultan Aljibori, Amir Al-Falahi, Abdul Amir H. Kadhum

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2021
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsSheridan College
Fundersnot available
KeywordsMechanicsComputational fluid dynamicsFinite volume methodShock (circulatory)Shock waveExpansion tunnelDiscretizationShock tubeFlow (mathematics)PhysicsMathematicsHypersonic speedMathematical analysis

Abstract

fetched live from OpenAlex

In the current research, an axisymmetric model is developed to study high-speed unsteady flow in the test section of a 7 meter-long shock tunnel. The computational calculations of the shock tunnel are conducted using the Fluent CFD solver. The Finite Volume Method (FVM) is used to discretize the governing equations of mass, momentum, and energy. The accuracy of the numerical model is investigated with first-order upwind, second-order upwind, and third-order MUSCL schemes. Adaptive mesh refinement is implemented to resolve the shock wave and contact surface regions accurately. The numerical results are compared with theoretical calculations and experimental data from experimental tests and the comparison shows good agreement. Different test gases of Helium, Air and CO2, are utilized in the current study. The results show that steady test conditions are maintained for a longer test time by adjusting the pressure ratio and gas combination across the diaphragm. The highest shock wave speed and strength are achieved for a gas combination of Helium-CO2, but a longer test duration is observed when using Air as the test gas.

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.

How this classification was reachedexpand

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.112
GPT teacher head0.455
Teacher spread0.343 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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