Quasi-Two-Dimensional Numerical Model for Shock Wave Reformers
Bibliographic record
Abstract
Abstract The article details a numerical investigation of methane pyrolysis inside a shock wave reformer using a quasi-2-dimensional (Q2D) Reynolds-Averaged Navier-Stokes (RANS) CFD model. This work is in support of the New Wave Hydrogen, Inc. (NWH2) proprietary technology development. To take account of the characteristics of the flow in the presence of shock waves, a simplified approach is proposed that captures the gas dynamics during partial opening with a lower computational cost suitable for the wave reformer design. The model is based on the three-dimensional, compressible, and unsteady Navier-Stokes equation coupled with k-ω - SST turbulence closure. Boundary conditions are implemented through a cell-centered approach with fictitious cells outside of the domain boundaries. The numerical results are compared with solutions from a quasi-one-dimensional (Q1D) unsteady model reported in literature. The simulations show a good agreement between the two different modelling approaches in terms of spatial distribution of the pressure gradient for one complete cycle. It is observed from the Q2D results that the entrance for each passage, especially upon opening of the high-pressure driver gas port, is a location of particular interest in the formation of the shock. The resulting acute pressure gradients induce loss inside the channel, decreasing the maximum temperature during a complete wave cycle by 15%, and consequently, reducing the methane pyrolysis process.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".