Kinetics and Reactor Modeling of a High Temperature Water−Gas Shift Reaction (WGSR) for Hydrogen Production in a Packed Bed Tubular Reactor (PBTR)
Bibliographic record
Abstract
Kinetic, experimental, modeling, and simulation studies of a catalytic high temperature (673−873 K) water−gas shift reaction (WGSR) were performed in a packed bed tubular reactor (PBTR) at several values of W / F A0 (ratio of the mass of the catalyst to the mass flow rate of CO, g (cat) ·h/mol of CO) over a new Ni−Cu/CeO 2 −ZrO 2 (UFR-C) catalyst. Out of the kinetic models evaluated, the one that best predicted the experimental rates was based on the Langmuir−Hinshelwood (LH) formulation, assuming that the rate determining step (RDS) was the surface reaction between molecularly adsorbed carbon monoxide and water to give a formate intermediate and atomically adsorbed hydrogen. Reactor modeling was performed using a comprehensive numerical model consisting of two-dimensional coupled material and energy balance equations. The best mechanistic kinetic model developed was incorporated in the reactor model, which also contained the axial dispersion term, and was solved using the finite elements method. The validity of the reactor model was tested against the experimental data and a satisfactory agreement between the model prediction and measured results were obtained. In addition, the predicted concentration and temperature profiles for our process in both axial and radial direction indicate that the assumption of plug flow isothermal behavior is justified within certain kinetic operating conditions. Moreover, the well-known criteria for neglecting the axial dispersion term have been met in this case and it can conclusively be recommended to be eliminated from the model.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".