Simulation of a Two-Stage Micro Trickle-Bed Hydrotreating Reactor using Athabasca Bitumen-Derived Heavy Gas Oil over Commercial NiMo/Al <sub>2</sub> O <sub>3</sub> Catalyst: Effect of H <sub>2</sub> S on Hydrodesulfurization and Hydrodenitrogenation
Bibliographic record
Abstract
A two-stage, micro trickle-bed reactor (for studies of the effects of hydrogen sulfide on hydrodesulfurization (HDS) and hydrodenitrogenation (HDN) of Athabasca bitumen-derived heavy gas oil over commercial NiMo/Al2O3 catalyst) has been simulated. One dimensional homogeneous mass transfer and a two dimensional heat transfer models were developed. The essence of the simulation was to enhance the understanding of the effects of hydrogen sulfide in the hydrotreating catalyst bed in a two-stage mode and also to predict the catalyst requirements for deep HDS and HDN processes. The kinetic model used in the simulation was based on the Langmuir-Hingshelwood method of rate determination. Adsorption constants were estimated by non-linear least squares method. The kinetic models were tested on independent set of data and found to predict the experimental data satisfactorily. The mass transfer simulation considered the effects of variables such as temperature and catalyst loading or liquid hourly space velocity (LHSV) on the trends of hydrogen sulfide generation and, sulfur and nitrogen conversions along the catalyst bed. The model was numerically solved using a fourth-order Runge-Kutta technique. The 1:3 wt/wt catalyst loading with inter-stage hydrogen sulfide removal was found to give the best HDN and HDS activities. Simulated results showed that doubling the present catalyst mass and operating at 653 °C with inter-stage hydrogen sulfide removal would give 6 and 179 ppm product sulfur and nitrogen, respectively. On the other hand, without hydrogen sulfide removal, only 49 and 302 ppm product sulfur and nitrogen could be attained, respectively. The heat transfer simulation compared temperature profiles in the two-stage process to a single stage process for the 1:3 wt/wt catalyst loading at 653 K. The temperature regime in Stage II was found to be more uniform unlike Stage I and the single stage. Crank Nicholson algorithm was used to solve the 2-D partial differential equations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".