Theoretical investigation of hydrogen-rich fuel production through ammonia decomposition
Bibliographic record
Abstract
Abstract Considering the challenges related to hydrogen storage and transportation which hinder its widespread adoption, ammonia has emerged as a carbon-free carrier for hydrogen due to several advantages such as simple inexpensive storage. But, due to some limitations related to net ammonia combustion, the suggestion is to store hydrogen in the form of ammonia and convert it into hydrogen-rich fuel before utilization in different applications like engines and turbines. Therefore, in this article, a comprehensive thermodynamic analysis of hydrogen-rich fuel production via ammonia decomposition is conducted utilizing Aspen Plus V.12, to assess the impact of operating parameters on key criteria such as conversion rate (CR) and enthalpy of reaction, to establish the maximum level of efficiency of the process. The results show that at a specific temperature, the CR of ammonia decreases as the pressure rises so that the CR of more than 50% occurred at temperatures of 427 and 513 K for pressures of 1 and 10 bar, respectively. Moreover, the adiabatic flame temperature of hydrogen-rich fuel is investigated so that increasing the molar percentage of hydrogen from 0 to 50 leads to an increase in the maximum adiabatic flame temperature from 2,079 to 2,216 K.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".