Energy assessment of an integrated hydrogen production system
Bibliographic record
Abstract
Hydrogen is believed to be the future energy carrier that will reduce environmental pollution and solve the current energy crisis, especially when produced from a renewable energy source. Solar energy is a renewable source that has been commonly utilized in the production process of hydrogen for years because it is inexhaustible, clean, and free. Generally, hydrogen is produced by means of a water splitting process, mainly electrolysis, which requires energy input provided by harvesting solar energy. The proposed model integrates the solar harvesting system into a conventional Rankine cycle, producing electrical and thermal power used in domestic applications, and hydrogen by high temperature electrolysis (HTE) using a solid oxide steam electrolyzer (SOSE). The model is divided into three subsystems: the solar collector(s), the steam cycle, and an electrolysis subsystem, where the performance of each subsystem and their effect on the overall efficiency is evaluated thermodynamically using first and second laws. A parametric study investigating the hydrogen production rate upon varying system operating conditions (e.g. solar flux and area of solar collector) is conducted on both parabolic troughs and heliostat fields as potential solar energy harvesters. Results have shown that, heliostat-based systems were able to attain optimum performance with an overall thermal efficiency of 27% and a hydrogen production rate of 0.411 kg/s, whereas, parabolic trough-based systems attained an overall thermal efficiency of 25.35% and produced 0.332 kg/s of hydrogen.
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 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".