Design and analysis of an integrated renewable hydrogen production and storage system for hydrogen refueling station in a sustainable community
Bibliographic record
Abstract
This research designs a conceptual system where both solar and biomass energy subsystems are uniquely integrated to turn wastewater into useful outputs, such as hydrogen, fresh water and heat to achieve sustainable communities where renewable energy is utilized with the wastewater treated effectively. The system integrates several subsystems, including a reheat Rankine cycle, an organic Rankine cycle, a multi-stage flash desalination system, and a biohydrogen production unit employing a microbial electrolysis process. In order to study a potential application of this conceptually developed system, the city of Oshawa in Ontario, Canada is identified with its wastewater treatment facility which is designed to produce clean biohydrogen that is liquefied and stored for distribution to refueling stations for hydrogen-based transportation. In this regard, thermodynamic analysis and assessment studies are conducted using the Engineering Equation Solver and demonstrating that the system achieves the overall energetic and exergetic efficiencies of 34.94% and 32.84%, respectively. Furthermore, the system produces freshwater at a rate of 5.36 kg/s and biohydrogen at 0.03 kg/s, contributing to environmental sustainability and efficient resource utilization in addition to the heat recovered and used in the community as a useful output. This research highlights the potential of the system to significantly reduce greenhouse gas emissions while promoting sustainable energy and transportation developments in Oshawa and similar regions.
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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 | 0.001 | 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) | 0.002 | 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".