Bibliographic record
Abstract
Reducing environmental and health impacts of using fossil fuel are the main concerns in the majority of countries which resulted in shifting from the use of fossil fuels (e.g., coal, oil, natural gas) to renewable energy (e.g., solar, wind, water) for electricity generation. The use of renewable energy sources is becoming more popular in the majority of Middle Eastern countries, particularly in Oman. In Oman, the use of renewable energy to produce electricity is rapidly growing considering that renewable energy will reduce the use of fossil fuel as the major source of energy. Hydropower is an important renewable energy resource globally. However, the feasibly of a hydropower plant in Oman has not been investigated. Therefore, the purpose of this project was to determine the feasibility of hydropower which can be installed in the Wadi Dayqah dam in Oman. The objectives are to explore the potential power to be harvested by hydropower, to assess financial saving and cost analysis and to investigate the environmental impact of hydropower in Oman. \n \nThe RETScreen expert was used to assess the feasibility of a hydropower system and to recommend the possibility of installing the system in the Wadi Dayqah Dam in Oman. The RETScreen expert is a Clean Energy Management Software developed by the Government of Canada which is a free-of-charge decision support software for pre-feasibility or feasibility analysis and also ongoing energy efficiency performance analysis. \n \nIn this project, two cases have been analysed. For the case one (the design flow was 0.3 m3/s, and installed capacity was 110 kW), the RETScreen analysis showed estimated cost 338,000 AUD, annual savings and revenue 57,165 AUD and Gross Annual GHG reduction 605.3 tCO2/year. For the case two (the design flow was 13 m3/s, and installed capacity was 5 MW), the RETScreen analysis demonstrated the estimated cost 6,204,000 AUD, annual savings and revenue 1,802,747 AUD and Gross Annual GHG reduction 19,090.1 tCO2/year. \n \nOverall, this project indicated that the use of the hydropower system in the Wadi Dayqah Dam in Oman is viable regarding technical, economic, and environmental aspects.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.010 | 0.001 |
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".