Performance Investigation of Flat Plate and Evacuated Tube Collectors under Jordan Climate Conditions Using TRNSYS Software
Bibliographic record
Abstract
The performance of the Flat Plate Collector (FPC) and Evacuated Tube Collector (ETC) for domestic hot water applications under Jordan climate conditions was theoretically investigated using TRNSYS software. The presented simulation model can provide a long-term evaluation of system performance at different weather conditions. This simulation was carried out during 24 hours in 21 June, is considered as a hot climate and 21 January is considered as a cold climate; under the meteorological conditions of both Irbid and Aqaba cities in Jordan. The inlet water temperature of the first collector, collector area, water flow rate and tilt angle were considered 15℃, 2.04 m2, 0.0139 kg/s and 45 degrees respectively. The outlet temperature of each collector was considered as the inlet of the previous collector. Three collectors in series were applied to increase the output temperature up to 90-100℃. The results showed that TE increased with the decrease in the inlet temperature, which means the useful energy gain (Qu) of the first collector is greater than the 2nd and the 3rdcollector. The useful energy gain (Qu) of ETC is greater than of FPC, and the useful energy gain (Qu) of cold climate is less than hot climate. The output temperature of ETCs is greater than that of FPCs for Irbid city in cold and hot climate. Furthermore, for Aqaba in cold climate and in hot climate the outlet temperature of ETCs is higher than FPCs. Additionally, the daily thermal performance of the ETCs is significantly better than the FPCs in cold climate. Meanwhile, thermal performance of both collectors are close in a hot climate.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.001 |
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".