Perhitungan Beban Refrigerasi Terhadap Hasil Tangkapan Pada Km. Harapan Sri Jaya Juwana, Pati, Jawa Tengah
Bibliographic record
Abstract
Beban refrigerasi pada ruang pembekuan dan ruang palkah di KM. Harapan Sri Jaya terdiri dari beban produk dan beban non produk. Pada ruang pembekuan, beban kalor yang harus ditanggung berasal dari beban produk, beban infiltrasi dan beban transmisi. Pada ruang palkah beban kalor yang harus ditanggung berasal dari beban infiltrasi, beban transmisi dan beban internal. Beban keseluruhan yang harus ditanggung oleh ruang pembekuan dan ruang palkah adalah penjumlahan dari beban di ruang pembekuan dan ruang palkah. Besarnya beban tersebut adalah 56 kW. Faktor keamanan dalam perhitungan beban kalor adalah sebesar 15% sehingga besarnya beban kalor yang ada di ruang pembekuan dan ruang palkah adalah sebesar 56 kW + ( 15 % x 8,92 kW ) = 56 kW + 8,92 kW = 68.4 kW. Diketahui total beban kalor refrigerasi adalah sebesar 68,4 kW dan daya kompresor yang penulis ketahui pada spesifikasi yaitu 29,84 kW jika 3 kompresor dinyalakan secara bersamaan maka akan menghasilkan daya (29,84 kW x 3 = 89,52 kW). Dengan demikian dapat diketahui masing – masing kompresor menerima beban kalor sebesar 22,84 kW dimana (68,4 kW : 3 kompresor = 22,84 kW). Maka persentase dari perbandingan beban kalor refrigerasi terhadap daya motor penggerak kompresor adalah 76 %.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.092 | 0.015 |
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".