Perbaikan dan Proteksi Pondasi Tiang Dermaga Dengan Metode Pile Encapsulation
Bibliographic record
Abstract
Problems encountered in this research is the occurrence of foundation damage pier dock building PT. Reliance Refinery in Gujarat Province of India resulting in dock structure under sub standard condition, unsafe condition and at any time dock structure may experience colapse. The specific point of this problem is the dock building is supported by a 120 cm diameter pile foundation with a height of 14 meters above ground level and over 200 meters towards the Indian Ocean. The purpose of this study is to provide an overview of how the specifications of materials, work equipment and methods of implementing the repair of damaged pier building foundations. Improvement using pile encapsulation method is by cleaning the damaged piling surface with water jeting and mechanical, installing FRP jacketing cover and grouting with underwater material specifications epoxy grout. The improvement results show the epoxy grout and FRP jacket bonding well to the existing piling surface. This repair method is proven to improve the damage of the piling and protect the piling against corrosion, abrasion, scouring and mechanical impact. These improvements have been replicated to address similar problems in Canada, Australia, Singapore and Indonesia.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".