Influence of thermal cycling on the cable-joint interfacial pressure
Bibliographic record
Abstract
Cable joints are generally known to be the weak points of underground distribution lines. One of the most common failure modes of premolded cable joints is linked to the occurrence of dielectric breakdown at the interface. Many parameters may influence the dielectric strength of a cable-joint interface: surface roughness, the presence of dielectric grease, and the length of the interface to name a few. Nevertheless, interfacial pressure is known to be a key factor that sets the cable-joint interfacial breakdown strength. AC dielectric breakdown strength is proportional to interfacial pressure up to a threshold pressure. A high interfacial pressure leads to good dielectric breakdown strength whereas a lower pressure leads to a poor long-term performance. Interfacial pressure decreases with the number of thermal cycles. Moreover, partial discharge (PD) monitoring during thermal cycles with thermal gradients in the insulation, following IEEE 404 standard protocol, did reveal a maximum PD intensity at the end of the temperature decrease for each cycle. This could be linked to a decrease in the interfacial pressure. We study the behavior of interfacial pressure when a cable-joint assembly is thermally cycled and identify the worse case for cycles at 75, 90 and 130/spl deg/C with thermal gradients in the bulk of the insulation. The cycling protocol is based on existing IEEE 404 standard for cable joints for use with extruded dielectric cable rated 5-138 kV.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".