EPRI Soils Research Program
Bibliographic record
Abstract
The maximum ampacity of underground circuits is determined by two thermal limiting conditions: thermal aging of the electrical insulation, and the thermal limitations of backfill material to maintain good heat transfer properties. To improve the ampacity of cable, research must be undertaken in two distinct areas: to improve thermal properties of dielectric materials, and improve the thermal stability of back- fill. This latter area is being addressed under the EPRI soils research program. Increased safe loading criteria by increased confidence in soil thermal behavior and accurate measurement techniques should be a benefit from the program. Advanced instrumentation research is being conducted by Ontario Hydro. The objectives are to characterize soil thermal stability, develop in-situ measurement equipment for determining thermal resistivity (p) thermal diffusivity (D) and stability and to gather historical weather data that will reduce cable operation safety limits. Improvement in thermal stability of backfill is being pursued through research on chemical additives at the University of California. Two types of additives were investigated: water absorbing compounds and those that are substitutes for retaining water between soil particles. Another objective of this project is to develop analytical methods for computing temperature and moisture distribution around buried cable in two or three dimensions.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.121 | 0.053 |
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".