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Record W2162019883 · doi:10.1109/ccece.2006.277479

Accurate Assessment of Thermal Field and Ampacity of Underground Power Cables

2006· article· en· W2162019883 on OpenAlexaff
M. S. Al-Saud, M. A. El-Kady, R.D. Findlay

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicThermal Analysis in Power Transmission
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAmpacityPower cableSensitivity (control systems)Finite element methodComputationHeat sinkThermalPower (physics)Field (mathematics)Direct-buried cableEngineeringEnvironmental scienceComputer scienceElectrical conductorElectrical engineeringStructural engineeringElectronic engineeringMaterials scienceMathematicsPhysicsMeteorology

Abstract

fetched live from OpenAlex

A newer approach to cable thermal field and ampacity computations using a proposed concept of perturbed finite-element analysis is formulated. This approach involves the use of derived sensitivity coefficients associated with various cable parameters of interest and using such sensitivity coefficients to achieve optimal cable performance. The technique is applied to both design phase and operational aspects of power cable buried in a complex media of soils, heat sources and sinks as well as variable boundary conditions

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.230
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2006
Admission routes1
Has abstractyes

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