System-Based Safety Tenets Applied to the Extra-High Voltage Transmission Line Design for Common Uses of Highway Right-of-Way
Bibliographic record
Abstract
The rapidly increasing demand for electricity in recent years resulted in increasing needs of electrical system capacity and deployment for alternate uses of highway right-of-way (ROW) for the purpose of electric power generation, transmission, and distribution. In this framework, a systems approach—fundamental principles of system dynamics for identifying, understanding, and analyzing safety requirements of the extra-high voltage power line (EHV)—is used to objectively focus on two main safety issues related to the design and the risk of the EHV transmission line within highway ROW: (1) assess the design and the operation, and (2) evaluate causally related impacts on the public and workers’ safety that matter. A generalized model of the electromagnetic fields distribution and the clearance model are developed for the analysis of the causally related impacts of a conceptual design and the reliability of materials of construction of the electric systems by introducing the number of exposed individuals and the level of the environmental impacts as a second dimension in addition to the risk factors. A worst-case design scenario is evaluated. Sensitivity analysis of effects of the design attributes such as the route configuration, over voltages, and conductor clearance is performed by determining the magnitude of the electromagnetic field strengths and predicting the resulting maximum voltage. Information obtained on the structural design scenario, conductor size and configuration, insulators, and connectors is of value in determining the safety of the design for operation at extra-high voltages within highway ROW.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".