A Study of Ice Accretion Shape on Cables Under Freezing Rain Conditions
Bibliographic record
Abstract
The influence of atmospheric conditions (specifically precipitation rate and external heat flux) on the freezing rain ice accretion forming on a non-rotating, horizontal cylinder is studied, using an analytical model based on a simple form of the equations for conservation of mass and heat balance. In keeping with the freezing rain application, but in order to simplify this first step, we have assumed vertical incidence of precipitation (no wind) and no dripping from the accretion (hence light to moderate precipitation rates with relatively low air temperatures). The initial ice accretion shape and the location of its center of mass are examined as a function of the ratio of the precipitation mass flux to the total heat flux lost from the ice surface. An increase in the flux ratio leads to a quantifiable downward displacement of the accretion center of mass. We complement this analysis with numerical simulations, using an improved, two-dimensional version of the Szilder-Lozowski morphogenetic model that predicts the evolution of the accretion shape. For the first time, the freezing probability, which is the critical model parameter, is expressed as a function of location and atmospheric conditions for an accretion shape evolving with time. Using the morphogenetic model, we examine the influence of atmospheric conditions on the accretion shape and ice load. In particular, we address the question of what gives rise to extreme ice loads by identifying the range of atmospheric conditions that tends to maximize (or minimize) the ice load for a given amount of precipitation. The results of this research are applicable to predicting ice formation on overhead transmission lines.
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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 | 0.001 |
| 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) | 0.000 | 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".