Safety of Nuclear Reactors: Part B — Unsteady State Strength Mathematical Model
Bibliographic record
Abstract
The significant mechanical properties that determine the strength of concrete-filled square steel columns are compressive strength, modulus of elasticity, ultimate strain of the concrete, yield strength and modulus of elasticity of the steel. A survey of the literature shows that the variation of these properties with temperature is influenced by many factors. The compressive strength of concrete at elevated temperature is affected by the rate and duration of heating, the size and shape of the test specimen and the loading during the heating. During exposure to fire the strength of the column decreases with the duration of exposure. The strength of the column can be calculated by a method based on load-deflection analysis which in turn is based on a stress-strain analysis of cross-sections. A mathematical model describing the behavior of concrete-filled square steel column structures under load and heat has been thoroughly examined in this paper. The main goals of this model are to study the structure member characteristics (temperature, deformation and strength) under excessive heat conditions and to study the possibility of increasing the endurance time by changing the column composite structure.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".