Application of FDM heat transfer model to study the reinforced concrete in thermal aspects
Bibliographic record
Abstract
Fiber-reinforced polymer (FRP) reinforced concrete are made by combining a plastic polymer resin together with strong fibers reinforced with concrete. This materials are commonly used in building structure. One of main safety requirements in structural is the fire protection requirements. It is important to understand the behavior of FRP reinforced concrete when the temperature increase (20–250°C) and high (>250 °C) are challenging and important. Severe degradation and bond properties will be effected when the temperature increase. Therefore, in order to understand the structural behavior, the thermal response of FRP reinforced concrete under elevated and high temperature needs be understood and predicted. In this study, Finite Difference Method (FDM) will be used to solve the heat transfer model to study the behavior of FRP composite in thermal aspects. The numerical algorithm of FDM heat transfer model will be constructed and used to analyze the heat thermal response of FRP composite. The temperature result obtained by the numerical method will be validated with data test.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".