Influence of elevated temperature on the engineering properties of ultra-high-performance fiber-reinforced concrete
Bibliographic record
Abstract
Abstract This paper investigates the effect of high temperatures on the compressive strength, flexural strength, and splitting tensile strength of ultra-high-performance concrete (UHPC), and ultra-high-performance, fiber-reinforced concrete (UHPFRC). The experimental variables in this study were fiber type, fiber content, and high-temperature exposure levels. Three different types of fibers were evaluated, including steel fibers, polypropylene (PP), and polyvinyl alcohol (PVA) fibers. Six concrete mixes were prepared with and without different combinations of fibers. One mix was made with no fibers. Others were made with either steel fibers alone; a hybrid of steel fibers and PVA; and a hybrid system of steel, PP, and PVA fibers. These mixes were tested under a range of temperatures and compared for strength. The UHPC and UHPFRC were exposed to high temperatures at 100°C, 300°C, 400°C, and 500°C for 3 hours. The results showed that UHPFRC did not exhibit any significant degradation when exposed to 100°C. However, reductions of approximately 18% to 25%, 12% to 22%, and 14% to 25% in the compressive strength, splitting tensile strength, and flexural strength were observed when the UHPFRC was exposed to 400°C. UHPFRC made of steel fibers showed higher mechanical properties after exposure to 400°C compared to UHPFRC made of PP and PVA fibers. The results also demonstrate the use of PVA and/or PP fibers, along with steel fiber, to withstand the effects of highly elevated temperature and prevent spalling of UHPC after exposure to elevated temperature. The observed spalling was a direct result of the melting and evaporation of PVA and/or PP fibers when exposed to high temperature, an effect that was confirmed using scanning electron microscopy.
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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 | 0.000 |
| 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) | 0.001 | 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".