Flexural fatigue behavior of ultra-high performance concrete under low temperatures
Bibliographic record
Abstract
Ultra-high performance concrete (UHPC) shows superior mechanical performance, which leads to increasing applications in infrastructure constructions that are subjected to different loading (i.e., flexure, tension, compression, etc.) and environmental conditions (ambient, freeze, etc.). Among them, the flexural performance of UHPC under low temperatures (i.e., sub-zero temperature) is still little understood especially under fatigue loading. To investigate the flexural fatigue properties of UHPC under low temperatures, eleven UHPC prisms are subjected to cyclic bending at different stress levels from 0.40 to 0.80 (the ratio between applied maximum fatigue stress and static flexural strength) and temperatures of 20 °C, -10 °C, and -20 °C. Results indicate that the fracture interfaces for specimens under static and fatigue loading exhibit distinct differences. No fiber buckling appears for the monotonically-loaded specimens, while for specimens under fatigue loading, fibers buckled and fractured. Low temperature improves the mechanical properties of UHPC under monotonic loading due to enhanced matrix strength. Conversely, low temperature adversely affects the flexural fatigue performance of UHPC due to the cold brittleness nature of matrix and steel fibers, leading to the accumulation of matrix deterioration and the fracture of steel fiber. When the temperature drops from 20 °C to -10 °C and -20 °C, there is a 15.0% and 12.7% decline in the flexural fatigue strength of UHPC, respectively. In addition, low temperature accelerates the degradation of UHPC, resulting in a larger and faster accumulation of fatigue deformation, including tensile strain, mid-span deflection, and fatigue deformation modulus.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".