Fatigue Life Estimation Model for Plain Concrete Under Uniaxial Stress Reversal Loading
Bibliographic record
Abstract
ABSTRACT The fatigue life of plain concrete under uniaxial stress reversal loading conditions has been scarcely addressed in the literature. Predicting the fatigue life of plain concrete under different stress reversal loading conditions provides valuable insight during the design phase of any major project. After combining the fatigue test results of 40 years of experimental data into one comprehensive database, a simple model is proposed in this study to estimate the shape and scale parameters of a two‐parameter Weibull distribution that appropriately describes the fatigue life of concrete in uniaxial stress reversal. The model was developed considering 201 experimental data points and uses only the maximum stress level as an input, simplifying its application and use. The model's validity is checked against experimental data available in the literature. The comparison shows a good agreement between the results, showing a mean absolute percentage error below 12% for all stress levels. A methodology is also presented to modify the model based on the number of available experimental tests. This is particularly useful for cases where the safety level is paramount and a more conservative result is desired. The efficacy of the proposed adjustment is tested against experimental data not used for model development. The results indicate the method's capability to yield conservative fatigue life estimations with reasonable efficacy.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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".