Parametric Damage of Concrete under High-Cycle Fatigue Loading in Compression
Bibliographic record
Abstract
Concrete elements degrade due to the continuous application of compressive fatigue loads.The irreversible deformation or induced compressive strains evolve; hence, the progressive stress redistribution between concrete and embedded steel reinforcing bars should be accounted for in fatigue analysis of concrete structures.Experimental investigations were conducted to study the behavior of four small-scale reinforced concrete deep beams with shear-span to effective-depth ratio of 1.25.The principal compressive strain evolutions from the beam struts were obtained from the strain transformation analysis of LVDT data, and compared with the predicted principal strain evolutions.Each predicted strain evolution was obtained by substituting the initial strut compressive stress estimated from the static analysis of the fatigue load into a strain evolution model from the literature.The comparison between the measured compressive strain evolution from the experiments and the predicted strain evolutions indicated that the design approach in the literature is overly conservative for concrete.However, this is generally attributed to the neglect of the contribution of the tensile strength of concrete in fatigue resistance.The strut-and tie method was used for the fatigue resistance verification of deep beams by modifying the constitutive models and effectiveness factor of concrete with fatigue damage models.The irreversible compressive strain is considered as a pseudo-load, and the progressive crack growth of steel reinforcement resulting from the evolving stresses is accounted for using an equivalent cycle concept with the Paris crack growth model.Within the developed algorithm, failure will occur when one of the evolving stresses in either the concrete strut or steel reinforcement approaches the corresponding residual strength.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| 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".