Strength Reduction Method for the Assessment of Existing Large Reinforced Concrete Structures
Bibliographic record
Abstract
This work presents a new developed assessment methodology based on strength reduction and finite element methods which is suitable for existing large reinforced concrete structures commonly used in hydraulic constructions. The methodology is based on a reloading phase of the finite element model and is preceded by an intermediate reduction phase of concrete tensile strength and an initial loading phase up to service level. Rosenblueth’s point estimate method was used to compute a global resistance factor and to deduce a design resistance value of the structure. After validations, the methodology was applied to two existing complex and large hydraulic structures: a spiral case and a draft tube. If compared with existing methodologies using sophisticated non-linear finite element methods, the developed approach is simpler, more practical, and provides results that are on the conservative side. Considering the difficulties in characterizing the tensile peak and post-peak strength of concrete, along with uncertainties regarding the damage conditions of facilities, the developed methodology is deemed robust and well suited for assessing existing critical large reinforced concrete infrastructures.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".