Appraisal of Reciprocal Load Method for Reinforced Concrete Columns of Normal and High Strength Concrete
Bibliographic record
Abstract
Use of the reciprocal load method for evaluating the capacity of reinforced concrete (RC) columns under axial load and biaxial bending is suggested in concrete design handbooks and in commentaries to the design codes. The reciprocal load method interpolates such a capacity from the interaction diagrams obtained for the uniaxial bending cases. The adequacy of the reciprocal load method for short reinforced concrete columns of normal strength concrete has been verified in the literature. It is noted that the validity of this method for reinforced concrete columns of high strength concrete is rarely discussed, and that the characteristic of the stress–strain relation of normal strength concrete differs from that of high strength concrete. A numerical assessment of the adequacy of the reciprocal load method for short RC columns of normal and high strength concrete was presented in this study. Also, the possibility of using the reciprocal load method for slender reinforced concrete columns was investigated. The assessment was carried out by comparing the predicted capacities obtained using the reciprocal load method and those obtained by solving several nonlinear coupled governing equations that are established based on statics and considering the nonlinear stress–strain relations of concrete and steel.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".