PHAETHON: Software for Analysis of Shear-Critical Reinforced Concrete Columns
Bibliographic record
Abstract
Earthquake collapse of substandard reinforced concrete (RC) buildings, designed and constructed before the development of modern seismic design Codes, has triggered intense efforts by the scientific community for accurate assessment of this building stock. Most of the proposed procedures for the prediction of building strength and deformation indices were validated by assembling databases of RC column specimens tested under axial load and reversed cyclic lateral drift histories. Usually a column structural behavior is assessed by considering all involving mechanisms of behavior, namely flexure with or without the presence of axial load, shear and anchorage. In the present paper a force-based fiber beam/column element was developed accounting for shear and tension stiffening effects in order to provide an analytical test-bed for simulation of experimental cases such as the lightly reinforced columns forced to collapse. Their peculiar characteristics are the outcome of the shear – flexure interaction mechanism modeled here based on the Modified Compression Field Theory (MCFT) and the significant contribution of the tensile reinforcement pullout from its anchorage to the total column’s lateral drift. These features are embedded in this first-proposed stand-alone Windows program named “Phaethon” -with user’s interface written in C++ programming language code- aiming to facilitate engineers in executing analyses both for rectangular and circular substandard RC columns.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.030 | 0.006 |
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".