Consideration of the state of corrosion in seismic assessment of columns
Bibliographic record
Abstract
Purpose Seismic assessment procedures of RC members quantify member strength, deformation capacity and failure mode using detailed information regarding member geometry and reinforcement amount and arrangement. However, the condition of the reinforcing materials is not explicitly accounted for in the calculation process. The paper aims to discuss this issue. Design/methodology/approach This problem is explored in the present paper through consistent evaluation of the evidence from a database of column tests which were subjected to cyclic lateral load reversals simulating earthquake effects after being subjected to accelerated corrosion. The column performance expressed in terms of the shear vs drift resistance envelope is introduced in the available methodologies of rapid assessment of reinforced concrete structures showcasing the limitations and uncertainties of the existing state of the art in the field of seismic assessment of existing structures. Findings Simple estimations as well as experimental observation show that the effect can be staggering, in terms of reduced deformation capacity, prevailing mode of failure and residual strength under seismic loading. It has been observed in the field that deterioration and ageing can reduce a well detailed structural component to behave as a poorly constructed one, by means of cover delamination, transverse and longitudinal bar area loss and steel embrittlement. Originality/value The amount of deterioration in the residual life of the component, in the face of a future seismic hazard, is fraught with uncertainty regarding the amount and intensity of material deprecation and the manner in which this may be considered in the logistics of the assessment process.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".