Reliability basis for assessment of existing building structures with reference to sans 10160
Bibliographic record
Abstract
The principles of structural reliability are firmly established to provide the basis for structural performance as incorporated in design standards. Reliability-based procedures provide for variabilities and uncertainties that could reasonably be expected during the design service life of the structure. However, not all possible conditions to which all structures are exposed during such an extended service period can be accounted for effectively and economically at the design stage. The assessment of the reliability performance of an existing structure therefore forms an integral part of structural management and engineering practice. Despite the lag between the development and implementation of a basis for design and assessment of structures, the extensive body of information on structural assessment progresses steadily towards standardisation. This paper provides a review of the progress to provide background information towards extending the scope of South African structural standards to include guidance on structural assessment. The focus is on such developments to include provisions for existing structures in Eurocode, together with related investigations. In addition to a general review of background investigations, interrelationships between the basis of design and assessment for Eurocode (potentially also for South Africa) are considered. The main elements of a standardised basis for assessment are defined, and alternative assessment approaches are presented and demonstrated by representative examples. In conclusion, an outline of a possible development path for implementation in South Africa is provided.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".