A Reliability-Based Comparison of EC3 and SANS 10162-1
Bibliographic record
Abstract
Wind and seismic activity effects are described in SANS 10160 (2018) [13]; however, these loading conditions' scope and depth are limited.Typically, South African practicing engineers refer to other international design standards when seeking information that is not described in the current national standards.It is essential to understand that these international standards cannot be used without considering local conditions.In this study the authors compare Eurocode 3 and SANS 10162-1 (the steel standards) using reliability principles to determine if the adoption or adaption of the Eurocode is possible.The reliability analysis presented in this paper assessed the material resistance reliability of a member in bending and a member under axial compression.The resulting reliability indices of the study, from a Monte Carlo Simulation, were compared to their respective target reliability index values.The beam and column ,for their respective steel design standards, achieved minimum reliability index levels, with the column generally resulting in higher reliability indices.The authors also concluded that the SANS 10162-1 standard is usually consistent with European practice, which is confirmed by similar reliability levels.However, the differences in reliability levels show the effect and significance of local differences (e.g., construction methods, design loads, local conditions).Finally, the authors concluded that an adaption of the Eurocode's relevant sections is possible without a need for further calibration.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".