Bibliographic record
Abstract
The reliability of reinforced concrete elements and design iceberg impact loads for offshore structures were studied. The reliability program RELAN was used to perform FORM reliability analysis for reinforced beams subjected to bending, and for a reinforced concrete wall from the Hibernia offshore structure subjected to complex loading. RELAN was also used to establish the probabilistic distribution of ice impact loads. To study the reliability of concrete beams accounting for the variability of the intervening variables, and in order to determine the theoretical flexural capacity of concrete beam, computer program TIN was developed. TIN uses a strain compatibility approach accounting for the non-linear stress-strain relationships of concrete and reinforcing steel. As a pilot study on the reliability of concrete elements, a beam designed according to the Canadian concrete code was analyzed with the objective of evaluating the effect of different spans and reinforcing steel ratios on the reliability of the beam. To study the reliability of more complex elements, an element from the icewall of the Hibernia offshore structure was used. The theoretical strength of the wall element was evaluated with program SHELL474. In order to link SHELL474 to RELAN for the reliability study, the main subroutine in SHELL474 was modified. Since one of the major factors in reliability studies of concrete offshore structures are the uncertainties associated with extreme environmental load conditions, the statistics for ice impact loads for the Hibemia structure were derived using RELAN and applications of energy conservation principles. For the purpose of deriving the ice load distributions to evaluate the reliability of the Hibemia icewall element, the program PROB, which is a product of the reliability program RELAN and the energy conservation principles, was developed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".