The strain limit state criterion for hollow section joints
Bibliographic record
Abstract
Abstract This paper focuses on discussions about establishing the design resistance of hollow section joints, which have now been ongoing for 30 years. The question arose once physical experiments could be replaced by numerical tests and was temporarily solved by agreement on a displacement limit within the IIW. With the advent of design using finite element (FE) solutions and the use of high‐strength steels, this question is being raised once more. Many design guides and standards with considerable international consensus are now available for the design of welded hollow section joints in onshore and offshore construction. However, they typically cover relatively standardized joint types, geometries and loading cases. In the event of unusual joints it is now common for finite element modelling to be performed, but specific guidance needs to be provided on acceptable FE modelling procedures and the interpretation of the output in order to determine a suitable joint design resistance. With this objective in mind, this paper describes appropriate FE modelling and ultimate limit states that can be used; in particular, a 5 % ultimate strain limit state. Application of these ultimate limit states is demonstrated using validated FE models for RHS‐to‐RHS (rectangular hollow section) X‐joints, with braces in axial compression and tension, and brace plate‐to‐CHS (circular hollow section) joints with braces loaded in axial compression.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".