Bibliographic record
Abstract
The practice of filling Hollow Structural Section (HSS) columns with concrete is now commonplace, and most national or international design specifications give specific recommendations for determining the resistance of such elements. In addition, tubular members have been filled with concrete or grout at critical locations as a means of connection reinforcement, rather than externally plating the main hollow section member. Initially, the advantages and disadvantages of concrete (or grout)-filling are reviewed, including the issues of self-weight, cost, connection strength, truss stiffness, fire resistance and truss strength. Concrete-filling affects truss performance by enabling strut or compression members to behave as composite HSS beam-columns, as well as transforming the truss into a rigid-jointed structure. In order to examine the structural implications of concrete-filling, two roof trusses are designed for typical Canadian roof loads in square hollow sections -a 36.6m medium span Warren truss, and a 70m long span Pratt truss. Each truss is designed as unfilled, to the 1994 Canadian (CSA) structural steel specification and filled. Furthermore, the design for the grout-filled trusses is also performed to the 1995 CIDECT Design Guide for Concrete-Filled Hollow Section Columns (which generally conforms with Eurocode 4). Overall, the paper shows that modest benefits are produced by concrete (or grout)-filling, with regard to increased fire resistance, reduced steel weights, and increased truss stiffness.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".