Performance Evaluation of Portal Frame System in Low-Rise Light-Frame Wood Structures
Bibliographic record
Abstract
In this paper, results are presented from a testing program focused on evaluating the performance of portal frame systems. A total of nine full-scale portal frame assemblies with six different configurations were tested under monotonic and reversed cyclic loading. The portal frames were 3.66 m in length and 2.44 m in height, with a 406-mm wall segment at each end of the portal frame. From the experimental results, it was observed that the corner joint between the header and narrow braced wall segment governs the lateral load-carrying capacity and ultimate displacement of the portal frame. Installation of metal straps considerably increased the lateral load-carrying capacity of the portal frame assemblies. Straps placed directly on the lumber framing showed increased resistance compared to those installed on the oriented strand board. Portal frames with hold-downs had a greater lateral load-carrying capacity those without hold-downs. A comparison was made between portal frames and conventional braced walls used in low-rise light-frame wood buildings. The portal frames in general have lower initial stiffness than the braced walls. A portal frame with sheathing on one side only and no hold-down has an ultimate load-carrying capacity equivalent to a 2.44-m long braced wall with hold-down. A portal frame with hold-down can on average achieve a capacity similar to that of a 4.88-m long braced wall without hold-down.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".