NDM-535: STRUCTURAL MODELLING AND VERIFICATION METHODS TO DEVELOP A CABLE ROOF HARNESS RETROFIT SYSTEM
Bibliographic record
Abstract
Load paths in light-frame wood structures have historically been nailed connections between the sheathing and rafters, and toenail connections between the rafters and stud walls. However, these connections have poor resistance to uplifting forces, as occurs in high wind speed events, causing sheathing or roof-to-wall-connection (RTWC) failures. The improvements made to building codes after Hurricane Andrew affected only new construction, and the economic losses caused by roof failures in homes built prior to 1993 from Hurricane Katrina pointed to a need to retrofit older structures. This paper will investigate the design, analysis, and testing of a temporary cable-netting roof harness as an alternative to relatively expensive and invasive retrofitting options. To do this, a non-linear finite element analysis (FEA) is performed to model a typical light-frame wood structure with the roof harness, which is then validated through test results. After, as a comparative study, scaled down versions of the structure with and without the roof harness are created and tested using real wind load until failure at the WindEEE facility. This is done to assess the efficacy of the retrofit system. Corresponding FEA and computational fluid dynamics (CFD) models are then created to simulate the test.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".