Short-term performance of a newly developed connection for use in precast double tee systems.
Bibliographic record
Abstract
The focus of this work was to investigate the effectiveness of using advanced composite materials to enhance double tee to double tee connections in regions of significant seismic and lateral load. This work stems partly from the unfortunate losses experienced during the 1994 Northridge California earthquake. Moreover, this work was also developed from discussions with a local precasting company, which is concerned about premature failure of the connection due to stress concentrations. The author contends that the current connection method, intermittent welded plates, does result in stress concentrations, which can effect the system's overall performance. The proposed connection was formed by using a grouting material in conjunction with CFRP (Carbon Fiber Reinforced Polymer) fabrics, placed at +/- 45° from the axis of the joint under consideration. It is believed that this connection will not only enhance the system's diaphragm action and reduce stress concentrations in the connectors currently used, but it will also enhance the system's load distribution mechanisms. At the University of Windsor a special set of experiments were conducted in the Civil Engineering Structures laboratory. These experiments were conducted at a 1:4 scale based on reviewed, full scale plans from a local precasting company. These experiments involved testing of two connected double tees with various connection designs. The tests conducted included dynamic analysis and ultimate loading. The experimental work was verified using a Finite Element Model. Overall, the proposed composite connection performed well and has proven itself suitable for repair and new construction works. It should be noted that this connection's performance is only known for the short term, thus long term effects are not yet know. This dissertation includes a discussion of design considerations and recommendations for future work. Also provided is a new connection design that enhances double tee to double tee connections in terms of both gravity and seismic loading.Dept. of Civil and Environmental Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .T37. Source: Dissertation Abstracts International, Volume: 66-02, Section: B, page: 1057. Advisers: J. B. Kennedy; M. K. S. Madugula. Thesis (Ph.D.)--University of Windsor (Canada), 2004.
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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) | 0.001 | 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".