Shaking Table Test and Numerical Analysis of a Precast Frame Structure with Replaceable Box Connectors
Bibliographic record
Abstract
In view of the construction difficulties and other problems faced by structure construction in areas with high-altitude, high-intensity seismic regions, a dry-connection fully precast concrete frame structure was proposed. The connections in this structure eliminate the need for templates or auxiliary supports, facilitating simultaneous component installation on multiple floors and at multiple locations. This significantly reduces construction labor intensity and enhances the construction efficiency. To investigate the seismic performance of the structure, a 3-story test structure with a scale ratio of 1/2 was designed, and shaking table tests were conducted to study the dynamic characteristics and damage progression of the test structure under various intensities of earthquakes. The test results show that the structure performs well as designed. Then, a finite-element model of the structure was established, and numerical simulations were performed to investigate the seismic response characteristics and seismic vulnerability. The numerical simulation results indicated that the seismic performance of the fully precast concrete frame structure is slightly lower than that of the cast-in-place concrete frame structure, but sufficient to survive rare earthquakes without collapsing even under the action of near-field earthquakes.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".