Evaluation of seismic performance of a pre-cast concrete block arch system through testing and numerical modeling
Bibliographic record
Abstract
Lock-Block Ltd. from Vancouver, Canada, has developed an arch structural system made from modular pre-cast concrete blocks. The intention of the arch is to provide an easy to construct, cost effective and long lasting structure. This could be achieved with a modular, steel-free system. This study aims to assess the seismic performance of these arches characterizing their seismic behavior using a combination of experimental testing and numerical modeling. Several small scale unreinforced and reinforced arch models were subjected to quasi-static and dynamic testing. For the dynamic testing, a suite of earthquake records was selected of varying magnitudes, types and locations, and applied on a shake-table. From the results of the shake-table testing on the unreinforced models it was found that the arches tend to collapse by the four-hinge mechanism which is typical for these types of structures. For the reinforced arch testing, a steel band was instrumented to provide information on the loads. The reinforced arch performed well when subjected to the same suite of earthquakes. A numerical distinct element model was developed using 3DEC software and calibrated to the quasi-static test. The response of the numerical model matched the experiments with the arch exhibiting the same four-hinge failure mechanism. From numerical analysis, sensitivity studies were performed on various parameters of the arch. This included geometry, material properties and boundary/interface conditions. It was found that in this configuration, the arches are vulnerable to seismic excitation and at risk of collapse when unreinforced and unconfined. There are several solutions to reduce that risk based on the results of this work: 1) addition of external or internal reinforcement to prevent hinge opening 2) restraint of the bottom courses of blocks and 3) modification of the geometry at the base to improve stability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".