Numerical model tests of building response to excavation-induced ground movements
Bibliographic record
Abstract
Distortion and damage to masonry and frame structures on shallow foundations subjected to excavation-induced ground movements have been investigated using numerical model tests. The numerical tests were modeled using the two-dimensional (2-D) universal distinct element code (UDEC) version 3.1 in which each masonry unit was modeled as a block, with the contacts between blocks having stiffness and strength characteristics of mortar. The soil was modeled elastically with a stiffness selected to provide the same pressure–displacement relation for the 2-D model as that for the three-dimensional (3-D) foundation condition. To give a justifiable basis for the numerical tests, two physical model tests were simulated numerically, and the results from the numerical tests were compared with those from the physical model tests. The good agreements between the numerical simulations and physical model tests led to extended numerical studies. The studies included the effect of cracking in structures and structural types (brick and frame structures) on the building response, considering soil–structure interaction. The numerical studies indicated that the structural response to excavation-induced ground movements is highly dependent on both cracking in structures and structural types, and therefore their effects should be considered for better assessing the building response to excavation-induced ground movements.
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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) | 0.001 | 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 | 0.001 |
| 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".