A numerical study of deep excavations adjacent to existing tunnels: integrating CPTU and SDMT to calibrate soil constitutive model
Why this work is in the frame
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Bibliographic record
Abstract
Accurate determination of parameters for an advanced soil constitutive model highly relies on laboratory testing, even though it is notoriously difficult to obtain undisturbed samples for soft soils. This study explores the potential use of in situ tests, such as piezocone penetration tests (CPTU) and seismic dilatometer tests (SDMT), to estimate the constitutive model parameters. Based on a case history of a deep excavation adjacent to existing tunnels in silt/sand-dominated sediments, a calibration approach of a set of the HSSmall (Hardening Soil Model with small strain stiffness) model parameters is presented, and the derived parameters are used to numerically compute the interactive responses of tunnels and deep excavations. Several comparisons against field monitoring data indicate that the numerical model with the CPTU/SDMT-interpreted HSSmall model parameters adequately reproduces observed deformation responses of deep excavations adjacent to tunnels. However, in the considered case study, the use of laboratory tests with disturbed samples to estimate the stiffness parameters of the HSSmall model results in an overconservative solution. This finding supports the use of CPTU/SDMT to provide representative parameters for a range of soil layers, leading to the conclusion that tunnel linings may be beneficial to mitigate ground movements and wall deflections due to a “barrier” effect.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it