The application of a multilaminate model to simulate tunnelling in structured clays : a dissertation
Bibliographic record
Abstract
Due to the complex characteristics of tunneling problems, tunneling engineering is perhaps one of the areas in which numerical methods are more frequently adopted in practice. One important application is to examine the influence of an excavation and construction procedures on the stress distribution and deformation in the ground surrounding the opening and on the tunnel lining. Another important aspect of tunneling problems that can be accounted for in a numerical analysis is the complex geometry associated with typical applications. This is not only related to the shape of the opening, but also to the presence of non-homogenous or non-isotropic soil strata. A constitutive model that is suitable for the analysis of structured clays has been developed in this study based on the multilaminate framework. The model takes into account the elastic unloading-reloading, inherent and induced anisotropy, destructuration and bonding effects. The model is implemented into Plaxis finite element program, successfully calibrated and used to investigate the response of structured sensitive clay to the construction of the Gatineau tunnel in Gatineau, Quebec and the Ottawa sewer tunnel in Ottawa, Ontario. Numerical results were compared to the field measurements taken during the tunnel construction. To improve the performance of the numerical model, an implicit integration algorithm is implemented and proven to be very effective as compared to the conventional explicit integration methods. The effect of different soil parameters including bonding and anisotropy on the tunneling induced displacements and lining stresses is also examined using a comprehensive parametric study. The results indicated that soil bonding and anisotropy have significant effects on the shape of the settlement trough as well as the magnitudes of surface displacements and lining stresses induced by tunneling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".