Discrete element modelling of CPT using shaking table tests in sands
Bibliographic record
Abstract
This thesis contains an overview of the results obtained from detailed study exploring the ability of two-dimensional discrete element method (2D DEM) models to reproduce cone penetration tests in saturated sand deposits. The simulations of the cone penetration and triaxial tests are carried out under application of the commercially available numerical analysis software PFC2D (Itasca, 2008). This software is based on DEM with additional basic fluid analysis option. The soil sample used in the laboratory experiments was uniform, river clean quartz sand, which was similar to Ottawa sand. The material properties that required calibration were normal stiffness, tangential stiffness and interparticle friction. These parameters were determined by trial and error from 2D DEM biaxial test simulations. Data from five laminar box shaking table tests of saturated sand was analysed with particular attention to the measured cone penetration resistance in assemblages deposited at various relative densities. Each shake table test was subjected to three series of shaking tests (at the same intensities) by using one-degree of freedom shaking table system, which allowed obtaining wide scope of different porosities. A new scaling factor was implemented in order to compare the data obtained from tests on real soil (3D) with numerical simulations by DEM (2D). Observations of the behaviour of discrete material at laminar box enabled us to make a correlation between porosity from large scale experiment and PFC2D model. To examine the effects of boundary conditions, porosity, particle diameter size, fluid grid dimensions, contacts, coordination number and others on the tip resistance value, multiple simulation tests were performed. From the results presented we can deduce that 2D DEM CPT model can be powerful tool to enrich the conventional physical calibration tests. In this thesis it is also proven that CPT laminar box based correlations facilitate to overcome limitations of 2D simulation and can be widely and successfully applied for both scientific research and engineering practice purposes.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".