The Application of Deep Mixing Method for a River Wall and Finite Element Simulation
Bibliographic record
Abstract
This paper presents an application of using deep cement mixing method to construct a river wall.The geotechnical characteristics, construction sequence and its behaviours were presented in this paper.The behaviours of river wall were simulated by 3dimensional finite element by using Midas GTS NX software.The different type of constitutive models of cement admixed clay were used in the analysis.The stress-strain simulation of stress path triaxial test for cement admixed clay was conducted using SoilTest feature in GTS NX software.The Mohr Coulomb model showed the best performance to predict the deformation characteristics of cement admixed Pasak Clay among UBCSand Model and Hardening Soil Model.The predicted stiffness from stress response develops overestimated the stiffness of cement mixed clay when having low mean stress.The three-dimensional finite element analysis can predict the overall behaviours of river wall improved with cement.The best model for cement admixed clay was Mohr Coulomb Model.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".