Stabilizing soft clay soil using nano-modified cementitious binders, basalt fiber pellets, and a novel geosynthetic composite
Bibliographic record
Abstract
Constructing on soft clay entails engineering challenges, such as significant volumetric changes and/or differential settlements. Hence, a prompt solution, like chemical stabilization which effectively imparts additional strength and durability, is needed for this problematic soil. While lime is the commonly preferred choice, it is prohibited in many regions, including Manitoba, Canada, due to environmental concerns about groundwater quality and vegetation. Hence, it is imperative to find innovative alternatives. The first part of this thesis investigated the effects of nano-modified cementitious additives, comprising cement, slag, and nano-silica, on the properties of soft clay at optimum moisture content under reference (22±2°C) and cold (+5°C) temperatures representing different periods of the construction season. The second part investigated using higher binders’ proportions with a wide range of water contents simulating wet conditions in the field. Subsequently, promising stabilizing binders were reinforced with a novel type of fiber (basalt fiber pellets) to achieve a balanced mechanical and durability behavior at a lower binder content. The mechanical properties (e.g., California Bearing Ratio, compressive strength, unconsolidated-undrained triaxial behavior) and the durability performance (freezing-thawing resistance) of treated soft clay were assessed along with microstructural analyses. In the last part of the thesis, a new geosynthetic composite containing a reinforcement layer (geogrid) to provide stiffness and volumetric control, and a filtration layer (geotextile), has been investigated by conducting large-scale pullout and direct shear tests. Furthermore, a numerical study using SIGMA/W (GeoStudio software) was carried out to predict the behavior of the new composite in a full-scale pavement application. The synoptic results of this thesis showed that stabilizing the soft clay using nano-modified ternary binders presents a viable option for field applications with the possibility of extending the construction season in cold regions during fall and spring periods due to the synergistic effects of combining variable reactivities and multiscale materials. Additionally, incorporating the basalt pellets provided further skeletal rigidity and reduced the required binders’ content. Lastly, the proposed novel geocomposite granted significant interaction improvements (adhesion and internal friction angle) and enhanced the long-term behavior by providing a higher Traffic Benefit Ratio under cyclic loading.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".