Limed soils as a replacement for construction sand in stabilized sands
Bibliographic record
Abstract
ABSTRACT Sand is one of the main raw materials used in infrastructure and road construction. While it is a common natural raw material worldwide, the locations where it can be found are not evenly distributed. Natural sand can be extracted from the riverbed or from sandbanks in sea. In some cases sand is derived from quarries by crushing rock. In Flanders excavation and extraction of sand from the riverbed is restricted and there are no mountains available to crush rock. The amount of sand dredged in sea at the Belgian coast is insufficient to cover the need of the building industry. Therefore Flanders is highly dependent on the foreign import of sand. Soil like clay and loam are found locally but are not fitted as a replacement for sand in construction applications. This paper presents the results of the investigation of the application of lime treated soil particles as sand replacement. The first part of this paper takes a closer look at the economic feasibility of this idea. The second part of this paper delivers a proof of concept. During this part soil was treated with lime, and differences in soil properties between untreated and treated soils were characterized. This comparison of the results shows a significant increase in sand equivalent value and a lowering in methylene blue value. During the second part of this proof of concept cement and/or lime were added as hydraulic binders. The various mixtures were examined for their mechanical properties such as IPI and compressive strength. These results show that the strength development of these mixtures is similar to that of normal sand-cement mixtures.
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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) | 0.000 | 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) | 0.000 | 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".