Field investigation on the performance of low-carbon MgO-carbonated composite piles for ground treatments
Bibliographic record
Abstract
Carbonation technology using MgO and CO2 has been considered a rapid, effective, and environmentally friendly method for improving weak soils, mainly applied in shallow foundation treatments. This study introduced a novel MgO-carbonated composite pile (MCP) technique developed by injecting CO2 through a gas-permeable pipe pile into a MgO-mixing column for carbonation and solidification and its applications in weak subgrade treatments. Several field tests were carried out to study the characteristics of MCP as well as the performance of the MCP-reinforced foundations, including carbonation reaction temperature monitoring, pore-water pressure monitoring, standard penetration tests (SPTs), unconfined compressive strength (UCS) tests, static load tests, and subgrade deformation monitoring. Results showed vigorous and uniform carbonation within the MgO-mixing column, confirming the feasibility of constructing large-diameter MgO-mixing columns. The distribution, evolution, and affected zone of excess pore-water pressure induced by MCP installation were determined. The MCP exhibited good pile quality, with average SPT blow count and UCS value of 39 and 1021 kPa, respectively. MCP’s bearing capacity was superior to prestressed high-strength concrete pipe piles, with ultimate vertical and lateral bearing capacities of 1920 and 119 kN, respectively. The MCP-reinforced foundation exhibited a small settlement of 54.5 mm under embankment loads. Life cycle assessment indicated significant carbon reduction benefits for MCP, with 44.7% lower carbon emissions compared to traditional composite piles.
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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".