Carbonation curing and performance of pervious concrete using Portland limestone cement
Bibliographic record
Abstract
Pervious concrete is an innovative material with several environmental advantages. Studies on the properties and performance of ordinary Portland cement (OPC) pervious concrete have been done worldwide. Portland limestone cement (PLC) has recently been introduced into the Canadian market as a greener option than OPC. This thesis explores the possibility of using PLC in pervious concrete to achieve technical and environmental benefits.Since the major application of pervious concrete is pavements, it is important to find a way to accelerate the concrete curing process, as one of the most important factors in determining the cost and impact of road work is the construction time. Pervious concrete is the ideal material to cure by carbonation in a feasible way. It is usually designed without reinforcement, so the reduction of the concrete pH value resulting from the process has no impact. Additionally, the open massive pore structure provides a larger surface to optimize CO₂ penetration during the curing process. This study focuses on the effect of carbonation on early age strength and freezing and thawing durability of PLC pervious concrete. It was found that, under the same conditions, PLC pervious concrete shows lower compressive strengths and higher absorption than the OPC counterpart. The optimization of the mixture proportion by including admixtures would permit the use of PLC to generate a pervious concrete with strengths equivalent to OPC pervious concrete. Carbonation curing of PLC pervious concrete increased early age compressive strength, and maintained a comparable final strength. In addition, carbonation curing increased resistance to absorption, but decreased the resistance to freezing and thawing cycles in saline solution. Therefore, carbonation curing of pervious concrete is not recommended for cold climates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".