Changes in rheology of self-consolidating concrete induced by pumping
Bibliographic record
Abstract
Abstract Pumping is an easy and flexible process to place concrete inside a formwork. Many studies have recently been performed to understand and optimize the pumping process and identify the main differences between pumping of conventional vibrated concrete and self-consolidating concrete (SCC). However, due to pumping, changes in fresh concrete properties and the air-void system have been noticed. This paper describes the consequences of pumping on the fresh properties of SCC by means of two experimental pumping campaigns. In many cases, the concrete undergoes a large shear rate in the pipe, thus (re-)dispersing cement particles. This is expected to be the main cause of the observed decrease in plastic viscosity, V-Funnel flow time and pumping pressure resulting from increased flow rate or pumping time. The changes in yield stress or slump flow are anticipated to be influenced by the same phenomenon, but the final outcome is assumed to depend on the availability of residual superplasticizer in the mixing water. Pumping can cause a stable SCC to become segregating if both the yield stress and plastic viscosity decrease, or it can provoke a significant loss in filling ability, passing ability and self-consolidation of the concrete if the yield stress increases dramatically.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".