Effects of Coal Ash and Walnut Shell on the Impact Resistance and Mechanical Properties of Eco-Efficient Self-Compacting Concrete
Bibliographic record
Abstract
This study investigated the effects of incorporating up to 20% coal ash (CA) by weight and 25% walnut shell (WS) by volume of coarse aggregate on the fresh and hardened properties of self-compacting concrete (SCC).A total of 12 SCC mixtures were designed, divided into two groups, with a constant water-to-binder (w/b) ratio of 0.309 and a total binder content of 550 kg/m .In the first and second groups, cement was replaced with 10% and 20% CA by weight, respectively.Mixtures in both groups utilized WS as a partial replacement for coarse aggregate at ratios ranging from 0% to 25% in 5% increments by volume.The results indicated that increasing CA and WS content adversely impacted the fresh properties of SCC, though the mixtures still met the necessary requirements.The slump flow diameter decreased by up to 13%, while the time to reach 50% flow (T50) increased.A notable reduction in the H2/H1 ratio was observed as WS content increased.Additionally, the segregation ratio experienced a 75% increase.A decline in compressive strength was recorded at a 25% WS replacement level, amounting to 29.2% and 17.6% for 10% and 20% CA mixtures, respectively.However, 20% CA mixtures exhibited higher compressive strength than 10% CA mixtures at the same WS replacement level, with a 21.7% increase observed at 25% WS substitution.Flexural strength exhibited similar trends.With increasing WS content for the same CA replacement level, the first fracture impact energy was found to decrease.The first crack impact energy results remained unaffected by CA replacement levels.Failure impact energy demonstrated analogous outcomes.
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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 | 0.001 | 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 | 0.001 |
| 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".