The properties of concrete containing coconut shell as fine aggregate
Bibliographic record
Abstract
Green environments or environmentally friendly buildings have become a main focus among researchers. It refers to the concept of reusing waste materials to improve or make new products. Therefore, this study aims to examine the use of fine coconut shell (FCS) as a partial replacement of sand and its low thermal conductivity applications. The first part of the research focused on the characterisation properties of fine coconut shell and sand through sieve analysis, laser diffraction sieve, specific gravity tests, bulk density tests, scanning electron microscopy (SEM) and water absorption test. Next, the mechanical properties of fine coconut shell as a partial replacement of sand in concrete were determined through slump tests, compressive strength tests, flexural strength tests, modulus of elasticity tests, splitting tensile strength tests, water absorption tests and water permeability testing. The second part of the research focused on low thermal conductivity applications of fine coconut shell concrete through the thermal conductivity test (k-value) and thermal resistance (r-value) calculations. After collecting the data, a relationship analysis was conducted to find the optimum percentage of fine coconut shell replacement. Next, from the optimum percentage, a wall panel was constructed to check the temperature that penetrated the house. A validation of temperature data from real monitoring was then conducted using Autodesk Ecotect software. The results showed that FCS was finer (≤ 600 μm) than sand (4.25 mm - 150 μm). In terms of mechanical properties, concrete containing fine coconut shell as a partial replacement of fine aggregate demonstrated better performance than normal concrete. Apart from that, the thermal conductivity values for specimens containing coconut shell were lower compared to normal concrete. 50 % of fine aggregate with fine coconut shell was found to be the optimum replacement percentage as it fulfilled all the requirements set by the British Standard and also that of previous research.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".