| Issue |
EPJ Web Conf.
Volume 354, 2026
19th Global Congress on Manufacturing and Management (GCMM 2025)
|
|
|---|---|---|
| Article Number | 02009 | |
| Number of page(s) | 20 | |
| Section | Artificial Intelligence, Machine Learning, and Intelligent Decision Systems | |
| DOI | https://doi.org/10.1051/epjconf/202635402009 | |
| Published online | 02 March 2026 | |
https://doi.org/10.1051/epjconf/202635402009
Mechanical Characterization of Concrete with Replaced Shell Ash Aggregates Using ANOVA and Regression Methods
Department of Civil Engineering, VISTAS, India
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 2 March 2026
Abstract
The increasing erosion of river sand has documented the emergency to use alternative materials with the environmental-friendly. The paper examines the use of oyster shell ash (OSA) and walnut shell ash (WSA) as artificial aggregates in concrete by partial replacement of fine aggregates. Aggregates were made using 0, 20, 40, 60, 80 and 100 (weight percent) OSA and WSA replacing the sand weight but keeping cement to sand ratio of 1:2. They were applied to M25 grade concrete and allowed to dry after 7, 14 and 28 days. The mechanical properties such as compressive, split tensile, flexural strength, modulus of elasticity and impact resistance were evaluated. The durability was tested by exposing to 3% hydrochloric acid and 5% sodium sulfate solutions in 28 days. ANOVA has used for measure the performance levels as statistically significant, and regression analysis. The results showed best mechanical characteristics and chemical resistance at 80% replacement and performance worsened at this point. The research concludes that artificial aggregates based on OSA and WSA are practical alternatives to sustainability, as they decrease the reliance on natural resources and offer efficient waste usage.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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