Engineering optimization of ternary waste‐ash blends for sustainable cementitious materials using ANOVA and response surface method

Abstract The rapid accumulation of household waste and the environmental impacts of Portland cement production highlight the need for sustainable strategies that promote waste valorization and reduce cement consumption. This study investigates chicken bone ash (ChBA), cow bone ash (CBA), and wood waste ash (WWA) as partial Portland cement replacements in mortar. The ashes were incorporated at 0%, 2.5%, 5%, 7.5%, and 10%, while curing age ranged from 2 to 56 days. Compressive strength, flexural strength, and dynamic modulus of elasticity were evaluated experimentally. Response surface methodology (RSM) and analysis of variance (ANOVA) were employed to develop predictive models, assess factor effects and interactions, and optimize ternary ash formulations. The models demonstrated satisfactory predictive performance, with R 2 values of 0.95, 0.82, and 0.96 for compressive strength, flexural strength, and dynamic modulus of elasticity, respectively, while differences between predicted and adjusted R 2 values remained below 0.20. Results showed that combinations of ChBA, CBA, and WWA can enhance long‐term mechanical performance while reducing cement content. Statistical optimization identified suitable ternary formulations that balance cement reduction and mechanical performance. The study demonstrates an integrated experimental–statistical approach for simultaneously valorizing household waste ashes and developing more sustainable cement‐based materials within a circular‐economy framework.

Authors

Institutions

Publication Details

Journal
Environmental Progress & Sustainable Energy
Published
2026-09-29
DOI
https://doi.org/10.1002/ep.70712
Primary Topic
Concrete and Cement Materials Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Engineering optimization of ternary waste‐ash blends for sustainable cementitious materials using ANOVA and response surface method

George Uwadiegwu Alaneme, Assia Aidoud, Ghania Boukhatem, Bencheikh Messaouda et al.
Environmental Progress & Sustainable Energy
Concrete and Cement Materials Research
article

Engineering optimization of ternary waste‐ash blends for sustainable cementitious materials using ANOVA and response surface method

George Uwadiegwu Alaneme, Assia Aidoud, Ghania Boukhatem, Bencheikh Messaouda, Mehmet Serkan Kırgız, Ouassila Bahloul
article en

Abstract

Abstract The rapid accumulation of household waste and the environmental impacts of Portland cement production highlight the need for sustainable strategies that promote waste valorization and reduce cement consumption. This study investigates chicken bone ash (ChBA), cow bone ash (CBA), and wood waste ash (WWA) as partial Portland cement replacements in mortar. The ashes were incorporated at 0%, 2.5%, 5%, 7.5%, and 10%, while curing age ranged from 2 to 56 days. Compressive strength, flexural strength, and dynamic modulus of elasticity were evaluated experimentally. Response surface methodology (RSM) and analysis of variance (ANOVA) were employed to develop predictive models, assess factor effects and interactions, and optimize ternary ash formulations. The models demonstrated satisfactory predictive performance, with R 2 values of 0.95, 0.82, and 0.96 for compressive strength, flexural strength, and dynamic modulus of elasticity, respectively, while differences between predicted and adjusted R 2 values remained below 0.20. Results showed that combinations of ChBA, CBA, and WWA can enhance long‐term mechanical performance while reducing cement content. Statistical optimization identified suitable ternary formulations that balance cement reduction and mechanical performance. The study demonstrates an integrated experimental–statistical approach for simultaneously valorizing household waste ashes and developing more sustainable cement‐based materials within a circular‐economy framework.

Environmental Progress & Sustainable Energy
Badji Mokhtar-Annaba University (DZ), University of Batna 1 (DZ), University of South Africa (ZA), Kampala International University (UG), University of Guelma (DZ), Istanbul University-Cerrahpaşa (TR), Istanbul University (TR)
Openalex Percentile: Top 17%
Concrete and Cement Materials Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.