Predictive models for strength properties of sustainable mortars containing waste concrete powder: an empirical approach

Waste concrete powder (WCP), obtained from discarded concrete, was used as a fractional substitute for cement in mortar production. During mortar preparation, cement was partially replaced with WCP at intervals of 10%, ranging from 0 to 30%. The obtained results showed that increasing the WCP level led to a considerable reduction in mechanical properties of the mortars. For instance, replacing 30% of the cement with WCP led to a reduction in the control mortar’s compressive strength from 40 N/mm² to 30 N/mm² over a 28-day period. However, the mortars still met the strength required for masonry applications. Also, predictive models were developed using the experimental data to estimate the compressive and flexural strengths of WCP mortars. The developed models’ effectiveness was assessed using experimental data gathered from published studies. The proposed models make it feasible to change conventional mortars’ standard strength grades into equivalent values for WCP-based mortars. Hence, the models can be effectively applied for practical predictions, as well as for the design and analysis of sustainable mortars incorporating WCP.

Authors

Institutions

Publication Details

Journal
Discover Sustainability
Published
2025-08-14
DOI
https://doi.org/10.1007/s43621-025-01575-1
Primary Topic
Recycled Aggregate Concrete Performance
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictive models for strength properties of sustainable mortars containing waste concrete powder: an empirical approach

Molusiwa Ramabodu, Eric Ababio Ohemeng, Nana-Addy Edward
Discover Sustainability
Recycled Aggregate Concrete Performance
article

Predictive models for strength properties of sustainable mortars containing waste concrete powder: an empirical approach

Molusiwa Ramabodu, Eric Ababio Ohemeng, Nana-Addy Edward
article en

Abstract

Waste concrete powder (WCP), obtained from discarded concrete, was used as a fractional substitute for cement in mortar production. During mortar preparation, cement was partially replaced with WCP at intervals of 10%, ranging from 0 to 30%. The obtained results showed that increasing the WCP level led to a considerable reduction in mechanical properties of the mortars. For instance, replacing 30% of the cement with WCP led to a reduction in the control mortar’s compressive strength from 40 N/mm² to 30 N/mm² over a 28-day period. However, the mortars still met the strength required for masonry applications. Also, predictive models were developed using the experimental data to estimate the compressive and flexural strengths of WCP mortars. The developed models’ effectiveness was assessed using experimental data gathered from published studies. The proposed models make it feasible to change conventional mortars’ standard strength grades into equivalent values for WCP-based mortars. Hence, the models can be effectively applied for practical predictions, as well as for the design and analysis of sustainable mortars incorporating WCP.

Discover SustainabilityVol. 6(1)
Durban University of Technology (ZA), Sunyani Technical University (GH)
National Research Foundation
Openalex Percentile: Top 70%
Recycled Aggregate Concrete Performance
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.

Predictive models for strength properties of sustainable mortars containing waste concrete powder: an empirical approach — Molusiwa Ramabodu, Eric Ababio Ohemeng, et al. · Discover Sustainability (2025) | TGRS Research Map | TGRS