Optimising fine-aggregate gradation for enhanced strength properties of cement mortar: a study using gradation fractal dimension

The construction sector faces mounting pressure to maximise material efficiency, particularly given the progressive depletion of naturally occurring aggregate reserves. The shift from naturally graded river sand to crusher-produced manufactured sand enables the deliberate manipulation of particle size distribution, offering new opportunities to enhance the performance of cement mortar and concrete through optimised gradation design. This research develops a systematic optimisation framework that employs gradation fractal dimension (GFD) to refine fine aggregate particle size distributions in cement mortar, leveraging the inherent efficiency principles of fractal geometries. Nine distinct fine aggregate gradation sets, each characterised by unique GFD values spanning from 2.1 to 2.9, were systematically generated and physically prepared through sieving protocols for subsequent cement mortar mixes. The mechanical and fracture characteristics of all nine GFD-based mixtures were experimentally assessed and benchmarked against Zone-II sand and standard sand compositions to identify the optimal gradation configuration. Additional analyses, including fractal analysis of fractured surfaces, surface void analysis, and compressible packing model (CPM) analysis, were conducted to corroborate the trends observed in the mechanical and fracture properties. The optimised gradation within the GFD range of 2.4–2.6 demonstrated performance enhancement of 7.66%–22.37% across both mechanical and fracture properties compared to conventional Zone-II sand.

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Publication Details

Journal
European Journal of Environmental and Civil engineering
Published
2026-07-23
DOI
https://doi.org/10.1080/19648189.2026.2705946
Primary Topic
Concrete and Cement Materials Research
Type
article
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article

Optimising fine-aggregate gradation for enhanced strength properties of cement mortar: a study using gradation fractal dimension

S. Pruthviraj, M H Prashanth
European Journal of Environmental and Civil engineering
Concrete and Cement Materials Research
article

Optimising fine-aggregate gradation for enhanced strength properties of cement mortar: a study using gradation fractal dimension

S. Pruthviraj, M H Prashanth
article en

Abstract

The construction sector faces mounting pressure to maximise material efficiency, particularly given the progressive depletion of naturally occurring aggregate reserves. The shift from naturally graded river sand to crusher-produced manufactured sand enables the deliberate manipulation of particle size distribution, offering new opportunities to enhance the performance of cement mortar and concrete through optimised gradation design. This research develops a systematic optimisation framework that employs gradation fractal dimension (GFD) to refine fine aggregate particle size distributions in cement mortar, leveraging the inherent efficiency principles of fractal geometries. Nine distinct fine aggregate gradation sets, each characterised by unique GFD values spanning from 2.1 to 2.9, were systematically generated and physically prepared through sieving protocols for subsequent cement mortar mixes. The mechanical and fracture characteristics of all nine GFD-based mixtures were experimentally assessed and benchmarked against Zone-II sand and standard sand compositions to identify the optimal gradation configuration. Additional analyses, including fractal analysis of fractured surfaces, surface void analysis, and compressible packing model (CPM) analysis, were conducted to corroborate the trends observed in the mechanical and fracture properties. The optimised gradation within the GFD range of 2.4–2.6 demonstrated performance enhancement of 7.66%–22.37% across both mechanical and fracture properties compared to conventional Zone-II sand.

European Journal of Environmental and Civil engineeringVol. 30(1)
National Institute of Technology Karnataka (IN)
Openalex Percentile: Top 14%
Concrete and Cement Materials Research
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