Compressive strength is often predicted from porosity or mix-design parameters. The inability to
convert laboratory scale-compaction-energy to industrial-scale limits the application of performance
prediction models. ...
Sajeevan, M.; Subramaniam, D.N.; Rinduja, R.; Pratheeba, J.(Chinese Society of Pavement Engineering, 2025)
Pervious concrete (PC) is a sustainable substitute for conventional concrete application yet limited due to lack of understanding
on its performance characteristics. The mix design affects the performance, mainly due to ...
Material that constitute aggregate depend on their packing efficiency that is defined by the shape distribution of
aggregates. Geometrical shape descriptors would not capture morphological aspects of different dimensional
scales ...
Optimizing compaction energy reduces uncertainty in mass production of pervious concrete, but depends on
aggregate-shape. This study analyses impact of aggregate size and shape on porosity and compressive strength.
Agg ...
This study investigates the significant impact of fly ash’s chemical composition on cement mortar’s
compressive strength, employing advanced machine-learning models to enhance prediction
accuracy. As the demand for ...
This study uses machine learning to predict the compressive strength of cement-sand mortar
incorporating supplementary cementitious materials (SCMs). The research addresses a gap in the
literature by specifically examining ...
The increasing environmental impact of traditional cement production necessitates the exploration of sustainable alternatives in construction materials. This paper investigates corncob ash (CCA), an agro-waste by-product, ...
The present study explores the potential of machine learning to predict the porosity and permeability of
pervious concrete constructed on mix parameters (compaction energy, aggregate-to-cement ratio and
aggregate size) ...
This study investigates the influence of aggregate size, aggregate-to-cement ratio, and compaction effort on pervious concrete's porosity and compressive strength. It proposes using response surface methodology and machine ...
The present study investigates the effect of the total amount of chemical constituents in cement and supplementary cementitious materials on the compressive strength of pervious concrete. Experimental datasets were collected ...
The current study aimed to investigate the possibility of predicting the compressive strength of geopolymer mortar by mix design parameters, ultrasonic pulse velocity (UPV) and machine learning techniques. Here the geopolymer ...
The porosity and compressive strength of pervious concrete are critical determinants of its suitability for
various applications. Therefore, it is necessary to recognise the factors influencing the performance and
its ...
Pervious concrete is a special type of concrete consisting of cement, coarse aggregate and water. Cement
is a widely used raw material for construction including pervious concrete and had led to the release of
huge amounts ...
Aggregates are packed effectively packed in applications including pervious concrete, mechanical
performance of which, depends primarily on packing characteristics. Size and shape distribution of
aggregates affect packing. ...
Utilizing silica fume as a substitute for cement in pervious concrete offers a viable approach to achieve sustainability within
the realm of construction industry. The mechanical characteristics of pervious concrete are ...
This study aims to investigate aggregate geometric characteristics and analyze the possible aggregate shape factors on their statistical relationships. The study used 2192 crushed rock particles from 5 to 30 mm in diameter ...
The shape and size of aggregates are rarely investigated in pervious concrete
research despite their impact on porosity and compressive strength.
This study analyses the impact of size and shape distribution of aggregates
and ...
This article investigates the importance of moisture content in cement-stabilized
earth blocks (CSEBs) and explores methods for their prediction using machine learning.
A key aspect of the research is the development of ...
Using groundnut shell ash (GSA) as a component in concrete mixtures is a viable
approach to achieving sustainability in building practices. This particular kind of concrete
has the potential to effectively mitigate the ...
This study employs machine learning models to predict the compressive strength of hollow block masonry and examines the key factors that influence this strength. Accurate prediction of its compressive strength is crucial ...