Please use this identifier to cite or link to this item: http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/9940
Title: Investigation of Compaction on Compressive Strength and Porosity of Pervious Concrete
Authors: Sajeevan, M.
Daniel Niruban, S.
Rinduja, R.
Pratheeba, J.
Keywords: Pervious concrete;Effective porosity;Compaction energy distribution;Compressive strength;Actual porosity the environment;concept of sustainable development
Issue Date: 2023
Publisher: Springer
Abstract: 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 its porous structure that is also not uniform in characteristics when mass produced. Although zero compaction is envisaged for casting of PC, it is important for mass production of PC with uniform properties. This study analyses the impact of compaction on two primary performance indicators of pervious concrete, porosity and compressive strength. Laboratory specimens of size 150 mm cubic were cast with varying aggregate-to-cement ratio (2.5—7.0), compaction (15—75 blows by standard proctor hammer) and compaction distributions (two types), where water-to-cement ratio was maintained at 0.3 and aggregates used were between 12 and 25 mm. Twelve specimens of each design were cast, and six specimens were tested for compressive strength and porosity and another six specimens were cored to obtain cylindrical cores of 100 mm diameter for porosity measurements and porosity distribution analysis using image analytical tools. Results revealed that actual porosity (measured through image analysis) represented the performance of pervious concrete, and that it is perfectly linearly correlated with effective porosity. The type of compaction distribution had significant impact on the relationship between porosity and compressive strength, while the impact was not statistically evident in porosity and compressive strength separately. The performance of the samples, however, showed correlation to the type of compaction employed when machine learning tools are employed.
URI: http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/9940
Appears in Collections:Civil Engineering

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