Green interlocking paving units

•Ultra, lightweight paving units were produced with sawdust and laterite.•The paving units can be used in low-traffic buildings and pedestrian walkways.•Optimum sawdust content of 10% is recommended with 90 curing days.•Preferable order of curing media: water > laterite > alkaline > acid.•A...

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Veröffentlicht in:Construction & building materials 2018-06, Vol.173, p.600-614
Hauptverfasser: Sojobi, A.O., Aladegboye, O.J., Awolusi, T.F.
Format: Artikel
Sprache:eng
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Zusammenfassung:•Ultra, lightweight paving units were produced with sawdust and laterite.•The paving units can be used in low-traffic buildings and pedestrian walkways.•Optimum sawdust content of 10% is recommended with 90 curing days.•Preferable order of curing media: water > laterite > alkaline > acid.•ANN model prediction efficiency of compressive strength is very good. Our research produced ultra-lightweight green interlocking paving units through combined usage of sawdust and laterite as partial cement and fine aggregate replacements respectively. Interlocking paving units, water-cured for 90 days at optimum 10% sawdust content, achieved compressive strength of 16.6 MPa and skid resistance of 64.5 PVT, which exceeded the minimum requirements of 3.45–15 MPa and 45PVT respectively. The developed ANN model was classified as very good in terms of prediction efficiency of compressive strength (CS) and skid resistance for different curing media based on Nash & Sutcliffe criterion of efficiency (NSE). However, the prediction efficiency for CS was better than SR in terms of NSE, root-mean-square error (RMSE) and mean-square error (MSE), and was able to capture the interactive effects of considered factors. In line with ANN results, CS and SR increased with curing age but decreased with increasing sawdust content. In terms of durability performance and compressive strength development, the preferable order of curing media is water > laterite > alkaline > acid. Multi-criteria evaluation of ANN models is recommended for better interpretation of model efficiency.
ISSN:0950-0618
1879-0526
DOI:10.1016/j.conbuildmat.2018.04.061