Predicting nanocomposite binder improved unsaturated soil UCS using genetic programming

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dc.contributor.authorOnyelowe, Kennedy C.
dc.contributor.authorEbid, Ahmed M.
dc.contributor.authorOnyia, Michael E.
dc.contributor.authorNwobia, Light I.
dc.date.accessioned2022-09-12T13:25:01Z
dc.date.available2022-09-12T13:25:01Z
dc.date.issued2021
dc.description.abstractThe ability of the compacted soils and treated/compacted soils to withstand loads as foundation materials depends on the stability and durability of the soils. The design of such phenomena in treated soils whether as subgrade of pavements or embankments, backfills, etc., is a crucial phase of foundation constructions. Often, it is observed that soil mechanical and structural properties fall below the minimum design and construction requirements and this necessitates the stabilization in order to improve the needed properties. It can be observed that for this reason, there is a steady use of the laboratory and equipment prior to any design and construction as the case may be. In this work, genetic programming (GP) has been employed to predict the unconfined compressive strength of unsaturated lateritic soil treated with a hybridized binder material called hybrid cement (HC), which was formulated by blending nanotextured quarry fines (NQF) and hydrated lime activated nanotextured rice husk ash. Tests were conducted to generate multiple values for output and inputs parameters, and the values were deployed into soft computing technique to forecast UCS adopting three (3) different performance complexities (2, 3 and 4 levels of complexity). The results of the prediction models show that the four (4) levels of complexity GP model outclassed the others in performance and accuracy with a total error (SSE) of 2.4% and coefficient of determination (R2) of 0.991. Generally, GP has shown its robustness and flexibility in predicting engineering problems for use in design and performance evaluation.en_US
dc.identifier.citationOnyelowe, K. C., Ebid, A. M., Onyia, M. E., & Nwobia, L. I. (2021). Predicting nanocomposite binder improved unsaturated soil UCS using genetic programming. Nanotechnology for Environmental Engineering, 6(2), 1-12. https://doi.org/10.1007/s41204-021-00134-zen_US
dc.identifier.urihttps://doi.org/10.1007/s41204-021-00134-z
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/4693
dc.language.isoenen_US
dc.publisherNanotechnology for Environmental Engineeringen_US
dc.subjectHybrid cement (HC)en_US
dc.subjectNanostructured rice husk ash (NRHA)en_US
dc.subjectUnsaturated lateritic soilen_US
dc.subjectSoft computing (genetic programming)en_US
dc.subjectUnconfined compressive strengthen_US
dc.subjectSoil stabilizationen_US
dc.subjectNanostructured quarry fines (NQF)en_US
dc.titlePredicting nanocomposite binder improved unsaturated soil UCS using genetic programmingen_US
dc.typeArticleen_US
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