In this study, municipal plastic waste is used in producing paving blocks. Binders in the form of melted waste plastic bottles (Polyethelene Terephthalate (PET)) and water sachets (High Density Polyethylene (HDPE) with river sand, were used in making the blocks. Mix ratios; 1:1, 1:1.5 and 1:2 of sand-plastic waste were considered. Sand-cement mixes were adopted as the controls. 230mm x 140mm x 55mm blocks were cast, cured in water at ambient temperature and tested for 72-hours for water absorption and 21 days compressive strength. 3 specimen were prepared for each mixture. Sand-HDPE mix produced stronger blocks than sand-PET and sand-cement mixes. Topmost compressive strength of 17N/mm2 was generated from sand-HDPE mix of 1:2. Sand-PET blocks should be avoided since they generate very low strengths. Sand-plastic waste blocks melt faster at higher temperatures. Therefore, plastic paving blocks can only be used for light load pavements not subjected to high temperature.

In this paper, a regression model is developed to predict and optimise the compressive strength of periwinkle shell aggregate concrete using Scheffe’s regression theory. The results obtained from the derived regression model agreed favourably with the experimental data. The model was tested for adequacy using a student t-test at 95% confidence level and was found to be adequate. A computer programme coded in basic language was used to select the mix ratios that optimized the compressive strength of periwinkle shell aggregate concrete. The optimum compressive strength was found to be 19.50N/mm2corresponding to a mix ratio of 1:3:6 (cement, sand and periwinkle shell) at a water-cement ratio of 0.65. With the formulated model, the mix ratios corresponding to a desired strength value can be predicted with reasonable accuracy and without waste of time. http://dx.doi.org/10.4314/njt.v36i1.5

The California bearing ratio and the unconfined compressive strengths of sand-cement were measured in ten (10) different prepared CBR and UCS specimens. The sand-cement mix was prepared by mixing 10.5kg of sand with 5.5% by weight of cement and moisture content of 12%. The CBR specimens were cured for 6 days followed by 24 hours soaking while the UCS specimens were cured for 7 days. The CBR and UCS specimens were tested after their curing and soaking periods and gave values greater than 200% and 2500kpa respectively. The data obtained were subjected to regression analysis to check their correlation. The R 2 obtained showed that there is a little correlation between CBR and UCS.

In this study, a multivariate regression model for predicting the 28days flexural strength of lime-cement concrete prototype beam was developed. The response function is a multivariate function of the proportions of the component materials of concrete. A total of twenty mix ratios, consisting of water, Portland cement, hydrated lime, river sand and granite chipping were used in the prediction process. The first ten mix ratios were used for model development while the remaining ten mix ratios were used as check points for model validation. The model developed was tested for adequacy at 95% level of confidence using the t-statistic. Calculated t-value was -1.3342 and this was less than the critical t-value of 2.2622. Thus, the model was found to be adequate. An average percentage difference of 14.303% was observed between the model prediction and the experimental values. A visual basic program using the Visual studio 2015 software was developed based on the regression model. It was invoked to quicken the process of selecting the mix ratios of the component materials corresponding to any desired flexural strength value that falls within the region of experimentation and vice versa Keywords— Concrete , flexural strength, multivariate regression model, response function.

This study developed empirical-mathematical models to predict the California Bearing Ratio (CBR) using soil index properties in Ogbia-Nembe road in the Niger Delta region of Nigeria. The determination of CBR of soil is a laborious operation that requires a longer time and materials leading to increased cost and schedule; this can be reduced by adopting an empirical-mathematical How to cite this paper: Irokwe,