Compressive strength of concrete, renowned as one of the most substantial mechanical properties of concrete and key factors for the quality assurance of concrete. In the present study, two different data-driven models, i.e., Adaptive Neuro-Fuzzy Inference System (ANFIS), and Multiple Linear Regression (MLR) were used to predict the 28 days compressive strength of recycled aggregate concrete (RAC). 16 different input parameters, including both dimensional and non-dimensional parameters, were used for predicting the 28 days compressive strength of concrete. The present study established that estimation of 28 days compressive strength of recycled aggregate concrete was performed better by ANFIS in comparison to MLR. Besides, the performance of data-driven models with and without the non-dimensional parameters is explored. It was observed that the data-driven models show better accuracy when the non-dimensional parameters were used as additional input parameters. Furthermore, the effect of each non-dimensional parameter on the performance of each data-driven model is investigated and 28 days compressive strength of concrete is examined.
The source of groundwater seepage problem being experienced by some engineering buildings in a part of southwestern Nigeria was investigated by carrying out comparative study of the hydraulic conductivity (K) of the soil types underlying the area using integrated approaches involving geotechnical and geophysical methods.Soil samples were collected from six different towns on which standard geotechnical tests including natural moisture content, grain size distribution, linear shrinkage, specific gravity, liquid and plastic limits, compaction, triaxial and K test were carried out. Also, geophysical data were acquired at seventy-two locations using Schlumberger array with a current electrode spacing of 40m. The resistivity data obtained were subsequently inverted to obtain the subsurface 2D hydraulic conductivity section.The results obtained imply that the soil types investigated is semi-pervious with K values ranging from 1.06 x 10-5 to 5.71 x10-5cm/s. These values suggest moderate groundwater flow which might account for the seepage that was observed. Four lithologies (lateritic topsoil, clayey-sand, sandy-clay and fractured/weathered bedrock) were delineated. The geotechnical analysis result suggests the soil investigated could be classified as poorly graded sandy-clay and/or silty-clay. This soil exhibit plasticity index ranging from 12.72 to 19.75%, with specific gravity ranging from 2.47 to 2.73; the maximum dry density (MDD) varies from 1699.5 kg/cm3 to 1915kg/cm3 and the optimum moisture content (OMC) ranges from 12.05% to 16.32%.The result of the t-test results performed implied that at 95% t–confidence level, there is a good correlation between the results obtained from both approaches employed.
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