Vol. 17, Issue 2, July 2022

Numerical Solution of Fractional Order Partial Differential Equation with Sturm-Liouville Problem Using Homotopy Analysis and Homotopy Perturbation Methods

Sun, 17 Jul 2022 00:00:00 GMT

Numerical Solution of Fractional Order Partial Differential Equation with Sturm-Liouville Problem Using Homotopy Analysis and Homotopy Perturbation Methods Yisa, B. M.; Adelabu, N. A. This research work is concerned with the application of both homotopy analysis and homotopy perturbation methods to linear and nonlinear, homogeneous, and nonhomogeneous fractional order partial differential equations and fractional order SturmLiouville equation. The fractional order derivatives are interpreted in Caputo sense. The applications of the two semi analytical methods are extended to one dimensional fractional order wave equation. Although homotopy perturbation method involves asymptotic expansion of terms with small parameter, but it pays off in the accuracy of the results obtained through which are similar to results using homotopy analysis method. All the problems selected from the existing literature made provision for results with integral order values, but in the present work we equally present results for fractional order. Our results are presented in 3D graphs and compared well with the existing results in the literature.

Anthropometric Determination of Body Height from Foot Length of Adults in Abeokuta Southwest Nigeria

Sun, 17 Jul 2022 00:00:00 GMT

Anthropometric Determination of Body Height from Foot Length of Adults in Abeokuta Southwest Nigeria Musa, Adekunle I.; Ogedengbe, Temitayo S.; Amusan, Grace M.; Giwa, Solomon O. Forensic identification of an individual in this time of unrest in some parts of the world cannot be overemphasized. The study was conducted to investigate and determine the body height (Bh) from foot length (Fl). Two hundred and sixty (260) adults (male and female) of ages ranged between 24years and 55years in Abeokuta Southwest Nigeria participated. The Bh and Fl of participants were measured using a stadiometer with a venier caliper and subsequently analysed. Descriptive statistics and simple linear regression model was determined. The result shows that the participants have an average of 168.36 ± 8.99cm and 26.06 ± 1.99cm as Bh and Fl respectively. The result also revealed that a statistical coefficient existed between Bh and Fl (P<0.001) with R2 of 0.598 and standard error estimate (S.E.E) of 5.710. With the analysed result, a linear regression model was established to determine the Bh from Fl. The study concluded that Fl has been identified as a predictor of Bh estimation and it is therefore recommended the use of anthropologist, forensic examination and medico-legal experts in demonstrating the identity of an individual and to determine Bh of adult Nigerian based on Fl.

Development of Efficient Empirical Models for the Prediction of Oil Well Fracture Pressure Gradient

Sun, 17 Jul 2022 00:00:00 GMT

Development of Efficient Empirical Models for the Prediction of Oil Well Fracture Pressure Gradient Ajibona, A. I.; Taiwo, Blessing Olamide; Afeni, Thoma Busuyi; Akinbinu, Victor Abioye; Emmanuel, Okeleye; Ogunyemi, Olaoluwa Bidemi Evaluation of fracture pressure gradient during oil well drilling has been best achieved in the past using the leak-off test. This study however, utilized artificial intelligence techniques involving Hunter Point-Artificial Neural Network (HP-ANN), Multivariate Regression (MVR), and Adaptive Neuro-Fuzzy Inference System (ANFIS) to develop a prediction model for fracture pressure gradient based on the input parameters of pore pressure, vertical depth, fracture pressure, and overburden pressure. The dataset used for training the models were extracted from the works of Akinbinu 2010 and Udo et al. 2020. The three models' prediction performance was compared with existing literature models using RSME, MAE, and R2 error analysis indicators. The HP-ANN model was found to have the highest prediction accuracy for oil well drilling fracture pressure gradient. Using the optimum HP-ANN model weights and the biases, an empirical mathematical equation was extracted for the prediction of the Fracture pressure gradient. Along these lines, the created HP-ANN models can be utilized to predict the Fracture pressure inclination of an oil well for practical purposes.

Assessment of Influence of Steel Fiber on the Improvement of Concrete’s Mechanical Properties

Sun, 17 Jul 2022 00:00:00 GMT

Assessment of Influence of Steel Fiber on the Improvement of Concrete’s Mechanical Properties Shohag, J. M. R. I.; Chowdhury, S.; Hasan, A. In recent days concrete usage has been increased all over the world. Concrete is one of the most developed materials. Different types of waste materials used in concrete as fiber reinforcement to develop its mechanical performance. Steel fiber is such type of waste material used in concrete. The main focus of this paper is to improve the compressive and tensile strength of concrete using steel fibers as fiber reinforcement. In this paper, several number of normal concrete cylinders and several number of fiber reinforced concrete cylinders with addition of 1%, 2% and 3% of steel fiber are investigated. Several tests have been performed under UTM Machine. Compressive strength & split tensile strength of concrete are found better for 2% addition of steel fiber. This paper shows a summary of the improvement of concrete’s mechanical performance including steel fiber as fiber reinforcement.