Structural Imposed Load Analysis of Isotropic Rectangular Plate Carrying a Uniformly Distributed Load Using Refined Shear Plate Theory

This presents the static flexural analysis of a three edge simply supported, one support free (SSFS) rectangular plate under uniformly distributed load using a refined shear deformation plate theory. The shear deformation profile used, is in the form of third order. The governing equations were determined by the method of energy variational calculus, to obtain the deflection and shear deformation along the direction of x and y axis. From the formulated expression, the formulars for determination of the critical lateral imposed load of the plate before deflection reaches the specified maximum specified limit and its corresponding critical lateral imposed load before plate reaches an elastic yield stress is established. The study showed that the critical lateral imposed load decreased as the plates span increases, the critical lateral imposed load increased as the plate thickness increases, as the specified thickness of the plate increased, the value of critical lateral imposed load increased and increase in the value of the allowable deflection value required for the analysis of the plate reduced the chances of failure of a structural member. This approach overcomes the challenges of the conventional practice in the structural analysis and design which involves checking of deflection and shear after design; the process which is proved unreliable and time consuming. It is concluded that the values of critical lateral load obtained by this theory achieve accepted transverse shear stress to the depth of the plate variation in predicting the flexural characteristics for an isotropic rectangular SSFS plate. Numerical comparison was conducted to verify and demonstrate the efficiency of the present theory, and they agreed with previous studies. This proved that the present theory is reliable for the analysis of a rectangular plate. Keywords— Allowable deflection, critical imposed load, energy method, plate theories, shear deformation, SSFS rectangular plate

Numerical Investigation of Iron Ore Tailings Filled Epoxy Composite as Heat Resistant Material

The thermal properties of epoxy composites reinforced with iron ore tailings were used to investigate the thermal performance of the composite as heat resistant material. Thermal properties are important parameters for determining the behaviour and appropriate applications of materials. This paper focuses on investigating the thermal performance of epoxy composite reinforced with iron ore tailings (IOT) of particles sizes 150 µm, 10% reinforced. The thermal properties of the selected epoxy-IOT composite were specific heat capacity – 2352 J/kg-K, thermal resistivity – 4.788 °C-m/W, thermal diffusivity – 0.089 mm2/s and Thermal conductivity – 0.209 W/m-K. The selected epoxy-IOT composite was numerically compared with an existing material (gypsum board) of the following thermal properties: specific heat capacity – 1090 J/kg-K, thermal resistivity – 3.87°C-m/W, thermal diffusivity – 0.333 mm2/s and Thermal conductivity – 0.258 W/m-K. The numerical analysis was done using Autodesk Fusion360, by modelling the materials as slabs.The heat transfer process of the composite and the prediction of the heat resistance capability were explained by comparing the results with an existing material (gypsum plasterboard) using their mechanical and thermal properties.The numerical results indicated that the epoxy-IOT composite has lower minimum temperature and thermal stress compared with the existing material (gypsum board), which implies that epoxy-IOT composite when used as a heat insulator will resist heat and sustain thermal stress better than the gypsum board of the same geometry under the same conditions. In conclusion, an epoxy-IOT composite of appropriate mixing ratio and geometry can be comfortable use as heat resistant materials. Keywords— Epoxy-IOT, Numerical Analysis, Temperature Distribution, Thermal Performance, Thermal Stress

Development and Performance Evaluation of a Soil Moisture Sensor

This study was aimed at developing a soil moisture sensor to effectively monitor moisture level for optimum crop growth. The sensor was made using a programmed Arduino microcontroller. It is attached to a sensing panel with two probes made of nickel that measures the volumetric content of water in soil. The probes were non-corrosive and robust material suitable for use in wet surfaces. The developed sensor was tested and evaluated. The two legged Lead (probes) goes into the soil where water content was to be measured by passing current through the soil, and then reads the resistance to get the moisture level. Nine different soil classification samples (Sandy Clay, Fine Sandy Loam, Sandy Loam, Salty Loam, Loamy Sand, Coarse Sand, Fine Sand, Sandy Clay Loam and clay soils) at different depths (3, 6, 9, 12 and 14.3 cm) were used to analyse the moisture meter at three different portion of each soil sample. Results obtained indicates that there was a progressive increase in moisture levels the more the sensor was being dipped into the soil. Results obtained also shows that all the nine soil samples but one (Silt Loam Soil Sample) analysed were within acceptable range of accuracy (0.1 - 5.0 %). The moisture sensor whose cost was approximately #22,300:00 was found to be effective, high precision at less efforts and a suitable guide for farmer for determining soil moisture levels.Keywords- Moisture, Probe, Sensor, Soil Classification

Development of a Millet Destoner for Small Scale Farmers

Post-harvest processes of millet rely on labour-intensive manual operations in Nigeria while its produce is associated with contaminants. A manually-operated destoner was developed to increase grain value for commercial production and reduce drudgery. To construct the destoner sieves, physical properties of one thousand randomly selected grains were determined digital Vernier callipers. Millet grains to be destoned was fed through the upper portion of the destoner being operated through the crank handle while the pure grains were collected at the discharge outlet. Results obtained shows the geometric diameter of the grains increase progressively from 3.51-4.22mm as moisture content increases. A screen aperture of 3.5mm was constructed. Grains’ surface area, volume and sphericity increased from 22.67-34.82mm², 8.19-13.98mm³ and 0.691-0.776g respectively. Mass, true density and terminal velocity of 1000 seed increased from 13.56-43.84g, 1548.91-1689.87kg/m³ and 2.69-4.58m/s respectively. The bulk density of millet also increased as moisture content increases but decreased beyond 12.5% moisture level indicating that millet floats on water and was transpoted with the aid of an auger. About 50kg of millet was poured into the destoner to occupy its ⅓ capacity while the remaining ⅔ was filled with water. Destoner output was at 95% efficiency.Key words: Destoner, Millet, Processing, Properties, Contaminants

An Improved Hybrid Micro-Grid Load Frequency Control Scheme for an Autonomous System

This paper presents an improved hybrid micro-grid load frequency control scheme for an autonomous system. The micro-grid system comprises of renewable and non-renewable energy-based Power Generating Units (PGU) which consist of Solar Photovoltaic, WT Generator, Solar Thermal Power Generator, Diesel Engine Generator, Fuel Cell (FC) with Aqua Electrolizer (AE). However, power produce from renewable sources in microgrid are intermittent in supply, hence make it difficult to maintain power balance between generated power and demand. Therefore, Battery energy storage system, ultra-capacitor and flywheel energy storage systems make up the energy storage units. These separate units are selected and combined to form two different scenarios in this study. This approach mitigates frequency fluctuations during disturbances (sudden load changes) by ensuring balance between the generated power and demand. For each scenario, Moth flame optimization algorithm optimized Proportional-Integral controllers were utilized to control the micro-grid (to minimize fluctuations from the output power of the non-dispatchable sources and from sudden load change). The results of the developed scheme were compared with that of Quasi-Oppositional Harmony Search Algorithm for overshoot and settling time of the frequency deviation. From the results obtained, the proposed scheme outperformed that of the quasi-oppositional harmony search algorithm optimized controller by an average percentage improvement of 35.95% and 28.76% in the case of overshoot and settling time when the system step input was suddenly increased. All modelling analysis were carried out in MATLAB R2019b environment. Keywords—Frequency Deviation, Micro-grid, Moth flame optimization algorithm, Quasi-Oppositional Harmony Search Algorithm.

Performance Evaluation of Pre-processing Techniques on Diabetes Prediction

Medical industry contains a large amount of sensitive data that must be evaluated in order to get insight into records. The nonlinearity, non-normality, correlation structures and complicated diabetic medical records, on the other hand, makes accurate predictions difficult. The Pima Indian Diabetes dataset is one of them, owing to the dataset's imbalance, large number of missing values and difficulty in identifying highly risk factors. Some of these challenges have been solved using computational approaches such as machine learning methods, but they have not performed ideally, with pre-processing techniques being recognized as critical to achieving correct findings. The goal of this work is to apply multiple pre-processing approaches to increase the accuracy of some simple models. These multiple pre-processing techniques are median imputation in which null values are substituted by finding the median of the input variables dependent on whether or not the patient is diabetic and then follow by applying oversampling and under-sampling procedures on both majority and minority votes. These votes are applied in order to address the problem of class imbalance as pointed out from the literature. Finally, the dimension reduction Pearson correlation is used to detect high-risk features since it is effective at quantifying information between attributes and their labels. In this study, these techniques are applied in the same order to Linear Regression, Naive Bayes, Decision Tree, K Nearest Neighbor, Random Forest and Gaussian Boosting classifiers. The utility of the techniques on the mentioned classifiers is validated using performance measures such as Accuracy, Precision and Recall. The Random Forest Classifier is found to be the best-improved model, with 95 percent accuracy, 94.25 percent precision and 95.35 percent recall. Medical practitioners may find the provided strategies beneficial in improving the efficiency of diabetes analysis. Keywords— Classifiers, diabetes, Pima Indian Diabetes dataset, pre-processing techniques

Device to Device Hybridization in 5G and Beyond: A Literature Review

Abstract- Device-to-Device (D2D) communication is one of the most promising technologies to enhance user experience in 5G and beyond. Despite the huge benefit anticipated, enabling D2D in cellular network has encounter some challenges, these challenges include peer discovery and synchronization, mode selection and interference management. However, resolving these challenges promises improved service delivery, spectrum efficiency and reduced latency amongst other gains. Attempts to enable D2D in both microwave and millimeter wave network gained some traction in recent years in a bid to enable wider coverage and utilization of the technology. Some of the research attempts, challenges and prosects are discussed in this paper.Keywords- Device-to-Device, Microwave, millimeter wave, Inter-cell Interference

Disruptive Engineering: Maximizing the Feedback Relationship between Industry 4.0 and the Nigerian Engineering Education Sector

The Fourth Industrial Revolution (4IR) continues to drive a fusion of physical, digital and biological technology in ways that are rewriting the norms in engineering practice by introducing new approaches such as Internet of things (IoT) and the Industry 4.0 paradigm, that are poised to also change the educational sector globally. Nigeria is yet to tap into the full potential of the Third Industrial Revolution. The relationship between 4IR and engineering education is considered as a positive feedback loop. 4IR technologies have great potential to enhance the quality of the Nigerian engineering education system, which in turn fosters an improved engineering education sector that is better-equipped to produce sustainable outcomes in Industry 4.0 era. This paper explores the potentials for application of 4IR technologies in improving the Nigerian engineering education delivery system by review and suggests ways through which the educational system can enhance the potentials of its educands to become competitive professionals in the disruptive-technology engineering era. It was concluded that the feedback relationship which exists between engineering education and Industry 4.0 needs rapt attention of stakeholders in order to address the reality of disruptive technology. Keywords— Industrial revolution, Internet of things, Engineering education, Positive feedback, Disruptive technology

Assessment of Moringa oleifera Seeds as a Natural Coagulant in Treating Low Turbid Water

This research examined the coagulating potential of Moringa oleifera seeds in treating low turbid water. The active ingredient of the seeds was extracted using Soxhlet Apparatus with hexane as the solvent, after which the coagulant was dosed from 0.03g/L to 0.4g/L and used to treat a water sample with a low Turbidity of 18.4NTU, yielding an optimum value of 4.90NTU, an optimum dose of 0.03g/L and a turbidity reduction of 100% when compared with the World Health Organization (WHO) standard which is 5NTU. The study affirms Moringa oleifera as an effective natural coagulant in low turbid water treatment and it is recommended for household water treatments. Keywords— Hexane, Low turbid water, Moringa oleifera, Natural coagulant, Soxhlet apparatus

Passenger Capacity and Safety: Investigating the Likelihood of COVID-19 Transmission in Public Transport Modes within Makurdi Metropolis

Following its outbreak in the Wuhan region of China, the spread of Corona Virus (COVID-19) across the world has threatened national and local authorities or policy makers and transport experts due to its effects on human mobility. This study investigated the transmissibility of COVID-19 among passengers in transit using public transport modes in Makurdi metropolis. Analytical simulation using stochastic search method called Genetic Algorithm (GA) technique was used to simulate the transmissibility of the infectious disease within enclosed spaces of transport modes based on layouts and capacities. The sum of arithmetic sequence was used as the objective function of individual arrivals in each mode, it was minimised to obtain optimum safe capacity. Capacities of public transport modes were subdivided into; Normal, Above Normal and Below Normal (50% of Normal). Findings of the experiments indicated that optimum safe capacity of minibuses, taxies, tricycles and motorcycles used in Makurdi metropolis were at 8, 3, 2 and 1 person respectively. This occurred at 50% capacity which agreed with findings of previous studies. An efficient and sustainable public transport policy framework was designed for policy makers and transport experts to help achieve safe travel and healthier living in Makurdi metropolis during the COVID-19 era. Keywords— COVID-19 transmission, Makurdi Metropolis, Modal Split, Mode capacity, Passenger Safety, Public Transport.