Journal of Engineering Research最新文献

Occurrence of tracking and erosion on surface of polymer insulator leads to breakdown of these materials and has negative impact on their quality. Contaminants forms surface layer on insulators and chemically interact with it. This effect reduces smoothness of surface insulator and forms conducting paths. It allow passage of higher values of leakage current and cause ionization of field around insulator and rise temperature of surfaces, this leads to formation phenomenon of tracking and erosion.it cause deterioration, ageing and collapse of insulator, which affect safety of electric system. How to significantly enhance the tracking and erosion properties of nitrile butadiene rubber (NBR) are a major topic in electric insulators. With a view to enhancing the tracking and erosion properties of NBR used in power systems, nanoparticles are usually added to pure materials to enhance their electrical and physical properties. This work deals with experimental studies on tracking and erosion properties on NBR loaded with [0, 0.5, 1, 1.5, and 3 part per hundred part of rubber (Phr.)] titanium dioxide (TiO₂) nanoparticles. Composite materials have been experimentally tested by inclined plane test (IPT) according to the ASTM D2303 standard. When it is necessary to explore a new insulating material, the inclined plane test is used. This is because IPT is used to evaluate the properties of laboratory modified polymers under different voltages. The times to track during the test were recorded. Data processing, analog to digital systems, and data acquisition have been used to measure leakage current passing through samples. When comparing result of leakage current measurements, it was noted that its value was lower for modified samples compared to virgin samples. This positive effect indicates to enhancement of NBR as a result of formation of stable chemical bonds.

The use of electric motors instead of internal combustion engines has been increasing in the automotive industry, particularly over the past decade. Studies attempting to use electrical energy as the only source to obtain the required movement from the wheels have run into difficulties due to the limitations of electricity storage units. Li-ion batteries as a power source have shown some interesting characteristics, especially in electric vehicles, but there is still research for development in the storage device. Findings from this research recommend combining battery and supercapacitor technology to power an electric scooter. Both of these power sources are modulated for maximum efficiency in transferring energy to the motors. For this reason, a fuzzy logic-based control algorithm for energy management is developed to keep the battery and supercapacitor at their optimal states of charge (SOC), meet load demands during braking and counter-loading, and boost the energy system's independence. An electric scooter's performance under varying loads is simulated in MATLAB and Simulink to verify the effectiveness of the EMS. The simulation results findings validate the usefulness of the proposed approach and present the novel EMS as very good solution for energy management problem using the fuzzy logic expert system to take decision.

This study seeks to investigate the heat transfer analysis of hybrid nanofluids containing fractionalized water and kerosene oil, which flow through a vertical channel via convection. To represent the problem in terms of fractional partial differential equations, we utilized the Prabhakar time-fractional derivative, a recent advancement in the concept of fractional derivatives. The governing equations were then solved using physical initial and boundary conditions that include momentum, concentration, and energy equations. Stehfest and Tzou's Laplace inversion techniques are used to provide semi-analytical solutions for governed equations, such as temperature, concentration, and momentum profiles, and we applied the fractional Laplace transformation to find solutions in the transform domain. Furthermore, the resultant solutions in tabular form are also derived using Tzou and Stehfest's numerical methods for Laplace inversion to ensure the accuracy of our findings. According to our research, an increase in volumetric fraction causes a reduction in fluid velocity. Due to the physical properties of the investigated nanoparticles, the water-based hybrid nanofluid has a bigger effect on the temperature and momentum profile than the kerosene oil-based hybrid nanofluid.

Achieving financial sustainability is a critical challenge for Public higher education institutions ‎worldwide. This study aims to provide modified strategic planning tools for planning financial ‎sustainability in higher education institutions. The paper employs modified forms of three ‎strategic planning tools: a strategy map (SM), the balanced scorecard (BSC), and business-‎model-canvas (BMC), which were applied to support the analysis of planning financial ‎sustainability at King Abdulaziz University (KAU). These tools enhance the planning process ‎and contribute to the outcomes. The paper also draws a roadmap of key milestones for ‎financial sustainability at the university by identifying sources and indicators of the university's ‎financial capacity. This paper contributes to the literature on financial sustainability in higher ‎education institutions and offers novel insights for other universities that seek to adopt similar ‎plans. Furthermore, four recommendations are suggested to boost business development and ‎connect with the university investment network. These recommendations involve investing in ‎competent human resources, increasing financial assets, and utilizing technical capabilities. ‎Further research includes examining the applicability of this novel approach in other contexts ‎and identifying potential challenges and limitations of implementing and achieving financial ‎sustainability.

Assembly line balancing is a compulsory approach which enables mass production of similar parts with proper efficacy. Multiple heuristics are proposed in literature to solve single model assembly line balancing problems (SALBP-1). Previous work has focused on developing and evaluating assembly line balancing heuristics and apply them to different fields. Other work investigates the factors affecting the performance of particular assembly line balancing heuristic. However, there is still a need for a guideline for selecting the most suitable heuristic for a particular application with insights into multiple performance measures. This research presents a grey relational analysis (GRA)-based approach to aid process designers in selecting the heuristic generating that yields the best line balancing. Specifically, combinations of factors of cycle time, order strength, number of tasks, and time variability are considered as operational setups of the line balancing process. The solution of each setup is solved by each heuristic, and the performance of the solution is evaluated. Then, GRA is applied to rank the heuristics on basis of the resulting grey rational grades. The proposed approach provides useful insights into the combinations suitable for a particular heuristic. In this study, time variability and cycle time are shown to have the greatest impact on the overall performance of the considered heuristics.

When sensor nodes in wireless sensor networks (WSNs) have limited energy, data minimization is crucial. Usually, data communications use up energy. A sensor node's lifespan can frequently be increased by sending and receiving the proper quantity of data. The PISAE (Partially Informed Sparse Autoencoder) is a state-of-the-art unmapped neural network architecture designed to reconstruct all sensor inputs from a limited number of sensors. It is presented in this publication. Use this architecture to create a system for selecting sensors. We now propose the cross-layer based opportunistic routing protocol (CORP) as an opportunistic routing mechanism for WSNs. In order to cut down on processing time and energy consumption and increase the dependability of data transfer, the best way is selected utilizing the CORP technique, which is suggested.For energy-efficient routing based combinatorial random sampling bat optimisation (ERFN-CSSBO), we also suggest using fuzzy neural networks. This enables you to conserve energy, increase the lifespan of your wireless sensor network, and keep your energy consumption in check. With CSSBO (Combined Random Sampling Prevosti Bat Optimisation), the best path is identified by integrating features (such as distance, energy, trust, and internode measurement connection stability) from all the bats.The key challenge in WSN is choosing cluster heads (CH). K-Medoid is used to enhance sensor node clustering. Important considerations include the effect on quality of service (QoS), sensor node position, proximity, and energy state needs. This study combines Hybrid BFO (Bacterial Foraging Optimization) and HSA (Harmony Search Algorithm), two well-known optimization techniques, to pick cluster heads in wireless sensor networks that are optimal in terms of distance and energy. On-task completion. The outcomes of the simulation indicate that the proposed technique improves QoS. Endpoints, throughput (1.0 Mbps), (98.5 % of packets are forwarded), and packet loss rate (1.5 %), and other QoS factors are all included in the performance statistics plotted. It performs better than conventional routing protocols in terms of network lifetime (6100 rounds), delay at both ends (1.5 s), and energy usage (30.35 mJ).

The major goal of the present contribution is to fully examine the linear stability analysis of two-dimensional nanofluid flow over a moving as well as a static wedge under the impact of an adverse or favorable pressure gradient. Using similarity variables, the velocity profiles for the mean flow are obtained by converting the mean flow equations into a nonlinear ODE that is numerically solved using the fourth-order Runge-Kutta method. The stability equations for the flow of nanofluids are solved using the spectral Chebyshev collocation technique. Numerous numerical simulations are performed to understand the impact and influence of various parameters such as the concentration of the selected nanoparticle, wedge velocity, pressure gradient, and types of nanofluid. The obtained outcomes indicate that the critical dimensionless value of Reynolds number of instability decreases significantly with increasing wedge velocity in the same direction of fluid motion, with increasing concentration of nanoparticles, and when the pressure is adverse, which makes the flow more stable. On the contrary, the flow becomes unstable when the wedge moves against the fluid flow's direction in the instance of a favorable pressure.

This research presents a review of computer-based production planning, scheduling, and control (CPPSC). The purpose of this study is to illustrate the progress made in the current research on the planning and control of production and scheduling. Twenty-two papers selected for this study focused on the recent trends, approaches, and problems associated with CPPSC. Progress in the manufacturing paradigm in engineering justified why CPPSC could be applied to a set of systems to increase the production of goods and services and to further highlight the relevance of the decisions made and why substantial progress was made in the development of the theory regarding decision making in each of those areas in the past. The integration of line balancing and process plan selection in the Smart Manufacturing System would lead to more efficient production processes, reduced downtime, and improved resource utilization. Additionally, it would provide a comprehensive view of the production environment, allowing for data-driven decision-making and optimization strategies. To demonstrate the effectiveness of this novelty approach, researchers could set up a real-world pilot in a manufacturing facility. They can compare production performance before and after implementing the AI-driven Smart Manufacturing System. Key performance indicators (KPIs) such as production throughput, machine utilization, cycle time, and lead time can be used to quantify the improvements. Furthermore, case studies and simulation scenarios can be used to validate the system's potential benefits in various manufacturing settings.