Yanbu Journal of Engineering and Science (YJES)
Not a member yet
202 research outputs found
Sort by
FRICTION BEHAVIOR OF CARBON FIBRES REINFORCED EPOXY FLOOR COATED BY POLYURETHANE AND SAND
No full textFriction coefficient displayed by contact and separation as well as sliding when bare foot and foot wearing rubber contacting epoxy reinforced by carbon fibres (CF) and coated by polyurethane and sand particles is investigated. Generation of electrostatic charge (ESC) and its effect on friction coefficient will be discussed. It was found that ESC generated from contact and separation of PU coated by sand particles (SiO2) and reinforced by CF recorded much higher values than PU and epoxy surfaces. Slight decrease in ESC was observed as the distance of CF from friction surface increased. ESC generated from sliding of PU coated by sand against bare foot displayed relatively higher values than that measured for epoxy and PU surfaces. Presence of sand increases friction coefficient due to the abrasive action of particles in bare foot surfaces which increases ESC. The penetration of sand particles into bare foot increases the contact area and hence increases ESC. Friction coefficient values recorded relatively higher values than that shown for epoxy and PU coating. ESC generated from contact and separation of rubber footwear and PU coated by sand displayed lower values than that observed for bare foot. In condition of sliding of PU coated by sand and reinforced by CF against rubber, it was found that ESC displayed values higher than that observed for contact and separation. The influence of sand was more pronounced during sliding than contact and separation. Friction coefficient decreased with increasing the distance of CF location from the surface. The friction values guaranteed the good adhesion required for floor materials
MICROCONTROLLER-BASED ULTRASONIC SENSORS SYSTEM FOR MOBILE ROBOT OBSTACLE AVOIDANCE
No full textThe complete contact-less sensory coverage of the workspace represents a fundamental difficulty for the navigation of autonomous mobile systems. Usually, several sensor systems are used in combination which could be complementary or redundant. The task of combining the information into a usable form, suitable for making navigation decisions, is known as sensor fusion. The use of the microcontroller in the robot system gives the opportunity to store a large amount of data gathered about the environment. The algorithms designed for obstacle avoidance during navigation are also easily executed. In this paper, a microcontroller system designed to control the navigation of a mobile robot while avoiding obstacles in its route is presented. A system of 24 ultrasonic sensors was designed and the operation algorithms were described
Modelling and performance assessment of a two-bed adsorption chiller at different operating conditions
No full textThe study aims to assess the performance of an adsorption chiller using the Maxsorb III- methanol as an adsorbent pair. A modified transient lumped parameter model was deve- loped to evaluate the dynamic behavior of the system at various operating parameters. Methanol is used as refrigerant as it has a significant latent heat of evaporation, high no- rmal boiling point, low melting point and environmentally friendly. The results showed that the modified transient lumped parameter model can predict well the dynamic behav -ior of the adsorption chiller under different operating conditions. The system was able to produce about 13.65 kW (227 W kg-1) cooling capacity with a thermal COP of 0.73 at 85 and 30 oC driving source and cooling temperatures respectively. In addition, simulat -ion tests were made to compare the performance of the Maxsorb III-methanol system with the different working pairs at the same physical dimensions of the present system. components and operating parameters. At heat source temperatures of 85 oC which can be gained from waste heat or solar energy, the COP of the Maxsorb III-methanol cycle was about 12.0%, 44.0% and 6.6% higher than that of ACF-ethanol, silica-gel-water and activated charcoal/methanol cycles. The Maxsorb III/methanol adsorption cycle can wor k effectively with low grade heat sources, which can be gained from renewable energy or waste heat sources
Public Safety in Smart Cities: An Experimental Study to Monitor and Record Vehicles’ Movements
No full textThis research addresses the critical issue of enhancing public safety in smart cities, with a particular focus on industrial cities in Saudi Arabia. Despite the advanced infrastructure and high safety standards in industrial cities, there are safety challenges, particularly the vulnerability of residential properties to burglaries during holidays and extended breaks. To mitigate these risks, the research proposes leveraging existing infrastructure to implement surveillance systems that monitor vehicle movements using RFID technology and smart sensors, thereby enhancing safety, supporting law enforcement in crime detection, and protecting local communities. The study also acknowledges the reduced social interaction often associated with the heavy reliance on technology in smart cities, emphasizing the need to foster social connections alongside technological advancements. A proposed vehicle monitoring solution is introduced, capable of detecting and identifying registered and unregistered vehicles while recording movement data in urban areas for subsequent analysis. Future research is recommended to expand this concept, focusing on real-world implementation with real-time connectivity and cloud-based services integrated into secure and certified database systems
Improving Arabic Coffee Production through Disease Detection based AI Frameworks
No full textCoffee is the second most traded commodity globally after oil and represents a major source of income in many countries. Kingdom of Saudi Arabia has a great interest in growing and expanding of coffee in line with the Saudi Green Initiative as implementation of Vision 2030 AD. This expansion is accompanied by a greater spread of insect pests and the emergence of diseases affecting coffee. Recently, machine learning technologies have been beneficial in the agricultural era in detection and classification of fruit and tree diseases. The study initially focuses on kind of disease that appears in the leafy area of the coffee plant, which is susceptible to many diseases such as Cercospora spp., magnesium deficiency, and others. Deep learning, convolutional neural networks (CNN), support vector machines (SVM), and other imaging and machine learning techniques are used in this paper to detect and classify leaf diseases. The JMuBEN and JMuBEN2 databases from Kenya were used in the first experiment, and the Fyfa Mountains database from the Jizan region was used in the second experiment to automatically detect and classify coffee tree leaf disease. In an SVM model, data preprocessing and data transformation methods are used to generate accurate information to train the model. Grid search is also used across the parameter grid to optimize the estimator parameters used in applying the model. The experimental results showed superior performance compared to many modern basic methods in terms of accuracy, reaching 100%. CNNs have also proven their effectiveness and accuracy in the fields of pattern recognition and image classification. As a result, a CNN model is introduced that takes advantage of transfer learning, which significantly reduces the model training time
The Use of Smart Sensors to Enhance Road Safety: An Experimental Study to Explore the Usability of Smart Traffic Light Systems with Emergency Vehicles
No full textThe evolving landscape of transportation systems is being reshaped by the integration of sensors and Internet of Things (IoT) technology, particularly in the context of traffic light systems. These innovations aim to transform traditional traffic lights into smart devices capable of being controlled by emergency vehicles (EVs) to ensure safe passage, thereby enhancing road safety, and reducing intersection accidents. However, there are challenges in implementing such technologies and gaining the trust of EV drivers navigating busy intersections. The traditional fixed-time traffic signal plans are contrasted with the dynamic adjustment made possible by smart sensors and applications, which collect real-time traffic data and adapt signal timings to changing conditions, reducing congestion, and enhancing traffic flow. However, security concerns arise, necessitating the strengthening of systems with advanced technologies to address potential security and safety issues. The technological advancements have a significant impact on the transportation industry. Smart sensors in streetlights play a crucial role in solving long-standing transportation issues, and machine learning is employed for data analysis and traffic forecasting, benefiting both regular and EV drivers. Further research is needed to advance technologies like IoT and smart sensors and to integrate GSM sim cards and GPS to support EV drivers in finding the quickest route to their final destinations. EVs are becoming more than vehicles, evolving into smart devices equipped with technical tools allow drivers to control traffic lights, ensuring a clear path and more safety
A SURVEY OF PRIVACY PRESERVING DATA MINING ALGORITHMS
No full textData mining is the extraction of vast interesting patterns or knowledge from huge amount of data. In recent years, with the explosive developments in Internet, data storage and data processing technologies, privacy preservation has been one of the greater concerns in data mining. Privacy preserving data mining (PPDM) has become increasingly popular because it allows sharing of privacy sensitive data for analysis purposes. Privacy-preserving data mining considers the problem of running data mining algorithms on confidential data that is not supposed to be revealed even to the party running the algorithm. There are two classic settings for privacy-preserving data mining (although these are by no means the only ones). In the First setting, the data is divided among two or more different parties; the aim is to run a data mining algorithm on the union of parties\u27 databases without allowing any party to view another individual\u27s private data. In the second setting, some statistical data that is to be released (so that it can be used for research using statistics and/or data mining) may contain confidential data; hence, it is first modified so that (a) the data does not compromise anyone\u27s privacy, and (b) it is still possible to obtain meaningful results by running data mining algorithms on the modified data set. In recent years, PPDM has been studied extensively, because of the wide proliferation of sensitive information on the internet. This paper provides a wide survey of different PPDM algorithms and analyses of the representative techniques for PPDM, and points out their merits and demerits. Finally the present problems and directions for future research are discussed
Using Arithmetic Optimization Algorithm to Allocate and Size Wind Energy Systems in RDSs
No full textRecent years have seen a marked increase in the world\u27s energy needs. Numerous studies have been conducted to examine distributed generation (DG) utilizing renewable energy sources (RESs) in order to address this need. The number of environmental problems that are raised by the usage of traditional power plants is also decreased by these renewable sources. The ideal position and size of the RESS-DG significantly influence the bus volta- ge profile, power quality, and efficiency of Radial Distribution Systems (RDS) because of power losses. In this study, the use of wind energy systems as a DG source in RDS is investigated. One of the most common RESs used as DG sources, the ideal location and size for wind system, was chosen to demonstrate this enquiry. The goal of this optimizat- ion work, which used the Arithmetic Optimization Algorithm (AOA), was to increase syst- em efficiency by minimizing power losses and improving the voltage profile and power quality. Two widely used RDS, including the IEEE 31 and 69 bus systems, have been us- ed to evaluate how well the recommended technique has been implemented. Genetic Al- gorithm (GA) is offered to examine the efficacy of the recommended AOA. The findings show that the used AOA approach can pinpoint the appropriate size and positioning of a wind farm in order to reduce power loss, enhance voltage profile, and outperform other existing tactics with superiority over GA
THERMO-ECONOMICS ANALYSIS OF GAS TURBINES POWER PLANTS WITH COOLED AIR INTAKE
No full textGas turbine (GT) power plants operating in arid climates suffer a decrease in output power during the hot summer months because of insufficient cooling. Cooling the air intake to the compressor has been widely used to mitigate this shortcoming. An energy analysis of a GT Brayton cycle coupled to a refrigeration cycle shows a promise for increasing the output power with a little decrease in thermal efficiency. A thermo-economics algorithm is developed and applied to an open cycle, Hitachi MS700 GT plant at the industrial city of Yanbu by the Red Sea in the Kingdom of Saudi Arabia. Result shows that the enhancement in output power depends on the degree of chilling the air intake to the compressor (a 12 - 22 K decrease is achieved). For this case study, maximum power gain ratio (PGR) is 15.46%, at a decrease in thermal efficiency of 12.25%. The cost of adding the air cooling system is also investigated and a cost function is derived that incorporates time-dependent meteorological data, operation characteristics of the GT and the air intake cooling system and other relevant parameters such as interest rate, lifetime, and operation and maintenance costs. The profit of adding the air cooling system is calculated for different electricity tariff
EXPERIMENTAL INVESTIGATION OF THE PART-LOAD PERFORMANCE AND EMISSIONS OF A SPARK IGNITION ENGINE FUELLED WITH GASOLINE RON95 AND RON97
No full textThe effect of gasoline RON95 and RON97 on performance and exhaust emissions in spark ignition engine was investigated. The results were obtained from a 1.6 liter, 4- cylinder Mitsubishi 4G92 engine with compression ratio 11:1. The engine was run at constant speed between 1500 and 3500 rpm with 500 rpm increment at various part- load conditions from 0 to 5 Nm with 1.25 Nm increment. An engine control system, a hydraulic dynamometer and a portable exhaust gas analyzer were used to control engine operations and record engine performance, cylinder pressure and emissions data. Results showed that RON 95 fuel produced higher engine performance for both no-load and part-load tests condition. Gasoline RON95 produced 4.4% higher brake torque, brake power, brake mean effective pressure as compared to RON97. The difference in engine performance between these two fuels was more significant at higher engine speed and loads. RON97 yielded 2.8% higher fuel conversion efficiency compared to that of RON95. RON97 fuel yielded 2.3% lower brake specific fuel consumption throughout all load condition. In terms of exhaust emissions, RON95 fuel produced 7.7% lower NOx emission but higher CO2, CO and HC emissions by 7.9%, 36.9% and 20.3% respectively as compared to RON 97