Articles in This Issue
Abstract
Milling includes a variety of different tasks and tools, ranging from small individual pieces to large, powerful group processes. It is one of the most commonly used techniques for producing custom parts with exact tolerances. Surface roughness of machined parts has a significant impact on the finished item's quality, which may have an impact on its tolerance and performance. This paper studies the prediction of the values of surface roughness of low-carbon steel AISI 1015 in milling operations. Three different machining parameters with nine variable samples are selected to investigate the resultant surface roughness of the AISI 1015 low-carbon steel samples, including different spindle speeds, feed rates, and depths of cut. The results revealed that the feed rate of 100 mm/min at a spindle speed of 930 rpm and a depth of 1.5 mm produced the lowest surface roughness (Ra) value of 1.170 µm, while the feed rate of 300 mm/min at a spindle speed of 1100 rpm produced the greatest surface roughness value of 2.605.
Abstract
Switched reluctance motor (SRM) is an electric motor works based on the reluctance torque produced due to the variation of the rotor pole position with respect to stator poles. This paper adopts a thermal analysis on a 4-phase, 8/6 pole, 550W, SRM. Lumped parameters thermal network method(LPTN) is used in this analysis based on a combination of RMXprt/Motor-CAD software, in two- dimensional(2D), steady-state, with different cooling methods, and with different loading conditions. Motor losses like core losses, copper losses, and mechanical losses are regarded as the heat sources in SRM which are calculated by RMXprt software. The thermal analysis achieved by Motor-CAD includes displaying the temperature distribution on different motor parts like stator winding, stator poles, stator yoke, rotor poles, rotor yoke, shaft, covers, and housing. The analysis results showed the increasing temperature distribution on different motor parts with increasing motor loading conditions. Also, this temperature distribution is recorded using three different cooling methods. The comprehensive thermal analysis applied in this work will assist the motor designer in choosing a better motor thermal design without needing to produce and test costly prototype motors.
Abstract
This study aims to investigate the durability properties and microstructural changes of self-compacting concrete (SCC) incorporating waste polyethylene terephthalate (PET) as fibers and as fine aggregate replacement. This is after exposed to saline environment (Alkalies, Sulphates, and Chlorides). PET effect into two forms was also evaluated for routine rheological properties of SCC and mechanical strength before and after exposure to sulphate salt. Five proportions of each form of PET incorporation in SCC mixtures were utilized. The volume fractions considered for PET as fibers were (0.25, 0.5, 0.75, 1.0, and 1.25)% by volume, with aspect ratio of 28%, and (2, 4, 6, 8, and 10)% by volume for fine aggregate replacements. Results indicated that the inclusion of PET adversely affected fresh propertis especially high proportions of PET as fine aggregate. Alkali silica reaction (ASR) outcomes illustrated an enhancement in the mix containing PET fibers, while fine-PET mix was slightly enhanced. Magnesium sulphate reduced mass and compressive strength of all mixes in percentages ranging from (0.18-0.90) % for mass loss and from (0.47-55.13) % for compressive strength loss. Ultrasonic pulse velocity (UPV) and dynamic modulus of elasticity (Ed) increased due to the sulphate impact except for M0.5 and M10 which decreased in both tests. Chloride's theoretical and modelled results illustrated higher diffusion coefficients and lower surface chloride content of fiber-PET mixes as compared to fine-PET mixes. The predicted SCC cover depths for fiber-PET mixes were lower than those predicted for fine-PET mixes for 20 and 50 years of service life design.
Abstract
A fundamental score of this paper is to explain in detail how to create a 3D-provided modeled scene by data obtained at minimal cost to the client or users by manufacturing a smart, automated system for heritage documentation (SAS-HD). The steps can be classified by manufacturing, parts connection and simulation, selection of work sites, and obtaining data. The most important acquiesced data are digital images which are fundamentally used by the structure from motion (SFM) approach in MATLAB. The obtained images were subjected to sequenced tips by getting 3D sparse points of each object. Two objects have been considered by this article in an indoor case study: first feature is Ishtar Gate, and the second one is the winged ball inside Iraqi museum in Baghdad capital. The results are promising; hence 3- Structure From Motion SFM method has been utilized to document heritage by manipulating 3D models on MATLAB interphase, which is approved for its efficiency as well as its quick, super advanced processing steps.
Abstract
Due to the expansion of industrial operations globally in recent years, waste output has risen. So these wastes must be reduced by recycling and reusing to achieve environmentally friendly buildings and find various alternative materials in critical cases. The statistical indicators are used as practical study including Multiple linear regression (MLR) and artificial neural network (ANN) models. The study's goals were to assess the effectiveness of granite waste (GW) as a replacement for cement, sand, plastic, and binder in specific building applications and the relationships between MLR and ANN approaches. Results show the efficiency of adding granite waste to some construction stages and replacing it with cement in the mixture and examining its strength, it gave excellent results in addition to good results for its use as a binder in cement mortar, while the results were weak when used as a substitute for sand and plastic in insulator because it's classified as fine sand, Therefore, it cannot be used as a substitute for sand in the construction. The statistical models give an effective indicator to use GW as an alternative material ( binder and cement) based on the coefficient of correlation (R2) for the two models MLR and ANN equal to 83.4 % and 80 % respectively.
Abstract
Obesity is the excess of body weight relative to height above the desired level as a result of excessive increase in the ratio of body fat mass to lean mass. It causes many health problems due to its negative effects on body systems (cardiovascular system, musculoskeletal system, gastrointestinal system, respiratory system, skin, endocrine system, genitourinary system) and psychosocial status. In this study is aimed to effective detection of the eating and physical condition-based obesity stages using machine learning algorithms. The dataset contains data for the estimation of obesity stages in individuals from Mexico, Peru, and Colombia and is available as open source. There are 2111 records and 17 attributes in the dataset. In the records, obesity stages were categorized as insufficient weight, normal weight, overweight level I, overweight level II, obesity type I, obesity type II and obesity type III. The 10-fold cross-validation method was used to validate the model and the performances of the Support Vector Machine (SVM), Random Forest (RF), and Multilayer Perceptron (MLP) classification algorithms were compared. It has been determined that the highest performance among the algorithms whose performances are compared belongs to the RF Algorithm (95.78%). This paper’s abstract has been presented at the International Conference on Computational Mathematics and Engineering Sciences held in Ordu (Turkey), / 20-22 May. 2022.
Abstract
In order to increase output power and thermal efficiency, the temperature going into a gas turbine is much higher than the point at which the material would melt. In order to protect the airfoil of a gas turbine from hot gas and, as a result, extend the blade's life, new internal and film cooling arrangements must be developed immediately. When the incoming air is heated, the gas turbine's output rises proportionately as well. The power output of a gas turbine is determined by the amount of mass flowing through it. Because of this, electricity generation decreases on warm days due to a decrease in air density. It takes a 1% rise in air temperature to reduce power production by 1%. The purpose of this research is to discuss current strategies for cooling incoming air to gas turbines. Mechanical chillers, evaporative coolers, and fogging methods have all been examined. This study focuses primarily on the fogging inlet air cooling system. There are many ways to cool the air going into the engine, but the high-pressure intake fogging method has become more popular over the past ten years because it costs less and makes a big difference in power.
Abstract
Water treatment sludge (WTS) is a byproduct generated during the treatment of wastewater. In recent years, researchers have explored the potential of using WTS as a soil stabilizer to improve the geotechnical properties of soils. In this review, we will examine the current state of knowledge on the use of WTS for this purpose. The organic matter content of WTS is usually high and can range from 30% to 60%. The high organic matter content makes WTS a potential source of nutrients for plants, and it can also enhance soil structure and water retention. Another important consideration is the environmental impact of using WTS. The use of WTS can be an eco-friendly alternative to chemical stabilizers, which can have adverse effects on the environment. However, there are concerns about the potential for heavy metal contamination in WTS. To mitigate this risk, it is recommended to conduct thorough testing of WTS before using it as a soil stabilizer. Finally, the use of WTS as a soil stabilizer has the potential to improve the geotechnical properties of soils. However, it is essential to consider factors such as the type and dosage of WTS, the soil type, and the environmental impact before using it. Further research is also needed to explore the potential of using WTS in different soil types and environmental conditions.
Abstract
Cosmetic surgery is more prevalent in the world in recent years. A beautiful and flawless face is everyone's dream. Aging, environmental factors, disease, or poor diet are among the factors that influence body wrinkles. Various methods are used to reduce these lines. It can be said that the simplest and most effective solution is to inject cosmetic fluids into these areas. But, due to the increase in facial injections using cosmetic fluids, which are considered toxins, the risk of injury to the surrounding facial nerves and injury to one of the main facial nerves is increasing, creating a catastrophe or deformation in the face irreversibly. Deep learning algorithms have been used to determine whether cosmetic fluids are injected or not. Deep Convolutional Neural Networks (CNNs), VGG16, ResNet....etc deep learning algorithms have demonstrated excellent performance in terms of object detection, picture classification, and semantic segmentation. all the suggested approach consists of three stages: feature extraction, training, and testing/validation. Deep learning technology is used to train and test the system with before and after photographs. Numerous investigations have been carried out using various deep learning algorithms and databases the main goal is to attain maximum accuracy to ensure that injected cosmetic fluids by specialists have been injected in safe areas in addition to facial recognition and determining whether or not the person received an injection. The most used databases are IIITD plastic surgery and HDA_Plastic surgery.
Abstract
Reverse osmosis (RO) is a membrane filtering system that uses a semipermeable membrane to remove contaminants from water before sending the purified water on to be used in a number of settings, such as households and factories. The goal of this study is to investigate the process of reverse osmosis as well as the current status of the membrane materials that are used in the process. These membrane materials are the driving elements in the process. This review also includes a discussion on the cleaning of membranes, the utilization of RO systems for a number of applications, and new advancements in the field of reverse osmosis. In the process of cleaning water, reverse osmosis, also known as RO, is a potent technique that makes use of a semi-permeable membrane to remove hazardous bacteria as well as dissolved particles. This technique is utilized on a regular basis for the purpose of desalinating seawater for use in drinking, agricultural, and industrial applications.
Abstract
In recent decades, functionally graded porous structures have been utilized due to their light weight and excellent energy absorption. They have various applications in the aerospace, biomedical, and engineering fields. Therefore, the balance between material strength and light weight is the goal of the researchers to decrease the cost. Samples of PLA material were designed and manufactured using a 3D printer according to international standard specifications to study the effect of porosity gradient through thickness. An experimental three-point bending test was performed, and then simulations were performed using ANSYS 2022 R1 software on samples with functionally gradient different porosity layers to verify the experimental results. The results from the experiment and the numerical values were in excellent alignment with an error rate of no more than 13%. The maximum bending load and maximum deflection of the beam were specified experimentally and compared with the numerical solution. The maximum bending and the maximum deflection When the porosity layer in the middle of the beam, matched the ideal maximum bending load (190,194) N experimentally and numerically, respectively. The maximum deflection (5.9,6.4) mm experimentally and numerically, respectively was obtained in samples with varying porous layers.