The design aspects and performance of the Solar Water Pumping Systems (SWPS) have been discussed already in earlier literature. But, unlike other authors, this paper is presented with the novelty of prediction of output parameters of SWPS like output energy of photovoltaic (PV) array, the energy in excess that can be supplied to the grid, load energy, and the discharge of water for irrigation. Non-linear curve fitting through the Polynomial Regression Analysis (PRA) method is used to achieve the above-said parameters. Primarily, the objective of this paper is to predict these parameters directly by using the solar insolation values. The predicted values of these parameters are compared with estimated values. This method of approach is used to reduce the complexity in the estimation of all the above parameters using the conventional procedure presented in this paper.
{"title":"An innovative method of forecasting the performance parameters of the Solar Water Pumping System","authors":"","doi":"10.59018/1123300","DOIUrl":"https://doi.org/10.59018/1123300","url":null,"abstract":"The design aspects and performance of the Solar Water Pumping Systems (SWPS) have been discussed already in\u0000earlier literature. But, unlike other authors, this paper is presented with the novelty of prediction of output parameters of\u0000SWPS like output energy of photovoltaic (PV) array, the energy in excess that can be supplied to the grid, load energy, and\u0000the discharge of water for irrigation. Non-linear curve fitting through the Polynomial Regression Analysis (PRA) method is\u0000used to achieve the above-said parameters. Primarily, the objective of this paper is to predict these parameters directly by\u0000using the solar insolation values. The predicted values of these parameters are compared with estimated values. This\u0000method of approach is used to reduce the complexity in the estimation of all the above parameters using the conventional\u0000procedure presented in this paper.","PeriodicalId":38652,"journal":{"name":"ARPN Journal of Engineering and Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140482305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Waste in millions of tons is produced in the world each year and most of it is not recyclable. Furthermore, recycling waste consumes energy and produces pollution. In addition, the accumulation of waste in suburbs and disposal of waste is dangerous for the environment. Using waste material in concrete production is an appropriate method for achieving two goals i.e. eliminating waste and adding positive properties in concrete. Since the green concrete industry is expanding, it is necessary to evaluate concrete that contains waste from all aspects to determine its capability. This research consists of analyzing the use of waste as a partial substitute for sand. Leading waste material that has been used as substitutes is highlighted and the characteristic of the resulting concrete is evaluated in this research. Among other findings, rubber was found to have improved fire resistance and ductility in concrete, and agricultural and Polyethylene terephthalate (PET) wastes were successfully used in non-structural concrete, while glass helped to improve thermal stability. In this research aggregate and sand is replaced by waste materials of Polyvinyl Chloride (PVC) and Glass to check their effect on the mechanical properties. Lab tests were performed to analyze the flexural behavior of concrete samples having waste material. The results show how partial replacement of sand affects the behavior of concrete and based on that specify the conditions where it can be used. The results show that Young’s modulus, maximum bending stress, and bending deflection varies with the percentage composition of PVC and glass. Bedding stress and bending deflection decrease with PVC and glass composition up to 35%. Although Young’s modulus is fluctuating bending deflection will decrease.
{"title":"Effect of partial sand replacement with PVC and glass mix on flexural behavior of concrete","authors":"","doi":"10.59018/1123297","DOIUrl":"https://doi.org/10.59018/1123297","url":null,"abstract":"Waste in millions of tons is produced in the world each year and most of it is not recyclable. Furthermore,\u0000recycling waste consumes energy and produces pollution. In addition, the accumulation of waste in suburbs and disposal of\u0000waste is dangerous for the environment. Using waste material in concrete production is an appropriate method for\u0000achieving two goals i.e. eliminating waste and adding positive properties in concrete. Since the green concrete industry is\u0000expanding, it is necessary to evaluate concrete that contains waste from all aspects to determine its capability. This\u0000research consists of analyzing the use of waste as a partial substitute for sand. Leading waste material that has been used\u0000as substitutes is highlighted and the characteristic of the resulting concrete is evaluated in this research. Among other\u0000findings, rubber was found to have improved fire resistance and ductility in concrete, and agricultural and Polyethylene\u0000terephthalate (PET) wastes were successfully used in non-structural concrete, while glass helped to improve thermal\u0000stability. In this research aggregate and sand is replaced by waste materials of Polyvinyl Chloride (PVC) and Glass to\u0000check their effect on the mechanical properties. Lab tests were performed to analyze the flexural behavior of concrete\u0000samples having waste material. The results show how partial replacement of sand affects the behavior of concrete and\u0000based on that specify the conditions where it can be used. The results show that Young’s modulus, maximum bending\u0000stress, and bending deflection varies with the percentage composition of PVC and glass. Bedding stress and bending\u0000deflection decrease with PVC and glass composition up to 35%. Although Young’s modulus is fluctuating bending\u0000deflection will decrease.","PeriodicalId":38652,"journal":{"name":"ARPN Journal of Engineering and Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140483925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Breast tumors are a dangerous disease among women worldwide. They are the second leading cause of death among all forms of cancers in women. Their early detection is critical to increasing the survival rate of women. Mammography is a reliable screening technique in the early detection of abnormal breast tissue severity. Radiologist abnormalities in the breast tissue, radiologists employ mammography. However, detecting breast abnormalities through digital diagnostic techniques by a radiologist could be time consuming. Consequently, computerized studying of digital mammography has emerged via the development of CAD systems. Several CAD systems have been developed for breast cancer detection. However, obtaining a satisfactory performance of CAD systems is a challenging task. We propose a CAD architecture for the classification of breast tissues as either benign or malignant using an LS-SVM classifier with various kernels namely linear, quadratic, polynomial, MLP, and RBF kernels. From the experimental outputs, it is clear that GA based LS-SVM classifier with RBF kernel outputs classification accuracy of 94.59% for normal/abnormal case classification is better, when it is compared with all other kernels. It is also stated that GA based LS-SVM classifier with RBF kernel produces a better classification accuracy of 98.26% for benign/malignant case classification when it is compared with other reported works.
乳腺肿瘤是全世界妇女的一种危险疾病。在各种癌症中，乳腺肿瘤是导致妇女死亡的第二大原因。早期发现乳腺肿瘤对于提高妇女的存活率至关重要。乳房 X 射线照相术是一种可靠的筛查技术，可以及早发现乳房组织的严重异常。放射科医生在发现乳腺组织异常时，会采用乳房 X 射线照相术。然而，放射科医生通过数字诊断技术检测乳腺异常可能会耗费大量时间。因此，通过开发 CAD 系统，对数字乳腺 X 射线摄影进行计算机化研究应运而生。目前已开发出几种用于乳腺癌检测的计算机辅助诊断系统。然而，要获得令人满意的 CAD 系统性能是一项具有挑战性的任务。我们提出了一种 CAD 架构，利用 LS-SVM 分类器和各种核（即线性、二次、多项式、MLP 和 RBF 核）对乳腺组织进行良性或恶性分类。从实验结果来看，与所有其他内核相比，基于 GA 的 LS-SVM 分类器和 RBF 内核的正常/异常病例分类准确率高达 94.59%。此外，基于 GA 的 LS-SVM 分类器与 RBF 内核相比，在良性/恶性病例分类方面的分类准确率高达 98.26%。
{"title":"Genetic algorithm based detection of breast cancer using least square-support vector machine classifier","authors":"","doi":"10.59018/1123290","DOIUrl":"https://doi.org/10.59018/1123290","url":null,"abstract":"Breast tumors are a dangerous disease among women worldwide. They are the second leading cause of death among all forms of cancers in women. Their early detection is critical to increasing the survival rate of women. Mammography is a reliable screening technique in the early detection of abnormal breast tissue severity. Radiologist abnormalities in the breast tissue, radiologists employ mammography. However, detecting breast abnormalities through digital diagnostic techniques by a radiologist could be time consuming. Consequently, computerized studying of digital mammography has emerged via the development of CAD systems. Several CAD systems have been developed for breast cancer detection. However, obtaining a satisfactory performance of CAD systems is a challenging task. We propose a CAD architecture for the classification of breast tissues as either benign or malignant using an LS-SVM classifier with various kernels namely linear, quadratic, polynomial, MLP, and RBF kernels. From the experimental outputs, it is clear that GA based LS-SVM classifier with RBF kernel outputs classification accuracy of 94.59% for normal/abnormal case classification is better, when it is compared with all other kernels. It is also stated that GA based LS-SVM classifier with RBF kernel produces a better classification accuracy of 98.26% for benign/malignant case classification when it is compared with other reported works.","PeriodicalId":38652,"journal":{"name":"ARPN Journal of Engineering and Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Weeding is one of the most significant practices in agricultural production. Weeds are unwanted plants that grow along with the crops and compete with the crops for space, light, water, and soil nutrients. Weeds propagate themselves either through seeding or creeping rootstalk and decrease yields, increase production costs, interfere with the harvest, and lower the product quality. The use of herbicides reduces labor requirements for weed control by up to 60 percent but affects environmental quality and can be toxic to a wide range of organisms. Hence it is necessary to develop an automated system to identify and remove weeds from the vegetable fields. The objective of the proposed work is to develop a mobility level tracked bot that identifies the weeds and removes them with the help of a robotic end effector and to develop a machine learning model to identify the weeds. This functional module will be processed in a Raspberry Pi processor and by using a Raspberry Pi camera module the bot will detect the weeds in vegetable fields. We performed weed detection with different machine learning models like Haar cascade, YOLOv5, and CNN. To evaluate the performance of the machine learning models used, the performance metrics accuracy, precision, recall, and F-measure are estimated and it has been found that CNN has better accuracy, precision, and recall as compared to YOLOv5 and Haar cascade. CNN has the highest F-measure among the three algorithms at 98%. The weed removal is done using a robotic end-effector which is controlled by the Arduino UNO based on the signal from Raspberry Pi.
除草是农业生产中最重要的做法之一。杂草是与农作物一起生长的多余植物，与农作物争夺空间、光照、水分和土壤养分。杂草通过播种或根茎匍匐繁殖，会降低产量、增加生产成本、影响收成并降低产品质量。使用除草剂最多可减少 60% 的除草劳动力，但会影响环境质量，并对多种生物有毒。因此，有必要开发一种自动系统来识别和清除菜地里的杂草。拟议工作的目标是开发一个移动级跟踪机器人，在机器人末端效应器的帮助下识别杂草并将其清除，同时开发一个机器学习模型来识别杂草。该功能模块将在 Raspberry Pi 处理器中处理，通过使用 Raspberry Pi 摄像头模块，机器人将检测到菜地中的杂草。我们使用 Haar cascade、YOLOv5 和 CNN 等不同的机器学习模型进行杂草检测。为了评估所使用的机器学习模型的性能，我们估算了准确度、精确度、召回率和 F-measure，结果发现，与 YOLOv5 和 Haar 级联相比，CNN 的准确度、精确度和召回率更高。在三种算法中，CNN 的 F-measure 最高，达到 98%。杂草清除是通过机器人末端执行器完成的，该执行器由 Arduino UNO 根据 Raspberry Pi 发出的信号控制。
{"title":"Weed detection and removal using robotic system","authors":"","doi":"10.59018/1123293","DOIUrl":"https://doi.org/10.59018/1123293","url":null,"abstract":"Weeding is one of the most significant practices in agricultural production. Weeds are unwanted plants that grow along with the crops and compete with the crops for space, light, water, and soil nutrients. Weeds propagate themselves either through seeding or creeping rootstalk and decrease yields, increase production costs, interfere with the harvest, and lower the product quality. The use of herbicides reduces labor requirements for weed control by up to 60 percent but affects environmental quality and can be toxic to a wide range of organisms. Hence it is necessary to develop an automated system to identify and remove weeds from the vegetable fields. The objective of the proposed work is to develop a mobility level tracked bot that identifies the weeds and removes them with the help of a robotic end effector and to develop a machine learning model to identify the weeds. This functional module will be processed in a Raspberry Pi processor and by using a Raspberry Pi camera module the bot will detect the weeds in vegetable fields. We performed weed detection with different machine learning models like Haar cascade, YOLOv5, and CNN. To evaluate the performance of the machine learning models used, the performance metrics accuracy, precision, recall, and F-measure are estimated and it has been found that CNN has better accuracy, precision, and recall as compared to YOLOv5 and Haar cascade. CNN has the highest F-measure among the three algorithms at 98%. The weed removal is done using a robotic end-effector which is controlled by the Arduino UNO based on the signal from Raspberry Pi.","PeriodicalId":38652,"journal":{"name":"ARPN Journal of Engineering and Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To preserve the lives of both mother and foetus during the early phases of childbirth, heart abnormality diagnosis is essential. In remote places where understanding of maternal care is limited, the death rate caused by carelessness or a failure to detect abnormalities is still a problem. The signal will contain various external or internal noise sources to isolate the key components of the foetal heart rate from the mother's belly during labour. The likelihood that the genuine signal would be misinterpreted and result in a false report will increase in the presence of such noise sources. Although there are many software programs available for extracting the QRS features from foetal ECG signals, it is unavoidable that specialized hardware is required for a significant reduction in both area and power. This paper's main goal is to extract the QRS complex using LDA, then improve Social Spider classifier performance using the suggested TAODV as a distance metric calculator, and then compare against existing methods to discover sounds that are distorting the normal heart rate. Systolic array filter with suggested Glitch Avoidance Circuit employing MUX is simulated using Cadence Virtuoso in 65nm technology to remove noise from the observed QRS complex. Over 100 records with the necessary examples from MIT-BIH Arrhythmia were used in the simulations, and it was discovered that MATLAB 2010b was used to adopt a unique technique for classifying noise. The suggested TAODV-based SSA classifier's accuracy is 96.8%, whereas the accuracy of a filter with a glitch avoidance circuit is 96.13%. The primary benefit of these strategies comprises cutting-edge hardware and computational solutions.
{"title":"Optimized systolic array filters with noise classification for extracting FECG","authors":"","doi":"10.59018/1123287","DOIUrl":"https://doi.org/10.59018/1123287","url":null,"abstract":"To preserve the lives of both mother and foetus during the early phases of childbirth, heart abnormality diagnosis is essential. In remote places where understanding of maternal care is limited, the death rate caused by carelessness or a failure to detect abnormalities is still a problem. The signal will contain various external or internal noise sources to isolate the key components of the foetal heart rate from the mother's belly during labour. The likelihood that the genuine signal would be misinterpreted and result in a false report will increase in the presence of such noise sources. Although there are many software programs available for extracting the QRS features from foetal ECG signals, it is unavoidable that specialized hardware is required for a significant reduction in both area and power. This paper's main goal is to extract the QRS complex using LDA, then improve Social Spider classifier performance using the suggested TAODV as a distance metric calculator, and then compare against existing methods to discover sounds that are distorting the normal heart rate. Systolic array filter with suggested Glitch Avoidance Circuit employing MUX is simulated using Cadence Virtuoso in 65nm technology to remove noise from the observed QRS complex. Over 100 records with the necessary examples from MIT-BIH Arrhythmia were used in the simulations, and it was discovered that MATLAB 2010b was used to adopt a unique technique for classifying noise. The suggested TAODV-based SSA classifier's accuracy is 96.8%, whereas the accuracy of a filter with a glitch avoidance circuit is 96.13%. The primary benefit of these strategies comprises cutting-edge hardware and computational solutions.","PeriodicalId":38652,"journal":{"name":"ARPN Journal of Engineering and Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140510608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The latest pandemic of monkeypox is a significant cause for worry for the public's health due to the rapidity with which it has spread to more than 40 nations outside of Africa. When monkeypox is so like both measles and chickenpox, making an accurate clinical diagnosis of the disease may be difficult. The monitoring and early identification of suspected cases of monkeypox may benefit from computer-assisted detection of lesions. This is particularly true in environments where confirmatory Polymerase Chain Reaction (PCR) assays are not easily accessible. It has been shown that it is possible to do automated skin lesion identification via deep learning (DL) approaches given sufficient training instances. However, it is expected that these procedures will be followed. However, there are currently no datasets of this sort available for monkeypox. Focusing on forecasting monkeypox disease from skin pictures, this study focuses on developing a transfer learning-based multi-layer convolutional neural network (MLCNN) algorithm. Through pre-processing, we can ensure that all the images are of the same quality and that any distracting sounds have been eliminated. The simulation results showed that the proposed MLCNN outperformed the conventional model, proving the validity of the proposed approach. The MLCNN resulted in an accuracy is 99.1, precision is 99.1%, recall is 99.1%, and F1-score is 99.1%.
{"title":"Monkeypox detection and classification using multi-layer convolutional neural network from skin images","authors":"","doi":"10.59018/1123288","DOIUrl":"https://doi.org/10.59018/1123288","url":null,"abstract":"The latest pandemic of monkeypox is a significant cause for worry for the public's health due to the rapidity with which it has spread to more than 40 nations outside of Africa. When monkeypox is so like both measles and chickenpox, making an accurate clinical diagnosis of the disease may be difficult. The monitoring and early identification of suspected cases of monkeypox may benefit from computer-assisted detection of lesions. This is particularly true in environments where confirmatory Polymerase Chain Reaction (PCR) assays are not easily accessible. It has been shown that it is possible to do automated skin lesion identification via deep learning (DL) approaches given sufficient training instances. However, it is expected that these procedures will be followed. However, there are currently no datasets of this sort available for monkeypox. Focusing on forecasting monkeypox disease from skin pictures, this study focuses on developing a transfer learning-based multi-layer convolutional neural network (MLCNN) algorithm. Through pre-processing, we can ensure that all the images are of the same quality and that any distracting sounds have been eliminated. The simulation results showed that the proposed MLCNN outperformed the conventional model, proving the validity of the proposed approach. The MLCNN resulted in an accuracy is 99.1, precision is 99.1%, recall is 99.1%, and F1-score is 99.1%.","PeriodicalId":38652,"journal":{"name":"ARPN Journal of Engineering and Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Several industries, including shipbuilding and automobile manufacturing, extensively use welding as a joining method. Welding processes are always plagued by distortion. Many parameters influence distortion on weld joints, including the properties of materials and welding parameters. To obtain optimal distortion parameters, the Shielded Metal Arc Welding (SMAW) process on angular distortion is used. However, this technique contains slag inclusions and it gives low productivity. To overcome this issue the Flux-Cored Arc Welding (FCAW) technique is used to combine the metals and alloys in a variety of sectors. It offers several advantages over other methods, including simplicity and adaptability over Submerged-arc welding (SAW), higher productivity over SMAW, and superior surface appearance. In this work, during the welding operation, two dissimilar high-carbon steels (EN8 and EN19) are used and the welding quality is checked by utilizing destructive and microstructure tests. To analyze the effects of process parameters on welded joints, mechanical tests like yield strength, tensile strength, and hardness test are performed and optimized using TAGUCHI design (L9 array). The accurate input parameter of EN8 and EN19 steel with a thickness of 6mm is determined. The welding process parameters are optimized by utilizing the MINITAB-17 software. As a result, the FCAW has higher tensile and yield strength than the conventional method of SAW.
{"title":"Structure safety and weld strength evaluation by metallic weld joints in FCAW with TAGUCHI design","authors":"","doi":"10.59018/1123291","DOIUrl":"https://doi.org/10.59018/1123291","url":null,"abstract":"Several industries, including shipbuilding and automobile manufacturing, extensively use welding as a joining method. Welding processes are always plagued by distortion. Many parameters influence distortion on weld joints, including the properties of materials and welding parameters. To obtain optimal distortion parameters, the Shielded Metal Arc Welding (SMAW) process on angular distortion is used. However, this technique contains slag inclusions and it gives low productivity. To overcome this issue the Flux-Cored Arc Welding (FCAW) technique is used to combine the metals and alloys in a variety of sectors. It offers several advantages over other methods, including simplicity and adaptability over Submerged-arc welding (SAW), higher productivity over SMAW, and superior surface appearance. In this work, during the welding operation, two dissimilar high-carbon steels (EN8 and EN19) are used and the welding quality is checked by utilizing destructive and microstructure tests. To analyze the effects of process parameters on welded joints, mechanical tests like yield strength, tensile strength, and hardness test are performed and optimized using TAGUCHI design (L9 array). The accurate input parameter of EN8 and EN19 steel with a thickness of 6mm is determined. The welding process parameters are optimized by utilizing the MINITAB-17 software. As a result, the FCAW has higher tensile and yield strength than the conventional method of SAW.","PeriodicalId":38652,"journal":{"name":"ARPN Journal of Engineering and Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The presented paper is to investigate the characteristics of the switched reluctance motor (SRM) under different types of controllers. For this study, two different control strategies; namely; voltage and current control strategies are considered. The theoretical background of under consideration controllers is reported. The motor structure, model equations, operation principles as well as the power converter topology and operation are carried out in this research. Motor magnetic characteristics such as inductance profile, phase flux linkages, and static torque profile are studied and simulated. Simulation results of motor performance under each controller are presented. Some recommended conclusions about the SRM suitable controller type selection are introduced.
{"title":"Characteristics study of switched reluctance motor under voltage controller and current controller strategies","authors":"","doi":"10.59018/1123289","DOIUrl":"https://doi.org/10.59018/1123289","url":null,"abstract":"The presented paper is to investigate the characteristics of the switched reluctance motor (SRM) under different types of controllers. For this study, two different control strategies; namely; voltage and current control strategies are considered. The theoretical background of under consideration controllers is reported. The motor structure, model equations, operation principles as well as the power converter topology and operation are carried out in this research. Motor magnetic characteristics such as inductance profile, phase flux linkages, and static torque profile are studied and simulated. Simulation results of motor performance under each controller are presented. Some recommended conclusions about the SRM suitable controller type selection are introduced.","PeriodicalId":38652,"journal":{"name":"ARPN Journal of Engineering and Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cement, as a concrete-forming material, is a contributor to CO2 emissions around the world. One technique to make concrete green without sacrificing quality is to use less cement and substitute ingredients like fly ash and silica fume. A durable concrete material is required since the marine environment's concrete is frequently harmed by harsh environmental elements, such as abrasion by waves and ocean currents. This study aimed to examine the impact of different substitutions for additional materials on concrete's compressive strength and mass loss due to abrasion. The test object is thereafter partially submerged in freshwater and seawater. Furthermore, the specimens underwent laboratory testing to get specific performance metrics including compressive strength and abrasion coefficient. The strength value for the test object treated with freshwater or seawater has exceeded the compressive design strength of 30 MPa, according to an analysis of the compressive strength test findings. Testing for abrasion on the specimens resulted in substituting additive materials in the optimal amount for the concrete, which can reduce mass loss due to abrasion. According to the overall results of concrete testing, which are influenced by seawater, fly ash substitution improves concrete's compressive strength and resistance to abrasion. In contrast, the values of compressive strength and abrasion in silica fume concrete with replacement variations of 5%, 7%, and 10% have a value equivalent to the required accomplishments.
{"title":"Effect of fly ash and silica fume on the abrasion resistance of concrete in marine environment","authors":"","doi":"10.59018/1123292","DOIUrl":"https://doi.org/10.59018/1123292","url":null,"abstract":"Cement, as a concrete-forming material, is a contributor to CO2 emissions around the world. One technique to make concrete green without sacrificing quality is to use less cement and substitute ingredients like fly ash and silica fume. A durable concrete material is required since the marine environment's concrete is frequently harmed by harsh environmental elements, such as abrasion by waves and ocean currents. This study aimed to examine the impact of different substitutions for additional materials on concrete's compressive strength and mass loss due to abrasion. The test object is thereafter partially submerged in freshwater and seawater. Furthermore, the specimens underwent laboratory testing to get specific performance metrics including compressive strength and abrasion coefficient. The strength value for the test object treated with freshwater or seawater has exceeded the compressive design strength of 30 MPa, according to an analysis of the compressive strength test findings. Testing for abrasion on the specimens resulted in substituting additive materials in the optimal amount for the concrete, which can reduce mass loss due to abrasion. According to the overall results of concrete testing, which are influenced by seawater, fly ash substitution improves concrete's compressive strength and resistance to abrasion. In contrast, the values of compressive strength and abrasion in silica fume concrete with replacement variations of 5%, 7%, and 10% have a value equivalent to the required accomplishments.","PeriodicalId":38652,"journal":{"name":"ARPN Journal of Engineering and Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140510982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Energy transition is critical in the context of the current global climate situation. It is also important for Indonesia to achieve Sustainable Development in the Clean and Affordable Energy sector; given that the country’s primary energy mix is still dominated by fossil energy, which accounts for around 90% of energy production. Wind is a new renewable energy that can be utilized to produce electrical energy through energy conversion. In addition, wind power is a type of renewable energy that has the lowest price compared to other types. This study aims to determine the characteristics of the selected airfoil types, including; NACA 2412, NACA 4412, NACA 6409 and SG6043. These characteristics included lift and drag coefficient. The BEM (Blade Element Momentum) method approach was used to obtain the performance parameter values of the airfoil and wind turbine, which include; lift and drag coefficient, lift-to-drag ratio, power coefficient, torque coefficient, turbine rotation, and power with variations ranging from angle of attack, tip speed ratio and wind speed. The results obtained for the highest lift coefficient value produced by SG6043 airfoil of 1.838 at an angle of attack of 16 °, and the lowest value produced by NACA 2412 of 1.529 at an angle of attack of 16 °. For the drag coefficient value, all types of airfoils produced values that increased as the angle of attack increased. Then, the highest power coefficient value produced by the SG6043 airfoil of 0.496 at TSR 5, and the lowest value produced by the NACA 6409 airfoil of 0.481 at TSR 5. Then, the power generated was based on the results of the power coefficient, where the SG6043 airfoil produced the greatest power for each wind speed used, and the NACA 6409 airfoil produced the lowest power. From the results of this study, it can also be concluded that the SG6043 airfoil produced the best performance compared to other types used.
{"title":"The effect of airfoil type and wind speed on HAWT wind turbine performance using QBlade software","authors":"","doi":"10.59018/1123286","DOIUrl":"https://doi.org/10.59018/1123286","url":null,"abstract":"Energy transition is critical in the context of the current global climate situation. It is also important for Indonesia to achieve Sustainable Development in the Clean and Affordable Energy sector; given that the country’s primary energy mix is still dominated by fossil energy, which accounts for around 90% of energy production. Wind is a new renewable energy that can be utilized to produce electrical energy through energy conversion. In addition, wind power is a type of renewable energy that has the lowest price compared to other types. This study aims to determine the characteristics of the selected airfoil types, including; NACA 2412, NACA 4412, NACA 6409 and SG6043. These characteristics included lift and drag coefficient. The BEM (Blade Element Momentum) method approach was used to obtain the performance parameter values of the airfoil and wind turbine, which include; lift and drag coefficient, lift-to-drag ratio, power coefficient, torque coefficient, turbine rotation, and power with variations ranging from angle of attack, tip speed ratio and wind speed. The results obtained for the highest lift coefficient value produced by SG6043 airfoil of 1.838 at an angle of attack of 16 °, and the lowest value produced by NACA 2412 of 1.529 at an angle of attack of 16 °. For the drag coefficient value, all types of airfoils produced values that increased as the angle of attack increased. Then, the highest power coefficient value produced by the SG6043 airfoil of 0.496 at TSR 5, and the lowest value produced by the NACA 6409 airfoil of 0.481 at TSR 5. Then, the power generated was based on the results of the power coefficient, where the SG6043 airfoil produced the greatest power for each wind speed used, and the NACA 6409 airfoil produced the lowest power. From the results of this study, it can also be concluded that the SG6043 airfoil produced the best performance compared to other types used.","PeriodicalId":38652,"journal":{"name":"ARPN Journal of Engineering and Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140511218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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