Pub Date : 2024-07-09DOI: 10.53982/ajerd.2024.0702.04-j
Usman Garba, D. Rouzineau, Michel Meyer
This study investigates the effective interfacial area in a novel rotating packed bed (RPB) equipped with dual gas inlets instead of the conventional single-gas-inlet RPB. The aim is to enhance the mass transfer efficiency of gas-liquid contacting processes in RPBs by increasing the number of gas inlets to improve the spread of gas supply into the packing. The RPB is a promising gas-liquid contactor configuration known for its intensified mass transfer characteristics. However, the impact of additional gas inlets on the effective interfacial area of the packing remains unexplored. An experimental method assessed the interfacial area under varying operational conditions which include a liquid flow rate of 0.30-0.60 m3/h, a gas flow rate of 100-300 Nm3/h, and a rotation speed of 600-1000 rpm. At operating conditions covering the maximum rotation speed of 1400 rpm, gas flow and liquid flow rates of 300 Nm3/h and 0.60 m3/h respectively, the results showed that on average, 55 to 97% of the 2400m2/m3 specific packing area can be effectively utilized for gas-liquid mass transfer during separation operations using the RPB. Compared to results reported for single-gas-inlet RPBs using similar packings, the RPB with double gas inlet proved to provide higher utilization of the packing. By simply doubling the number of gas inlets, the findings provide valuable insights into optimizing RPB designs and operations which could enhance mass transfer efficiency for various chemical and environmental applications.
{"title":"Evaluation of Effective Interfacial Area in a Rotating Packed Bed Equipped with Dual Gas Inlets","authors":"Usman Garba, D. Rouzineau, Michel Meyer","doi":"10.53982/ajerd.2024.0702.04-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0702.04-j","url":null,"abstract":"This study investigates the effective interfacial area in a novel rotating packed bed (RPB) equipped with dual gas inlets instead of the conventional single-gas-inlet RPB. The aim is to enhance the mass transfer efficiency of gas-liquid contacting processes in RPBs by increasing the number of gas inlets to improve the spread of gas supply into the packing. The RPB is a promising gas-liquid contactor configuration known for its intensified mass transfer characteristics. However, the impact of additional gas inlets on the effective interfacial area of the packing remains unexplored. An experimental method assessed the interfacial area under varying operational conditions which include a liquid flow rate of 0.30-0.60 m3/h, a gas flow rate of 100-300 Nm3/h, and a rotation speed of 600-1000 rpm. At operating conditions covering the maximum rotation speed of 1400 rpm, gas flow and liquid flow rates of 300 Nm3/h and 0.60 m3/h respectively, the results showed that on average, 55 to 97% of the 2400m2/m3 specific packing area can be effectively utilized for gas-liquid mass transfer during separation operations using the RPB. Compared to results reported for single-gas-inlet RPBs using similar packings, the RPB with double gas inlet proved to provide higher utilization of the packing. By simply doubling the number of gas inlets, the findings provide valuable insights into optimizing RPB designs and operations which could enhance mass transfer efficiency for various chemical and environmental applications.","PeriodicalId":394198,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":"102 36","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141666432","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}
Pub Date : 2024-07-09DOI: 10.53982/ajerd.2024.0702.06-j
B. Aliemeke, Lucky Charles, Peace Omoregie, Abdulrazak Momodu, Christopher Jerry, Emmanuel Akpan
The optimization of wear rate parameters in metallic alloys using Response Surface Methodology (RSM) has been experimentally performed. The wear rate, a critical factor affecting the durability and performance of metallic components, served as the response parameter, while track diameter, sliding speed, and mass difference were considered as independent variables. The Central Composite Design (CCD) experimental method systematically explored the response surface and optimizes the wear rate. A mathematical model was developed, revealing a significant p-value of 0.043 in the ANOVA table, indicating the collective influence of the independent variables on wear rate at a significance level of 0.05. Furthermore, the model demonstrates a substantial explanatory power, with R-squared of 69.45% and adjusted R-squared of 51.95%. The p-value calculated to be 0.60 for the statistical Lack of fit indicated a satisfactory model. These findings highlight the effectiveness of RSM in optimizing the experimental input values and offer valuable insights for enhancing the durability and performance of metallic alloys in various industrial applications. The obtained result addresses the problem of uncertainty inherent in optimal levels of input parameters wear experimentation.
实验采用响应面法（RSM）对金属合金的磨损率参数进行了优化。磨损率是影响金属部件耐久性和性能的关键因素，被视为响应参数，而轨道直径、滑动速度和质量差被视为自变量。中央复合设计（CCD）实验方法系统地探索了响应面，并优化了磨损率。建立的数学模型在方差分析表中显示出 0.043 的显著 p 值，表明在 0.05 的显著性水平下，自变量对磨损率有共同影响。此外，该模型还具有很强的解释力，R 方为 69.45%，调整 R 方为 51.95%。统计拟合度的 p 值为 0.60，表明模型令人满意。这些发现凸显了 RSM 在优化实验输入值方面的有效性，并为提高金属合金在各种工业应用中的耐用性和性能提供了宝贵的见解。所获得的结果解决了输入参数磨损实验最佳水平固有的不确定性问题。
{"title":"Response Surface Methodology Optimization of wear rate Parameters in metallic alloys","authors":"B. Aliemeke, Lucky Charles, Peace Omoregie, Abdulrazak Momodu, Christopher Jerry, Emmanuel Akpan","doi":"10.53982/ajerd.2024.0702.06-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0702.06-j","url":null,"abstract":"The optimization of wear rate parameters in metallic alloys using Response Surface Methodology (RSM) has been experimentally performed. The wear rate, a critical factor affecting the durability and performance of metallic components, served as the response parameter, while track diameter, sliding speed, and mass difference were considered as independent variables. The Central Composite Design (CCD) experimental method systematically explored the response surface and optimizes the wear rate. A mathematical model was developed, revealing a significant p-value of 0.043 in the ANOVA table, indicating the collective influence of the independent variables on wear rate at a significance level of 0.05. Furthermore, the model demonstrates a substantial explanatory power, with R-squared of 69.45% and adjusted R-squared of 51.95%. The p-value calculated to be 0.60 for the statistical Lack of fit indicated a satisfactory model. These findings highlight the effectiveness of RSM in optimizing the experimental input values and offer valuable insights for enhancing the durability and performance of metallic alloys in various industrial applications. The obtained result addresses the problem of uncertainty inherent in optimal levels of input parameters wear experimentation.","PeriodicalId":394198,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":"122 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141666326","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}
Pub Date : 2024-07-09DOI: 10.53982/ajerd.2024.0702.05-j
F. Ariba, F. K. Ojo, Zacheeus Kayode Adeyemo
In Heterogeneous Wireless Networks (HWNs), Radio Access Technologies (RAT) can only consider the situation of one particular Radio Resource Management (RRM) which is unsuitable for managing multiple RATs. This study deployed an adaptive RAT selection scheme model to allocate users to the best RAT with the use of the cost function variable. The adopted model uses different input criteria like signal strength, network loads, service type and QoS requirement for the best access network selections. The adaptive RAT selection algorithm was executed in different service mixes (voice and data service) to access model suitability for users in Global System for Mobile Communications with Enhanced Data Rates for Global Evolution Radio Access Network (GERAN) and Universal Mobile Telecommunications System Radio Access Network (UTRAN). The proposed algorithm resulted in the call blocking probability reduction by 0.03 for GERAN and 0.14 for UTRAN as validated with the existing algorithm based on load balancing, service-based and priority-based. The drop implied an increased probability of ensuring session stability and high quality of the active service, leading to a high load distribution.
在异构无线网络（HWN）中，无线接入技术（RAT）只能考虑一种特定无线资源管理（RRM）的情况，不适合管理多种 RAT。本研究采用自适应 RAT 选择方案模型，利用成本函数变量将用户分配到最佳 RAT。所采用的模型使用不同的输入标准，如信号强度、网络负载、服务类型和 QoS 要求，以选择最佳接入网络。在不同的服务组合（语音和数据服务）中执行了自适应 RAT 选择算法，以获得模型对全球移动通信系统增强数据速率全球演进无线接入网（GERAN）和通用移动电信系统无线接入网（UTRAN）用户的适用性。与基于负载均衡、基于服务和基于优先级的现有算法相比，提议的算法使 GERAN 的呼叫阻塞概率降低了 0.03，UTRAN 的呼叫阻塞概率降低了 0.14。这一下降意味着确保会话稳定性和主动服务高质量的可能性增加，从而导致高负载分布。
{"title":"Adaptive Radio Access Technology Selection Algorithm for Heterogeneous Wireless Networks","authors":"F. Ariba, F. K. Ojo, Zacheeus Kayode Adeyemo","doi":"10.53982/ajerd.2024.0702.05-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0702.05-j","url":null,"abstract":"In Heterogeneous Wireless Networks (HWNs), Radio Access Technologies (RAT) can only consider the situation of one particular Radio Resource Management (RRM) which is unsuitable for managing multiple RATs. This study deployed an adaptive RAT selection scheme model to allocate users to the best RAT with the use of the cost function variable. The adopted model uses different input criteria like signal strength, network loads, service type and QoS requirement for the best access network selections. The adaptive RAT selection algorithm was executed in different service mixes (voice and data service) to access model suitability for users in Global System for Mobile Communications with Enhanced Data Rates for Global Evolution Radio Access Network (GERAN) and Universal Mobile Telecommunications System Radio Access Network (UTRAN). The proposed algorithm resulted in the call blocking probability reduction by 0.03 for GERAN and 0.14 for UTRAN as validated with the existing algorithm based on load balancing, service-based and priority-based. The drop implied an increased probability of ensuring session stability and high quality of the active service, leading to a high load distribution.","PeriodicalId":394198,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":"63 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141663180","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}
Pub Date : 2024-07-09DOI: 10.53982/ajerd.2024.0703.03-j
Hassan Abdullahi Maikano, T. Akanbi
This research investigates the potential of palm kernel shells (PKS) and quarry dust (QD) as sustainable and cost-effective replacements for sand and gravel in concrete production. The study explores the impact of varying PKS and QD content on workability, density, water absorption, and mechanical properties. While increasing these alternative aggregates decreases workability and density, it improves water absorption and, in some cases, mechanical strength. Response Surface Methodology (RSM) identified a combination of 5% PKS and 20% QD (-1, -1) as the optimal replacement level for achieving a balance between cost and performance. This mix offers a significant cost reduction of 18.2% relative to concrete made with conventional aggregates. The study highlights the potential of PKS and QD as sustainable alternatives for conventional aggregates. Utilizing these readily available waste materials can reduce reliance on natural resources, promote waste management practices, and contribute to a more environmentally friendly construction industry. Additionally, the research suggests that quarry dust alone might be a more suitable replacement material than PKS due to its superior influence on concrete strength. This research provides valuable insights for optimizing concrete mix design with PKS and QD, promoting cost-effective and sustainable construction practices in regions with abundant palm oil production and quarrying activities.
{"title":"Unlocking the Potential of Palm Kernel Shell and Quarry Dust: A Cost-Driven Approach to Replacing Sand and Gravel in Concrete","authors":"Hassan Abdullahi Maikano, T. Akanbi","doi":"10.53982/ajerd.2024.0703.03-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0703.03-j","url":null,"abstract":"This research investigates the potential of palm kernel shells (PKS) and quarry dust (QD) as sustainable and cost-effective replacements for sand and gravel in concrete production. The study explores the impact of varying PKS and QD content on workability, density, water absorption, and mechanical properties. While increasing these alternative aggregates decreases workability and density, it improves water absorption and, in some cases, mechanical strength. Response Surface Methodology (RSM) identified a combination of 5% PKS and 20% QD (-1, -1) as the optimal replacement level for achieving a balance between cost and performance. This mix offers a significant cost reduction of 18.2% relative to concrete made with conventional aggregates. The study highlights the potential of PKS and QD as sustainable alternatives for conventional aggregates. Utilizing these readily available waste materials can reduce reliance on natural resources, promote waste management practices, and contribute to a more environmentally friendly construction industry. Additionally, the research suggests that quarry dust alone might be a more suitable replacement material than PKS due to its superior influence on concrete strength. This research provides valuable insights for optimizing concrete mix design with PKS and QD, promoting cost-effective and sustainable construction practices in regions with abundant palm oil production and quarrying activities.","PeriodicalId":394198,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":"42 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141663595","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}
Pub Date : 2024-07-01DOI: 10.53982/ajerd.2024.0702.02-j
Lambe Mutalub Adesina, O. Ogunbiyi, Bilkisu Jimada-Ojuolape
Power utility customers in a developing country like Nigeria have constituted a habit of changing the electricity supply line from an unavailable or unstable phase to the most available or stable phase. The category of customers involved in this character are those on single phase power supply. However, this act is being carried out manually at the meter point using the cut-out fuses. This attitude results in phase unbalances, overheating electrical equipment including feeder pillars, transformer coils, network faults, and overall system instability. Thus, this paper presents the development of an Automatic Phase Selector for Nigerian Power Utility Customers. The device automatically selects an available phase from the three-phase power supply lines. The research comprises designing an automatic phase selector circuit, simulation of the designed circuit, programming code development in C- Language for the microcontroller, construction of the designed circuit, and carrying out tests on completed work done to ascertain the effectiveness of the developed system. The system operation involved a three-phase supply from the closest distribution network of the power utility company which is connected to a three-in-one gang switch while the switching ON and OFF of their static switches represent phase-off in an ideal situation. The operational results of this system are presented in the form of the truth table which indicates that the affected customer would not have a power supply only when the 3-phases are under voltage or overvoltage or unavailable. This implies that one of the three phases that meet the three criteria would be switched ON. A pure sine wave was used as input into the Optocoupler and the output waveform of the rectified pulsating signal is separately displayed. This output waveform is very clean and noiseless. Finally, the system when practically tested with an unbalanced three-phase supply, worked perfectly enhancing the flexibility of operating an Automatic Phase selector and hence avoiding manual switching of the phase selector which has been attributed to changing of cut-out fuses and associated stress as well as having a user-friendly phase selector.
在尼日利亚这样的发展中国家，电力客户已经养成了将供电线路从不可用或不稳定的相位切换到最可用或最稳定的相位的习惯。出现这种情况的用户属于单相供电用户。然而，这种行为是在电表点使用切断熔断器手动进行的。这种做法会导致相位不平衡、电气设备（包括馈线支柱、变压器线圈）过热、网络故障和整个系统的不稳定。因此，本文介绍了为尼日利亚电力公司客户开发的自动选相器。该设备可从三相供电线路中自动选择可用相位。研究内容包括设计自动选相器电路、模拟所设计的电路、用 C 语言为微控制器开发编程代码、构建所设计的电路，以及对已完成的工作进行测试，以确定所开发系统的有效性。系统运行涉及电力公司最近配电网络的三相电源，该电源与三合一群组开关相连，其静态开关的接通和断开代表理想情况下的分相。该系统的运行结果以真值表的形式显示，只有当三相电压过低、过高或不可用时，受影响的用户才无法获得供电。这意味着满足三个标准的三相中的一相将被接通。光耦合器使用纯正弦波作为输入，并分别显示整流脉动信号的输出波形。输出波形非常干净、无噪音。最后，在对不平衡三相电源进行实际测试时，该系统工作完美，提高了操作自动选相器的灵活性，从而避免了手动切换选相器，因为手动切换选相器会导致保险丝熔断和相关压力的变化，同时也方便了用户使用选相器。
{"title":"Development of an Automatic Phase Selector for Nigerian Power Utility Customers","authors":"Lambe Mutalub Adesina, O. Ogunbiyi, Bilkisu Jimada-Ojuolape","doi":"10.53982/ajerd.2024.0702.02-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0702.02-j","url":null,"abstract":"Power utility customers in a developing country like Nigeria have constituted a habit of changing the electricity supply line from an unavailable or unstable phase to the most available or stable phase. The category of customers involved in this character are those on single phase power supply. However, this act is being carried out manually at the meter point using the cut-out fuses. This attitude results in phase unbalances, overheating electrical equipment including feeder pillars, transformer coils, network faults, and overall system instability. Thus, this paper presents the development of an Automatic Phase Selector for Nigerian Power Utility Customers. The device automatically selects an available phase from the three-phase power supply lines. The research comprises designing an automatic phase selector circuit, simulation of the designed circuit, programming code development in C- Language for the microcontroller, construction of the designed circuit, and carrying out tests on completed work done to ascertain the effectiveness of the developed system. The system operation involved a three-phase supply from the closest distribution network of the power utility company which is connected to a three-in-one gang switch while the switching ON and OFF of their static switches represent phase-off in an ideal situation. The operational results of this system are presented in the form of the truth table which indicates that the affected customer would not have a power supply only when the 3-phases are under voltage or overvoltage or unavailable. This implies that one of the three phases that meet the three criteria would be switched ON. A pure sine wave was used as input into the Optocoupler and the output waveform of the rectified pulsating signal is separately displayed. This output waveform is very clean and noiseless. Finally, the system when practically tested with an unbalanced three-phase supply, worked perfectly enhancing the flexibility of operating an Automatic Phase selector and hence avoiding manual switching of the phase selector which has been attributed to changing of cut-out fuses and associated stress as well as having a user-friendly phase selector.","PeriodicalId":394198,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":"24 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141694191","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}
Pub Date : 2024-07-01DOI: 10.53982/ajerd.2024.0702.01-j
Samuel Omaji, Glory Nosawaru Edegbe, J. Ogbiti, Esosa Enoyoze, Ijegwa David Acheme
Today, optimization is crucial to solving energy crises, especially in smart homes. However, the optimization-based methods for energy management in smart agriculture available globally need further improvement, which motivates this study. To resolve the problem, an efficient scheduling farm energy management system is required. Therefore, this study proposes a Farm Energy Management System (FEMS) for smart agriculture by adopting a honey-badger optimization algorithm. In the proposed system, a multi-objective optimization problem is formulated to find the best solutions for achieving the set of objectives, such as electricity cost, load minimization and peak-to-average ratio minimization, while considering the farmers' comfort. The proposed system considers commercialized agriculture with the integration of Renewable Energy Resources (RES). Also, the proposed system minimizes both load consumption and electricity costs via the scheduling of farm appliances in response to Real-Time Pricing (RTP) and Time-of-Use (ToU) pricing schemes in the electricity market. Extensive experiments are carried out in MATLAB 2018A to determine the efficacy of the proposed system. The proposed FEMS consists of sixteen farm appliances with their respective power ratings, inclusive of RES. The simulation results showed that a system without FEMS has a high electricity cost of 50.69% as compared to 43.04% for FEMS without RES and 6.27% for FEMS with RES when considering the ToU market price. For RTP market price, a system without FEMS has an electricity cost of 42.30%, as compared to 30.64% for FEMS without RES and 27.24% for FEMS with RES. Besides, the maximum load consumption for a system without FEMS is 246.80 kW, as compared to 151.40 kW for FEMS without RES and 18.85 kW for FEMS with RES when considering the ToU market price. Also, for the RTP market price, the maximum load consumption for a system without FEMS is 246.80 kW, as compared to 186.40 kW for FEMS without RES and 90.68 kW for FEMS with RES. The significance of the study is to propose a conceptualized FEMS based on the honey badger optimization algorithm. The proposed system provides scheduling of farm appliances that alleviates the burden of the electricity grid and is cost-effective for large and small-scale farmers.
{"title":"Efficient Energy Management System using Honey Badger Algorithm for Smart Agriculture","authors":"Samuel Omaji, Glory Nosawaru Edegbe, J. Ogbiti, Esosa Enoyoze, Ijegwa David Acheme","doi":"10.53982/ajerd.2024.0702.01-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0702.01-j","url":null,"abstract":"Today, optimization is crucial to solving energy crises, especially in smart homes. However, the optimization-based methods for energy management in smart agriculture available globally need further improvement, which motivates this study. To resolve the problem, an efficient scheduling farm energy management system is required. Therefore, this study proposes a Farm Energy Management System (FEMS) for smart agriculture by adopting a honey-badger optimization algorithm. In the proposed system, a multi-objective optimization problem is formulated to find the best solutions for achieving the set of objectives, such as electricity cost, load minimization and peak-to-average ratio minimization, while considering the farmers' comfort. The proposed system considers commercialized agriculture with the integration of Renewable Energy Resources (RES). Also, the proposed system minimizes both load consumption and electricity costs via the scheduling of farm appliances in response to Real-Time Pricing (RTP) and Time-of-Use (ToU) pricing schemes in the electricity market. Extensive experiments are carried out in MATLAB 2018A to determine the efficacy of the proposed system. The proposed FEMS consists of sixteen farm appliances with their respective power ratings, inclusive of RES. The simulation results showed that a system without FEMS has a high electricity cost of 50.69% as compared to 43.04% for FEMS without RES and 6.27% for FEMS with RES when considering the ToU market price. For RTP market price, a system without FEMS has an electricity cost of 42.30%, as compared to 30.64% for FEMS without RES and 27.24% for FEMS with RES. Besides, the maximum load consumption for a system without FEMS is 246.80 kW, as compared to 151.40 kW for FEMS without RES and 18.85 kW for FEMS with RES when considering the ToU market price. Also, for the RTP market price, the maximum load consumption for a system without FEMS is 246.80 kW, as compared to 186.40 kW for FEMS without RES and 90.68 kW for FEMS with RES. The significance of the study is to propose a conceptualized FEMS based on the honey badger optimization algorithm. The proposed system provides scheduling of farm appliances that alleviates the burden of the electricity grid and is cost-effective for large and small-scale farmers.","PeriodicalId":394198,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":"10 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141709230","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}
Pub Date : 2024-02-12DOI: 10.53982/ajerd.2024.0701.01-j
Sunday Oluyele, Ibrahim Adeyanju, Adedayo A. Sobowale
Visually impaired persons encounter certain challenges, which include access to information, environmental navigation, and obstacle detection. Navigating daily life becomes a big task with challenges relating to the search for misplaced personal items and being aware of objects in their environment to avoid collision. This necessitates the need for automated solutions to facilitate object recognition. While traditional methods like guide dogs, white canes, and Braille have offered valuable solutions, recent technological solutions, including smartphone-based recognition systems and portable cameras, have encountered limitations such as constraints relating to cultural-specific, device-specific, and lack of system autonomy. This study addressed and provided solutions to the limitations offered by recent solutions by introducing a Convolutional Neural Network (CNN) object recognition system integrated into a mobile robot designed to function as a robotic assistant for visually impaired persons. The robotic assistant is capable of moving around in a confined environment. It incorporates a Raspberry Pi with a camera programmed to recognize three objects: mobile phones, mice, and chairs. A Convolutional Neural Network model was trained for object recognition, with 30% of the images used for testing. The training was conducted using the Yolov3 model in Google Colab. Qualitative evaluation of the recognition system yielded a precision of 79%, recall of 96%, and accuracy of 80% for the Robotic Assistant. It also includes a Graphical User Interface where users can easily control the movement and speed of the robotic assistant. The developed robotic assistant significantly enhances autonomy and object recognition, promising substantial benefits in the daily navigation of visually impaired individuals.
{"title":"Robotic Assistant for Object Recognition Using Convolutional Neural Network","authors":"Sunday Oluyele, Ibrahim Adeyanju, Adedayo A. Sobowale","doi":"10.53982/ajerd.2024.0701.01-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0701.01-j","url":null,"abstract":"Visually impaired persons encounter certain challenges, which include access to information, environmental navigation, and obstacle detection. Navigating daily life becomes a big task with challenges relating to the search for misplaced personal items and being aware of objects in their environment to avoid collision. This necessitates the need for automated solutions to facilitate object recognition. While traditional methods like guide dogs, white canes, and Braille have offered valuable solutions, recent technological solutions, including smartphone-based recognition systems and portable cameras, have encountered limitations such as constraints relating to cultural-specific, device-specific, and lack of system autonomy. This study addressed and provided solutions to the limitations offered by recent solutions by introducing a Convolutional Neural Network (CNN) object recognition system integrated into a mobile robot designed to function as a robotic assistant for visually impaired persons. The robotic assistant is capable of moving around in a confined environment. It incorporates a Raspberry Pi with a camera programmed to recognize three objects: mobile phones, mice, and chairs. A Convolutional Neural Network model was trained for object recognition, with 30% of the images used for testing. The training was conducted using the Yolov3 model in Google Colab. Qualitative evaluation of the recognition system yielded a precision of 79%, recall of 96%, and accuracy of 80% for the Robotic Assistant. It also includes a Graphical User Interface where users can easily control the movement and speed of the robotic assistant. The developed robotic assistant significantly enhances autonomy and object recognition, promising substantial benefits in the daily navigation of visually impaired individuals.","PeriodicalId":394198,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":"76 42","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139844056","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}
Pub Date : 2024-02-12DOI: 10.53982/ajerd.2024.0701.01-j
Sunday Oluyele, Ibrahim Adeyanju, Adedayo A. Sobowale
Visually impaired persons encounter certain challenges, which include access to information, environmental navigation, and obstacle detection. Navigating daily life becomes a big task with challenges relating to the search for misplaced personal items and being aware of objects in their environment to avoid collision. This necessitates the need for automated solutions to facilitate object recognition. While traditional methods like guide dogs, white canes, and Braille have offered valuable solutions, recent technological solutions, including smartphone-based recognition systems and portable cameras, have encountered limitations such as constraints relating to cultural-specific, device-specific, and lack of system autonomy. This study addressed and provided solutions to the limitations offered by recent solutions by introducing a Convolutional Neural Network (CNN) object recognition system integrated into a mobile robot designed to function as a robotic assistant for visually impaired persons. The robotic assistant is capable of moving around in a confined environment. It incorporates a Raspberry Pi with a camera programmed to recognize three objects: mobile phones, mice, and chairs. A Convolutional Neural Network model was trained for object recognition, with 30% of the images used for testing. The training was conducted using the Yolov3 model in Google Colab. Qualitative evaluation of the recognition system yielded a precision of 79%, recall of 96%, and accuracy of 80% for the Robotic Assistant. It also includes a Graphical User Interface where users can easily control the movement and speed of the robotic assistant. The developed robotic assistant significantly enhances autonomy and object recognition, promising substantial benefits in the daily navigation of visually impaired individuals.
{"title":"Robotic Assistant for Object Recognition Using Convolutional Neural Network","authors":"Sunday Oluyele, Ibrahim Adeyanju, Adedayo A. Sobowale","doi":"10.53982/ajerd.2024.0701.01-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0701.01-j","url":null,"abstract":"Visually impaired persons encounter certain challenges, which include access to information, environmental navigation, and obstacle detection. Navigating daily life becomes a big task with challenges relating to the search for misplaced personal items and being aware of objects in their environment to avoid collision. This necessitates the need for automated solutions to facilitate object recognition. While traditional methods like guide dogs, white canes, and Braille have offered valuable solutions, recent technological solutions, including smartphone-based recognition systems and portable cameras, have encountered limitations such as constraints relating to cultural-specific, device-specific, and lack of system autonomy. This study addressed and provided solutions to the limitations offered by recent solutions by introducing a Convolutional Neural Network (CNN) object recognition system integrated into a mobile robot designed to function as a robotic assistant for visually impaired persons. The robotic assistant is capable of moving around in a confined environment. It incorporates a Raspberry Pi with a camera programmed to recognize three objects: mobile phones, mice, and chairs. A Convolutional Neural Network model was trained for object recognition, with 30% of the images used for testing. The training was conducted using the Yolov3 model in Google Colab. Qualitative evaluation of the recognition system yielded a precision of 79%, recall of 96%, and accuracy of 80% for the Robotic Assistant. It also includes a Graphical User Interface where users can easily control the movement and speed of the robotic assistant. The developed robotic assistant significantly enhances autonomy and object recognition, promising substantial benefits in the daily navigation of visually impaired individuals.","PeriodicalId":394198,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":"51 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139783987","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}
Pub Date : 2023-08-14DOI: 10.53982/ajerd.2023.0602.05-j
Lawal Muhammed Nasir, Victor Ogbeide-Igiebor, I. Ozigis
Exhaust emission has remained a big global concern in atmospheric change, and has thus, lead to stiffer polices on emission. To achieve the set emission targets different fuel mix and combustion process are continuously been investigated. This work is used to practically model the condition of a two-stroke engine that has run over time whose used lubricating oil finds its way from the sump to the combustion chamber and thus resulting to greater rate of incomplete combustion and higher emission. An exhaust analyser with a deep probe was deployed to access the out-going burnt gasses from a two-stroke spark ignition engine that is fed with multi blends of petrol, ethanol and spent engine oil. The characteristics of the emission constituents were investigated and compared to the global limits set by different organizations such as California Air Resources Board, Environmental Protection Agency in USA, International Council on Clean Transportation, Road Transport Bureau- in Japan, and European Emission Standard Agency, among others. The result shows an increase in , and emissions with samples that contain spent oil as against those with new engine oil which is also more effective. It was also found that samples with higher quantity of ethanol show lower emission of , and gases. This is likely due to interstation of ethanol molecules with that of the spent oil, thus making it more potent for further combustion. This was also supported with the fact that emission was higher in blends with higher quantity of ethanol. Thus, the presence of ethanol in fuel blend used in two-stroke spark ignition engine may be considered to be a source of improvement in combustion and hence a means of reducing emission in two-stroke port operated spark ignition engines.
{"title":"Emission Characterization of Petrol, Ethanol and Spent Engine Oil Blends for Two-Stroke Spark Ignition Engine","authors":"Lawal Muhammed Nasir, Victor Ogbeide-Igiebor, I. Ozigis","doi":"10.53982/ajerd.2023.0602.05-j","DOIUrl":"https://doi.org/10.53982/ajerd.2023.0602.05-j","url":null,"abstract":"Exhaust emission has remained a big global concern in atmospheric change, and has thus, lead to stiffer polices on emission. To achieve the set emission targets different fuel mix and combustion process are continuously been investigated. This work is used to practically model the condition of a two-stroke engine that has run over time whose used lubricating oil finds its way from the sump to the combustion chamber and thus resulting to greater rate of incomplete combustion and higher emission. An exhaust analyser with a deep probe was deployed to access the out-going burnt gasses from a two-stroke spark ignition engine that is fed with multi blends of petrol, ethanol and spent engine oil. The characteristics of the emission constituents were investigated and compared to the global limits set by different organizations such as California Air Resources Board, Environmental Protection Agency in USA, International Council on Clean Transportation, Road Transport Bureau- in Japan, and European Emission Standard Agency, among others. The result shows an increase in , and emissions with samples that contain spent oil as against those with new engine oil which is also more effective. It was also found that samples with higher quantity of ethanol show lower emission of , and gases. This is likely due to interstation of ethanol molecules with that of the spent oil, thus making it more potent for further combustion. This was also supported with the fact that emission was higher in blends with higher quantity of ethanol. Thus, the presence of ethanol in fuel blend used in two-stroke spark ignition engine may be considered to be a source of improvement in combustion and hence a means of reducing emission in two-stroke port operated spark ignition engines.","PeriodicalId":394198,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":"324 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131594630","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}
Pub Date : 2023-08-14DOI: 10.53982/ajerd.2023.0602.04-j
Adedamola Abdulmatin Adeniji, K. E. Jack, Muhammed Kamil Idris, S. S. Oyewobi, Hamza Musa, Abdulhafeez Oluwatobi Oyelami
This groundbreaking research introduces an AI-based approach for revolutionizing weed management in legume farmland, addressing the limitations of traditional methods and introducing a new era of cost-effective and precise weed detection and removal. Traditional methods of removing weeds from farmland involving machinery or chemicals often resulted in high costs and imprecise outcomes. To address these challenges, an advanced image recognition algorithm was proposed, which harnessed smart machines to minimize costs and environmental risks. By utilizing computer vision technology, weeds were accurately identified and targeted for removal. A machine learning model was trained using relevant datasets to enable precise weed management. The AI-powered robot, equipped with advanced image recognition algorithms, demonstrated exceptional accuracy and speed, performing weed removal and decomposition 1.2 times faster than traditional manual labour. This breakthrough in weed management technology offers farmers a means to optimize crop yields, enhance food production, and minimize the environmental impact associated with chemical herbicides. A prototype of the robot was fabricated and evaluated in real-world farming conditions. Field tests were conducted on a bean farm and it’s demonstrated the robot's exceptional accuracy, with only a 2% deviation from the actual weed quantity. This research showcased the potential of AI-based weed management systems in legume farming, offering cost-effective and precise weed detection and removal. This research sets a precedent for the integration of AI in modern agriculture, driving the industry toward a more environmentally conscious and economically viable future. The AI-based weed management system empowers farmers, ensuring bountiful harvests, increased profitability, and a greener, more sustainable tomorrow while attention should be given to manufacturing this model for industrial and or commercial applications.
{"title":"Deployment of an Artificial Intelligent Robot for Weed Management in Legumes Farmland","authors":"Adedamola Abdulmatin Adeniji, K. E. Jack, Muhammed Kamil Idris, S. S. Oyewobi, Hamza Musa, Abdulhafeez Oluwatobi Oyelami","doi":"10.53982/ajerd.2023.0602.04-j","DOIUrl":"https://doi.org/10.53982/ajerd.2023.0602.04-j","url":null,"abstract":"This groundbreaking research introduces an AI-based approach for revolutionizing weed management in legume farmland, addressing the limitations of traditional methods and introducing a new era of cost-effective and precise weed detection and removal. Traditional methods of removing weeds from farmland involving machinery or chemicals often resulted in high costs and imprecise outcomes. To address these challenges, an advanced image recognition algorithm was proposed, which harnessed smart machines to minimize costs and environmental risks. By utilizing computer vision technology, weeds were accurately identified and targeted for removal. A machine learning model was trained using relevant datasets to enable precise weed management. The AI-powered robot, equipped with advanced image recognition algorithms, demonstrated exceptional accuracy and speed, performing weed removal and decomposition 1.2 times faster than traditional manual labour. This breakthrough in weed management technology offers farmers a means to optimize crop yields, enhance food production, and minimize the environmental impact associated with chemical herbicides. A prototype of the robot was fabricated and evaluated in real-world farming conditions. Field tests were conducted on a bean farm and it’s demonstrated the robot's exceptional accuracy, with only a 2% deviation from the actual weed quantity. This research showcased the potential of AI-based weed management systems in legume farming, offering cost-effective and precise weed detection and removal. This research sets a precedent for the integration of AI in modern agriculture, driving the industry toward a more environmentally conscious and economically viable future. The AI-based weed management system empowers farmers, ensuring bountiful harvests, increased profitability, and a greener, more sustainable tomorrow while attention should be given to manufacturing this model for industrial and or commercial applications.","PeriodicalId":394198,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131729320","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：