Pub Date : 2023-05-31DOI: 10.3390/inventions8030076
T. Nguyen, L. Dang, Truong-Dong Do, J. Lim
Growth factors affect farm owners, environmental conditions, nutrient adaptation, and resistance to chrysanthemum diseases. Healthy chrysanthemum plants can overcome all these factors and provide farms owners with a lot of income. Chrysanthemum white rust disease is a common disease that occurs worldwide; if not treated promptly, the disease spreads to the entire leaf surface, causing the plant’s leaves to burn, turn yellow, and fall prematurely, reducing the photosynthetic performance of the plant and the appearance of the flower branches. In Korea, chrysanthemum white rust disease most often occurs during the spring and autumn seasons, when temperature varies during the summer monsoon, and when ventilation is poor in the winter. Deep neural networks were used to determine healthy and unhealthy plants. We applied the Raspberry Pi 3 module to recognize white rust and test four neural network models. The five main deep neural network processes utilized for a dataset of non-diseased and white rust leaves include: (1) data collection; (2) data partitioning; (3) feature extraction; (4) feature engineering; and (5) prediction modeling based on the train–test loss of 35 epochs within 20 min using Linux. White rust recognition is performed for comparison using four models, namely, DenseNet121, ResNet50, VGG-19, and MobileNet v2. The qualitative white rust detection system is achieved using a Raspberry Pi 3 module. All models accomplished an accuracy of over 94%, and MobileNet v2 achieved the highest accuracy, precision, and recall at over 98%. In the precision comparison, DenseNet121 obtained the second highest recognition accuracy of 97%, whereas ResNet50 and VGG-19 achieved slightly lower accuracies at 95% and 94%, respectively. Qualitative results were obtained using the Raspberry Pi 3 module to assess the performance of the four models. All models had accuracies of over 91%, with ResNet50 obtaining a value of 91%, VGG19 reaching a value of 93%, and DenseNet121 reaching 95%. The highest accuracy rate was 97% (MobileNet v2). MobileNet v2 was validated as the most effective model to recognize white rust in chrysanthemums using the Raspberry Pi 3 system. Raspberry Pi 3 module was considered, in conjunction with the MobileNet v2 model, to be the best application system. MobileNet v2 and Raspberry Pi require a low cost for the recognition of chrysanthemum white rust and the diagnosis of chrysanthemum plant health conditions, reducing the risk of white rust disease and minimizing costs and efforts while improving floral production. Chrysanthemum farmers should consider applying the Raspberry Pi module for detecting white rust, protecting healthy plant growth, and increasing yields with low-cost.
{"title":"The First Study of White Rust Disease Recognition by Using Deep Neural Networks and Raspberry Pi Module Application in Chrysanthemum","authors":"T. Nguyen, L. Dang, Truong-Dong Do, J. Lim","doi":"10.3390/inventions8030076","DOIUrl":"https://doi.org/10.3390/inventions8030076","url":null,"abstract":"Growth factors affect farm owners, environmental conditions, nutrient adaptation, and resistance to chrysanthemum diseases. Healthy chrysanthemum plants can overcome all these factors and provide farms owners with a lot of income. Chrysanthemum white rust disease is a common disease that occurs worldwide; if not treated promptly, the disease spreads to the entire leaf surface, causing the plant’s leaves to burn, turn yellow, and fall prematurely, reducing the photosynthetic performance of the plant and the appearance of the flower branches. In Korea, chrysanthemum white rust disease most often occurs during the spring and autumn seasons, when temperature varies during the summer monsoon, and when ventilation is poor in the winter. Deep neural networks were used to determine healthy and unhealthy plants. We applied the Raspberry Pi 3 module to recognize white rust and test four neural network models. The five main deep neural network processes utilized for a dataset of non-diseased and white rust leaves include: (1) data collection; (2) data partitioning; (3) feature extraction; (4) feature engineering; and (5) prediction modeling based on the train–test loss of 35 epochs within 20 min using Linux. White rust recognition is performed for comparison using four models, namely, DenseNet121, ResNet50, VGG-19, and MobileNet v2. The qualitative white rust detection system is achieved using a Raspberry Pi 3 module. All models accomplished an accuracy of over 94%, and MobileNet v2 achieved the highest accuracy, precision, and recall at over 98%. In the precision comparison, DenseNet121 obtained the second highest recognition accuracy of 97%, whereas ResNet50 and VGG-19 achieved slightly lower accuracies at 95% and 94%, respectively. Qualitative results were obtained using the Raspberry Pi 3 module to assess the performance of the four models. All models had accuracies of over 91%, with ResNet50 obtaining a value of 91%, VGG19 reaching a value of 93%, and DenseNet121 reaching 95%. The highest accuracy rate was 97% (MobileNet v2). MobileNet v2 was validated as the most effective model to recognize white rust in chrysanthemums using the Raspberry Pi 3 system. Raspberry Pi 3 module was considered, in conjunction with the MobileNet v2 model, to be the best application system. MobileNet v2 and Raspberry Pi require a low cost for the recognition of chrysanthemum white rust and the diagnosis of chrysanthemum plant health conditions, reducing the risk of white rust disease and minimizing costs and efforts while improving floral production. Chrysanthemum farmers should consider applying the Raspberry Pi module for detecting white rust, protecting healthy plant growth, and increasing yields with low-cost.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44466964","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 : 2023-05-26DOI: 10.3390/inventions8030075
Giulio Galiè, Michele Cappelli, Pietro Maffei, Matteo Robusti, Igor Vasileski, L. Frizziero
In the contemporary automobile scene, environmental effect abatement is being increasingly sought; this demands a full rethinking of the entire system and entails more than just the reduction in exhaust pollutant emissions. Currently, the most popular approach is the electrification of automobiles, which significantly reduces pollution in major urban areas while simultaneously posing a new set of problems. The two types of zero-emission vehicles that are now being developed the most are hydrogen fuel cells and battery electric cars, but another option is the Hydrogen Internal Combustion Engine (HYICE) engine, which is highly advantageous in terms of pollutants, aside from Nitrogen Oxides (NOx), which can be considerably decreased. The purpose of this study is to develop a novel vehicle design that transports this type of technology into a sporting context while striving for considerable environmental benefits and integrating them into a society where the love of automobiles still has a strong following. The cutting-edge Industrial Design Structure (IDeS) methodology is used in this work, and a sample structure was created to demonstrate how the problems and technical limitations represented can be solved. The steps of the methodology are followed to shape the final product, with careful consideration given to the design of the styling component through the use of the Stylistic Design Engineering (SDE) method. With the ultimate goal of achieving sustainable driving pleasure, the study looks into whether recyclable materials can be used for the body and whether extremely light materials can be used for the chassis.
{"title":"Use of IDeS Method to Design an Innovative HYICE Sportscar","authors":"Giulio Galiè, Michele Cappelli, Pietro Maffei, Matteo Robusti, Igor Vasileski, L. Frizziero","doi":"10.3390/inventions8030075","DOIUrl":"https://doi.org/10.3390/inventions8030075","url":null,"abstract":"In the contemporary automobile scene, environmental effect abatement is being increasingly sought; this demands a full rethinking of the entire system and entails more than just the reduction in exhaust pollutant emissions. Currently, the most popular approach is the electrification of automobiles, which significantly reduces pollution in major urban areas while simultaneously posing a new set of problems. The two types of zero-emission vehicles that are now being developed the most are hydrogen fuel cells and battery electric cars, but another option is the Hydrogen Internal Combustion Engine (HYICE) engine, which is highly advantageous in terms of pollutants, aside from Nitrogen Oxides (NOx), which can be considerably decreased. The purpose of this study is to develop a novel vehicle design that transports this type of technology into a sporting context while striving for considerable environmental benefits and integrating them into a society where the love of automobiles still has a strong following. The cutting-edge Industrial Design Structure (IDeS) methodology is used in this work, and a sample structure was created to demonstrate how the problems and technical limitations represented can be solved. The steps of the methodology are followed to shape the final product, with careful consideration given to the design of the styling component through the use of the Stylistic Design Engineering (SDE) method. With the ultimate goal of achieving sustainable driving pleasure, the study looks into whether recyclable materials can be used for the body and whether extremely light materials can be used for the chassis.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43141297","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 : 2023-05-22DOI: 10.3390/inventions8030074
N. Tudoroiu, M. Zaheeruddin, Roxana-Elena Tudoroiu, M. Radu, Hana Chammas
This research paper aims to design and implement an intelligent least short time memory (LSTM) deep learning classification technique to detect possible anomalies in measurements dataset within a particular Li-ion battery type. For the state of charge (SOC) and battery faults estimation, a Joint State and Parameter Extended Kalman Filter (JEKF) estimator is developed. The SOC accuracy performance is excellent, with less than 0.5% error during steady-state, compared to the 2% error reported in the literature. For the design and implementation of JEKF SOC and parameter estimation is chosen a preset Li-ion battery Simulink Simscape generic model. It is also helpful to generate the healthy and faulty measurement dataset to design and implement the proposed intelligent LSTM classifier deep learning technique. The generic Li-ion battery model is wisely selected for the “proof concept” purpose, model validation, and algorithms’ robustness, accuracy, and effectiveness. Compared to the traditional EKF fault diagnosis and isolation (FDI), a model-based estimation strategy, the proposed classification LSTM technique is an intelligent data-driven-based deep learning algorithm of high accuracy (around 80%) and loss performance close to zero. Therefore, this feature makes data collection of dataset measurements directly from Li-ion battery sensors possible, which is beneficial for generating online fault scenarios. Additionally, the LSTM deep learning technique can remarkably classify all detected anomalies with high accuracy, independent of battery model accuracy, uncertainties, and unmodeled dynamics. Also, high-performance accuracy root mean square error (RMSE) of 0.0588 (voltage fault), approximately 5.5×10−7 (healthy) and 8.87 × 10−6 (current fault) for deep learning shallow neural network (DLSNN) reveals an obvious superiority of both compared to the traditional FDI estimation strategies.
{"title":"Investigations on Using Intelligent Learning Techniques for Anomaly Detection and Diagnosis in Sensors Signals in Li-Ion Battery—Case Study","authors":"N. Tudoroiu, M. Zaheeruddin, Roxana-Elena Tudoroiu, M. Radu, Hana Chammas","doi":"10.3390/inventions8030074","DOIUrl":"https://doi.org/10.3390/inventions8030074","url":null,"abstract":"This research paper aims to design and implement an intelligent least short time memory (LSTM) deep learning classification technique to detect possible anomalies in measurements dataset within a particular Li-ion battery type. For the state of charge (SOC) and battery faults estimation, a Joint State and Parameter Extended Kalman Filter (JEKF) estimator is developed. The SOC accuracy performance is excellent, with less than 0.5% error during steady-state, compared to the 2% error reported in the literature. For the design and implementation of JEKF SOC and parameter estimation is chosen a preset Li-ion battery Simulink Simscape generic model. It is also helpful to generate the healthy and faulty measurement dataset to design and implement the proposed intelligent LSTM classifier deep learning technique. The generic Li-ion battery model is wisely selected for the “proof concept” purpose, model validation, and algorithms’ robustness, accuracy, and effectiveness. Compared to the traditional EKF fault diagnosis and isolation (FDI), a model-based estimation strategy, the proposed classification LSTM technique is an intelligent data-driven-based deep learning algorithm of high accuracy (around 80%) and loss performance close to zero. Therefore, this feature makes data collection of dataset measurements directly from Li-ion battery sensors possible, which is beneficial for generating online fault scenarios. Additionally, the LSTM deep learning technique can remarkably classify all detected anomalies with high accuracy, independent of battery model accuracy, uncertainties, and unmodeled dynamics. Also, high-performance accuracy root mean square error (RMSE) of 0.0588 (voltage fault), approximately 5.5×10−7 (healthy) and 8.87 × 10−6 (current fault) for deep learning shallow neural network (DLSNN) reveals an obvious superiority of both compared to the traditional FDI estimation strategies.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48864039","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 : 2023-05-16DOI: 10.3390/inventions8030072
Meysam Gheisarnejad, Mohammad-Hassan Khooban
While impressive progress has been already achieved in wide-bandgap (WBG) semiconductors such as 4H-SiC and GaN technologies, the lack of intelligent methodologies to control the gate drivers has prevented exploitation of the maximum potential of semiconductor chips from obtaining the desired device operations. Thus, a potent ongoing trend is to design a fast gate driver switching scheme to upgrade the performance of electronic equipment at the system level. To address this issue, this work proposed a novel intelligent scheme for the control of gate driver switching using the concept of quantum computation in machine learning. In particular, the quantum principle was incorporated into deep reinforcement learning (DRL) to address the hardware limitations of conventional computers and the growing amount of data sets. Taking potential benefit of the quantum theory, the DRL algorithm influenced by quantum specifications (referred to as QDRL) not only ameliorates the performance of the native algorithm on traditional computers but also enhances the progress of relevant research fields like quantum computing and machine learning. To test the practicability and usefulness of QDRL, a dc/dc parallel boost converter feeding constant power loads (CPLs) was chosen as the case study, and several power hardware-in-the-loop (PHiL) experiments and comparative analysis were performed.
{"title":"Quantum Power Electronics: From Theory to Implementation","authors":"Meysam Gheisarnejad, Mohammad-Hassan Khooban","doi":"10.3390/inventions8030072","DOIUrl":"https://doi.org/10.3390/inventions8030072","url":null,"abstract":"While impressive progress has been already achieved in wide-bandgap (WBG) semiconductors such as 4H-SiC and GaN technologies, the lack of intelligent methodologies to control the gate drivers has prevented exploitation of the maximum potential of semiconductor chips from obtaining the desired device operations. Thus, a potent ongoing trend is to design a fast gate driver switching scheme to upgrade the performance of electronic equipment at the system level. To address this issue, this work proposed a novel intelligent scheme for the control of gate driver switching using the concept of quantum computation in machine learning. In particular, the quantum principle was incorporated into deep reinforcement learning (DRL) to address the hardware limitations of conventional computers and the growing amount of data sets. Taking potential benefit of the quantum theory, the DRL algorithm influenced by quantum specifications (referred to as QDRL) not only ameliorates the performance of the native algorithm on traditional computers but also enhances the progress of relevant research fields like quantum computing and machine learning. To test the practicability and usefulness of QDRL, a dc/dc parallel boost converter feeding constant power loads (CPLs) was chosen as the case study, and several power hardware-in-the-loop (PHiL) experiments and comparative analysis were performed.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136066282","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 : 2023-05-12DOI: 10.3390/inventions8030071
O. Afanaseva, O. Bezyukov, D. Pervukhin, D. Tukeev
The article discusses the method and results of processing statistical data from an experimental study of vibrations in marine diesel engines caused by the operation of cylinder-piston groups. The results of the application of a ranking method for identifying factors that influence vibration in marine diesel engines are presented to determine the most significant ones. A series of experiments were conducted according to special plans to actively implement the random balance method. This helped to establish the correctness of selecting the most significant factors from a variety of factors that influence the process under study. The article presents a mathematical model that enables the calculation of current values and prediction of changes in the most significant indicators, with the clearance between the piston and the cylinder liner being the most important.
{"title":"Experimental Study Results Processing Method for the Marine Diesel Engines Vibration Activity Caused by the Cylinder-Piston Group Operations","authors":"O. Afanaseva, O. Bezyukov, D. Pervukhin, D. Tukeev","doi":"10.3390/inventions8030071","DOIUrl":"https://doi.org/10.3390/inventions8030071","url":null,"abstract":"The article discusses the method and results of processing statistical data from an experimental study of vibrations in marine diesel engines caused by the operation of cylinder-piston groups. The results of the application of a ranking method for identifying factors that influence vibration in marine diesel engines are presented to determine the most significant ones. A series of experiments were conducted according to special plans to actively implement the random balance method. This helped to establish the correctness of selecting the most significant factors from a variety of factors that influence the process under study. The article presents a mathematical model that enables the calculation of current values and prediction of changes in the most significant indicators, with the clearance between the piston and the cylinder liner being the most important.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41853612","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 : 2023-05-09DOI: 10.3390/inventions8030069
Arkar Minn, R. M. R. D. Abeyrathna, Victor Massaki Nakaguchi, T. Ahamed
Developing countries in Asia widely use manual seed broadcasting methods due to a lack of appropriate seeding machinery. The agricultural sector is currently facing labor shortages and high labor costs, especially seasonal labor shortages for broadcasting and transplanting operations. However, the primary constraint in adopting existing broadcasting seeders for small-scale farmers in developing countries is the high initial purchase costs. Therefore, developing locally commercial accessible technology for small-scale farmers is an urgent requirement. In this regard, attempt was taken to develop a new low-cost 3D printed seeder that can be used for multi-crop seed broadcasting operations when integrated with an autonomous terrain vehicle. A new seed metering mechanism was proposed for seed broadcasting that can be controlled electronically from the autonomous terrain vehicle. Positional sensors based on the real time kinematics—global navigation satellite system (RTK-GNSS) were used to record positional information. The best observation was noted at a vehicle operational speed of 0.351 ms−1 and had a coefficient of variation (CV) referring to the distribution uniformity of seeds of 19% for green peas, 22% for cowpeas, and 25% for chickpeas. The developed seeder could spread multi-crop seeds and adjust the seed rates electronically at the different ranges of rotational speeds. Therefore, the use of 3D printed fabricated prototype seed broadcasting units with small-scale autonomous vehicles can be implemented to help in labor supplements and perform the broadcasting of different seeds.
{"title":"Development of a 3D Printed New Metering Mechanism for a Multi-Crop Seed Broadcasting System Using an Autonomous Small-Scale Vehicle","authors":"Arkar Minn, R. M. R. D. Abeyrathna, Victor Massaki Nakaguchi, T. Ahamed","doi":"10.3390/inventions8030069","DOIUrl":"https://doi.org/10.3390/inventions8030069","url":null,"abstract":"Developing countries in Asia widely use manual seed broadcasting methods due to a lack of appropriate seeding machinery. The agricultural sector is currently facing labor shortages and high labor costs, especially seasonal labor shortages for broadcasting and transplanting operations. However, the primary constraint in adopting existing broadcasting seeders for small-scale farmers in developing countries is the high initial purchase costs. Therefore, developing locally commercial accessible technology for small-scale farmers is an urgent requirement. In this regard, attempt was taken to develop a new low-cost 3D printed seeder that can be used for multi-crop seed broadcasting operations when integrated with an autonomous terrain vehicle. A new seed metering mechanism was proposed for seed broadcasting that can be controlled electronically from the autonomous terrain vehicle. Positional sensors based on the real time kinematics—global navigation satellite system (RTK-GNSS) were used to record positional information. The best observation was noted at a vehicle operational speed of 0.351 ms−1 and had a coefficient of variation (CV) referring to the distribution uniformity of seeds of 19% for green peas, 22% for cowpeas, and 25% for chickpeas. The developed seeder could spread multi-crop seeds and adjust the seed rates electronically at the different ranges of rotational speeds. Therefore, the use of 3D printed fabricated prototype seed broadcasting units with small-scale autonomous vehicles can be implemented to help in labor supplements and perform the broadcasting of different seeds.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41765179","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 : 2023-05-09DOI: 10.3390/inventions8030070
Jakfar, H. Husin, Mohammadi Zaki, Lia Mairiza, Mirna Zulrika, F. Nasution, Ahmadi
Increasing CO2 gas emissions results in climate change by increasing air temperature and worsening environmental problems. It is necessary to control CO2 gas in the air to overcome this. This research aims to optimize the absorption of CO2 gas in the air with 0.1 M NaOH absorbent in the tower of the Raschig ring stuffing material using the response surface methodology (RSM). This research was conducted using a continuous system of three independent variables by varying the contact time (10–80 min), the flow rate of NaOH absorbent (2–5 L/min), and the flow rate of CO2 gas (1–5 L/min). The response variables in this study were the absorption rate (L/min) and mass transfer coefficient, while the air flow rate was constant at 20 L/min. Air and CO2 gas mix before absorption occurs and flow into the Raschig ring packing column so that contact occurs with the NaOH absorbent. Mass transfer of CO2 gas occurs into the NaOH absorbent, resulting in absorption. The results showed that the effect of contact time (min), the flow rate of NaOH absorbent (L/min), and CO2 gas flow rate individually and the interaction on CO2 absorption rate and mass transfer coefficient were very significant at a p-value of 0.05. Chemical absorption of CO2 also occurred due to the reaction between CO2 and OH- to form CO32− and HCO3−, so the pH decreased, and the reaction was a function of pH. Optimization using Design Expert 13 RSM Box–Behnken Design (BBD) yielded optimal conditions at an absorption time of 80 min, NaOH absorbent flow rate of 5 L/min, CO2 gas flow rate of 5 L/min, absorption rate of CO2 gas of 3.97 L/min, and CO2 gas mass transfer coefficient of 1.443 mol/min m2 atm, with the desirability of 0.999 (≈100%).
{"title":"Optimization Study of CO2 Gas Absorption with NaOH Absorbent Continuous System in Raschig Ring Packing Column Using Box–Behnken Design","authors":"Jakfar, H. Husin, Mohammadi Zaki, Lia Mairiza, Mirna Zulrika, F. Nasution, Ahmadi","doi":"10.3390/inventions8030070","DOIUrl":"https://doi.org/10.3390/inventions8030070","url":null,"abstract":"Increasing CO2 gas emissions results in climate change by increasing air temperature and worsening environmental problems. It is necessary to control CO2 gas in the air to overcome this. This research aims to optimize the absorption of CO2 gas in the air with 0.1 M NaOH absorbent in the tower of the Raschig ring stuffing material using the response surface methodology (RSM). This research was conducted using a continuous system of three independent variables by varying the contact time (10–80 min), the flow rate of NaOH absorbent (2–5 L/min), and the flow rate of CO2 gas (1–5 L/min). The response variables in this study were the absorption rate (L/min) and mass transfer coefficient, while the air flow rate was constant at 20 L/min. Air and CO2 gas mix before absorption occurs and flow into the Raschig ring packing column so that contact occurs with the NaOH absorbent. Mass transfer of CO2 gas occurs into the NaOH absorbent, resulting in absorption. The results showed that the effect of contact time (min), the flow rate of NaOH absorbent (L/min), and CO2 gas flow rate individually and the interaction on CO2 absorption rate and mass transfer coefficient were very significant at a p-value of 0.05. Chemical absorption of CO2 also occurred due to the reaction between CO2 and OH- to form CO32− and HCO3−, so the pH decreased, and the reaction was a function of pH. Optimization using Design Expert 13 RSM Box–Behnken Design (BBD) yielded optimal conditions at an absorption time of 80 min, NaOH absorbent flow rate of 5 L/min, CO2 gas flow rate of 5 L/min, absorption rate of CO2 gas of 3.97 L/min, and CO2 gas mass transfer coefficient of 1.443 mol/min m2 atm, with the desirability of 0.999 (≈100%).","PeriodicalId":14564,"journal":{"name":"Inventions","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48378965","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 : 2023-05-08DOI: 10.3390/inventions8030068
R. Ilyasov
This paper describes a universal method proposed by the author for the evaluative analytical calculation of the main parameters of synchronous electrical machines, including superconducting ones. Traditional methods for analytical calculation of parameters to build a phasor diagram of electrical machines require a calculation of all dimensions of the active zone, tooth-slot zone and frontal parts of armature windings. All sizes and local states of magnetic circuit saturation are necessary for the calculation of magnetic conductivities. Traditional analytical methods use, among other things, empirical formulas and non-physical coefficients and allow one to calculate only standard machines with classic tooth-slot zones and armature winding types. As a result of drawing a phasor diagram using traditional methods, the angle between the electromotive force and voltage is calculated, which is the machine’s internal parameter and has no major significance for users. The application of modern computer programs for simulation requires a preliminary analytical calculation in order to obtain all dimensions of the three-dimensional model. FEM simulation programs are expensive, require expensive high-performance computers and highly paid skilled personnel. Fast analytical techniques are also required to assess the correctness of the obtained automatic computer simulation results. The proposed analytical method makes it possible to quickly obtain all the main parameters of a newly designed machine (including superconducting ones and those of non-traditional design) without a detailed calculation of the dimensions of the tooth-slot zone and armature end-windings. The characteristic values of load angles are set according to the results of simple calculations, and the desired values, obtained via plotting, represent the inductive resistances of armature winding and inductive voltage drop across it. Results of practical significance, calculated from the voltage diagram, are as follows: the inductor’s magnetomotive force necessary to maintain the nominal load voltage value, regardless of the magnitude (including double overload) and type of the connected load, or the main dimensions of the active zone.
{"title":"The Phasor Diagram of a Superconducting Synchronous Electrical Machine","authors":"R. Ilyasov","doi":"10.3390/inventions8030068","DOIUrl":"https://doi.org/10.3390/inventions8030068","url":null,"abstract":"This paper describes a universal method proposed by the author for the evaluative analytical calculation of the main parameters of synchronous electrical machines, including superconducting ones. Traditional methods for analytical calculation of parameters to build a phasor diagram of electrical machines require a calculation of all dimensions of the active zone, tooth-slot zone and frontal parts of armature windings. All sizes and local states of magnetic circuit saturation are necessary for the calculation of magnetic conductivities. Traditional analytical methods use, among other things, empirical formulas and non-physical coefficients and allow one to calculate only standard machines with classic tooth-slot zones and armature winding types. As a result of drawing a phasor diagram using traditional methods, the angle between the electromotive force and voltage is calculated, which is the machine’s internal parameter and has no major significance for users. The application of modern computer programs for simulation requires a preliminary analytical calculation in order to obtain all dimensions of the three-dimensional model. FEM simulation programs are expensive, require expensive high-performance computers and highly paid skilled personnel. Fast analytical techniques are also required to assess the correctness of the obtained automatic computer simulation results. The proposed analytical method makes it possible to quickly obtain all the main parameters of a newly designed machine (including superconducting ones and those of non-traditional design) without a detailed calculation of the dimensions of the tooth-slot zone and armature end-windings. The characteristic values of load angles are set according to the results of simple calculations, and the desired values, obtained via plotting, represent the inductive resistances of armature winding and inductive voltage drop across it. Results of practical significance, calculated from the voltage diagram, are as follows: the inductor’s magnetomotive force necessary to maintain the nominal load voltage value, regardless of the magnitude (including double overload) and type of the connected load, or the main dimensions of the active zone.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47499933","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 : 2023-05-06DOI: 10.3390/inventions8030067
I. D. Pranata, Phuc Thanh-Thien Nguyen, Kuo-Ho Su, Yu-Cheng Kuo, C. Kuo
This paper presents a microcontroller-based solution for generating real-time normal walking knee angle of a powered transfemoral prosthetic leg prototype. The proposed control algorithm was used to determine the prosthetic knee angle by utilizing seven hip angle movement features generated from only the inertia measurement unit (IMU) deployed on the prosthetic socket on the thigh of the same side. Then, a proportional–integral–derivative (PID) controller is developed to control the motor to reach the desired knee angle in real time. Furthermore, a novel parallel four-bar linkage-based master–slave validation framework combining a motion capture system was introduced to evaluate the performance of the knee angle generation on a speed-adjustable treadmill with able-bodied subjects. In the framework evaluation, 3 different walking speeds were applied to the treadmill to validate different speed adaptation capabilities of the prosthetic leg control system, precisely 50 cm/s, 60 cm/s, and 70 cm/s. Through the proposed 4-bar linkage framework, the prosthesis’s movement can simulate able-bodied subjects well with maximum RMSE never exceeding 0.27° in the swing flexion phase, 4.4° to 5.8° in the stance phase, and 1.953° to 13.466° in the swing extension phase. The treadmill results showed that the prosthetic leg is able to perform a normal walking gait following different walking speeds of the subject. Finally, a corridor walking experiment with a bypass adapter was successfully performed to examine the feasibility of real prosthetic walking situations.
{"title":"Knee Angle Generation with Walking Speed Adaptation Ability for a Powered Transfemoral Prosthetic Leg Prototype","authors":"I. D. Pranata, Phuc Thanh-Thien Nguyen, Kuo-Ho Su, Yu-Cheng Kuo, C. Kuo","doi":"10.3390/inventions8030067","DOIUrl":"https://doi.org/10.3390/inventions8030067","url":null,"abstract":"This paper presents a microcontroller-based solution for generating real-time normal walking knee angle of a powered transfemoral prosthetic leg prototype. The proposed control algorithm was used to determine the prosthetic knee angle by utilizing seven hip angle movement features generated from only the inertia measurement unit (IMU) deployed on the prosthetic socket on the thigh of the same side. Then, a proportional–integral–derivative (PID) controller is developed to control the motor to reach the desired knee angle in real time. Furthermore, a novel parallel four-bar linkage-based master–slave validation framework combining a motion capture system was introduced to evaluate the performance of the knee angle generation on a speed-adjustable treadmill with able-bodied subjects. In the framework evaluation, 3 different walking speeds were applied to the treadmill to validate different speed adaptation capabilities of the prosthetic leg control system, precisely 50 cm/s, 60 cm/s, and 70 cm/s. Through the proposed 4-bar linkage framework, the prosthesis’s movement can simulate able-bodied subjects well with maximum RMSE never exceeding 0.27° in the swing flexion phase, 4.4° to 5.8° in the stance phase, and 1.953° to 13.466° in the swing extension phase. The treadmill results showed that the prosthetic leg is able to perform a normal walking gait following different walking speeds of the subject. Finally, a corridor walking experiment with a bypass adapter was successfully performed to examine the feasibility of real prosthetic walking situations.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43866187","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 : 2023-04-28DOI: 10.3390/inventions8030065
S. Korsakova, Vadim Korzin, Y. Plugatar, A. Kazak, V. Gorina, N. Korzina, S. Khokhlov, K. Makoveichuk
This study presents the results of the development of numerical models for predicting the timing of apricot flowering, including using experimental data on the emergence of plants from a state of deep dormancy. The best results of approximation of the process of accumulation of the necessary cooling in the autumn–winter period were obtained using the sigmoidal function. Models that take into account the combined effect of temperature and photoperiod on the processes of spring development showed a high accuracy of the process of accumulation of thermal units. Based on the results of testing, two models were selected with an accuracy of 3.0 days for the start of flowering and the absence of a systematic bias, which can be considered a good quality assessment These models describe well the interannual variability of apricot flowering dates and can be used to predict these dates. The discrepancy is no more than 2–4 days in 87–89% of cases. Estimates of the timing of flowering and the end of deep dormancy are very important for increasing the profitability of fruit production in the South of Russia without incurring additional costs, by minimizing the risks associated with irrational crop placement and the selection of varieties without taking into account the specifics of climate change. When constructing a system of protective measures and dates of treatments, it is also necessary to take into account the calendar dates of the shift in the development of plants.
{"title":"Modelling of Climate Change’s Impact on Prunus armeniaca L.’s Flowering Time","authors":"S. Korsakova, Vadim Korzin, Y. Plugatar, A. Kazak, V. Gorina, N. Korzina, S. Khokhlov, K. Makoveichuk","doi":"10.3390/inventions8030065","DOIUrl":"https://doi.org/10.3390/inventions8030065","url":null,"abstract":"This study presents the results of the development of numerical models for predicting the timing of apricot flowering, including using experimental data on the emergence of plants from a state of deep dormancy. The best results of approximation of the process of accumulation of the necessary cooling in the autumn–winter period were obtained using the sigmoidal function. Models that take into account the combined effect of temperature and photoperiod on the processes of spring development showed a high accuracy of the process of accumulation of thermal units. Based on the results of testing, two models were selected with an accuracy of 3.0 days for the start of flowering and the absence of a systematic bias, which can be considered a good quality assessment These models describe well the interannual variability of apricot flowering dates and can be used to predict these dates. The discrepancy is no more than 2–4 days in 87–89% of cases. Estimates of the timing of flowering and the end of deep dormancy are very important for increasing the profitability of fruit production in the South of Russia without incurring additional costs, by minimizing the risks associated with irrational crop placement and the selection of varieties without taking into account the specifics of climate change. When constructing a system of protective measures and dates of treatments, it is also necessary to take into account the calendar dates of the shift in the development of plants.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44142433","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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