Pub Date : 2024-01-18DOI: 10.3390/inventions9010015
Carlos Mauricio Ruiz-Díaz, Erwing Eduardo Perilla-Plata, O. González-Estrada
The oil and gas industry consistently embraces innovative technologies due to the significant expenses associated with hydrocarbon transportation, pipeline corrosion issues, and the necessity to gain a deeper understanding of two-phase flow characteristics. These solutions involve the implementation of predictive models utilizing neural networks. In this research paper, a comprehensive database comprising 4864 data points, encompassing information pertaining to oil–water two-phase flow properties within vertical pipelines, was meticulously curated. Subsequently, an encoder-only type transformer neural network (TNN) was employed to identify two-phase flow patterns. Various configurations for the TNN model were proposed, involving parameter adjustments such as the number of attention heads, activation function, dropout rate, and learning rate, with the aim of selecting the configuration yielding optimal outcomes. Following the training of the network, predictions were generated using a reserved dataset, thus facilitating the creation of flow maps depicting the patterns anticipated by the model. The developed TNN model successfully predicted 9 out of the 10 flow patterns present in the database, achieving a peak accuracy of 53.07%. Furthermore, the various predicted flow patterns exhibited an average precision of 63.21% and an average accuracy of 86.51%.
{"title":"Two-Phase Flow Pattern Identification in Vertical Pipes Using Transformer Neural Networks","authors":"Carlos Mauricio Ruiz-Díaz, Erwing Eduardo Perilla-Plata, O. González-Estrada","doi":"10.3390/inventions9010015","DOIUrl":"https://doi.org/10.3390/inventions9010015","url":null,"abstract":"The oil and gas industry consistently embraces innovative technologies due to the significant expenses associated with hydrocarbon transportation, pipeline corrosion issues, and the necessity to gain a deeper understanding of two-phase flow characteristics. These solutions involve the implementation of predictive models utilizing neural networks. In this research paper, a comprehensive database comprising 4864 data points, encompassing information pertaining to oil–water two-phase flow properties within vertical pipelines, was meticulously curated. Subsequently, an encoder-only type transformer neural network (TNN) was employed to identify two-phase flow patterns. Various configurations for the TNN model were proposed, involving parameter adjustments such as the number of attention heads, activation function, dropout rate, and learning rate, with the aim of selecting the configuration yielding optimal outcomes. Following the training of the network, predictions were generated using a reserved dataset, thus facilitating the creation of flow maps depicting the patterns anticipated by the model. The developed TNN model successfully predicted 9 out of the 10 flow patterns present in the database, achieving a peak accuracy of 53.07%. Furthermore, the various predicted flow patterns exhibited an average precision of 63.21% and an average accuracy of 86.51%.","PeriodicalId":509629,"journal":{"name":"Inventions","volume":"117 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139616386","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 : 2024-01-12DOI: 10.3390/inventions9010014
Ping-Sheng Wang, Chien-Hung Lin, Cheng-Ta Chuang
This study proposes a drone system with visual identification and tracking capabilities to address the issue of limited communication bandwidth for drones. This system can lock onto a target during flight and transmit its simple features to the ground station, thereby reducing communication bandwidth demands. RealFlight is used as the simulation environment to validate the proposed drone algorithm. The core components of the system include DeepSORT and MobileNet lightweight models for target tracking. The designed fuzzy controller enables the system to adjust the drone’s motors, gradually moving the locked target to the center of the frame and maintaining continuous tracking. Additionally, this study introduces channel and spatial reliability tracking (CSRT) switching from multi-object to single-object tracking and multithreading technology to enhance the system’s execution speed. The experimental results demonstrate that the system can accurately adjust the target to the frame’s center within approximately 1.5 s, maintaining precision within ±0.5 degrees. On the Jetson Xavier NX embedded platform, the average frame rate (FPS) for the multi-object tracker was only 1.37, with a standard deviation of 1.05. In contrast, the single-object tracker CSRT exhibited a significant improvement, achieving an average FPS of 9.77 with a standard deviation of 1.86. This study provides an effective solution for visual tracking in drone systems that is efficient and conserves communication bandwidth. The validation of the embedded platform highlighted its practicality and performance.
{"title":"Real-Time Object Localization Using a Fuzzy Controller for a Vision-Based Drone","authors":"Ping-Sheng Wang, Chien-Hung Lin, Cheng-Ta Chuang","doi":"10.3390/inventions9010014","DOIUrl":"https://doi.org/10.3390/inventions9010014","url":null,"abstract":"This study proposes a drone system with visual identification and tracking capabilities to address the issue of limited communication bandwidth for drones. This system can lock onto a target during flight and transmit its simple features to the ground station, thereby reducing communication bandwidth demands. RealFlight is used as the simulation environment to validate the proposed drone algorithm. The core components of the system include DeepSORT and MobileNet lightweight models for target tracking. The designed fuzzy controller enables the system to adjust the drone’s motors, gradually moving the locked target to the center of the frame and maintaining continuous tracking. Additionally, this study introduces channel and spatial reliability tracking (CSRT) switching from multi-object to single-object tracking and multithreading technology to enhance the system’s execution speed. The experimental results demonstrate that the system can accurately adjust the target to the frame’s center within approximately 1.5 s, maintaining precision within ±0.5 degrees. On the Jetson Xavier NX embedded platform, the average frame rate (FPS) for the multi-object tracker was only 1.37, with a standard deviation of 1.05. In contrast, the single-object tracker CSRT exhibited a significant improvement, achieving an average FPS of 9.77 with a standard deviation of 1.86. This study provides an effective solution for visual tracking in drone systems that is efficient and conserves communication bandwidth. The validation of the embedded platform highlighted its practicality and performance.","PeriodicalId":509629,"journal":{"name":"Inventions","volume":" 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139624462","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 : 2024-01-11DOI: 10.3390/inventions9010013
P. Nagy, Ádám István Szabó, I. Zsoldos, György Szabados
Pollution from road vehicles enters the air environment from many sources. One such source could be if the vehicle is equipped with an auxiliary heater. They can be classified according to whether they work with diesel or gasoline and whether they heat water or air. The subject of our research series is an additional heating system that heats the air, the original fuel is gasoline. This device has been built up in a modern engine test bench, where the environmental parameters can be controlled. The length of the test cycle was chosen to be 30 min. The tested fuels were E10, E30, E100 and B7. A 30-min operating period has been chosen in the NORMAL operating mode of the device as a test cycle. The focus of the tests was particle number concentration and soot composition. The results of the particle number concentration showed that renewable fuel content significantly reduces the number concentration of the emitted particles (9.56 × 108 #/cycle for E10 vs. 1.65 × 108 #/cycle for E100), while B7 causes a significantly higher number of emissions than E10 (3.92 × 1010 #/cycle for B7). Based on the elemental analysis, most deposits are elemental carbon, but non-organic compounds are also present. Carbon (92.18 m/m% for E10), oxygen (6.34 m/m% for E10), fluorine (0.64 m/m% for E10), and zinc (0.56 m/m% for E10) have been found in the largest quantity of deposits taken form the combustion chamber.
{"title":"Particle Number Concentration and SEM-EDX Analyses of an Auxiliary Heating Device in Operation with Different Fossil and Renewable Fuel","authors":"P. Nagy, Ádám István Szabó, I. Zsoldos, György Szabados","doi":"10.3390/inventions9010013","DOIUrl":"https://doi.org/10.3390/inventions9010013","url":null,"abstract":"Pollution from road vehicles enters the air environment from many sources. One such source could be if the vehicle is equipped with an auxiliary heater. They can be classified according to whether they work with diesel or gasoline and whether they heat water or air. The subject of our research series is an additional heating system that heats the air, the original fuel is gasoline. This device has been built up in a modern engine test bench, where the environmental parameters can be controlled. The length of the test cycle was chosen to be 30 min. The tested fuels were E10, E30, E100 and B7. A 30-min operating period has been chosen in the NORMAL operating mode of the device as a test cycle. The focus of the tests was particle number concentration and soot composition. The results of the particle number concentration showed that renewable fuel content significantly reduces the number concentration of the emitted particles (9.56 × 108 #/cycle for E10 vs. 1.65 × 108 #/cycle for E100), while B7 causes a significantly higher number of emissions than E10 (3.92 × 1010 #/cycle for B7). Based on the elemental analysis, most deposits are elemental carbon, but non-organic compounds are also present. Carbon (92.18 m/m% for E10), oxygen (6.34 m/m% for E10), fluorine (0.64 m/m% for E10), and zinc (0.56 m/m% for E10) have been found in the largest quantity of deposits taken form the combustion chamber.","PeriodicalId":509629,"journal":{"name":"Inventions","volume":"40 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139534019","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 : 2024-01-09DOI: 10.3390/inventions9010012
Vladislav Liubčuk, Gediminas Kairaitis, V. Radziukynas, D. Naujokaitis
This paper focuses on both voltage transients and short-duration RMS variations, and presents a unique and heterogeneous approach to their assessment by applying AI tools. The database consists of both real (obtained from Lithuanian PQ monitoring campaigns) and synthetic data (obtained from the simulation and literature review). Firstly, this paper investigates the fundamental grid component and its harmonics filtering with an IIR shelving filter. Secondly, in a key part, both SVM and KNN are used to classify PQ events by their primary cause in the voltage–duration plane as well as by the type of short circuit in the three-dimensional voltage space. Thirdly, since it seemed to be difficult to interpret the results in the three-dimensional space, the new method, based on Clarke transformation, is developed to convert it to two-dimensional space. The method shows an outstanding performance by avoiding the loss of important information. In addition, a geometric analysis of the fault voltage in both two-dimensional and three-dimensional spaces revealed certain geometric patterns that are undoubtedly important for PQ classification. Finally, based on the results of a PQ monitoring campaign in the Lithuanian distribution grid, this paper presents a unique discussion regarding PQ assessment gaps that need to be solved in anticipation of a great leap forward and refers them to PQ legislation.
{"title":"IIR Shelving Filter, Support Vector Machine and k-Nearest Neighbors Algorithm Application for Voltage Transients and Short-Duration RMS Variations Analysis","authors":"Vladislav Liubčuk, Gediminas Kairaitis, V. Radziukynas, D. Naujokaitis","doi":"10.3390/inventions9010012","DOIUrl":"https://doi.org/10.3390/inventions9010012","url":null,"abstract":"This paper focuses on both voltage transients and short-duration RMS variations, and presents a unique and heterogeneous approach to their assessment by applying AI tools. The database consists of both real (obtained from Lithuanian PQ monitoring campaigns) and synthetic data (obtained from the simulation and literature review). Firstly, this paper investigates the fundamental grid component and its harmonics filtering with an IIR shelving filter. Secondly, in a key part, both SVM and KNN are used to classify PQ events by their primary cause in the voltage–duration plane as well as by the type of short circuit in the three-dimensional voltage space. Thirdly, since it seemed to be difficult to interpret the results in the three-dimensional space, the new method, based on Clarke transformation, is developed to convert it to two-dimensional space. The method shows an outstanding performance by avoiding the loss of important information. In addition, a geometric analysis of the fault voltage in both two-dimensional and three-dimensional spaces revealed certain geometric patterns that are undoubtedly important for PQ classification. Finally, based on the results of a PQ monitoring campaign in the Lithuanian distribution grid, this paper presents a unique discussion regarding PQ assessment gaps that need to be solved in anticipation of a great leap forward and refers them to PQ legislation.","PeriodicalId":509629,"journal":{"name":"Inventions","volume":"118 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139444618","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 : 2024-01-09DOI: 10.3390/inventions9010011
Sylwia Wciślik
This paper studies how the correlation with the Nusselt number affects the final result of the efficiency, ε, and exergy efficiency, ηex, of a chevron-type gasketed plate heat exchanger, which is installed in a typical small solar installation dedicated to single-family housing; the solar fluid is a TiO2:SiO2/EG:DI hybrid nanofluid with concentrations from 0% to 1.5% vol. The experimental model assumes constant flow of the solar fluid and varies on the domestic hot water side—from 3 lpm to 6 lpm. The inlet temperatures are 30 °C and 60 °C on the cold and hot sides of the heat exchanger, respectively. Of the six analysed correlations that showed similar trends, it is concluded that for the assumed flow conditions, geometry, and chevron angle of the plate heat exchanger, one model is the most accurate. The largest difference between the ηex values for a given concentration is 3.4%, so the exergy efficiency is not affected by the chosen Nusselt model by very much. However, the choice of correlation with the Nusselt number significantly affects the efficiency, ε; the difference between the values obtained within a given concentration is more than 40% and depends on the Reynolds number and flow. Most research discusses the scenario with the nanofluid as a coolant. This paper considers the opposite situation in which the solar fluid is a hotter working medium that transfers heat to domestic hot water installation.
{"title":"The Influence of Nusselt Correlation on Exergy Efficiency of a Plate Heat Exchanger Operating with TiO2:SiO2/EG:DI Hybrid Nanofluid","authors":"Sylwia Wciślik","doi":"10.3390/inventions9010011","DOIUrl":"https://doi.org/10.3390/inventions9010011","url":null,"abstract":"This paper studies how the correlation with the Nusselt number affects the final result of the efficiency, ε, and exergy efficiency, ηex, of a chevron-type gasketed plate heat exchanger, which is installed in a typical small solar installation dedicated to single-family housing; the solar fluid is a TiO2:SiO2/EG:DI hybrid nanofluid with concentrations from 0% to 1.5% vol. The experimental model assumes constant flow of the solar fluid and varies on the domestic hot water side—from 3 lpm to 6 lpm. The inlet temperatures are 30 °C and 60 °C on the cold and hot sides of the heat exchanger, respectively. Of the six analysed correlations that showed similar trends, it is concluded that for the assumed flow conditions, geometry, and chevron angle of the plate heat exchanger, one model is the most accurate. The largest difference between the ηex values for a given concentration is 3.4%, so the exergy efficiency is not affected by the chosen Nusselt model by very much. However, the choice of correlation with the Nusselt number significantly affects the efficiency, ε; the difference between the values obtained within a given concentration is more than 40% and depends on the Reynolds number and flow. Most research discusses the scenario with the nanofluid as a coolant. This paper considers the opposite situation in which the solar fluid is a hotter working medium that transfers heat to domestic hot water installation.","PeriodicalId":509629,"journal":{"name":"Inventions","volume":"56 32","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139442062","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 : 2024-01-03DOI: 10.3390/inventions9010008
Claudia Angélica Rivera-Romero, E. Palacios-Hernandez, O. Vite-Chávez, I. Reyes-Portillo
Constant monitoring is necessary for powdery mildew prevention in field crops because, as a fungal disease, it modifies the green pigments of the leaves and is responsible for production losses. Therefore, there is a need for solutions that assure early disease detection to realize proactive control and management of the disease. The methodology currently used for the identification of powdery mildew disease uses RGB leaf images to detect damage levels. In the early stage of the disease, no symptoms are visible, but this is a point at which the disease can be controlled before the symptoms appear. This study proposes the implementation of a support vector machine to identify powdery mildew on cucurbit plants using RGB images and color transformations. First, we use an image dataset that provides photos covering five growing seasons in different locations and under natural light conditions. Twenty-two texture descriptors using the gray-level co-occurrence matrix result are calculated as the main features. The proposed damage levels are ’healthy leaves’, ’leaves in the fungal germination phase’, ’leaves with first symptoms’, and ’diseased leaves’. The implementation reveals that the accuracy in the L * a * b color space is higher than that when using the combined components, with an accuracy value of 94% and kappa Cohen of 0.7638.
大田作物白粉病的预防需要持续监测，因为作为一种真菌病害，白粉病会改变叶片的绿色色素，造成产量损失。因此，需要能确保早期发现病害的解决方案，以实现对病害的主动控制和管理。目前用于识别白粉病的方法是使用 RGB 叶片图像来检测病害程度。在发病初期，症状并不明显，但此时可以在症状出现之前控制病情。本研究建议使用支持向量机，利用 RGB 图像和颜色变换来识别葫芦科植物上的白粉病。首先，我们使用了一个图像数据集，该数据集提供了不同地点和自然光条件下五个生长季节的照片。利用灰度级共现矩阵结果计算出 22 个纹理描述符作为主要特征。建议的损害等级为 "健康叶片"、"处于真菌发芽期的叶片"、"出现初期症状的叶片 "和 "病叶"。实施结果表明，在 L * a * b 色彩空间中的准确率高于使用组合成分时的准确率，准确率为 94%，kappa Cohen 为 0.7638。
{"title":"Early-Stage Identification of Powdery Mildew Levels for Cucurbit Plants in Open-Field Conditions Based on Texture Descriptors","authors":"Claudia Angélica Rivera-Romero, E. Palacios-Hernandez, O. Vite-Chávez, I. Reyes-Portillo","doi":"10.3390/inventions9010008","DOIUrl":"https://doi.org/10.3390/inventions9010008","url":null,"abstract":"Constant monitoring is necessary for powdery mildew prevention in field crops because, as a fungal disease, it modifies the green pigments of the leaves and is responsible for production losses. Therefore, there is a need for solutions that assure early disease detection to realize proactive control and management of the disease. The methodology currently used for the identification of powdery mildew disease uses RGB leaf images to detect damage levels. In the early stage of the disease, no symptoms are visible, but this is a point at which the disease can be controlled before the symptoms appear. This study proposes the implementation of a support vector machine to identify powdery mildew on cucurbit plants using RGB images and color transformations. First, we use an image dataset that provides photos covering five growing seasons in different locations and under natural light conditions. Twenty-two texture descriptors using the gray-level co-occurrence matrix result are calculated as the main features. The proposed damage levels are ’healthy leaves’, ’leaves in the fungal germination phase’, ’leaves with first symptoms’, and ’diseased leaves’. The implementation reveals that the accuracy in the L * a * b color space is higher than that when using the combined components, with an accuracy value of 94% and kappa Cohen of 0.7638.","PeriodicalId":509629,"journal":{"name":"Inventions","volume":"49 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139451679","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 : 2024-01-02DOI: 10.3390/inventions9010007
Haigang An, Po Yang, Hanyu Zhang, Xinquan Liu
In this work, a novel numerical method for studying the influence of gas types on drag reduction by microbubble injection is presented. Aimed at the microbubble drag reduction (MBDR) process for different types of gases, the mass transfer velocity of different types of gases in the gas–liquid phase is defined by writing a user-defined function (UDF), which reflected the influence of gas solubility on the drag reduction rate. An Eulerian multiphase flow model and the Realizable k−ε turbulence model are used for numerical calculation. The population balance model is used to describe the coalescence and breakup phenomena of the microbubble groups. Henry’s theorem is used to calculate the equilibrium concentration of the microbubble mixed flow. The interphase mass transfer rate of the microbubble injection process for different types of gases is studied by using permeation theory. The local mass fraction of the mixed flow is solved by the component transport equation. It is found that the larger the solubility of the gas, the lower the efficiency of MBDR. When the volume flow rate of the same type of gas is the same but the injection speed is different, the larger the solubility of the gas is, the greater the difference in the drag reduction ratio.
{"title":"Numerical Study of the Influence of the Type of Gas on Drag Reduction by Microbubble Injection","authors":"Haigang An, Po Yang, Hanyu Zhang, Xinquan Liu","doi":"10.3390/inventions9010007","DOIUrl":"https://doi.org/10.3390/inventions9010007","url":null,"abstract":"In this work, a novel numerical method for studying the influence of gas types on drag reduction by microbubble injection is presented. Aimed at the microbubble drag reduction (MBDR) process for different types of gases, the mass transfer velocity of different types of gases in the gas–liquid phase is defined by writing a user-defined function (UDF), which reflected the influence of gas solubility on the drag reduction rate. An Eulerian multiphase flow model and the Realizable k−ε turbulence model are used for numerical calculation. The population balance model is used to describe the coalescence and breakup phenomena of the microbubble groups. Henry’s theorem is used to calculate the equilibrium concentration of the microbubble mixed flow. The interphase mass transfer rate of the microbubble injection process for different types of gases is studied by using permeation theory. The local mass fraction of the mixed flow is solved by the component transport equation. It is found that the larger the solubility of the gas, the lower the efficiency of MBDR. When the volume flow rate of the same type of gas is the same but the injection speed is different, the larger the solubility of the gas is, the greater the difference in the drag reduction ratio.","PeriodicalId":509629,"journal":{"name":"Inventions","volume":"8 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139452371","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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