Pub Date : 2024-03-05DOI: 10.3390/inventions9020028
Mihnea Gall, O. Dumitrescu, V. Dragan, D. Crunțeanu
This research investigated a passive flow control technique to mitigate the adverse effects of shock wave–boundary layer interaction on a NACA 0012 airfoil. A perforated plate with a strategically positioned cavity beneath the shock wave anchoring spot was employed. Airfoils with perforated plates of varying orifice sizes (ranging from 0.5 to 1.2 mm) were constructed using various manufacturing techniques. Experimental analysis utilized an “Eiffel”-type open wind tunnel and a Z-type Schlieren system for flow visualization, along with static pressure measurements obtained from the bottom wall. Empirical observations were compared with steady 3D density-based numerical simulations conducted in Ansys FLUENT for comprehensive analysis and validation. The implementation of the perforated plate induced a significant alteration in shock structure, transforming it from a strong normal shock wave into a large lambda-type shock. The passive control case exhibited a 0.2% improvement in total pressure loss and attributed to the perforated plate’s capability to diminish the intensity of the shock wave anchored above. Significant fluctuations in shear stress were introduced by the perforated plate, with lower stress observed in the plate area due to flow detachment from cavity blowing. Balancing shock and viscous losses proved crucial for achieving a favorable outcome with this passive flow control method.
{"title":"Effects of Perforated Plates on Shock Structure Alteration for NACA0012 Airfoils","authors":"Mihnea Gall, O. Dumitrescu, V. Dragan, D. Crunțeanu","doi":"10.3390/inventions9020028","DOIUrl":"https://doi.org/10.3390/inventions9020028","url":null,"abstract":"This research investigated a passive flow control technique to mitigate the adverse effects of shock wave–boundary layer interaction on a NACA 0012 airfoil. A perforated plate with a strategically positioned cavity beneath the shock wave anchoring spot was employed. Airfoils with perforated plates of varying orifice sizes (ranging from 0.5 to 1.2 mm) were constructed using various manufacturing techniques. Experimental analysis utilized an “Eiffel”-type open wind tunnel and a Z-type Schlieren system for flow visualization, along with static pressure measurements obtained from the bottom wall. Empirical observations were compared with steady 3D density-based numerical simulations conducted in Ansys FLUENT for comprehensive analysis and validation. The implementation of the perforated plate induced a significant alteration in shock structure, transforming it from a strong normal shock wave into a large lambda-type shock. The passive control case exhibited a 0.2% improvement in total pressure loss and attributed to the perforated plate’s capability to diminish the intensity of the shock wave anchored above. Significant fluctuations in shear stress were introduced by the perforated plate, with lower stress observed in the plate area due to flow detachment from cavity blowing. Balancing shock and viscous losses proved crucial for achieving a favorable outcome with this passive flow control method.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140263442","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 : 2024-03-04DOI: 10.3390/inventions9020027
F. Sofos, G. Sofiadis, Efstathios Chatzoglou, Apostolos Palasis, T. Karakasidis, Antonios Liakopoulos
Convolutional neural networks (CNN) have been widely adopted in fluid dynamics investigations over the past few years due to their ability to extract and process fluid flow field characteristics. Both in sparse-grid simulations and sensor-based experimental data, the establishment of a dense flow field that embeds all spatial and temporal flow information is an open question, especially in the case of turbulent flows. In this paper, a deep learning (DL) method based on computational CNN layers is presented, focusing on reconstructing turbulent open channel flow fields of various resolutions. Starting from couples of images with low/high resolution, we train our DL model to efficiently reconstruct the velocity field of consecutive low-resolution data, which comes from a sparse-grid Direct Numerical Simulation (DNS), and focus on obtaining the accuracy of a respective dense-grid DNS. The reconstruction is assessed on the peak signal-to-noise ratio (PSNR), which is found to be high even in cases where the ground truth input is scaled down to 25 times.
过去几年，卷积神经网络（CNN）因其提取和处理流体流场特征的能力而被广泛应用于流体动力学研究。无论是在稀疏网格模拟还是基于传感器的实验数据中，建立包含所有空间和时间流动信息的密集流场都是一个未决问题，尤其是在湍流情况下。本文介绍了一种基于计算 CNN 层的深度学习（DL）方法，重点是重建不同分辨率的湍流明渠流场。我们从低/高分辨率的图像耦合开始，训练我们的 DL 模型，以高效地重建连续低分辨率数据（来自稀疏网格直接数值模拟（DNS））的速度场，并专注于获得相应密集网格 DNS 的精度。根据峰值信噪比（PSNR）对重建进行评估，发现即使地面实况输入缩减到 25 倍，峰值信噪比也很高。
{"title":"From Sparse to Dense Representations in Open Channel Flow Images with Convolutional Neural Networks","authors":"F. Sofos, G. Sofiadis, Efstathios Chatzoglou, Apostolos Palasis, T. Karakasidis, Antonios Liakopoulos","doi":"10.3390/inventions9020027","DOIUrl":"https://doi.org/10.3390/inventions9020027","url":null,"abstract":"Convolutional neural networks (CNN) have been widely adopted in fluid dynamics investigations over the past few years due to their ability to extract and process fluid flow field characteristics. Both in sparse-grid simulations and sensor-based experimental data, the establishment of a dense flow field that embeds all spatial and temporal flow information is an open question, especially in the case of turbulent flows. In this paper, a deep learning (DL) method based on computational CNN layers is presented, focusing on reconstructing turbulent open channel flow fields of various resolutions. Starting from couples of images with low/high resolution, we train our DL model to efficiently reconstruct the velocity field of consecutive low-resolution data, which comes from a sparse-grid Direct Numerical Simulation (DNS), and focus on obtaining the accuracy of a respective dense-grid DNS. The reconstruction is assessed on the peak signal-to-noise ratio (PSNR), which is found to be high even in cases where the ground truth input is scaled down to 25 times.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140266261","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 : 2024-01-05DOI: 10.3390/inventions9010010
Fariborz Ahmadi, Omid Abedi, S. Emadi
The evolution of agriculture towards a modern, intelligent system is crucial for achieving sustainable development and ensuring food security. In this context, leveraging the Internet of Things (IoT) stands as a pivotal strategy to enhance both crop quantity and quality while effectively managing natural resources such as water and fertilizer. Wireless sensor networks, the backbone of IoT-based smart agricultural infrastructure, gather ecosystem data and transmit them to sinks and drones. However, challenges persist, notably in network connectivity, energy consumption, and network lifetime, particularly when facing supernode and relay node failures. This paper introduces an innovative approach to address these challenges within heterogeneous wireless sensor network-based smart agriculture. The proposed solution comprises a novel connectivity management scheme and a dynamic clustering method facilitated by five distributed algorithms. The first and second algorithms focus on path collection, establishing connections between each node and m-supernodes via k-disjoint paths to ensure network robustness. The third and fourth algorithms provide sustained network connectivity during node and supernode failures by adjusting transmission powers and dynamically clustering agriculture sensors based on residual energy. In the fifth algorithm, an optimization algorithm is implemented on the dominating set problem to strategically position a subset of relay nodes as migration points for mobile supernodes to balance the network’s energy depletion. The suggested solution demonstrates superior performance in addressing connectivity, failure tolerance, load balancing, and network lifetime, ensuring optimal agricultural outcomes.
农业向现代化、智能化系统演进对于实现可持续发展和确保粮食安全至关重要。在此背景下，利用物联网（IoT）是提高作物数量和质量，同时有效管理水和肥料等自然资源的关键战略。无线传感器网络是以物联网为基础的智能农业基础设施的支柱，可收集生态系统数据并将其传输到汇和无人机。然而，挑战依然存在，特别是在网络连接、能耗和网络寿命方面，尤其是在面临超级节点和中继节点故障时。本文介绍了一种创新方法，以解决基于异构无线传感器网络的智慧农业所面临的这些挑战。所提出的解决方案包括一种新颖的连接管理方案和一种动态聚类方法，并通过五种分布式算法加以辅助。第一种和第二种算法侧重于路径收集，通过 k 个异点路径在每个节点和 m 个上节点之间建立连接，以确保网络的稳健性。第三和第四种算法通过调整传输功率和根据剩余能量对农业传感器进行动态聚类，在节点和超级节点发生故障时提供持续的网络连接。在第五种算法中，对支配集问题实施了优化算法，战略性地将中继节点子集定位为移动超级节点的迁移点，以平衡网络的能量消耗。所建议的解决方案在解决连通性、故障容忍度、负载平衡和网络寿命方面表现出卓越的性能，确保了最佳的农业成果。
{"title":"Enhancing Smart Agriculture Monitoring via Connectivity Management Scheme and Dynamic Clustering Strategy","authors":"Fariborz Ahmadi, Omid Abedi, S. Emadi","doi":"10.3390/inventions9010010","DOIUrl":"https://doi.org/10.3390/inventions9010010","url":null,"abstract":"The evolution of agriculture towards a modern, intelligent system is crucial for achieving sustainable development and ensuring food security. In this context, leveraging the Internet of Things (IoT) stands as a pivotal strategy to enhance both crop quantity and quality while effectively managing natural resources such as water and fertilizer. Wireless sensor networks, the backbone of IoT-based smart agricultural infrastructure, gather ecosystem data and transmit them to sinks and drones. However, challenges persist, notably in network connectivity, energy consumption, and network lifetime, particularly when facing supernode and relay node failures. This paper introduces an innovative approach to address these challenges within heterogeneous wireless sensor network-based smart agriculture. The proposed solution comprises a novel connectivity management scheme and a dynamic clustering method facilitated by five distributed algorithms. The first and second algorithms focus on path collection, establishing connections between each node and m-supernodes via k-disjoint paths to ensure network robustness. The third and fourth algorithms provide sustained network connectivity during node and supernode failures by adjusting transmission powers and dynamically clustering agriculture sensors based on residual energy. In the fifth algorithm, an optimization algorithm is implemented on the dominating set problem to strategically position a subset of relay nodes as migration points for mobile supernodes to balance the network’s energy depletion. The suggested solution demonstrates superior performance in addressing connectivity, failure tolerance, load balancing, and network lifetime, ensuring optimal agricultural outcomes.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139381540","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 : 2024-01-04DOI: 10.3390/inventions9010009
I. Starodumov, Sergey Sokolov, Pavel Mikushin, M. Nikishina, Timofey Mityashin, Ksenia Makhaeva, F. Blyakhman, Dmitrii Chernushkin, I. Nizovtseva
A computer vision algorithm to determine the parameters of a two-phase turbulent jet of a water-gas mixture traveling at a velocity in the range of 5–10 m/s was developed in order to evaluate the hydrodynamic efficiency of mass exchange apparatuses in real time, as well as to predict the gas exchange rate. The algorithm is based on threshold segmentation, the active contours method, the regression of principal components method, and the comparison of feature overlays, which allows the stable determination of jet boundaries and is a more efficient method when working with low-quality data than traditional implementations of the Canny method. Based on high-speed video recordings of jets, the proposed algorithm allows the calculation of key characteristics of jets: the velocity, angle of incidence, structural density, etc. Both the algorithm’s description and a test application based on video recordings of a real jet created on an experimental prototype of a jet bioreactor are discussed. The results are compared with computational fluid dynamics modeling and theoretical predictions, and good agreement is demonstrated. The presented algorithm itself represents the basis for a real-time control system for aerator operation in jet bioreactors, as well as being used in laboratory jet stream installations for the accumulation of big data on the structure and dynamic properties of jets.
{"title":"Computer Vision Algorithm for Characterization of a Turbulent Gas–Liquid Jet","authors":"I. Starodumov, Sergey Sokolov, Pavel Mikushin, M. Nikishina, Timofey Mityashin, Ksenia Makhaeva, F. Blyakhman, Dmitrii Chernushkin, I. Nizovtseva","doi":"10.3390/inventions9010009","DOIUrl":"https://doi.org/10.3390/inventions9010009","url":null,"abstract":"A computer vision algorithm to determine the parameters of a two-phase turbulent jet of a water-gas mixture traveling at a velocity in the range of 5–10 m/s was developed in order to evaluate the hydrodynamic efficiency of mass exchange apparatuses in real time, as well as to predict the gas exchange rate. The algorithm is based on threshold segmentation, the active contours method, the regression of principal components method, and the comparison of feature overlays, which allows the stable determination of jet boundaries and is a more efficient method when working with low-quality data than traditional implementations of the Canny method. Based on high-speed video recordings of jets, the proposed algorithm allows the calculation of key characteristics of jets: the velocity, angle of incidence, structural density, etc. Both the algorithm’s description and a test application based on video recordings of a real jet created on an experimental prototype of a jet bioreactor are discussed. The results are compared with computational fluid dynamics modeling and theoretical predictions, and good agreement is demonstrated. The presented algorithm itself represents the basis for a real-time control system for aerator operation in jet bioreactors, as well as being used in laboratory jet stream installations for the accumulation of big data on the structure and dynamic properties of jets.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139384877","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 : 2023-12-31DOI: 10.3390/inventions9010006
S. I. Saedi, Mehdi Rezaei
Olive fruits at different ripening stages give rise to various table olive products and oil qualities. Therefore, developing an efficient method for recognizing and sorting olive fruits based on their ripening stages can greatly facilitate post-harvest processing. This study introduces an automatic computer vision system that utilizes deep learning technology to classify the ‘Roghani’ Iranian olive cultivar into five ripening stages using color images. The developed model employs convolutional neural networks (CNN) and transfer learning based on the Xception architecture and ImageNet weights as the base network. The model was modified by adding some well-known CNN layers to the last layer. To minimize overfitting and enhance model generality, data augmentation techniques were employed. By considering different optimizers and two image sizes, four final candidate models were generated. These models were then compared in terms of loss and accuracy on the test dataset, classification performance (classification report and confusion matrix), and generality. All four candidates exhibited high accuracies ranging from 86.93% to 93.46% and comparable classification performance. In all models, at least one class was recognized with 100% accuracy. However, by taking into account the risk of overfitting in addition to the network stability, two models were discarded. Finally, a model with an image size of 224 × 224 and an SGD optimizer, which had a loss of 1.23 and an accuracy of 86.93%, was selected as the preferred option. The results of this study offer robust tools for automatic olive sorting systems, simplifying the differentiation of olives at various ripening levels for different post-harvest products.
{"title":"A Modified Xception Deep Learning Model for Automatic Sorting of Olives Based on Ripening Stages","authors":"S. I. Saedi, Mehdi Rezaei","doi":"10.3390/inventions9010006","DOIUrl":"https://doi.org/10.3390/inventions9010006","url":null,"abstract":"Olive fruits at different ripening stages give rise to various table olive products and oil qualities. Therefore, developing an efficient method for recognizing and sorting olive fruits based on their ripening stages can greatly facilitate post-harvest processing. This study introduces an automatic computer vision system that utilizes deep learning technology to classify the ‘Roghani’ Iranian olive cultivar into five ripening stages using color images. The developed model employs convolutional neural networks (CNN) and transfer learning based on the Xception architecture and ImageNet weights as the base network. The model was modified by adding some well-known CNN layers to the last layer. To minimize overfitting and enhance model generality, data augmentation techniques were employed. By considering different optimizers and two image sizes, four final candidate models were generated. These models were then compared in terms of loss and accuracy on the test dataset, classification performance (classification report and confusion matrix), and generality. All four candidates exhibited high accuracies ranging from 86.93% to 93.46% and comparable classification performance. In all models, at least one class was recognized with 100% accuracy. However, by taking into account the risk of overfitting in addition to the network stability, two models were discarded. Finally, a model with an image size of 224 × 224 and an SGD optimizer, which had a loss of 1.23 and an accuracy of 86.93%, was selected as the preferred option. The results of this study offer robust tools for automatic olive sorting systems, simplifying the differentiation of olives at various ripening levels for different post-harvest products.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139135823","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 : 2023-12-29DOI: 10.3390/inventions9010005
Luigi Fortuna, A. Buscarino
The aim of the Special Issue on Automatic Control and System Theory and Advanced Applications, the second volume of a previous paper selection, is to emphasize the role of new inventions in the area of automatic control applications [...]
{"title":"Automatic Control and System Theory and Advanced Applications—Volume 2","authors":"Luigi Fortuna, A. Buscarino","doi":"10.3390/inventions9010005","DOIUrl":"https://doi.org/10.3390/inventions9010005","url":null,"abstract":"The aim of the Special Issue on Automatic Control and System Theory and Advanced Applications, the second volume of a previous paper selection, is to emphasize the role of new inventions in the area of automatic control applications [...]","PeriodicalId":14564,"journal":{"name":"Inventions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139143689","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 : 2023-12-26DOI: 10.3390/inventions9010003
Shami Ahmad Assery, Xiao-Ping Zhang, Nan Chen
With the high penetration of renewable energy into power grids, frequency stability and oscillation have become big concerns due to the reduced system inertia. The application of the Battery Energy Storage System (BESS) is considered one of the options to deal with frequency stability and oscillation. This paper presents a strategy to size, locate, and operate the BESS within the power grid and, therefore, investigate how sizing capacity is related to renewable energy penetration levels. This paper proposes an identification method to determine the best location of the BESS using the Prony method based on system oscillation analysis, which is easy to implement based on measurements while actual physical system models are not required. The proposed methods for BESS size and location are applied using MATLAB/Simulink simulation software (version: R2023a) on the Kundur 2-area 11-bus test system with different renewable energy penetration levels, and the effectiveness of the applied method in enhancing frequency stability is illustrated in the study cases. The case studies showed a significant improvement in steady-state frequency deviation, frequency nadir, and ROCOF after implementing BESS at the selected bus. The integration of BESS can help to avoid Under-frequency Load Shedding (UFLS) by proper selections of size, location, and operating strategy of the BESS within the power grid.
{"title":"Large-Scale BESS for Damping Frequency Oscillations of Power Systems with High Wind Power Penetration","authors":"Shami Ahmad Assery, Xiao-Ping Zhang, Nan Chen","doi":"10.3390/inventions9010003","DOIUrl":"https://doi.org/10.3390/inventions9010003","url":null,"abstract":"With the high penetration of renewable energy into power grids, frequency stability and oscillation have become big concerns due to the reduced system inertia. The application of the Battery Energy Storage System (BESS) is considered one of the options to deal with frequency stability and oscillation. This paper presents a strategy to size, locate, and operate the BESS within the power grid and, therefore, investigate how sizing capacity is related to renewable energy penetration levels. This paper proposes an identification method to determine the best location of the BESS using the Prony method based on system oscillation analysis, which is easy to implement based on measurements while actual physical system models are not required. The proposed methods for BESS size and location are applied using MATLAB/Simulink simulation software (version: R2023a) on the Kundur 2-area 11-bus test system with different renewable energy penetration levels, and the effectiveness of the applied method in enhancing frequency stability is illustrated in the study cases. The case studies showed a significant improvement in steady-state frequency deviation, frequency nadir, and ROCOF after implementing BESS at the selected bus. The integration of BESS can help to avoid Under-frequency Load Shedding (UFLS) by proper selections of size, location, and operating strategy of the BESS within the power grid.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139157194","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 : 2023-12-21DOI: 10.3390/inventions9010001
I. Ashaev, Ildar A. Safiullin, Artur K. Gaysin, Adel F. Nadeev, Alexey A. Korobkov
Modern mobile networks exhibit a complex heterogeneous structure. To enhance the Quality of Service (QoS) in these networks, intelligent control mechanisms should be implemented. These functions are based on the processing of large amounts of data and feature extraction. One such feature is information about user mobility. However, directly determining user mobility remains challenging. To address this issue, this study proposes an approach based on multi-linear data processing. The user mobility is proposed to determine, using the multi-linear data, about the changing of the Signal-to-Interference-plus-Noise-Ratio (SINR). SINR varies individually for each user over time, relative to the network’s base stations. It is natural to represent these data as a tensor. A tensor-based preprocessing step employing Canonical Polyadic Decomposition (CPD) is proposed to extract user mobility information and reduce the data volume. In the next step, using the DBSCAN algorithm, users are clustered according to their mobility patterns. Subsequently, users are clustered based on their mobility patterns using the DBSCAN algorithm. The proposed approach is evaluated utilizing data from Network Simulator 3 (NS-3), which simulates a portion of the mobile network. The results of processing these data using the proposed method demonstrate superior performance in determining user mobility.
{"title":"An Approach for Using a Tensor-Based Method for Mobility-User Pattern Determining","authors":"I. Ashaev, Ildar A. Safiullin, Artur K. Gaysin, Adel F. Nadeev, Alexey A. Korobkov","doi":"10.3390/inventions9010001","DOIUrl":"https://doi.org/10.3390/inventions9010001","url":null,"abstract":"Modern mobile networks exhibit a complex heterogeneous structure. To enhance the Quality of Service (QoS) in these networks, intelligent control mechanisms should be implemented. These functions are based on the processing of large amounts of data and feature extraction. One such feature is information about user mobility. However, directly determining user mobility remains challenging. To address this issue, this study proposes an approach based on multi-linear data processing. The user mobility is proposed to determine, using the multi-linear data, about the changing of the Signal-to-Interference-plus-Noise-Ratio (SINR). SINR varies individually for each user over time, relative to the network’s base stations. It is natural to represent these data as a tensor. A tensor-based preprocessing step employing Canonical Polyadic Decomposition (CPD) is proposed to extract user mobility information and reduce the data volume. In the next step, using the DBSCAN algorithm, users are clustered according to their mobility patterns. Subsequently, users are clustered based on their mobility patterns using the DBSCAN algorithm. The proposed approach is evaluated utilizing data from Network Simulator 3 (NS-3), which simulates a portion of the mobile network. The results of processing these data using the proposed method demonstrate superior performance in determining user mobility.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138950938","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 : 2023-12-21DOI: 10.3390/inventions9010002
C. Rodríguez-Navarro, Francisco Portillo, Fernando Martínez, F. Manzano-Agugliaro, A. Alcayde
In the context of the global energy sector’s increasing reliance on fossil fuels and escalating environmental concerns, there is an urgent need for advancements in energy monitoring and optimization. Addressing this challenge, the present study introduces the Open Multi Power Meter, a novel open hardware solution designed for efficient and precise electrical measurements. This device is engineered around a single microcontroller architecture, featuring a comprehensive suite of measurement modules interconnected via an RS485 bus, which ensures high accuracy and scalability. A significant aspect of this development is the integration with the Non-Intrusive Load Monitoring Toolkit, which utilizes advanced algorithms for energy disaggregation, including Combinatorial Optimization and the Finite Hidden Markov Model. Comparative analyses were performed using public datasets alongside commercial and open hardware monitors to validate the design and capabilities of this device. These studies demonstrate the device’s notable effectiveness, characterized by its simplicity, flexibility, and adaptability in various energy monitoring scenarios. The introduction of this cost-effective and scalable tool marks a contribution to the field of energy research, enhancing energy efficiency practices. This research provides a practical solution for energy management and opens advancements in the field, highlighting its potential impact on academic research and real-world applications.
{"title":"Development and Application of an Open Power Meter Suitable for NILM","authors":"C. Rodríguez-Navarro, Francisco Portillo, Fernando Martínez, F. Manzano-Agugliaro, A. Alcayde","doi":"10.3390/inventions9010002","DOIUrl":"https://doi.org/10.3390/inventions9010002","url":null,"abstract":"In the context of the global energy sector’s increasing reliance on fossil fuels and escalating environmental concerns, there is an urgent need for advancements in energy monitoring and optimization. Addressing this challenge, the present study introduces the Open Multi Power Meter, a novel open hardware solution designed for efficient and precise electrical measurements. This device is engineered around a single microcontroller architecture, featuring a comprehensive suite of measurement modules interconnected via an RS485 bus, which ensures high accuracy and scalability. A significant aspect of this development is the integration with the Non-Intrusive Load Monitoring Toolkit, which utilizes advanced algorithms for energy disaggregation, including Combinatorial Optimization and the Finite Hidden Markov Model. Comparative analyses were performed using public datasets alongside commercial and open hardware monitors to validate the design and capabilities of this device. These studies demonstrate the device’s notable effectiveness, characterized by its simplicity, flexibility, and adaptability in various energy monitoring scenarios. The introduction of this cost-effective and scalable tool marks a contribution to the field of energy research, enhancing energy efficiency practices. This research provides a practical solution for energy management and opens advancements in the field, highlighting its potential impact on academic research and real-world applications.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138950305","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 : 2023-12-18DOI: 10.3390/inventions8060160
Real J. Kc, Trevor C. Wilson, Aaron S. Alexander, Jamey D. Jacob, Nicholas A. Lucido, B. Elbing
Backward-facing steps are commonly formed on wings and blades due to misalignment between segments or the addition of protective films. A backward-facing step (BFS) is known to degrade the airfoil performance. To mitigate these adverse effects, a three-dimensional low-profile serrated pattern (termed sBFS) was applied downstream of a BFS on an LA203A profile airfoil. The model drag was determined from wake surveys using a traversing Pitot-static probe within a subsonic wind tunnel operating at a chord-based Reynolds number of 300,000. The airfoil spanned the wind tunnel width (914 mm) and had a 197 mm chord length. Four different sBFS configurations were tested, each formed by applying a 1 mm thick film around the model leading edge. In addition, a BFS at various chord locations and a clean wing (i.e., no film applied) were tested for reference. The sBFS was able to reduce the drag relative the BFS by up to 8–10%, though not outperforming the clean wing configuration. In addition, the wake surveys showed the sBFS produced strong coherent structures that persist into the far-wake region (five chord length downstream of the model) with a scale that was much larger than the step height. Additionally, a computational study was carried out to further examine the flow behavior on the airfoil that produced the coherent structures. This showed that fluid near the surface gets entrained towards the sBFS downstream tip of the sBFS, which creates the initial rotation of these coherent structures that persist into the far-wake region.
{"title":"Evaluation of a Serrated Edge to Mitigate the Adverse Effects of a Backward-Facing Step on an Airfoil","authors":"Real J. Kc, Trevor C. Wilson, Aaron S. Alexander, Jamey D. Jacob, Nicholas A. Lucido, B. Elbing","doi":"10.3390/inventions8060160","DOIUrl":"https://doi.org/10.3390/inventions8060160","url":null,"abstract":"Backward-facing steps are commonly formed on wings and blades due to misalignment between segments or the addition of protective films. A backward-facing step (BFS) is known to degrade the airfoil performance. To mitigate these adverse effects, a three-dimensional low-profile serrated pattern (termed sBFS) was applied downstream of a BFS on an LA203A profile airfoil. The model drag was determined from wake surveys using a traversing Pitot-static probe within a subsonic wind tunnel operating at a chord-based Reynolds number of 300,000. The airfoil spanned the wind tunnel width (914 mm) and had a 197 mm chord length. Four different sBFS configurations were tested, each formed by applying a 1 mm thick film around the model leading edge. In addition, a BFS at various chord locations and a clean wing (i.e., no film applied) were tested for reference. The sBFS was able to reduce the drag relative the BFS by up to 8–10%, though not outperforming the clean wing configuration. In addition, the wake surveys showed the sBFS produced strong coherent structures that persist into the far-wake region (five chord length downstream of the model) with a scale that was much larger than the step height. Additionally, a computational study was carried out to further examine the flow behavior on the airfoil that produced the coherent structures. This showed that fluid near the surface gets entrained towards the sBFS downstream tip of the sBFS, which creates the initial rotation of these coherent structures that persist into the far-wake region.","PeriodicalId":14564,"journal":{"name":"Inventions","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138994703","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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