Dragos Gabriel Zisopol, Mihail Minescu, Dragos Valentin Iacob
The paper brings forward the results of a study on the compression test of 28 lattice structures made of PLA by FDM, with the height of the deposited layer at a pass of Hs = 0.20 mm and 50% filling percentage Pu. The 28 samples were made on Anycubic 4 Max Pro 2.0 the 3D printer, considering 7 filling patterns: Grid, Tri-hexagon, Octet, Triangles, Cubic subdivision, Gyroid, and Cross 3D for each type of lattice structure. The dimensions of the specimens, before and after the compression test, were determined using the DeMeet 3D coordinate measuring machine. In this context, a minimum printing accuracy value of 98.98% and a maximum deformation value of 57.70% were recorded for the lattice structure corresponding to the Triangles fill pattern. For the same Triangles type lattice structure, the highest average maximum compressive force of 87.32 kN was obtained. The maximization of the ratio between the use value and the production cost, one of the fundamental technical-economic principles of value analysis, was obtained for the lattice structure corresponding to the Cubic subdivision filling model.
本文提出了用FDM对28种PLA晶格结构进行压缩试验的研究结果，沉积层高度为Hs = 0.20 mm，填充率为50% Pu。28个样品在Anycubic 4 Max Pro 2.0 3D打印机上制作，考虑了7种填充模式:网格，三六边形，八边形，三角形，Cubic subdivision, Gyroid和Cross 3D对于每种类型的晶格结构。使用DeMeet三维坐标测量机测量压缩试验前后试件的尺寸。在这种情况下，与三角形填充图案相对应的晶格结构的最小打印精度值为98.98%，最大变形值为57.70%。对于相同的三角形晶格结构，获得的平均最大抗压力最高为87.32 kN。得到了与Cubic细分填充模型相对应的点阵结构的使用价值与生产成本之比的最大化，这是价值分析的基本技术经济原则之一。
{"title":"A Study on the Evaluation of the Compression Behavior of PLA Lattice Structures Manufactured by FDM","authors":"Dragos Gabriel Zisopol, Mihail Minescu, Dragos Valentin Iacob","doi":"10.48084/etasr.6262","DOIUrl":"https://doi.org/10.48084/etasr.6262","url":null,"abstract":"The paper brings forward the results of a study on the compression test of 28 lattice structures made of PLA by FDM, with the height of the deposited layer at a pass of Hs = 0.20 mm and 50% filling percentage Pu. The 28 samples were made on Anycubic 4 Max Pro 2.0 the 3D printer, considering 7 filling patterns: Grid, Tri-hexagon, Octet, Triangles, Cubic subdivision, Gyroid, and Cross 3D for each type of lattice structure. The dimensions of the specimens, before and after the compression test, were determined using the DeMeet 3D coordinate measuring machine. In this context, a minimum printing accuracy value of 98.98% and a maximum deformation value of 57.70% were recorded for the lattice structure corresponding to the Triangles fill pattern. For the same Triangles type lattice structure, the highest average maximum compressive force of 87.32 kN was obtained. The maximization of the ratio between the use value and the production cost, one of the fundamental technical-economic principles of value analysis, was obtained for the lattice structure corresponding to the Cubic subdivision filling model.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135918450","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}
Today, cyber attackers use Artificial Intelligence (AI) to boost the sophistication and scope of their attacks. On the defense side, AI is used to improve defense plans, robustness, flexibility, and efficiency of defense systems by adapting to environmental changes. With the developments in information and communication technologies, various exploits that are changing rapidly constitute a danger sign for cyber security. Cybercriminals use new and sophisticated tactics to boost their attack speed and size. Consequently, there is a need for more flexible, adaptable, and strong cyber defense systems that can identify a wide range of threats in real time. In recent years, the adoption of AI approaches has increased and maintained a vital role in the detection and prevention of cyber threats. This paper presents an Ensemble Deep Restricted Boltzmann Machine (EDRBM) to classify cybersecurity threats in large-scale network environments. EDRBM acts as a classification model that enables the classification of malicious flowsets in a large-scale network. Simulations were carried out to evaluate the efficacy of the proposed EDRBM model under various malware attacks. The results showed that the proposed method achieved a promising malware classification rate in malicious flowsets.
{"title":"Malware Attack Detection in Large Scale Networks using the Ensemble Deep Restricted Boltzmann Machine","authors":"Janani Kumar, Gunasundari Ranganathan","doi":"10.48084/etasr.6204","DOIUrl":"https://doi.org/10.48084/etasr.6204","url":null,"abstract":"Today, cyber attackers use Artificial Intelligence (AI) to boost the sophistication and scope of their attacks. On the defense side, AI is used to improve defense plans, robustness, flexibility, and efficiency of defense systems by adapting to environmental changes. With the developments in information and communication technologies, various exploits that are changing rapidly constitute a danger sign for cyber security. Cybercriminals use new and sophisticated tactics to boost their attack speed and size. Consequently, there is a need for more flexible, adaptable, and strong cyber defense systems that can identify a wide range of threats in real time. In recent years, the adoption of AI approaches has increased and maintained a vital role in the detection and prevention of cyber threats. This paper presents an Ensemble Deep Restricted Boltzmann Machine (EDRBM) to classify cybersecurity threats in large-scale network environments. EDRBM acts as a classification model that enables the classification of malicious flowsets in a large-scale network. Simulations were carried out to evaluate the efficacy of the proposed EDRBM model under various malware attacks. The results showed that the proposed method achieved a promising malware classification rate in malicious flowsets.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135917849","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}
Dragos Gabriel Zisopol, Alexandra Ileana Portoaca, Maria Tanase
This study conducts an experimental exploration and thorough analysis of the influence of annealing on the impact resistance of PLA 3D-printed components. The investigation extends its scope to encompass the influence of printing parameters, specifically layer thickness and infill percentage. The research highlights that the impact resistance of annealed 3D printed PLA components is predominantly influenced by the infill percentage, with the highest impact energy observed at a full 100% infill. It is noticeable that the application of annealing post-processing heat treatment results in a remarkable, up to threefold, increase of the impact energy highlighting its potential efficacy as a viable technique for enhancing the mechanical integrity of PLA 3D printed products. Consequently, this study establishes annealing as a promising methodology, particularly for PLA 3D printing applications that encounter significant mechanical loads.
{"title":"Improving the Impact Resistance through Annealing in PLA 3D Printed Parts","authors":"Dragos Gabriel Zisopol, Alexandra Ileana Portoaca, Maria Tanase","doi":"10.48084/etasr.6281","DOIUrl":"https://doi.org/10.48084/etasr.6281","url":null,"abstract":"This study conducts an experimental exploration and thorough analysis of the influence of annealing on the impact resistance of PLA 3D-printed components. The investigation extends its scope to encompass the influence of printing parameters, specifically layer thickness and infill percentage. The research highlights that the impact resistance of annealed 3D printed PLA components is predominantly influenced by the infill percentage, with the highest impact energy observed at a full 100% infill. It is noticeable that the application of annealing post-processing heat treatment results in a remarkable, up to threefold, increase of the impact energy highlighting its potential efficacy as a viable technique for enhancing the mechanical integrity of PLA 3D printed products. Consequently, this study establishes annealing as a promising methodology, particularly for PLA 3D printing applications that encounter significant mechanical loads.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135918046","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}
Omar M. Ahmed, Lailan M. Haji, Ayah M. Ahmed, Nashwan M. Salih
The field of finance makes extensive use of real-time prediction of stock price tools, which are instruments that are put to use in the process of creating predictions. In this article, we attempt to predict the price of Bitcoin in a manner that is both accurate and reliable. Deep learning models, as opposed to more traditional methods, are used to manage enormous volumes of data and to generate predictions. The purpose of this research is to develop a method for predicting stock prices using the Hybrid Convolutional Recurrent Model (HCRM) architecture. This model architecture integrates the advantages of two separate deep learning models: The 1-Dimensional-Convolusional Neural Network (1D-CNN) and the Long-Short Term Memory (LSTM). The 1D-CNN is responsible for the feature extraction, while the LSTM is in charge of the temporal regression. The developed 1D-CNN-LSTM model has an outstanding performance in predicting stock values.
{"title":"Bitcoin Price Prediction using the Hybrid Convolutional Recurrent Model Architecture","authors":"Omar M. Ahmed, Lailan M. Haji, Ayah M. Ahmed, Nashwan M. Salih","doi":"10.48084/etasr.6223","DOIUrl":"https://doi.org/10.48084/etasr.6223","url":null,"abstract":"The field of finance makes extensive use of real-time prediction of stock price tools, which are instruments that are put to use in the process of creating predictions. In this article, we attempt to predict the price of Bitcoin in a manner that is both accurate and reliable. Deep learning models, as opposed to more traditional methods, are used to manage enormous volumes of data and to generate predictions. The purpose of this research is to develop a method for predicting stock prices using the Hybrid Convolutional Recurrent Model (HCRM) architecture. This model architecture integrates the advantages of two separate deep learning models: The 1-Dimensional-Convolusional Neural Network (1D-CNN) and the Long-Short Term Memory (LSTM). The 1D-CNN is responsible for the feature extraction, while the LSTM is in charge of the temporal regression. The developed 1D-CNN-LSTM model has an outstanding performance in predicting stock values.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135918438","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}
Unmanned Aerial Vehicle (UAV) platforms are emerging as an essential tool for various studies in environmental engineering. The quadcopters drones have immense potential for sensor interfacing and stable data acquisition. These UAVs can perform critical activities like volcanic eruption monitoring, stack emission monitoring, urban air quality monitoring, identification of pollution levels in 3D space, etc. Carbon dioxide (CO2) and the Discomfort Index (DI) are essential indicators of air quality and climate comfort. Hence, it is critical to monitor them with extreme accuracy. This study demonstrates a novel application of CO2 profiling using low-cost drones at varied altitudes. The drone-aided vertical CO2 profiling was carried out at 60 m AGL (Above Ground Level) during summer and winter, in Nagpur city of India. This study retrieved some exciting data on the DI. It was found that CO2 concentration in the range of 20-70 m AGL was lower than the surface level. The derived DI was maximum at the height range of 40-50 m. Inversion was observed in the range of 30-40 m. A positive correlation between CO2 and temperature was observed in both seasons. The lightweight commercial drones are capable of tethering sensor modules to get accurate results in less cost and effort. This type of novel tethered sensor technique could be applicable in weather forecasting, landfill surface monitoring, volcanic eruption monitoring, and other probable applications with few drone flight limits.
{"title":"Atmospheric CO2 Level Measurement and Discomfort Index Calculation with the use of Low-Cost Drones","authors":"Piyush Kokate, Shashikant Sadistap, Anirban Middey","doi":"10.48084/etasr.6230","DOIUrl":"https://doi.org/10.48084/etasr.6230","url":null,"abstract":"Unmanned Aerial Vehicle (UAV) platforms are emerging as an essential tool for various studies in environmental engineering. The quadcopters drones have immense potential for sensor interfacing and stable data acquisition. These UAVs can perform critical activities like volcanic eruption monitoring, stack emission monitoring, urban air quality monitoring, identification of pollution levels in 3D space, etc. Carbon dioxide (CO2) and the Discomfort Index (DI) are essential indicators of air quality and climate comfort. Hence, it is critical to monitor them with extreme accuracy. This study demonstrates a novel application of CO2 profiling using low-cost drones at varied altitudes. The drone-aided vertical CO2 profiling was carried out at 60 m AGL (Above Ground Level) during summer and winter, in Nagpur city of India. This study retrieved some exciting data on the DI. It was found that CO2 concentration in the range of 20-70 m AGL was lower than the surface level. The derived DI was maximum at the height range of 40-50 m. Inversion was observed in the range of 30-40 m. A positive correlation between CO2 and temperature was observed in both seasons. The lightweight commercial drones are capable of tethering sensor modules to get accurate results in less cost and effort. This type of novel tethered sensor technique could be applicable in weather forecasting, landfill surface monitoring, volcanic eruption monitoring, and other probable applications with few drone flight limits.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135918442","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}
Windows play a vital role in daylight infusion, significantly impacting indoor visual comfort. Various metrics exist for evaluating visual comfort in which the uniformity ratio falls under the distribution category and is as crucial as illuminance levels. This ratio effectively reduces the likelihood of glare and the need for artificial lighting. The primary objective of this research is to assess the impact of window design on daylight uniformity ratio in a classroom setting. In pursuit of this objective, a study investigated the uniformity ratio (Uo) of north-oriented and south-oriented classrooms of Kendriya Vidyalaya (KV) Khagual, Patna. The study considered five common shapes of windows (excluding the existing base cases) at different window-sill levels. Ninety simulations were run in the DesignBuilder software under overcast, intermediate, and clear sky conditions. To assess the uniformity ratio on three dates: March 21st, June 21st, and December 21st, which correspond to the highest, equinox, and lowest solar availability during the year under intermediate and clear sky conditions at three distinct times. The omission of the specific time and date for overcast conditions and the particular year for clear and intermediate sky conditions is justified as the outcome remains consistent throughout all years. The results show that the window design and sill level significantly affect the uniformity ratio. The research findings show that window design in Case 9 at a sill of 1230 mm and lintel of 3050 mm (just below the slab) consistently produces the best uniformity ratio across all sky conditions, independent of classroom orientation. This paper offers valuable design recommendations by comparing the uniformity ratio for five commonly used window designs. This is one of the first studies of window design and position to evaluate the uniformity ratio in the classrooms at Patna.
{"title":"Assessing Window Design's Impact on Daylight Uniformity in Classrooms in Patna, India","authors":"Alok Kumar Maurya, Ravish Kumar, Ajay Kumar","doi":"10.48084/etasr.6212","DOIUrl":"https://doi.org/10.48084/etasr.6212","url":null,"abstract":"Windows play a vital role in daylight infusion, significantly impacting indoor visual comfort. Various metrics exist for evaluating visual comfort in which the uniformity ratio falls under the distribution category and is as crucial as illuminance levels. This ratio effectively reduces the likelihood of glare and the need for artificial lighting. The primary objective of this research is to assess the impact of window design on daylight uniformity ratio in a classroom setting. In pursuit of this objective, a study investigated the uniformity ratio (Uo) of north-oriented and south-oriented classrooms of Kendriya Vidyalaya (KV) Khagual, Patna. The study considered five common shapes of windows (excluding the existing base cases) at different window-sill levels. Ninety simulations were run in the DesignBuilder software under overcast, intermediate, and clear sky conditions. To assess the uniformity ratio on three dates: March 21st, June 21st, and December 21st, which correspond to the highest, equinox, and lowest solar availability during the year under intermediate and clear sky conditions at three distinct times. The omission of the specific time and date for overcast conditions and the particular year for clear and intermediate sky conditions is justified as the outcome remains consistent throughout all years. The results show that the window design and sill level significantly affect the uniformity ratio. The research findings show that window design in Case 9 at a sill of 1230 mm and lintel of 3050 mm (just below the slab) consistently produces the best uniformity ratio across all sky conditions, independent of classroom orientation. This paper offers valuable design recommendations by comparing the uniformity ratio for five commonly used window designs. This is one of the first studies of window design and position to evaluate the uniformity ratio in the classrooms at Patna.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135918445","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}
Investigation in the field of network forensics involves examining network traffic to identify, capture, preserve, reconstruct, analyze, and document network crimes. Although there are different perspectives on the practical and technical aspects of network forensics, there is still a lack of fundamental guidelines. This paper proposes a new detection and investigation model for capturing and analyzing network crimes, using design science research. The proposed model involves six processes: identification, verification, gathering, preservation, examination, analysis, and documentation. Each process is associated with several activities that provide the investigation team with a clear picture of exactly what needs to be performed. In addition, the proposed model has a unique activity, namely reporting. As a result, this model represents a comprehensive approach to network forensics investigations. It is designed to work in conjunction with established forensic techniques to ensure that forensic evidence from the network is collected and analyzed efficiently and effectively following accepted forensic procedures. The proposed model was compared with existing models in terms of completeness, showing that it is complete and can be adapted to any type of network and legal framework.
{"title":"A Detection and Investigation Model for the Capture and Analysis of Network Crimes","authors":"Iman S. Alansari","doi":"10.48084/etasr.6316","DOIUrl":"https://doi.org/10.48084/etasr.6316","url":null,"abstract":"Investigation in the field of network forensics involves examining network traffic to identify, capture, preserve, reconstruct, analyze, and document network crimes. Although there are different perspectives on the practical and technical aspects of network forensics, there is still a lack of fundamental guidelines. This paper proposes a new detection and investigation model for capturing and analyzing network crimes, using design science research. The proposed model involves six processes: identification, verification, gathering, preservation, examination, analysis, and documentation. Each process is associated with several activities that provide the investigation team with a clear picture of exactly what needs to be performed. In addition, the proposed model has a unique activity, namely reporting. As a result, this model represents a comprehensive approach to network forensics investigations. It is designed to work in conjunction with established forensic techniques to ensure that forensic evidence from the network is collected and analyzed efficiently and effectively following accepted forensic procedures. The proposed model was compared with existing models in terms of completeness, showing that it is complete and can be adapted to any type of network and legal framework.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135918768","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}
In this paper, photocatalytic TiO2 micro- and nano-powders coated by Ni and Co nanoclusters were prepared by the original electroless deposition method. The magnetic properties of Ni and Co nanoclusters decorating TiO2 grains were studied by the magnetometry measurements of the temperature dependence of magnetization. Their optical spectroscopy measurements showed a significant increase in light absorption by Ni and Co coated TiO2 nanopowders. The photocatalytic properties of the obtained magnetic nanopowders were studied with Electron Paramagnetic Resonance spectroscopy as well.
{"title":"Photocatalytic and Magnetic Properties of TiO2 Micro- and Nano- Powders decorated by Magnetic Cocatalysts","authors":"Tatiana Gegechkori, Grigor Mamniashvili, Tornike Gagnidze, Malkhaz Nadareishvili, Tinatin Zedginidze","doi":"10.48084/etasr.6244","DOIUrl":"https://doi.org/10.48084/etasr.6244","url":null,"abstract":"In this paper, photocatalytic TiO2 micro- and nano-powders coated by Ni and Co nanoclusters were prepared by the original electroless deposition method. The magnetic properties of Ni and Co nanoclusters decorating TiO2 grains were studied by the magnetometry measurements of the temperature dependence of magnetization. Their optical spectroscopy measurements showed a significant increase in light absorption by Ni and Co coated TiO2 nanopowders. The photocatalytic properties of the obtained magnetic nanopowders were studied with Electron Paramagnetic Resonance spectroscopy as well.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135918928","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}
V. Sudheer Kumar Sistla Sistla, Surendra Kumar Bitra, Santhosh Chella
Solar cells are one of the most effective methods available for energy harvesting and are constructed from a variety of materials. In recent years, the use of novel materials for low-cost, high-efficiency photovoltaics has been one of the most exciting breakthroughs. This study conducted an in-depth investigation into the optical characteristics of GaAs nanowires on a Ge bottom cell. Geometric optimization of nanowires is necessary to increase solar cell performance metrics. The absorption efficiency per unit volume was considerably boosted over its traditional bulk and thin-film counterparts as a result of inherent antireflection, intensive stimulation of resonant modes, and optical antenna effects. A 3D FDTD framework was used to acquire optical properties and incorporate numerical values. Under typical AM 1.5G illumination, the diameter of GaAs nanowires was optimized to 170 nm.
{"title":"Design and Optical Performance of a Single-Junction GaAs Nanowire-Ge Solar Cell","authors":"V. Sudheer Kumar Sistla Sistla, Surendra Kumar Bitra, Santhosh Chella","doi":"10.48084/etasr.6121","DOIUrl":"https://doi.org/10.48084/etasr.6121","url":null,"abstract":"Solar cells are one of the most effective methods available for energy harvesting and are constructed from a variety of materials. In recent years, the use of novel materials for low-cost, high-efficiency photovoltaics has been one of the most exciting breakthroughs. This study conducted an in-depth investigation into the optical characteristics of GaAs nanowires on a Ge bottom cell. Geometric optimization of nanowires is necessary to increase solar cell performance metrics. The absorption efficiency per unit volume was considerably boosted over its traditional bulk and thin-film counterparts as a result of inherent antireflection, intensive stimulation of resonant modes, and optical antenna effects. A 3D FDTD framework was used to acquire optical properties and incorporate numerical values. Under typical AM 1.5G illumination, the diameter of GaAs nanowires was optimized to 170 nm.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135917993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The growing concern about the energy crisis and environmental protection has caused a growing interest in wind power generation systems. Researchers and engineers urgently need to create new multiphase induction machines for the production of wind energy, since they are essential parts of wind turbines. This study offers control and stability analysis of a multiphase induction machine based on the entropy stability requirements for its linearized model. The generated model was used to assess the on-load properties of the multiphase induction machine and calculate its steady-state parameters under each operating circumstance. According to the analysis, the eigenvalues depend on the machine parameters, with the excitation capacitance and speed variation being the most important. Stabilization of the multiphase induction machine is the main focus of the singular values, which vary according to its variables. The simulated results include an examination of a multiphase induction machine steady state for voltage build-up at various types of load.
{"title":"Persistent Voltage Control of a Wind Turbine-Driven Isolated Multiphase Induction Machine","authors":"Marwa Ben Sliemene, Mohamed Arbi Khlifi","doi":"10.48084/etasr.6330","DOIUrl":"https://doi.org/10.48084/etasr.6330","url":null,"abstract":"The growing concern about the energy crisis and environmental protection has caused a growing interest in wind power generation systems. Researchers and engineers urgently need to create new multiphase induction machines for the production of wind energy, since they are essential parts of wind turbines. This study offers control and stability analysis of a multiphase induction machine based on the entropy stability requirements for its linearized model. The generated model was used to assess the on-load properties of the multiphase induction machine and calculate its steady-state parameters under each operating circumstance. According to the analysis, the eigenvalues depend on the machine parameters, with the excitation capacitance and speed variation being the most important. Stabilization of the multiphase induction machine is the main focus of the singular values, which vary according to its variables. The simulated results include an examination of a multiphase induction machine steady state for voltage build-up at various types of load.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"259 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135918004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：