Pub Date : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221506
X. Yi, Huaiyin Wang, Jing Zhang
Equalization-enhanced phase noise (EEPN) can be a major limitation in coherent receivers, when the large accumulated dispersion is compensated for high baud rate signals. One unique feature of EEPN is that its phase component can be larger than the amplitude one. Then the carrier phase recovery algorithm can squeeze the phase component, and therefore, the overall EEPN is also reduced. In this paper, we show that the EEPN and its ovality are both affected by the matched filter bandwidth. The reduction of EEPN by BPS can be more pronouncing when the bandwidth is larger.
{"title":"Reducing Equalization-enhanced Phase Noise via Carrier Phase Recovery in the Presence of Variable Matched-filter Bandwidth","authors":"X. Yi, Huaiyin Wang, Jing Zhang","doi":"10.1109/PIERS59004.2023.10221506","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221506","url":null,"abstract":"Equalization-enhanced phase noise (EEPN) can be a major limitation in coherent receivers, when the large accumulated dispersion is compensated for high baud rate signals. One unique feature of EEPN is that its phase component can be larger than the amplitude one. Then the carrier phase recovery algorithm can squeeze the phase component, and therefore, the overall EEPN is also reduced. In this paper, we show that the EEPN and its ovality are both affected by the matched filter bandwidth. The reduction of EEPN by BPS can be more pronouncing when the bandwidth is larger.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128125243","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 : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221292
Conor O'Sullivan, S. Coveney, X. Monteys, Soumyabrata Dev
We analyse the effectiveness of RMSE, PSNR, SSIM and FOM for evaluating edge detection algorithms used for automated coastline detection. Typically, the accuracy of detected coastlines is assessed visually. This can be impractical on a large scale leading to the need for objective evaluation metrics. Hence, we conduct an experiment to find reliable metrics. We apply Canny edge detection to 95 coastline satellite images across 49 testing locations. We vary the Hysteresis thresholds and compare metric values to a visual analysis of detected edges. We found that FOM was the most reliable metric for selecting the best threshold. It could select a better threshold 92.6% of the time and the best threshold 66.3% of the time. This is compared RMSE, PSNR and SSIM which could select the best threshold 6.3%, 6.3% and 11.6% of the time respectively. We provide a reason for these results by reformulating RMSE, PSNR and SSIM in terms of confusion matrix measures. This suggests these metrics not only fail for this experiment but are not useful for evaluating edge detection in general.
{"title":"The Effectiveness of Edge Detection Evaluation Metrics for Automated Coastline Detection","authors":"Conor O'Sullivan, S. Coveney, X. Monteys, Soumyabrata Dev","doi":"10.1109/PIERS59004.2023.10221292","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221292","url":null,"abstract":"We analyse the effectiveness of RMSE, PSNR, SSIM and FOM for evaluating edge detection algorithms used for automated coastline detection. Typically, the accuracy of detected coastlines is assessed visually. This can be impractical on a large scale leading to the need for objective evaluation metrics. Hence, we conduct an experiment to find reliable metrics. We apply Canny edge detection to 95 coastline satellite images across 49 testing locations. We vary the Hysteresis thresholds and compare metric values to a visual analysis of detected edges. We found that FOM was the most reliable metric for selecting the best threshold. It could select a better threshold 92.6% of the time and the best threshold 66.3% of the time. This is compared RMSE, PSNR and SSIM which could select the best threshold 6.3%, 6.3% and 11.6% of the time respectively. We provide a reason for these results by reformulating RMSE, PSNR and SSIM in terms of confusion matrix measures. This suggests these metrics not only fail for this experiment but are not useful for evaluating edge detection in general.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128169235","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 : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221234
Maksut Maksutogğlu, Elif Avinca, Farkhad Zainullin, K. Çinar, S. Yorulmaz, Sergiy Tarapov, F. Yildiz, B. Rameev
In this work, we show that the magnetostatic (MS) magnon modes (i.e., the spinwaves with wavelengths much larger than the exchange length), which are excited as a result of the coupling between the 2D microwave resonator and the YIG crystal, can be efficiently modeled by use of finite element method software (e.g., CST Studio Suite or Comsol MP). Yttrium iron garnet (YIG) has been used as a model material, which is a ferrimagnetic insulator transparent not only to MW but also to optical and telecommunication frequencies. It also has a very low damping parameter — a property advantageous from the point of view of potential applications. However, this benefit turns out in an issue in the FEM modeling because of the very high non-linearity in the EM properties of YIG near resonances due to uniform or MS modes. We found that it is possible to accelerate the FEM calculations by artificially increasing the damping constant of the model material (YIG). Our FEM modeling studies reveal an excellent agreement with experimental results. In full agreement with experimental data, our modeling study reveals a strong coupling between the YIG crystal and the microwave resonator, observed in the dispersion curves of the modes. We demonstrate the realization of the strong coupling regime, which is especially important for HQS implementations.
在这项工作中，我们表明，由于二维微波谐振器和YIG晶体之间的耦合而激发的静磁(MS)磁振子模式(即波长远大于交换长度的自旋波)可以通过使用有限元方法软件(例如，CST Studio Suite或Comsol MP)有效地建模。钇铁石榴石(YIG)是一种铁磁绝缘体，不仅对毫微米透明，而且对光通信频率透明。它还具有非常低的阻尼参数-从潜在应用的角度来看，这是一个有利的特性。然而，由于均匀模态或质模态导致YIG在共振附近的EM特性具有非常高的非线性，因此在FEM建模中出现了这种好处。我们发现通过人为地增加模型材料的阻尼常数(YIG)可以加速有限元计算。我们的有限元模拟研究结果与实验结果非常吻合。与实验数据完全一致，我们的模型研究揭示了YIG晶体和微波谐振器之间的强耦合，在模式的色散曲线中观察到。我们演示了强耦合机制的实现，这对HQS的实现尤其重要。
{"title":"FEM Modelling of Magnetostatic Modes in Hybrid Quantum Magnonic Systems","authors":"Maksut Maksutogğlu, Elif Avinca, Farkhad Zainullin, K. Çinar, S. Yorulmaz, Sergiy Tarapov, F. Yildiz, B. Rameev","doi":"10.1109/PIERS59004.2023.10221234","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221234","url":null,"abstract":"In this work, we show that the magnetostatic (MS) magnon modes (i.e., the spinwaves with wavelengths much larger than the exchange length), which are excited as a result of the coupling between the 2D microwave resonator and the YIG crystal, can be efficiently modeled by use of finite element method software (e.g., CST Studio Suite or Comsol MP). Yttrium iron garnet (YIG) has been used as a model material, which is a ferrimagnetic insulator transparent not only to MW but also to optical and telecommunication frequencies. It also has a very low damping parameter — a property advantageous from the point of view of potential applications. However, this benefit turns out in an issue in the FEM modeling because of the very high non-linearity in the EM properties of YIG near resonances due to uniform or MS modes. We found that it is possible to accelerate the FEM calculations by artificially increasing the damping constant of the model material (YIG). Our FEM modeling studies reveal an excellent agreement with experimental results. In full agreement with experimental data, our modeling study reveals a strong coupling between the YIG crystal and the microwave resonator, observed in the dispersion curves of the modes. We demonstrate the realization of the strong coupling regime, which is especially important for HQS implementations.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"8 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126007545","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}
Air pollution is a global issue that poses significant threats to human health and the environment due to industrial development. Forecasting the concentrations of major pollutants such as NO2 and CO can provide early warnings of harmful substances, minimizing health risks and losses. Recent deep learning models have shown promise in air quality prediction, but they have limitations such as insufficient feature representation, high computational costs, and poor generalization. This paper proposes a near-surface deep network (NeSDeepNet) to overcome these limitations. The NeSDeepNet integrates multiple deep learning models and a shallow model to form a hybrid forecasting system. The proposed framework consists of three modules: a preliminary extraction module, a deep extraction module, and a fusion module. The feature extraction module uses a multi-layer network to extract features from air pollutant and meteorological data, and each of which predicts air pollutants for different forecasting horizons. The fusion module combines the outputs of the deep learning module and the shallow models to produce the final prediction results. The proposed framework is evaluated on a real-world dataset, and the experimental results demonstrate that NeSDeepNet achieves optimal RMSE value of 9.59 for NO2 and 274.0 for CO, MAE value of 2.64 for NO2 and 13.75 for CO, and R2 values 0.89 for NO2 and 0.93 for CO, respectively, outperforming cutting-edge deep learning models. Therefore, NeSDeepNet can be a valuable tool for air quality forecasting and miti-gating the adverse effects of air pollution on human health and the environment. The source code for our proposed NeSDeepNet and comparative models is available on GitHub repository: https://github.com/Prasanjit-Dey/NeSDeepNet.
{"title":"NeSDeepNet: A Fusion Framework for Multi-step Forecasting of Near-surface Air Pollutants","authors":"Prasanjit Dey, Soumyabrata Dev, Bianca Schoen-Phelan","doi":"10.1109/PIERS59004.2023.10221327","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221327","url":null,"abstract":"Air pollution is a global issue that poses significant threats to human health and the environment due to industrial development. Forecasting the concentrations of major pollutants such as NO2 and CO can provide early warnings of harmful substances, minimizing health risks and losses. Recent deep learning models have shown promise in air quality prediction, but they have limitations such as insufficient feature representation, high computational costs, and poor generalization. This paper proposes a near-surface deep network (NeSDeepNet) to overcome these limitations. The NeSDeepNet integrates multiple deep learning models and a shallow model to form a hybrid forecasting system. The proposed framework consists of three modules: a preliminary extraction module, a deep extraction module, and a fusion module. The feature extraction module uses a multi-layer network to extract features from air pollutant and meteorological data, and each of which predicts air pollutants for different forecasting horizons. The fusion module combines the outputs of the deep learning module and the shallow models to produce the final prediction results. The proposed framework is evaluated on a real-world dataset, and the experimental results demonstrate that NeSDeepNet achieves optimal RMSE value of 9.59 for NO2 and 274.0 for CO, MAE value of 2.64 for NO2 and 13.75 for CO, and R2 values 0.89 for NO2 and 0.93 for CO, respectively, outperforming cutting-edge deep learning models. Therefore, NeSDeepNet can be a valuable tool for air quality forecasting and miti-gating the adverse effects of air pollution on human health and the environment. The source code for our proposed NeSDeepNet and comparative models is available on GitHub repository: https://github.com/Prasanjit-Dey/NeSDeepNet.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127902412","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 : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221326
B. Khalid, B. Khalesi, N. Ghavami, Giovanni Raspa, Mario Badia, S. Dudley, M. Ghavami, G. Tiberi
This paper focuses on executing a novel methodology to achieve imaging time reduction via 3D imaging algorithm based on Huygens principle using a microwave imaging device (MammoWave). Specifically, a three-layer cylindrical phantom with a 3D structured inclusion has been fabricated with varying dielectric properties. Various spiral-like (along z-axis) measurement scenarios have been considered to investigate the possibility of measurement time reduction. In the first scenario, we have performed measurements in spiral-like configuration-I at multiple planes along the z-axis, while for the second scenario we have applied spiral configuration-II in an alternate way in terms of receiving points. We found that the proposed spiral-like measurement scenarios may lead to a measurement time saving of 50%, with a lower S/C ratio (decrease of maximum 3.2 dB) and slightly higher error (approximately 3.5%) in inclusion dimensional analysis and localization.
{"title":"A Spiral-like Acquisition Strategy for 3D Huygens' Principle Based Microwave Imaging","authors":"B. Khalid, B. Khalesi, N. Ghavami, Giovanni Raspa, Mario Badia, S. Dudley, M. Ghavami, G. Tiberi","doi":"10.1109/PIERS59004.2023.10221326","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221326","url":null,"abstract":"This paper focuses on executing a novel methodology to achieve imaging time reduction via 3D imaging algorithm based on Huygens principle using a microwave imaging device (MammoWave). Specifically, a three-layer cylindrical phantom with a 3D structured inclusion has been fabricated with varying dielectric properties. Various spiral-like (along z-axis) measurement scenarios have been considered to investigate the possibility of measurement time reduction. In the first scenario, we have performed measurements in spiral-like configuration-I at multiple planes along the z-axis, while for the second scenario we have applied spiral configuration-II in an alternate way in terms of receiving points. We found that the proposed spiral-like measurement scenarios may lead to a measurement time saving of 50%, with a lower S/C ratio (decrease of maximum 3.2 dB) and slightly higher error (approximately 3.5%) in inclusion dimensional analysis and localization.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115810315","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 : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221339
Renzhou Gui, Aobo Zhang, Shuai Liu, M. Tong
The structure of human brain is complex, and fMRI data can be used to reveal the working mechanism of human brain. We construct a generative confrontation deep learning network based on DMFG-loss function. Using this network, we can not only reconstruct the simple scene images perceived and imagined by human brain with high precision, but also achieve good results for the restoration and reconstruction of complex natural images. In addition, we propose to set the detection threshold based on the constant false alarm algorithm. Further, we explore the distribution of brain sensitive areas, and make a deep analysis of the impact of different regions on image reconstruction. The contribution ratio of specific brain regions to the image reconstruction of human brain is gived. This will help to explore the unknown areas of human brain and reveal the mechanism of human brain operation. It has broad application prospects in brain computer interaction and human brain decoding.
{"title":"Analysis of Functional Areas of Human Brain Based on Reconstructed Images of DMFG-generated Countermeasure Network","authors":"Renzhou Gui, Aobo Zhang, Shuai Liu, M. Tong","doi":"10.1109/PIERS59004.2023.10221339","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221339","url":null,"abstract":"The structure of human brain is complex, and fMRI data can be used to reveal the working mechanism of human brain. We construct a generative confrontation deep learning network based on DMFG-loss function. Using this network, we can not only reconstruct the simple scene images perceived and imagined by human brain with high precision, but also achieve good results for the restoration and reconstruction of complex natural images. In addition, we propose to set the detection threshold based on the constant false alarm algorithm. Further, we explore the distribution of brain sensitive areas, and make a deep analysis of the impact of different regions on image reconstruction. The contribution ratio of specific brain regions to the image reconstruction of human brain is gived. This will help to explore the unknown areas of human brain and reveal the mechanism of human brain operation. It has broad application prospects in brain computer interaction and human brain decoding.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132504170","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 : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221429
Thomas Coombs, A. Ercole, M. Crisp
Radiofrequency (RF) signal attenuation and signal delay have been investigated as potential methods for detecting water in a variety of applications. This paper reviews experimental data on the use of RF signal attenuation and signal delay for detecting water in a lab environment and discusses the advantages and limitations of such as system. Measuring the RF signal attenuation as it passes through a material such solid or fissured concrete of a construction beam or the undamaged and tumour tissue of a liver has shown to be an effective imaging technique, in a variety of setting not just structural engineering or medical imaging. This in theory can be applied to sensing water in diagnostic medicine rather than traditional imaging, attempting to sense pulmonary oedema in a continuous fashion. However, RF signal attenuation is also affected by other factors such as the presence of other materials that can interfere with the signal. RF Signal delay involves measuring the time it takes for an RF signal to travel through a medium containing water. It can similarly be used for detecting water. This has been shown to be less affected by interfering materials than RF signal attenuation, and thus may provide more accurate results. This paper goes over experimentation making use of simple robust methods, with an innovative coplanar waveform design, to measure the effects of water on a simple phantom, using dimensions similar to those in the human lung and using a water salt mixture as an analogue to 0.9% saline solution. Polyurethane foam sponges are used to create the phantom of the lung. Water salt mixture was added in 40 g per sponge stages from 0 to 600 g, taking $S_{21}$ transmission readings using a Keysight Fieldfox. Significant reduction in signal gain of up to $0.09times 10^{-3}$ and significant delay of up to 1 nanosecond is seen with maximum saturation, across an 8 cm antenna separation. Overall, the use of RF signal attenuation and signal delay for detecting water in the lungs shows great potential for improving the diagnosis and monitor of pulmonary oedema. With continued research and development, these methods may eventually become a valuable tool for clinicians and researchers alike. Despite the promising results, further research is needed to validate the accuracy and reliability of these methods, as well as to explore their potential for new applications. With continued research and development, RF signal attenuation and signal delay may become valuable tools for a wide range of industries and fields, from agriculture and geology to medicine and beyond.
{"title":"Use of RF Signal Attenuation & Delay for the Detection of Pulmonary Oedema","authors":"Thomas Coombs, A. Ercole, M. Crisp","doi":"10.1109/PIERS59004.2023.10221429","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221429","url":null,"abstract":"Radiofrequency (RF) signal attenuation and signal delay have been investigated as potential methods for detecting water in a variety of applications. This paper reviews experimental data on the use of RF signal attenuation and signal delay for detecting water in a lab environment and discusses the advantages and limitations of such as system. Measuring the RF signal attenuation as it passes through a material such solid or fissured concrete of a construction beam or the undamaged and tumour tissue of a liver has shown to be an effective imaging technique, in a variety of setting not just structural engineering or medical imaging. This in theory can be applied to sensing water in diagnostic medicine rather than traditional imaging, attempting to sense pulmonary oedema in a continuous fashion. However, RF signal attenuation is also affected by other factors such as the presence of other materials that can interfere with the signal. RF Signal delay involves measuring the time it takes for an RF signal to travel through a medium containing water. It can similarly be used for detecting water. This has been shown to be less affected by interfering materials than RF signal attenuation, and thus may provide more accurate results. This paper goes over experimentation making use of simple robust methods, with an innovative coplanar waveform design, to measure the effects of water on a simple phantom, using dimensions similar to those in the human lung and using a water salt mixture as an analogue to 0.9% saline solution. Polyurethane foam sponges are used to create the phantom of the lung. Water salt mixture was added in 40 g per sponge stages from 0 to 600 g, taking $S_{21}$ transmission readings using a Keysight Fieldfox. Significant reduction in signal gain of up to $0.09times 10^{-3}$ and significant delay of up to 1 nanosecond is seen with maximum saturation, across an 8 cm antenna separation. Overall, the use of RF signal attenuation and signal delay for detecting water in the lungs shows great potential for improving the diagnosis and monitor of pulmonary oedema. With continued research and development, these methods may eventually become a valuable tool for clinicians and researchers alike. Despite the promising results, further research is needed to validate the accuracy and reliability of these methods, as well as to explore their potential for new applications. With continued research and development, RF signal attenuation and signal delay may become valuable tools for a wide range of industries and fields, from agriculture and geology to medicine and beyond.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132560347","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 : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221527
Ce Ding, Lizhen Yang, Ruoming Zhang, Yuechen Zhao, Han Wang, Yuxuan Li, Hai Lin
In order to grasp the operation law of aluminum electrolytic cell, it is necessary to conduct coupling simulation of thermodynamic field and hydrodynamics field, and obtain a grid with dielectric constant parameters through a series of processing results. In electromagnetic computation, the calculation platform is unable to calculate if the mesh is too dense and the tetrahedral elements are not uniform, hence the mesh must be simplified. This work proposes a Monte Carlo stochastic algorithm-based method for mesh simplification as a solution to the problem that the number of mesh is high relative to the computing platform and their distribution across scales is uneven. The octree was used to evaluate the mesh density in the region, the deletion probability of vertices was calculated, and the reserved points were utilized to renew a set of mesh using the Delaunay triangulation method. The most essential aspect of the Monte-Carlo algorithm is determining the deletion probability of each point to ensure that the freshly created mesh is sparse and uniform. Example of hemisphere will then be provided to demonstrate the mesh simplification effect of this strategy. Compared to previous mesh simplification methods in terms of time cost, memory cost, and calculation results, the outcomes are comparable, and the time and space costs are drastically decreased. Compared to previous simplification methods for tetrahedral mesh, this method is straightforward and user-friendly, with a time complexity of O(N) (where N is the number of vertices) and a space complexity of O(N).
{"title":"Mesh Simplification Method Based on Monte-Carlo Algorithm","authors":"Ce Ding, Lizhen Yang, Ruoming Zhang, Yuechen Zhao, Han Wang, Yuxuan Li, Hai Lin","doi":"10.1109/PIERS59004.2023.10221527","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221527","url":null,"abstract":"In order to grasp the operation law of aluminum electrolytic cell, it is necessary to conduct coupling simulation of thermodynamic field and hydrodynamics field, and obtain a grid with dielectric constant parameters through a series of processing results. In electromagnetic computation, the calculation platform is unable to calculate if the mesh is too dense and the tetrahedral elements are not uniform, hence the mesh must be simplified. This work proposes a Monte Carlo stochastic algorithm-based method for mesh simplification as a solution to the problem that the number of mesh is high relative to the computing platform and their distribution across scales is uneven. The octree was used to evaluate the mesh density in the region, the deletion probability of vertices was calculated, and the reserved points were utilized to renew a set of mesh using the Delaunay triangulation method. The most essential aspect of the Monte-Carlo algorithm is determining the deletion probability of each point to ensure that the freshly created mesh is sparse and uniform. Example of hemisphere will then be provided to demonstrate the mesh simplification effect of this strategy. Compared to previous mesh simplification methods in terms of time cost, memory cost, and calculation results, the outcomes are comparable, and the time and space costs are drastically decreased. Compared to previous simplification methods for tetrahedral mesh, this method is straightforward and user-friendly, with a time complexity of O(N) (where N is the number of vertices) and a space complexity of O(N).","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130423301","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 : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221276
Chenyu Guo, Hongxia Ye
The wave spectrum model of ocean surface, which describes the statistical characteristics of ocean surface fluctuation, is very important to electromagnetic scattering modeling of ocean surface. By dividing the wave spectrum into large-scale and small-scale parts, the two-scale model (TSM) combines Kirchhoff approximation (KA) with the small perturbation method (SPM) to expand the application range of the model. This paper uses the TSM to study the simulation performance of Durden-Vesecky (DV) spectrum, Apel spectrum and Elfouhaily spectrum in Ku-band. The cutoff wavenumber is one of the most important factors affecting the accuracy of TSM simulation. We simulate the backscattering coefficients by TSM with different cutoff wavenumbers, and compare with the NSCAT-4 geophysical model function (GMF) to find the minimum absolute error. Then these minimum absolute errors are used to calculate the mean absolute error to select the most appropriate wave spectrum model. The simulation results of different spectrums demonstrate that the Apel spectrum is more suitable for backscattering simulation of rough sea surfaces in Ku-band when the incidence angle is 30° ~ 66° and the wind speed is 3 ~ 20 m/s.
{"title":"Study on Sea Surface Spectrum Model for Electromagnetic Scattering in Ku-Band Based on Two-Scale Model","authors":"Chenyu Guo, Hongxia Ye","doi":"10.1109/PIERS59004.2023.10221276","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221276","url":null,"abstract":"The wave spectrum model of ocean surface, which describes the statistical characteristics of ocean surface fluctuation, is very important to electromagnetic scattering modeling of ocean surface. By dividing the wave spectrum into large-scale and small-scale parts, the two-scale model (TSM) combines Kirchhoff approximation (KA) with the small perturbation method (SPM) to expand the application range of the model. This paper uses the TSM to study the simulation performance of Durden-Vesecky (DV) spectrum, Apel spectrum and Elfouhaily spectrum in Ku-band. The cutoff wavenumber is one of the most important factors affecting the accuracy of TSM simulation. We simulate the backscattering coefficients by TSM with different cutoff wavenumbers, and compare with the NSCAT-4 geophysical model function (GMF) to find the minimum absolute error. Then these minimum absolute errors are used to calculate the mean absolute error to select the most appropriate wave spectrum model. The simulation results of different spectrums demonstrate that the Apel spectrum is more suitable for backscattering simulation of rough sea surfaces in Ku-band when the incidence angle is 30° ~ 66° and the wind speed is 3 ~ 20 m/s.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134391591","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 : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221366
Gang Zhang, Xuben Wang, Yushu Tang, Yu Ma, Xin-he Zhang, Dewei Li, Chunmei Huang, Xuelin Cai
A three-dimensional crust-mantle electrical structure of the Lushan earthquake area in the southern section of Longmenshan (LMS) is studied. The 3D inversion results of 108 MT array data showed that high-conductor layers (HCL) in the Songpan-Ganzi terrane (SGT) middle crust, Sichuan Basin (SCB) shallow surface, western Sichuan foreland depression (WSCFD) and LMS Moho. The Lushan earthquake area is subject to compressional deformation horizontally as the eastwards migration of Qinghai-Tibet Plateau material is blocked by the SCB and vertically by the upwards extension of high-conductor plastic material at depth. The aftershocks of the Lushan earthquake area are mainly confined within the Baoxing-Zhonglin-Daxing-Lushan high-conductor region, which has noticeable electrical structural differences compared to the overall high-resistivity structure of the LMS southern section; these differences explain why the aftershocks of the two earthquakes did not expand in the northeast and southwest directions of LMS. Because the 2022 and 2013 Lushan earthquakes both occurred in the same high-conductor region in the deep part of the Dachuan-ShuangShi fault to the Danyi blind fault, the 2022 Lushan earthquake was a strong aftershock of the 2013 Lushan earthquake in terms of electrical structural characteristics.
{"title":"Three-Dimensional Electrical Structure of the Crust-Mantle in the Southern Section of the Longmenshan and Its Relation to the Lushan Earthquake","authors":"Gang Zhang, Xuben Wang, Yushu Tang, Yu Ma, Xin-he Zhang, Dewei Li, Chunmei Huang, Xuelin Cai","doi":"10.1109/PIERS59004.2023.10221366","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221366","url":null,"abstract":"A three-dimensional crust-mantle electrical structure of the Lushan earthquake area in the southern section of Longmenshan (LMS) is studied. The 3D inversion results of 108 MT array data showed that high-conductor layers (HCL) in the Songpan-Ganzi terrane (SGT) middle crust, Sichuan Basin (SCB) shallow surface, western Sichuan foreland depression (WSCFD) and LMS Moho. The Lushan earthquake area is subject to compressional deformation horizontally as the eastwards migration of Qinghai-Tibet Plateau material is blocked by the SCB and vertically by the upwards extension of high-conductor plastic material at depth. The aftershocks of the Lushan earthquake area are mainly confined within the Baoxing-Zhonglin-Daxing-Lushan high-conductor region, which has noticeable electrical structural differences compared to the overall high-resistivity structure of the LMS southern section; these differences explain why the aftershocks of the two earthquakes did not expand in the northeast and southwest directions of LMS. Because the 2022 and 2013 Lushan earthquakes both occurred in the same high-conductor region in the deep part of the Dachuan-ShuangShi fault to the Danyi blind fault, the 2022 Lushan earthquake was a strong aftershock of the 2013 Lushan earthquake in terms of electrical structural characteristics.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131625196","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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