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Analysis of transient electromagnetic response for the borehole to airborne survey mode 航空测量模式下井眼瞬变电磁响应分析

IF 1.5 4区地球科学

Radio Science Pub Date : 2025-08-01 DOI: 10.1029/2025RS008234

Xin Wu;Liting Rao;Guoqiang Xue;Bo Dang;Junjie Xue;Weiying Chen;Nannan Zhou

{"title":"Analysis of transient electromagnetic response for the borehole to airborne survey mode","authors":"Xin Wu;Liting Rao;Guoqiang Xue;Bo Dang;Junjie Xue;Weiying Chen;Nannan Zhou","doi":"10.1029/2025RS008234","DOIUrl":"https://doi.org/10.1029/2025RS008234","url":null,"abstract":"This paper proposes a novel borehole to airborne survey mode for electromagnetic method by integrating the advantages of borehole excitation and airborne observation, which is applicable to the exploration of oil and gas reservoirs. The new approach is expected to offer potential exploration benefits such as large depth penetration, wide coverage area, high precision, and efficiency. Currently, the transient electromagnetic method (TEM) in the borehole to airborne survey mode has not been implemented domestically or internationally, lacking theoretical guidance for equipment development and exploration operations. This paper focuses on the analysis of electromagnetic response characteristics of the borehole to airborne TEM using the vertical electric source in the case of the vertical well condition. The characteristics including induced current diffusion, spatial distribution of multi-component electromagnetic responses, and signal attenuation at different measuring points, are investigated. The study identifies the optimal electromagnetic field components for observation, discusses the technical challenges and feasibility of detection equipment. In summary, the findings of this paper provide essential theoretical groundwork for advancing the new method in terms of detection equipment, operational techniques, data processing, and interpretation.","PeriodicalId":49638,"journal":{"name":"Radio Science","volume":"60 8","pages":"1-19"},"PeriodicalIF":1.5,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144934483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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IF 1.5 4区地球科学

Radio Science Pub Date : 2025-08-01 DOI: 10.1002/rds.21332

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Deep space network radio science and ground-based planetary radar in the next decade 未来十年的深空网络无线电科学和地基行星雷达

IF 1.5 4区地球科学

Radio Science Pub Date : 2025-07-01 DOI: 10.1029/2025RS008296

R. S. Park;J. E. Riedel;N. Rodriguez-Alvarez;M. Brozovic;L. A. M. Benner;P. Vergados;D. Buccino;C. S. Jacobs;L. S. Locke;S. W. Asmar;R. Castano;T. J. W. Lazio;J. Jao;C. Lee

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Decoding space radio waves: Self-supervised AI deciphers plasma frequency 解码太空无线电波：自我监督的人工智能解码等离子频率

IF 1.5 4区地球科学

Radio Science Pub Date : 2025-07-01 DOI: 10.1029/2024RS008101

Yi-Jiun Su;John A. Carilli

{"title":"Decoding space radio waves: Self-supervised AI deciphers plasma frequency","authors":"Yi-Jiun Su;John A. Carilli","doi":"10.1029/2024RS008101","DOIUrl":"https://doi.org/10.1029/2024RS008101","url":null,"abstract":"This article presents a methodology for the extraction of plasma frequency from the upper hybrid resonance traces obtained from space-based wave spectrograms utilizing self-supervised artificial intelligence. It elaborates on the development and implementation of a deep learning model. The model utilizes contrastive learning techniques, leveraging positive pairs without incorporating negative pairs. The model's architecture is described, encompassing data augmentation strategies and the employment of a convolutional residual network (ResNet) as the backbone architecture. Two self-supervised feature representation learning methods, Bootstrap Your Own Latent (BYOL) and PIXel-level Consistency Learning (PIXCL), are evaluated. The paper additionally examines the integration of a Fully Convolutional Network (FCN) structure for subsequent downstream tasks and the use of semi-self-supervised learning to enhance performance with limited labeled data. Results from experiments conducted using data from the Van Allen Probes (VAP) mission demonstrate the efficacy of the proposed method. The model's performance, assessed using the Hausdorff Distance (HD) metric, exhibits promising outcomes in comparison to supervised learning benchmarks, while significantly reducing the necessity for manual data labeling.","PeriodicalId":49638,"journal":{"name":"Radio Science","volume":"60 7","pages":"1-12"},"PeriodicalIF":1.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Detecting ionospheric disturbances using high frequency coastal radar transmissions from the west coast of the United States 从美国西海岸使用高频海岸雷达传输探测电离层扰动

IF 1.5 4区地球科学

Radio Science Pub Date : 2025-07-01 DOI: 10.1029/2025RS008235

Riley N. Troyer;Kenneth Obenberger;Michael Negale;Eugene Dao;Zsolt Balint;Eric Burnside;Kris Robinson;Jeffrey M. Holmes;Pavel Inchin;Jonathan Snively

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A review on unlocking performance insights for next generation connectivity with AI in 6G communication 关于在6G通信中解锁下一代AI连接的性能见解的综述

IF 1.5 4区地球科学

Radio Science Pub Date : 2025-07-01 DOI: 10.1029/2025RS008222

Nipun Sharma;Swati Sharma

{"title":"A review on unlocking performance insights for next generation connectivity with AI in 6G communication","authors":"Nipun Sharma;Swati Sharma","doi":"10.1029/2025RS008222","DOIUrl":"https://doi.org/10.1029/2025RS008222","url":null,"abstract":"The rapid expansion of 6G communication networks provides a disruptive potential to address the increasing need for ultra-fast, protected, and reliable connectivity. This review study critically explores three essential domains: Privacy and security, throughput and efficiency, and latency and signal-to-noise ratio (SNR) that are fundamental to the success of 6G systems. The interrelated structure for 6G, combined with the growth of IoT devices also decentralized architectures, raises the risk of data breaches along with network vulnerabilities, necessitating the development of AI-powered privacy-preserving frameworks and adaptive security mechanisms. Furthermore, with 6G's promise of unprecedented throughput, this paper explores the role of intelligent spectrum management and resource allocation techniques to optimize bandwidth utilization and ensure high-efficiency transmission in dynamic network environments. Furthermore, obtaining ultra-low latency and maintaining a high SNR is critical for live applications like self-navigating devices and immersive technologies, where any delay or signal loss can have a major impact on performance. This review highlights existing research gaps in these areas and presents a comprehensive analysis of AI-driven solutions, setting a pathway for future advancements in scalable, high-throughput, and low-latency 6G architectures.","PeriodicalId":49638,"journal":{"name":"Radio Science","volume":"60 7","pages":"1-27"},"PeriodicalIF":1.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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DynaClusterNet: A dynamic clustering network-based routing optimization for edge computing DynaClusterNet：基于动态集群网络的边缘计算路由优化

IF 1.5 4区地球科学

Radio Science Pub Date : 2025-07-01 DOI: 10.1029/2024RS008145

Ravula Rajesh;Ripon Patgiri;Laiphrakpam Dolendro Singh

{"title":"DynaClusterNet: A dynamic clustering network-based routing optimization for edge computing","authors":"Ravula Rajesh;Ripon Patgiri;Laiphrakpam Dolendro Singh","doi":"10.1029/2024RS008145","DOIUrl":"https://doi.org/10.1029/2024RS008145","url":null,"abstract":"The Internet of Things has led to a surge in data generation and network complexity, especially in edge environments with dynamic topologies and moving objects. Traditional clustering methods in edge computing often fail to address these challenges, such as efficient data aggregation and computational management. DynaClusterNet, a novel framework, introduces three protocols: Adaptive Cluster-Based Deployment Protocol (ACDP), Dynamic Algae Spider Protocol (DASP), and Deep Q Routing Protocol (DQRP). The ACDP uses Voronoi diagrams for optimal node deployment and cluster formation, while the DASP uses Artificial Algae and Black Widow Algorithms to dynamically select cluster heads and optimize data transmission. The DQRP uses deep reinforcement learning to determine efficient routing paths, adapting to environmental changes, node mobility, and evolving network topologies. DynaClusterNet significantly outperforms existing protocols in terms of end-to-end delay, energy consumption, and Packet Delivery Ratio. It ensures a robust, efficient, and adaptable network performance with a minimal end-to-end delay of approximately 0.05 s and significantly lower energy consumption profile than competing protocols.","PeriodicalId":49638,"journal":{"name":"Radio Science","volume":"60 7","pages":"1-20"},"PeriodicalIF":1.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Single-scattering radar cross section of the ocean surface without the small-slope and height assumptions 不考虑小坡度和小高度假设的海面单散射雷达横截面

IF 1.5 4区地球科学

Radio Science Pub Date : 2025-07-01 DOI: 10.1029/2025RS008265

M. Torabi;R. Shahidi;E. W. Gill

引用次数: 0

Gray optimized adaptive model predictive control for enhanced efficiency and misalignment tolerance in wireless EV charging systems 基于灰色优化的自适应模型预测控制提高了无线充电系统的效率和误差容忍度

IF 1.5 4区地球科学

Radio Science Pub Date : 2025-07-01 DOI: 10.1029/2025RS008228

T. A. Annai Raina;D. Marshiana

{"title":"Gray optimized adaptive model predictive control for enhanced efficiency and misalignment tolerance in wireless EV charging systems","authors":"T. A. Annai Raina;D. Marshiana","doi":"10.1029/2025RS008228","DOIUrl":"https://doi.org/10.1029/2025RS008228","url":null,"abstract":"Wireless power transfer (WPT) systems have gained a lot of attention in electric vehicle (EV) charging due to their potential for efficient, contactless energy transfer, offering enhanced convenience and safety compared to traditional plug-in methods. A phase-shifted full bridge inverter and continuous control set model predictive control are the foundations of a suggested primary side control technique for the WPT system. The optimal control variable is then found by converting the controller's gray wolf optimization issue into a problem of minimizing the cost function's value in order to get the best response from the system. According to the findings of the simulation, the control system operates at a frequency of 10 kHz to achieve real-time voltage adjustment, and about 8.6 kW of power is transmitted. Compared with the conventional technique, the power transferred is improved when misalignment is addressed by interference factors. The system, validated through hardware implementation and testing, demonstrated stable output power and voltage regulation with an average efficiency of 95.2%, demonstrating its reliability for real-world EV charging applications. The proposed method enhances double LCC compensated WPT systems' performance, making them suitable for compact, lightweight receiver applications, and enables real-time regulation of system output voltage.","PeriodicalId":49638,"journal":{"name":"Radio Science","volume":"60 7","pages":"1-22"},"PeriodicalIF":1.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Front matters 前面问题

IF 1.5 4区地球科学

Radio Science Pub Date : 2025-07-01 DOI: 10.1002/rds.21331

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