Journal of Fusion Energy最新文献_第8页

Retraction Note to: Design and Fabrication of Comparative Langmuir Ball-Pen Probe (LBP) for the Tokamak 退稿说明：托卡马克用朗缪尔球笔探针（LBP）的设计和制造

IF 1.9 4区工程技术

Journal of Fusion Energy Pub Date : 2024-07-04 DOI: 10.1007/s10894-024-00441-8

S. Meshkani, M. Ghoranneviss, A. Salar Elahi, M. Lafouti

引用次数: 0

Retraction Note: Two Semi-Empirical Methods for Determination of Shafranov Shift in IR-T1 Tokamak 撤稿说明：确定 IR-T1 托卡马克中沙弗拉诺夫位移的两种半经验方法

IF 1.9 4区工程技术

Journal of Fusion Energy Pub Date : 2024-07-02 DOI: 10.1007/s10894-024-00438-3

A. Salar Elahi, M. Ghoranneviss, A. Rahimi Rad

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Retraction Note to: Biasing Effect on Modifying of the Tokamak Plasma Horizontal Displacement 撤回说明：改变托卡马克等离子体水平位移的偏置效应

IF 1.9 4区工程技术

Journal of Fusion Energy Pub Date : 2024-07-02 DOI: 10.1007/s10894-024-00437-4

Ahmad Salar Elahi, M. Ghoranneviss, M. Tajdidzadeh, S. Mohammadi, Reza Arvin

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Retraction Note to: Controlling the Diffusion of Runaway Electrons by Safety Factor Changes in IR-T1 Tokamak 退稿说明：通过改变 IR-T1 托卡马克的安全系数控制失控电子的扩散

IF 1.9 4区工程技术

Journal of Fusion Energy Pub Date : 2024-07-02 DOI: 10.1007/s10894-024-00440-9

M. R. Ghanbari, M. Ghoranneviss, A. Salar Elahi, S. Mohammadi, R. Arvin

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Retraction Note: Fast Electrons Behavior in Presence of External Radial Electric Field in IR-T1 Tokamak 撤回说明：IR-T1 托卡马克中存在外部径向电场时的快速电子行为

IF 1.9 4区工程技术

Journal of Fusion Energy Pub Date : 2024-07-02 DOI: 10.1007/s10894-024-00428-5

A. Salar Elahi, M. Ghoranneviss

引用次数: 0

Retraction Note to: Theoretical and experimental approach in poloidal beta and internal inductance measurement on IR-T1 tokamak 撤回说明：IR-T1 托卡马克上极性贝塔和内电感测量的理论和实验方法

IF 1.9 4区工程技术

Journal of Fusion Energy Pub Date : 2024-07-02 DOI: 10.1007/s10894-024-00430-x

A. Salar Elahi, M. Ghoranneviss, M. Emami, A. Rahimi Rad

引用次数: 0

Plasma Breakdown Optimization Calculation Based on Improved Particle Swarm Algorithm for TT-1 Device 基于改进型粒子群算法的 TT-1 设备等离子体击穿优化计算

IF 1.9 4区工程技术

Journal of Fusion Energy Pub Date : 2024-06-26 DOI: 10.1007/s10894-024-00418-7

Shuangbao Shu, Jiaxin Zhang, Shurui Zhang, Jiarong Luo, Shanlin Liu

{"title":"Plasma Breakdown Optimization Calculation Based on Improved Particle Swarm Algorithm for TT-1 Device","authors":"Shuangbao Shu, Jiaxin Zhang, Shurui Zhang, Jiarong Luo, Shanlin Liu","doi":"10.1007/s10894-024-00418-7","DOIUrl":"10.1007/s10894-024-00418-7","url":null,"abstract":"<div><p>In the Tokamak discharge experiment, obtaining the largest possible null field region is a necessary condition for the smooth breakdown of the plasma, and adjusting the poloidal field coil current is key to achieving a better null field region. This paper, based on the Sino-Thai Tokamak cooperation project Thailand Tokamak-1 (TT-1) device, employs an exponentially decreasing Particle Swarm Optimization (PSO) algorithm to optimize the poloidal field coil current to create the desired null field region in the vacuum chamber area. First, a calculation model for the mutual inductance coefficient and the null field region is established according to the characteristics and magnetic structure of the TT-1 device, enabling the calculation of the null field region. Then, an optimization model for the poloidal field coil current is established, aiming to create a sufficiently large null field region (less than 10 Gauss) to facilitate breakdown. The optimization is carried out using both a typical linearly decreasing PSO algorithm and an improved PSO algorithm to determine the optimal poloidal field coil current. Compared to the unmodified PSO algorithm, the improved PSO algorithm reduces the root mean square error by 31.80%. The results show that the improved PSO algorithm is more suitable for the optimization of the poloidal field coil, has stronger optimization capabilities, and can effectively create the desired null field region, providing an important reference for the smooth breakdown of plasma in the TT-1 device.</p></div>","PeriodicalId":634,"journal":{"name":"Journal of Fusion Energy","volume":"43 2","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141501727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Direct Drive Laser Fusion Facility and Pilot Plant 直接驱动激光聚变设施和试验工厂

IF 1.9 4区工程技术

Journal of Fusion Energy Pub Date : 2024-06-18 DOI: 10.1007/s10894-024-00416-9

Malcolm W. McGeoch, Stephen P. Obenschain

引用次数: 0

Risk-Aware Framework Development for Disruption Prediction: Alcator C-Mod and DIII-D Survival Analysis 用于中断预测的风险意识框架开发：Alcator C-Mod 和 DIII-D 生存分析

IF 1.9 4区工程技术

Journal of Fusion Energy Pub Date : 2024-06-10 DOI: 10.1007/s10894-024-00413-y

Zander Keith, Chirag Nagpal, Cristina Rea, R. Alex Tinguely

{"title":"Risk-Aware Framework Development for Disruption Prediction: Alcator C-Mod and DIII-D Survival Analysis","authors":"Zander Keith, Chirag Nagpal, Cristina Rea, R. Alex Tinguely","doi":"10.1007/s10894-024-00413-y","DOIUrl":"10.1007/s10894-024-00413-y","url":null,"abstract":"<div><p>Survival regression models can achieve longer warning times at similar receiver operating characteristic performance than previously investigated models. Survival regression models are also shown to predict the time until a disruption will occur with lower error than other predictors. Time-to-event predictions from time-series data can be obtained with a survival analysis statistical framework, and there have been many tools developed for this task which we aim to apply to disruption prediction. Using the open-source Auton-Survival package we have implemented disruption predictors with the survival regression models Cox Proportional Hazards, Deep Cox Proportional Hazards, and Deep Survival Machines. To compare with previous work, we also include predictors using a Random Forest binary classifier, and a conditional Kaplan-Meier formalism. We benchmarked the performance of these five predictors using experimental data from the Alcator C-Mod and DIII-D tokamaks by simulating alarms on each individual shot. We find that developing machine-relevant metrics to evaluate models is an important area for future work. While this study finds cases where disruptive conditions are not predicted, there are instances where the desired outcome is produced. Giving the plasma control system the expected time-to-disruption will allow it to determine the optimal actuator response in real time to minimize risk of damage to the device.</p></div>","PeriodicalId":634,"journal":{"name":"Journal of Fusion Energy","volume":"43 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10894-024-00413-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141363462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The IFMIF-DONES Diagnostics and Control Systems: Current Design Status, Integration Issues and Future Perspectives Embedding Artificial Intelligence Tools IFMIF-DONES 诊断和控制系统：嵌入人工智能工具的设计现状、集成问题和未来展望

IF 1.9 4区工程技术

Journal of Fusion Energy Pub Date : 2024-06-10 DOI: 10.1007/s10894-024-00414-x

M. Cappelli, C. Torregrosa-Martin, J. Diaz, A. Ibarra

{"title":"The IFMIF-DONES Diagnostics and Control Systems: Current Design Status, Integration Issues and Future Perspectives Embedding Artificial Intelligence Tools","authors":"M. Cappelli, C. Torregrosa-Martin, J. Diaz, A. Ibarra","doi":"10.1007/s10894-024-00414-x","DOIUrl":"10.1007/s10894-024-00414-x","url":null,"abstract":"<div><p>As an integral part of the European strategy for advancing fusion-generated electricity, IFMIF-DONES represents a high-intensity neutron irradiation plant with the main purpose of assessing the suitability of materials for fusion reactor applications. Its primary mission is to examine how materials respond to irradiation within a neutron flux that mimics the conditions expected in the first wall of the proposed DEMO reactor, which is intended to succeed ITER. Consequently, IFMIF-DONES, whose construction is slated to commence shortly, plays a pivotal role in aiding the development, approval, and safe operation of DEMO, as well as future fusion power plants. This paper provides a quick overview of the current development of the IFMIF-DONES neutron source with a particular snapshot of the present engineering design status for what concerns the instrumentation and control systems together with its complex diagnostics, that guarantees the safe monitoring, supervision and regulation of all operations. The current status of design, after the completion of the preliminary design phase is presented, as well as the existing and future plans for their integration also using some of the new capabilities offered by Artificial Intelligence tools.</p></div>","PeriodicalId":634,"journal":{"name":"Journal of Fusion Energy","volume":"43 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10894-024-00414-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141361496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0