Improvement of Superconducting Linear Acceleration System for Pellet Injection: Optimization of Current Profile

Takayama, T.; Yamaguchi, Takazumi; Saitoh, Ayumu; Kamitani, Atsushi

doi:10.1109/tasc.2021.3064795

Cited by 4 publications

(5 citation statements)

References 11 publications

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“…The second level objective function concerns minimizing the HTS filaments. After optimisation, it turns out that the velocity of acceleration is highly increased by the enhancement of the length of HTS filaments and coil [233].…”

Section: Ai Techniques For Magnetic Levitationmentioning

confidence: 99%

Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring

Yazdani-Asrami

Sadeghi

Song

et al. 2022

Supercond. Sci. Technol.

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More than a century after the discovery of superconductors (SCs), numerous studies have been accomplished to take the advantage of SCs in physics, power engineering, quantum computing, electronics, communications, aviation, health care, and defence-related applications. However, there are still challenges that hinder the full-scale commercialization of SCs, such as the high cost of superconducting wires/tapes, technical issues related to AC losses, the structure of superconducting devices, the complexity and high cost of the cooling systems, the critical temperature, and manufacturing related issues. In the current century, massive advancements have been achieved on artificial intelligence (AI) techniques by offering disruptive solutions to handle engineering problems. Consequently, AI techniques can be implemented to tackle those challenges facing superconductivity and act as a shortcut towards full commercialization of SCs and their applications. AI approaches are capable of providing fast, efficient, and accurate solutions for the technical, manufacturing, and economic problems with a high level of complexity and nonlinearity in the field of superconductivity. In this paper, concept of AI and the widely used algorithms are first given. Then a critical topical review is presented for those conducted studies that used AI methods for improvement, design, condition monitoring, fault detection and location of superconducting apparatuses in large scale power applications, as well as the prediction of critical temperature and the structure of new SCs, and any other related applications. The topical review are presented in three main categories, AI for large-scale superconducting applications, AI for superconducting materials, and AI for physics of superconductors. In addition, the challenges to apply AI techniques to the superconductivity and its applications are given. Eventually, future trends on how to integrate AI techniques with superconductivity towards the commercialization are discussed.

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Section: Ai Techniques For Magnetic Levitationmentioning

confidence: 99%

Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring

Yazdani-Asrami

Sadeghi

Song

et al. 2022

Supercond. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…Details of the above equations can be found in Ref. [3]. The characteristic parameters of HTS are the critical current density (J C ), critical electric field (E C ), power N of the power law, and total mass (m) of HTS and pellet container.…”

Section: Simulation Modelmentioning

confidence: 99%

“…Previous studies simulated an SLA system by solving the time evolution problem of the shielding current density in HTS thin film using an axisymmetric model [2][3][4]. For the estimation of the pellet velocity, the shielding current in the propulsion film attached to the pellet container and the dynamic motion of the film were analyzed.…”

Section: Introductionmentioning

confidence: 99%

Numerical Investigations on Superconducting Linear Acceleration System by Using Finite Element Method: Influence of Magnet Current on Pellet Velocity

Takayama

Saitoh

Kamitani

et al. 2023

Plasma and Fusion Research

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The performance of a superconducting linear accelerator (SLA) system for pellet injection in fuel nuclear fusion reactors was investigated numerically. To this end, a numerical code using the finite element method was developed to analyze the shielding current density and dynamic motion of the high-temperature superconducting thin film of the SLA system. The computational results showed that applying an exponential current to the electromagnet, significantly improved the acceleration performance. It was concluded that SLA systems of the order of several hundred meters, and with realistic acceleration distances using the proposed currents can be designed.

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“…Previous studies have numerically investigated the SLA system by solving the time evolution problem of the shielding current density in the thin film of an axisymmetric HTS [4,5,6]. The shielding current in the propulsion thin film attached to the pellet container was analyzed to estimate pellet velocity.…”

Section: Introductionmentioning

confidence: 99%

“…Prior studies have also found that an increase in pellet velocity can be expected using the optimized shape of a single electromagnet [5,6]. The NSGA-II and the normalized Gaussian network (NGnet) methods were employed for the genetic algorithm and shape representation, respectively.…”

Section: Introductionmentioning

confidence: 99%

Numerical Approach to Enhanced-Performance of Superconducting Linear Accelerator Using Multiple-Electromagnets

Takayama

Saitoh

Kamitani

2023

JASSE

Self Cite

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The performance of a superconducting linear accelerator (SLA) system for a pellet injection to fuel nuclear fusion reactors has been investigated numerically. For this purpose, a numerical code has been developed to analyze the shielding current density and dynamic motion of a high-temperature superconducting thin film by means of finite element method. In the present study, an exponentially increasing current was employed to drastically accelerate a pellet in the container. Computational results indicate that the acceleration distance required for the SLA system to reach the target speed of 5 km/s was approximately 2.5 km, it is reduced to approximately 88%. It was therefore concluded that the proposed current has the potential to improve acceleration performance significantly.

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Improvement of Superconducting Linear Acceleration System for Pellet Injection: Optimization of Current Profile

Cited by 4 publications

References 11 publications

Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring

Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring

Numerical Investigations on Superconducting Linear Acceleration System by Using Finite Element Method: Influence of Magnet Current on Pellet Velocity

Numerical Approach to Enhanced-Performance of Superconducting Linear Accelerator Using Multiple-Electromagnets

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