Design and Performance Analysis Results of Iron-Core Type MgB<sub>2</sub> and HTS Magnets for Large-Scale Superconducting Induction Heaters

Choi, Jung Hye; Kim, Tae-Kue; Lee, Chankyeong; Sung-Kyu, Kim

doi:10.1109/tasc.2020.2982883

Cited by 7 publications

(2 citation statements)

References 17 publications

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“…DC induction heating methods enabled by superconduting technology have been proposed, and recently introduced at the practical level [225,226]. In DC induction heating, the billet was forced to rotate inside a transverse DC magnetic field produced without losses by superconducting coils, thus reaching an overall efficiency above 90%.…”

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.

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show abstract

“…It offers advantages such as fast heating speeds, high efficiency, and compliance with higher environmental and safety standards. This technology is applied in various industrial processes, medical settings, household stoves, and across different power levels [3][4]. Particularly, induction heating technology is widely employed in household cooking appliances [5][6].…”

Section: Introductionmentioning

confidence: 99%

Development of a Coaxial Dual-Coil Induction Heating System With a Composite Bridge-Type Inverter and a Flexible Switching Mechanism

Hung,

Huang,

Lee

et al. 2024

IEEE Access

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This study proposes a design of the composite bridge-type inverter with a flexible switching mechanism for a coaxial dual-coil induction heating system. Contemporary induction heating technologies predominantly adopt either a single-coil or multi-coil architecture. The former often suffers from limited heating coverage and lacks uniformity, while the latter is favored in applications necessitating broad heating ranges, requiring multiple inverters for effective coil switching control. Consequently, challenges persist in achieving rapid and consistent heating. In this regard, this study proposes a composite bridge-type inverter circuit comprising 5 power components. Through different power transistor switching mechanisms, the system enables independent or simultaneous operation of inner and outer coils, facilitating uniform and swift heating. Furthermore, the proposed inverter can adapt its coil architecture to various operating modes, optimizing heating consistency and performance. Notably, the system achieves an impressive efficiency rate of 96.2%. To validate the viability of our induction heating system concept, a laboratory prototype was constructed and tested. Results from the experiments affirm the system's flexible switching capabilities, catering to adjustable heating zone requirements in the coaxial dual-coil setup proposed in this study.INDEX TERMS Composite bridge-type circuit, flexible switching mechanism, coaxial dual-coil induction heating system, and uniform and swift heating.

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Heating Characteristics of TC4 Titanium Alloy in an HTS DC Induction Heater

Yang

Dai

et al. 2021

IEEE Trans. Appl. Supercond.

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Design and Performance Analysis Results of Iron-Core Type MgB₂ and HTS Magnets for Large-Scale Superconducting Induction Heaters

Cited by 7 publications

References 17 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

Development of a Coaxial Dual-Coil Induction Heating System With a Composite Bridge-Type Inverter and a Flexible Switching Mechanism

Heating Characteristics of TC4 Titanium Alloy in an HTS DC Induction Heater

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Design and Performance Analysis Results of Iron-Core Type MgB2 and HTS Magnets for Large-Scale Superconducting Induction Heaters

Cited by 7 publications

References 17 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

Development of a Coaxial Dual-Coil Induction Heating System With a Composite Bridge-Type Inverter and a Flexible Switching Mechanism

Heating Characteristics of TC4 Titanium Alloy in an HTS DC Induction Heater

Contact Info

Product

Resources

About

Design and Performance Analysis Results of Iron-Core Type MgB₂ and HTS Magnets for Large-Scale Superconducting Induction Heaters