Structural Design of a 9.4 T Whole-Body MRI Superconducting Magnet

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.

Section: Applications Of Scs and The Challengesmentioning

confidence: 99%

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

Yazdani-Asrami

Sadeghi

Song

et al. 2022

“…The coil bundles are solved for all three processes-winding, cooldown and electromagnetic excitation. There are well verified existing analytical approaches [33,34,[36][37][38] to model winding, thermal cool down [39] and electromagnetic charging [31,[40][41][42][43][44], but the computational approach based on FEA is well favored considering orthotropic material approximation, boundary conditions, geometric complexity, and multivariate elastic moduli of wire and mandrel. Hence, while employing FEA analysis; shifting from the wire length scale to the coil bundle length scale makes the problem multiscale and modeling the coil bundle for electromagnetic excitation stress-strain turns the model into multiphysics modeling.…”

Section: Methodsmentioning

confidence: 98%

“…It is critical to understand the strain development in magnetic coils of MgB 2 because of the low failure strain of the material. While multiscale and multiphysics FE analysis of NbTi superconducting magnets has been carried out by researchers [32][33][34][35][36][37][38], mechanical strain analysis of a conduction cooled MgB 2 based superconducting solenoid magnet is yet to be explored.…”

Section: Introductionmentioning

confidence: 99%

A multiscale and multiphysics model of strain development in a 1.5 T MRI magnet designed with 36 filament composite MgB₂superconducting wire

Amin

Baig

Deissler

et al. 2016

High temperature superconductors such as MgB2 focus on conduction cooling of electromagnets that eliminates the use of liquid helium. With the recent advances in the strain sustainability of MgB2, a full body 1.5 T conduction cooled magnetic resonance imaging (MRI) magnet shows promise. In this article, a 36 filament MgB2 superconducting wire is considered for a 1.5 T full-body MRI system and is analyzed in terms of strain development. In order to facilitate analysis, this composite wire is homogenized and the orthotropic wire material properties are employed to solve for strain development using a 2D-axisymmetric finite element analysis (FEA) model of the entire set of MRI magnet. The entire multiscale multiphysics analysis is considered from the wire to the magnet bundles addressing winding, cooling and electromagnetic excitation. The FEA solution is verified with proven analytical equations and acceptable agreement is reported. The results show a maximum mechanical strain development of 0.06% that is within the failure criteria of −0.6% to 0.4% (−0.3% to 0.2% for design) for the 36 filament MgB2 wire. Therefore, the study indicates the safe operation of the conduction cooled MgB2 based MRI magnet as far as strain development is concerned.

“…The main coils were wound with wire in a channel Nb-Ti/Cu conductors (figure 1(b)), and the compensation coils at a lower magnetic field were wound with rectangular Nb-Ti/Cu strand wires with smaller crosssectional areas to acquire a high current density. The conductor and winding properties are shown in the our previous [22,23]. The specification of all the coils and wires are shown in tables 1 and 2.…”

Section: Introduction Of the 94 T-800 MM Whole-body Magnetmentioning

confidence: 99%

Systematic analysis of the quench process performance and simulation of the 9.4 T-800 mm whole-body MRI magnet

Chen

Wang

Zhang

et al. 2023

In 2021, the Institute of Electrical Engineering, Chinese Academy of Sciences successfully reached 9.4T in a whole-body magnetic resonance imaging (MRI) superconducting magnet with an inner diameter of 800 mm. In this study, a systematic analysis of both the real quench protection performance and a simulation are reported. The four successful quench protections during the entire energization process proved the feasibility of the “in-out-in” quench protection protocol for a 9.4T-800 mm superconducting magnet. The quench trigger sequence was shown to be adjusted by changing the heater thickness, which demonstrates the flexibility of the “in-out-in” quench protection protocol to fit a different MRI magnet design. The high accuracy of the quench protection simulation method and code was confirmed through comparison of the simulation results with the real performance. Moreover, the limitations of the current quench protection and reference value to other MRI magnets were discussed. It is believed that this study will be useful to other research groups and promote the development of an extremely high-field whole-body MRI system.