2023
DOI: 10.1088/1361-6668/acbeea
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Thermal thin shell approximation towards finite element quench simulation

Abstract: Superconducting electromagnets commonly exhibit thin layers with high aspect ratio such as insulation layers or turn-to-turn contacts. A finite element analysis of these devices can lead to unfavorable meshes in these thin layers, either because of a high number of degrees of freedom or mesh elements of poor quality which decrease the accuracy of the simulation results. To mitigate these issues when conducting a thermal finite element analysis solving the heat equation, this work proposes to collapse thin volu… Show more

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Cited by 7 publications
(19 citation statements)
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“…The discontinuity of the tangential magnetic field strength can be introduced by two equivalent approaches: using a duplication of mesh DoF as in [17] or by ii) using dedicated FE basis functions with support restricted to one side of Γ c,cl [30]. In this work, we follow the latter approach as it allows to couple the thermal TSA of [16] and this work without needing two different meshes for the thermal and MQS system.…”
Section: Thin Shell Approximationmentioning
confidence: 99%
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“…The discontinuity of the tangential magnetic field strength can be introduced by two equivalent approaches: using a duplication of mesh DoF as in [17] or by ii) using dedicated FE basis functions with support restricted to one side of Γ c,cl [30]. In this work, we follow the latter approach as it allows to couple the thermal TSA of [16] and this work without needing two different meshes for the thermal and MQS system.…”
Section: Thin Shell Approximationmentioning
confidence: 99%
“…The TSA model has 2.2 times fewer DoF and 1.9 times shorter total solution time compared to the vol model. As discussed in [16], the more the T2TCL thickness approaches zero (for directly touching turns), the more the solution time is reduced. In such a case, the TSA becomes the only practical method expected to lead to a (correct) solution.…”
Section: Verification: Powering Cycle Simulationmentioning
confidence: 99%
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