Experimental Research on Electromechanical Properties of Multiple Contact Surfaces Copper Bulks under Normal Cyclic Loading and Variable Temperature

Liu, Limei; Yan, Jiangtao; Wang, Keyang; Liu, Yang; Ta, Wanquan; Gao, Yuanwen

doi:10.3390/ma12233883

Cited by 2 publications

(1 citation statement)

References 21 publications

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“…Lu et al measured the contact resistance between two REBCO tapes under load [30]. Gao et al introduced the interface similarity index to calculate the contact resistance [31], and they also investigated the copper to copper contact surface under cyclic load and variable temperature [32]. Yagotintsev et al pointed out that the contact resistance controls the coupling loss in an alternating magnetic field and the current sharing [12].…”

Section: Introductionmentioning

confidence: 99%

Nonlinear contact behavior of HTS tapes during pancake coiling and CORC cabling

Wang

Gao

Luo

et al. 2021

Supercond. Sci. Technol.

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Both the pancake coiling and conductor on round core (CORC) cabling processes consist of winding second-generation high-temperature superconducting tape (REBCO) in a core. The contact behavior between the tape and the core during the winding process directly affects the critical current, cable flexibility, mechanical support and electrical contact resistance. Therefore, the winding process needs to be optimized to produce pancake coils and CORC cables with the desired electrical and mechanical properties. This paper comprehensively considers the role of the relaxation and Poisson effects. The theoretical model and the finite element model (FEM) for calculating the contact stress during the winding process are established, and a formula for the estimation of the contact force is proposed. The suitable winding pre-tension force, winding curvature radius of SCS2030 (2 mm width and 30 μ m substrate thickness) and SCS4050 (4 mm width and 50 μ m substrate thickness) of REBCO tapes are obtained and discussed by accounting for the relaxation effect and the critical current degradation limit. With consideration of the Poisson effect, the nonlinear contact behavior is investigated. In addition, the relaxation effect, Poisson effect and plasticity of the REBCO tape are taken into account in the FEM model. The results show that the axial strain in the REBCO layer during the winding process is related to the contact behavior. The greater the winding pre-tension force, the smaller the helical curvature radius, and the greater the contact force. The distribution of contact stress for several winding factors (winding pre-tension force, winding angle and the core radius) is divided into three contact types: the single-line contact, the double-line contact and the surface contact. The FEM model results are consistent with the theoretical evaluation and are more suitable for practical winding cases. This research is the basis for designing and optimizing pancake coils and CORC cables.

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Section: Introductionmentioning

confidence: 99%

Nonlinear contact behavior of HTS tapes during pancake coiling and CORC cabling

Wang

Gao

Luo

et al. 2021

Supercond. Sci. Technol.

Self Cite

View full text Add to dashboard Cite

show abstract

Prediction of contact resistance between copper blocks under cyclic load based on deep learning algorithm

2022

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This paper establishes a data-driven Neural Network (NN) framework. The contact resistance of T2 copper blocks with different roughnesses is predicted by deep learning at room temperature and cyclic loading. The contact resistance problem can be regarded as a regression problem of mapping the high-dimensional array space of multiple variables to the contact resistance. This paper measures the contact resistance of copper blocks with different surface roughnesses under loading and unloading states and obtains the original dataset required by the algorithm. The data characteristics include three surface topography parameters, number of cyclic loads, loading and unloading conditions, and load magnitude, with the data labeled contact resistance. This paper compares the results of the NN model and Holm model results to verify the NN model’s effectiveness. The comparison results show that the prediction results of the NN are consistent with the predictions of the Holm model. After training and debugging, the root mean square error of the multiple hidden layers neural network test set is 6.81%, showing a good prediction effect. In conclusion, the deep learning algorithm provides a new way for fast and accurate prediction of the relationship between T2 copper blocks and contact resistance under cyclic loading times and unloading states.

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Experimental Research on Electromechanical Properties of Multiple Contact Surfaces Copper Bulks under Normal Cyclic Loading and Variable Temperature

Cited by 2 publications

References 21 publications

Nonlinear contact behavior of HTS tapes during pancake coiling and CORC cabling

Nonlinear contact behavior of HTS tapes during pancake coiling and CORC cabling

Prediction of contact resistance between copper blocks under cyclic load based on deep learning algorithm

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