Bench testing of hybrid ems prototype

Aim: To test the levitation performance of a hybrid EMS prototype. Materials and Methods: a levitation test setup with a 18 mm thick steel rail was constructed on a basis of the certified test bench 1958U-10-1 for measurement in the range up to 100 kN. The attractive force was investigated by varying the air gap size and coil current. Measured data were compared with parametric simulations. Results: Experimental and numerical results agreed with the accuracy required for practical application. Conclusions: A prototype of hybrid EMS (HEMS) for maglev transport has been designed, built, and tested at JSC NIIEFA. The HEMS concept has an advantage of reduced power loss and low stray field. The bench testing has proved good levitation performance and low power consumption of the proposed design. The measured data were used to check design solutions and verify 3D numerical models of the magnets. The comparison demonstrated a good match between measurements and simulations.

Neoclassical toroidal viscosity torque prediction via deep learning

GPECnet is a densely connected neural network that has been trained on GPEC data, to predict the plasma stability, neoclassical toroidal viscosity (NTV) torque, and optimized 3D coil current distributions for desired NTV torque profiles. Using NTV torque, driven by non-axisymmetric field perturbations in a tokamak, can be vital in optimizing pedestal performance by controlling the rotation profile in both the core, to ensure tearing stability, and the edge, to avoid edge localized modes (ELMs). The Generalized Perturbed Equilibrium Code (GPEC) software package can be used to calculate the plasma stability to 3D perturbations and the NTV torque profile generated by applied 3D magnetic fields. These calculations, however, involve complex integrations over space and energy distributions, which takes time to compute. Initially, GPECnet has been trained solely on data representative of the quiescent H-mode (QH) scenario, in which neutral beams are often balanced and toroidal rotation is low across the plasma profile. This work provides the foundation for active control of the rotation shear using a combination of beams and 3D fields for robust and high performance QH mode operation.

Numerical investigations of 2-D planar magnetic nozzle effects on pulsed plasma plumes

This paper presents a study of a novel type of magnetic nozzle that allows for three-dimensional (3-D) steering of a plasma plume. Numerical simulations were performed using Tech-X’s USim® software to quantify the nozzle’s capabilities. A 2-D planar magnetic nozzle was applied to plumes of a nominal pulsed inductive plasma (PIP) source with discharge parameters similar to those of Missouri S&T’s Missouri Plasmoid Experiment (MPX). Argon and xenon plumes were considered. Simulations were verified and validated through a mesh convergence study as well as comparison with available experimental data. Periodicity was achieved over the simulation run time and phase angle samples were taken to examine plume evolution over pulse cycles. The resulting pressure, velocity, and density fields were analysed for nozzle angles from 0° to 14°. It was found that actual plume divergence was small compared to the nozzle angle. Even with an offset angle of 14° for the magnetic nozzle, the plume vector angle was only about 2° for argon and less than 1° for xenon. The parameters that had the most effect on the vectoring angle were found to be the coil current and inlet velocity.

Optimization of leaky-wave surface coil current using an analytical approach

In this work, we investigate the optimal coefficients of the exponential current excited on a leaky wave surface coil. The respective functional is first derived analytically and later computed numerically using Python. The results are compared to the same problem modeled in Comsol Multiphysics.

Control of WPT Transmitter Coils for Power Distribution to Two Receiver Coils without Feedback

This paper proposes the algorithm to control the current ratio of the transmitting (Tx) coils for proper power distribution to the two receiving (Rx) coils in wireless power transfer (WPT) system. The proposed algorithm assumes that each Rx coil appears at different times to consider the situation where multiple users request power transmission as practically as possible. That is, suppose the second Rx coil enters the charging space later than the first Rx coil. When each coil enters the charging space, only the Tx coil is used to obtain the value required for calculation. Using the obtained result, the optimized Tx coil current is calculated by the proposed algorithm and proper power distribution to both Rx coils is achieved. Three Tx coils and two Rx coils are constructed using the ANSYS MAXWELL simulation tool. As a result of applying the proposed algorithm, it was confirmed that a similar level of power was transmitted between 40∼60%, respectively. The sum of the power transmitted to the two Rx coils also appeared as more than 75%.

Design Concept and Structural Configuration of Magnetic Levitation Stage with Z-Assist System

Magnetic levitation technology is expected to provide a solution for achieving nanometer-scale positioning accuracy. However, magnetic leakage limits the application of the magnetic levitation stage. To reduce magnetic density, motors should be installed at an appropriate distance from the table. This increases the axis interference between the horizontal thrust and the pitching, making it difficult to achieve stable levitation. In this study, a magnetic levitation stage system that has a unique motor structure fusing a gravity compensation function and pitching moment compensation is proposed. This compensation mechanism operates automatically using the passive magnetic circuit structure, ensuring that noises from the coil current and the timing gaps do not affect the driving characteristics and that neither wiring nor sensors are required. The basic characteristics were evaluated through the driving experiments, and the efficiency of the proposed gravity and pitching moment compensation system was demonstrated.

Error Analysis of Air-Core Coil Current Transformer Based on Stacking Model Fusion

Air-core coil current transformer is a key piece of equipment in the digital substation development. However, it is more vulnerable to various faults when compared with the traditional electromagnetic current transformer. Aiming at understanding the effect of various parameters on the performance of the air-core coil current transformer, this paper investigates the influence of these factors using the maximum information coefficient. The interference mechanism of influencing factors on the transformer error is also analyzed. Finally, the Stacking model fusion algorithm is used to predict transformer errors. The developed base model consists of deep learning, integrated learning and traditional learning algorithms. Compared with gated recurrent units and extreme gradient boosting algorithms, the prediction model based on stacking model fusion algorithm proposed in this paper features higher accuracy and reliability which helps improve the performance and safety of future digital substations.