The linear induction generator, recognized for its highly efficient, structural simplicity, and operational reliability, has garnered significant attention across various domains, including magnetic levitation systems, rail transportation, and wave energy conversion. This study presents an investigation into the power output performance of linear induction generators employed in rail vehicles, utilizing Matlab/Simulink for systematic analysis. The simulation model integrates a double closed-loop vector control system to address electromechanical coupling. Outer speed loop uses a PI regulator to track the given speed, while the inner cur-rent loop implements field-oriented control. The simulation achieves the modeling of train operation under constant speed conditions. Simulation results indicate that the linear induction motor reliably transition into the power generation state with the power generation exhibiting a non-monotonic relationship with the slip |s|. The power generation capacity shows an initial increase followed by a decrease within the range of 0.02 ≤ |s| ≤ 0.09, reaching its maximum value at |s| = 0.05.

Simultaneously enhancing the mechanical properties and damping capacity of alloys has long posed a significant challenge, including for Cu-Al alloys. In this work, Cu-Al-Zn alloy with synergistically improved strength and damping performance was successfully fabricated via Zn alloying and powder metallurgy. The addition of Zn promotes the precipitation of Al from the alpha-Cu matrix, leading to the formation of nanoscale ry2 precipitates that effectively contribute to precipitation strengthening. These hard ry2 particles interact with dislocations, pinning a high density of dislocations at the precipitate/matrix interfaces. Consequently, the stress necessary for dislocation unpinning is significantly elevated, leading to effective precipitation strengthening. In parallel, the increased Zn content promotes a higher ry2 phase fraction and a greater density of phase interfaces, which facilitates interface-mediated energy dissipation and improves damping. This approach enables the synergistic enhancement of strength and damping properties in the Cu-Al-Zn alloy.

Powering sensors through non-perforated conductive barriers using Wireless Power Transfer (WPT), specifically Inductive Power Transfer (IPT), is challenging due to eddy current losses and structural constraints in industrial settings like gas pipelines. This study presents a novel 3 kHz IPT system using an LCC-series (LCC-S) compensation topology and compact multilayer helical (MLH) coils with iron powder cores to deliver robust wireless power through a 2 mm aluminum barrier with an 18 mm air gap. Finite element analysis (FEA) validates the design, showing enhanced coupling via distributed-gap cores. The LCC-S prototype achieves 0.79 W at 3.11% efficiency across a 20 mm TX-RX separation, sustaining 0.13 W at 30 mm lateral misalignment. Exceeding a benchmark series-series (SS) topology, it ensures miniaturization and barrier integrity, unlike systems requiring bulky coils or perforations. This study pioneers LCC-S at 3 kHz with misalignment analysis, enabling robust power for industrial Internet of Things (IoT) applications.

This study focuses on the development of a high-efficiency computational model for predicting the magnetic field of high-temperature superconducting (HTS) magnets, which is crucial for the design and optimization of HTS-based devices. A fast-computational model for magnetic field was proposed, leveraging the feature extraction capabilities of the deep residual neural network. To validate the effectiveness and reliability of the proposed model, a prototyped HTS magnet system was employed for experimental verification. The comparison between the calculation results and the experimental data demonstrated a high degree of consistency, confirming the practical applicability of the model. Subsequently, an enhanced linear adaptive genetic algorithm was introduced for the optimization design of a 3 T magnetic resonance imaging magnet utilizing rare-Earth barium copper oxide superconducting tapes. The optimized magnet is composed of 60 double-pancake coils, operating at a cryogenic temperature of 30 K and featuring a coil inner diameter of 600 mm. An active shielding technique was adopted, which involves the strategic arrangement of additional coils to counteract the stray magnetic fields. Through this approach, the fringing field was effectively suppressed. In terms of field homogeneity, the magnet achieved 74 parts per million within a 250 mm diameter spherical volume.

Constructing an accurate battery model is fundamental for state estimation in lithium-ion batteries. The traditional lumped semi-empirical model (LPM) combines the advantages of both electrochemical and equivalent circuit models (ECM). However, the influence of external temperature on model parameters is neglected during the modeling process, which leads to reduced accuracy in varying temperature environments. To address this issue, the temperature effects on the battery model are explored, the sources of model error are identified, and a lumped semi-empirical model considering temperature effects (LPM-T) is proposed. In the model construction process, battery characterization and dynamic load experiments are conducted on lithium-ion batteries at different temperatures. From these experiments, we extract battery capacity and open circuit voltage (OCV) at specific temperatures, and identify the corresponding internal resistance parameters at these temperatures based on the LPM. Additionally, mapping relationships between these model parameters and temperature are established using polynomial fitting and the Arrhenius equation. Finally, the proposed model is validated through a high-rate variable-temperature dynamic cycling load and compared with the other three battery models. The results show that the proposed model significantly improves the accuracy of terminal voltage predictions under variable-temperature conditions, offering enhanced applicability and robustness.

Embedded sensors in structural health monitoring systems can be powered by wireless power transfer technology. However, misalignment between the transmitter and receiver is unavoidable, resulting in system efficiency and power decreases. To address this challenge, a 3-D positioning method for the embedded receiving coil based on a decoupled transformer is proposed. The decoupled transformer consists of two helical coils and one planar coil. These three coils are orthogonal to each other and decoupled magnetically. Coupling occurs only between the decoupled transformer and the receiving coil. This method requires neither auxiliary sources nor communication equipment, and it does not involve complex control. Experimental results show that when the transmission distance ranges from 50 to 80 mm, 93% of the positioning errors are within 10 mm in a 140 mm x 140 mm area. It is proved that the proposed method achieves a high accuracy.

Sensitivity and linearity are two crucial parameters in the context of quartz crystal microbalance (QCM) humidity sensors. Achieving a highly sensitive response in a QCM-based humidity sensor involves employing a significant mass of humidity-sensitive material; however, this approach may introduce a viscosity effect, leading to a nonlinear response from the sensor. The Sauerbrey equation suggests that a QCM device exhibits a linear mass-frequency response when a micro-mass is deposited on its surface. In this study, we present a design strategy for a QCM humidity sensor based on a small-size, high-frequency QCM transducer. A minimal mass ( 1 mu g) of graphene oxide (GO) serves as the moisture-sensitive material and is deposited on a 16-MHz QCM device enclosed in a 5032 package, resulting in the fabrication of a QCM humidity sensor. The sensor demonstrates both high sensitivity (82.40 Hz/%RH) and high linearity (adjusted R-square: 0.9892) across a relative humidity (RH) range of 11%-97%; furthermore, the sensor exhibits low humidity hysteresis (2.5% RH), excellent stability, and repeatability. The methodology proposed in this article is anticipated to contribute to the development of high-performance QCM humidity sensors.

This paper proposes an experimental investigation to validate the use of helium as the sole coolant in a pipe circulation cooling mode for a small 3 T NbTi superconducting magnet. Injecting helium into pipes and liquefying the magnet at 4.2 K will also be explored, utilizing the evaporation of small amounts of liquid helium within the pipes to cool the NbTi magnet and calculate its liquefaction volume and cooling time. Firstly, we investigated a novel approach to achieve acceptable temperatures for current leads by augmenting the top mass and increasing the length of the leads. Additionally, stainless steel (SS) loop tubes surrounding the magnet were designed in a new way to enhance convective heat exchange. Finally, various heat conduction devices were added and after successfully cooling all parts of the experimental apparatus, the heat transfer formula will be used to calculate the theoretical cooling time of pulsed supplementary helium gas, which will then be compared and discussed with actual experimental time. The cryogenic experiment shows that less liquid helium without any other coolants can be adopted efficiently to cool LTS magnets by SS pipelines. Consequently, this approach is significant to reducing consumption of coolant for cooling the LTS NbTi magnet to 4.2 K.

The adjacent segment degeneration after cervical spine fusion can severely impact the surgical efficacy. Therefore, it is necessary to monitor the stress of the adjacent segments and prevent degenerative diseases caused by excessive pressure. In this paper, a small magnetic coupler with a receiver of only 1.65 cm3 is proposed. And the power can be transferred to the stress transducer in the cervical spine through placing receiver in implants. First, an H-shape magnetic core is proposed to constrain the magnetic field, and the transmitting coil turn is increased to enhance the mutual inductance. Then, the magnetic sheets thickness, magnetic rod diameter and magnetic rod position are optimized by the finite element analysis software. Finally, the proposed structure is compared to existing structure, the mutual inductance is increased by 15 times, and the volume and core loss are basically unchanged. The experiment fully proves the feasibility and superiority of the proposed structure.

A double-layer metal-insulation method using brass sheets as the double-layer insulators is proposed in this paper. It can enhance the contact resistivity while preserving greater thermal conductivity merit. The underlying mechanism of the contact resistivity enhancement is to increase the number of contact surfaces and to degrade the contact quality between the insulators. Then, we wound a single-layer brass-insulation coil and a double-layer brass-insulation coil to compare their contact resistivities, and confirmed the effectiveness of the double-layer metal-insulation method. Furthermore, since the capacity to withstand the overcurrent is weakened with the increasing contact resistance of the metal-insulation coil, we further investigated the influence of the contact surface resistivity distribution on the coil performance under different scenarios to optimize the double-layer metal-insulation coil for receiving superior thermal stability. The simulation results indicate that dominant second contact surface resistivity and minimal first and third contact resistivity is the optimal design for the double-layer metal-insulation coil to receive the best thermal stability, irrespective of the cooling environment, contact resistivity magnitude, operating current and coil dimension. In addition, with regard to the thermal performance differences caused by the contact surface resistivity distribution, we found that the increment of contact surface resistivity and the overcurrent enlarged the distinctions at different levels.

We explore the potential to use machine learning methods to search for heavy neutrinos, from their hadronic final states including a fat-jet signal, via the processes $pp \rightarrow W^{\pm *}\rightarrow \mu^{\pm} N \rightarrow \mu^{\pm} \mu^{\mp} W^{\pm} \rightarrow \mu^{\pm} \mu^{\mp} J$ at hadron colliders. We use either the Gradient Boosted Decision Tree or Multi-Layer Perceptron methods to analyse the observables incorporating the jet substructure information, which is performed at hadron colliders with $\sqrt{s}=$ 13, 27, 100 TeV. It is found that, among the observables, the invariant masses of variable system and the observables from the leptons are the most powerful ones to distinguish the signal from the background. With the help of machine learning techniques, the limits on the active-sterile mixing have been improved by about one magnitude comparing to the cut-based analyses, with $V_{\mu N}^2 \lesssim 10^{-4}$ for the heavy neutrinos with masses, 100 GeV$~

Numerical characterization for the dynamic behaviour of DC-carrying HTS coils subjected to alternating magnetic fields is crucial for its design and protection. In conventional approaches, only superconducting layers are modeled. The missing current sharing effect in those models results in the overestimation of dynamic voltage/ resistance. In reality, the transport current will migrate into the metal layers, and therefore the dynamic voltage/ resistance is limited. In this paper, we present an equivalent modeling approach (EPM) instead of modeling the real geometry which will cost massive computation resources. The effectiveness of the approach is validated against a full-scale model containing all the layers. Then, this approach is applied to estimate the dynamic behaviour of a multiturn racetrack HTS coil. It is found that the current sharing effect mainly happens at the outer layers of the coil due to the shielding effect, and is enhanced with the increase of external field amplitude then gradually spreads to the inner layers. Moreover, the competition between the transport current and the induced current in the metal layers is observed.

The superconducting electrodynamic suspension (EDS) train has been expected to be a promising candidate for the future ultrahigh-speed transportation due to its excellent levitation and guidance stabilities, high lift-to-drag ratio, and being free of active control. As a core component of the EDS train, the onboard superconducting magnet (SCM) is usually required to generate a strong magnetic field, however, which may threaten the safety of passengers. Therefore, it is indispensable to design a magnetic shielding for onboard SCM, aiming at minimizing the magnetic field in the coach of the vehicle. In this article, a three-dimensional finite-element method model for solving the electromagnetic problems of the magnetic shielding system is established and validated by experimental results. Prior to global optimization, the effects of the thickness, multilayer structure, and partition of the shielding plate on the magnetic shielding are discussed primarily. It was found that the thickness has a great impact on the shielding effect, whereas the influence of the multilayer structure is weak. Moreover, the weight of the magnetic shielding plate can be effectively reduced by partitioning it into several blocks with different thicknesses. Based on the above-mentioned studies, the magnetic shielding plate is finally optimized in consideration of the thickness, multilayer structure, and partition. Consequently, the weight of the magnetic shielding plate can be reduced by 20% compared with the original one.

With the continuous increases of the train speed, the braking device that relies on the wheel-rail adhesion has approached its acceptable speed limit. Compared with traditional friction brakes, eddy current brakes (ECBs) have the advantages of non-wheel-rail contact, fast response, low noise, wide application range, and no pollution. This study describes an ECB with AC excitation based on Faraday's law. The two-dimensional analytical model of ECB is established by the sub-domain method. Then, the experiment system of rail ECB is designed and built to test the braking characteristics. The authenticity of mathematical model is verified by experimental results. The research indicated that braking force increased at first and reached a maximum value, then slowly decreased with the increase of speed, while normal attractive force was always reduced. This characteristic matches the requirements of high-speed trains with large braking force and low normal force, which makes it a great option for auxiliary braking mechanism in the high-speed trains.

For the classification and recognition of the working status in the warning and intervention of the fatigue and working status of high speed railway dispatchers, this paper proposed a classification and recognition method of high speed railway dispatchers’ working status based on eye-movement characteristics. Eye-movement data were collected by experimenters in the simulation experiment of the schedule job within the stage plan. The pre-set experimental tasks were used as the objective classification criteria for working status and as an influencing factor for studying the distribution law of the eye-movement characteristic index. Through discriminant analysis, a typical discriminant function was established to determine the prognosis of the dispatcher’s working status, and a discriminant threshold correction method considering misjudgment loss was proposed. Combined with the characteristics of the schedule job, a mechanism for the working status intervention time determination was established. The results show that dispatchers display signs of reduced vigilance in the monitoring tasks, and the discriminant analysis method can effectively identify the dispatcher’s working status with an average accuracy rate of 81.3%. On the basis of correcting the discrimination threshold and considering the misjudgment probability,the determination mechanism of working status intervention time effectively avoids the occurrence of wrong intervention.

高速铁路调度员监控作业的注意力水平识别是全周期注意识别的重要组成部分.针对监控作业交互少、反馈弱以及视觉特征不显著的特点,设计基于信息感知密度的注意诱导实验作为客观评价参照,采集全头脑电并提取了 57个通道的7项频段指标为识别特征.采用Pearson相关系数进行特征初筛,采用Logistic回归-预测变量重要性排序的包裹式方法对特征进行进一步降维并进行注意水平识别.实验结果表明:基于左额叶和双侧枕叶的17个脑电频段特征的多项Logistic回归模型对低注意水平有81％的识别准确率.脑电频段特征对应负责大脑思维功能和视觉加工处理的脑功能区,反映高铁调度员在监控工作中的注意水平变化对应的认知功能变化.

High-temperature superconducting magnets wound by REBCO (rare-earth-barium-copper-oxide) coated conductors are promising candidates for electrodynamic suspension system due to their high current-carrying capability, excellent mechanical tolerance and low cooling cost. Solid nitrogen as coolant to protect HTS magnets can significantly promote their dynamic performance and reduce the use of auxiliary equipment, which reduce the system dimension and weight. In this study, we propose a mechanical-thermal coupling model of solid nitrogen cryostat for electrodynamic suspension system. This model is capable of calculating the temperature distribution during cooling process and the transient behavior for the rewarming process of the solid nitrogen cryostat. The cooling capacity map for the two-stage RDK-415D cryocooler was extended for accuracy. The steady state temperature distribution of cooling process and the thermal evolution of three different rewarming processes, including cryocooler reserved, 5 W losses applied and cryocooler detached, were calculated and verified experimentally, followed by the investigation of the structural stresses and displacement of the solid nitrogen cryostat due to thermal displacement among different components. The developed model can serve as a reference and guide for the design and optimization of solid nitrogen cryostat for electrodynamic suspension system.

Air-cored linear synchronous motor (LSM) consisting of racetrack coils is a core part of electrodynamic suspension (EDS) as it propels train to realize high-speed running. Considering operating conditions, a precise and fast analysis of LSM is essential to investigate and optimize EDS system. An analytical model is proposed to calculate the magnetic field and three-dimensional (3-D) forces of LSM with considering the sectional power supply of the primary and multi-DOF motions of EDS train. Afterwards, the influence of sectional power supply was studied to acquire the ideal feeding position of balancing the stable thrust against the efficiency. The effects of multi-DOF motions on electromagnetic characteristics of LSM were analyzed by the proposed model and finite element model. The obtained results indicate that the lateral displacement of multi-DOF motions should be limited to ±28 mm and this model can simulate realistic operating conditions of superconducting LSM. Furthermore, the analytical model reduces the computation time by 96% with high accuracy compared with 3-D finite element model. Finally, experiments were performed to confirm the proposed model with measured magnetic field and forces.

The introduction of high temperature superconducting (HTS) magnet, which is capable of working at liquid nitrogen temperature, and the use of null-flux coil, make the liquid-helium-free electrodynamic suspension (EDS) train available. In essence, the electromagnetic force of a superconducting EDS train is generated by electromagnetic interaction between the onboard superconducting magnets and the ground null-flux coils. In order to obtain an efficient HTS EDS train, the design optimization of the HTS magnets and null-flux coils is indispensable. This study is devoted to this aspect. We first establish an improved load-line method for efficiently estimating the critical current of HTS magnets and an improved semianalytical model to accurately calculate the induced currents and electromagnetic forces in the EDS train. Based on above two improvements, the onboard HTS magnets and corresponding null-flux coils are then designed and optimized to enhance the overall performances of the HTS EDS train. At final, according to the optimized results, the HTS magnets and null-flux coils were manufactured and measured, followed by the performance analyses of the obtained HTS EDS train. The results have shown that the electromagnetic performances of the designed HTS EDS train are excellent, demonstrating the effectiveness of the optimization methodology.

High-temperature superconducting (HTS) magnets have been investigated widely for their higher upper critical magnetic field, larger engineering critical current density and simpler cryogenic system compared with low-temperature superconducting magnets. However, in order to keep the permanent-current mode of the HTS magnets, the external power supply is usually employed to charge the magnet via copper current leads, which is a considerable heat source to the cooling system. Thus, in order to avoid the heat disturbance brought by the current leads, a new ‘through-wall’ dynamo-type HTS flux pump using a pair of magnetic couplers is proposed, realizing the truly wireless power transfer, and exploring its possible application for the conduction cooled system. Based on the proposed structure, the heat conduction, which was calculated to be about 7.75 W, and heat convection could be minimized. In addition, to further improve the charging performance of the dynamo-type flux pump, a ferromagnetic (FM) slice was added at different positions of the system. The effect of the FM slice on charging performance is studied numerically and experimentally. According to the results of simulations and experiments, adding an FM slice under the HTS stator improves the saturated current and the charging speed of the dynamo-type flux pump by 20%–30%.