Browse Topic: Management and Organizations

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As high-speed train technology advances, the demands on braking system performance have intensified. Known for their efficiency, reliability, and eco-friendliness, Linear Eddy Current Brakes (LECB) have become a focal point in the research and development of high-speed train braking systems. This paper presents an innovative Orthogonal Excitation Eddy Current Brake (OEECB), which enhances the braking force without modifying the overall dimensions of the conventional LECB. By adding a set of longitudinal excitation coils parallel to the rail surface, the OEECB creates an orthogonal excitation structure that augments the braking force. Initially, this paper outlines the design concept of the OEECB and then analyzes its working principle based on electromagnetic field theory. Subsequently, a finite element solver is employed to numerically model the electromagnetic characteristics of the OEECB. Finally, by comparing the performance differences between the conventional LECB and OEECB, the
Huang, LiuwenZuo, JianyongZhang, Yu
The magnetic field modeling methodology for ships based on magnetic dipole arrays demonstrates heightened sensitivity to input data. When addressing overdetermined systems characterized by numerous variables and constrained measurement points, the coefficient matrix frequently develops pathological ill-conditioning, leading to solution divergence and compromised result accuracy. This research reformulates the ship magnetic field inversion challenge as a non-convex quadratic programming problem, employing the Successive Convex Approximation (SCA) algorithm as the computational solver. Rigorous comparative validation was performed against conventional stepwise regression algorithms and experimental datasets acquired from scaled ship model measurements. Results substantiate that while the modeling precision of the SCA algorithm remains comparable to that achieved by stepwise regression methods, SCA exhibits demonstrably superior solution stability. This enhanced robustness positions SCA
Chen, HaoPan, Xun
This paper uses a structured evaluation framework to study the ergonomics of electric pilot seats in modern civil aircraft. We have established a multi-level indicator system to examine the adjustability, pressure distribution, dynamic response and, fatigue relief effect of the seat. All experimental data were obtained from a full-scale cockpit simulator environment, where a ground-based mock-up and motion-free simulated cockpit were used to replicate real operational posture, control-reach conditions, and long-duration mission loads. This framework combines experimental measurement and fuzzy evaluation techniques to quantify the quality of human-computer interaction. Test results show that compared with ordinary seats, the prototype seat has a wider adjustment range, a more uniform pressure distribution, and a smoother dynamic response. It is particularly worth mentioning that it can delay the emergence of fatigue during long-term operation, which proves the advantages of the electric
Tian, YananPi, Zhengyang
The vehicles often accompanied by a huge impact in the collision process, high-quality and high-strength car-seats can better protect the safety of passengers. However, in the call for vehicle energy saving and emission reduction, the lightweight design of car-seats is imminent. Therefore, it is necessary to achieve lightweight seat weight while ensuring vehicle safety. Based on the dynamic condition of vehicle collision, this paper takes the rear seat of a certain model as the research object, takes multiple responses of the seat skeleton system as the target, establishes a multi-objective optimization model of the seat skeleton, determines the optimization result with the greatest comprehensive satisfaction, verifies the optimization result of the seat skeleton. The correctness and feasibility of the design method are proved.
Shao, YoulinNi, WeiyuChen, DaojiongCheng, Zhiqing
The collection of road high-frequency data often involves inputs from multiple sensors, such as stress and strain, and sampling of these data features a high sampling rate of up to 2,000 Hz. High-frequency sampling enables capturing of the internal stress and strain of the pavements when vehicles are passing and facilitates the analysis of the pavement structure and prediction of its long-term service performance. However, while the sensors are continuously collecting data, the time the vehicles pass is discrete and unpredictable, resulting in a large number of low information density or irrelevant data. Even when the massive high-frequency data are collected, challenges remain in data transmission, storage, and analysis—the challenges are attributable not only to the massive quantity and complexity of data from multiple sensors, but also to the inconsistent data formats, misaligned timestamps, and multi-sensor data fusion difficulties. In response to the challenges specified above, a
Gang, JianZhang, YueChen, YinghaoZheng, XiaoyanWang, TaojieLiu, YilinGuan, WeiWu, Jiangfeng
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