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Holloman High Speed Test Track Maglev Program UpdateThe Holloman High Speed Test Track Magnetically Levitated (MAGLEV) Sled Six Degree-of-Freedom ModelHolloman High Speed Test Track Maglev Program Update

U.S. Air Force T&E Days 2010, 2010
The Holloman High Speed Test Track is developing a Maglev capability that allows a test sled to levitate using magnetic forces to restrain the sled rather than an extremely stiff and violent metal-on-metal restraint system. The current sled allows for 6 HVAR motors to be used and to date has produced speeds of 420 mph.
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Light Weight Design for High Speed and MAGLEV Trains

SAE Technical Paper Series, 2001
<div class="htmlview paragraph">High-speed trains today operate at speeds between 200 and 320 km/h and MAGLEV trains between 400 and 500 km/h, whereas world record stands at 515 km/h for trains on wheels and 552 km/h for MAGLEV trains. This speed level can only be reached economically when light weight design is systematically used. Low axle load
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DISPOS - A New HCI for High Speed Maglev Train Supervision

IFAC Proceedings Volumes, 1995
Abstract The challenge of complete redesign of working areas for dispatchers in high speed maglev train supervision can offer advanced solutions in human centered design, man process communication, and cooperative interaction. Hence, sophisticated computer based display designs for visualisation of high speed train operation that are based on a ...
Jens-Olaf Müller, Eckehard Schnieder
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A High-Speed Running Test Platform for High-Temperature Superconducting Maglev

IEEE Transactions on Applied Superconductivity, 2022
Zigang Deng, Li Wang, Xucheng Zhou
exaly  

Influence of high-speed maglev train speed on tunnel aerodynamic effects

Building and Environment, 2022
Shuai Han, Xiao-Hui Xiong, Peng Ji
exaly  

Pennsylvania High-Speed Maglev Project

2006
Philip Rackliffe, Paul Thompson
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Novel method to detect the speed and position of the HTS Maglev train by using the TMR sensor and the magnet arrays

Measurement: Journal of the International Measurement Confederation, 2023
Siqi Jiang, Zigang Deng, Le Liang
exaly  

Track Defect Detection for High-Speed Maglev Trains via Deep Learning

IEEE Transactions on Instrumentation and Measurement, 2022
Yongxiang He, Jun Wu, Yaojia Zheng
exaly  

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