Chapter 14
PSD Random Vibration Strength
and Fatigue Analysis of a CNG Tube
Trailer
Zhiqian Liu, Caifu Qian, and Zuzhi Chen
Abstract Tube trailer is a kind of gas transportation equipment, which is widely
used in transportation of various industrial gases including compressed natural gas
(CNG). However, due to its particularity of carrying high-pressure gas and operating
and parking on urban roads, the requirements for its safety performance are especially
concerned. In this paper, finite element random vibration analysis on a tube trailer
was performed according to the standard GB/T 4857.23-2012, random vibration
analysis under the “ISTA 3A vehicle power spectral density (PSD) curve”. The first
9 orders natural frequencies are obtained from modal analysis and it is found that
only the first natural frequency is covered in the speed limitation of 80 km/h for the
tube trailer. The maximum deformations in the first 3 orders all occur in the middle
of the frame of the tube trailer; Stress analysis under random vibration excited by
the specified PSD found that the maximum stresses corresponding the probability
values at 1σ, 2σ and 3σ are all less than the yield stress of the material, meaning
that the structure meets the strength requirements. Within the fatigue life under PSD
random vibration, the trailer’s fatigue damage cycle ratio D is less than 1, meaning
the structure meets the fatigue design requirements.
Keywords Tube trailer · Finite element analysis · Random vibration analysis ·
PSD
14.1 Introduction
Compared with pipeline transportation, tube trailers have the advantages of lower
investment and higher suitable for short and medium distance transportation.
Z. Liu · C. Qian (B)
Beijing University of Chemical Technology, Beijing 100029, China
e-mail: qiancf@mail.buct.edu.cn
Z. Chen
China Special Equipment Inspection and Research Institute, Beijing 100029, China
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
J. Xu and K. M. Pandey (eds.), Mechanical Engineering and Materials,
Mechanisms and Machine Science 100,
https://doi.org/10.1007/978-3-030-68303-0_14
173
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