Current research papers use simulated load spectrums to assess bogie frames’ fatigue life but seldom consider traction and braking loads. Traction and braking loads play important roles in predicting fatigue life in high-speed and heavy haul operational scenarios. Hence, there is a research gap in terms of the consideration of longitudinal load spectrums while assessing bogie frames’ fatigue life. This paper presents research about this topic. A virtual prototype technique available in literature has been extended for this purpose; it uses multibody dynamics and finite element techniques to simulate the behaviour of bogie frames under real operational service loads. As a result, the special simulation methodology has been developed in this work and it includes the unique integration of simulation approaches that includes train dynamics, locomotive dynamics with the consideration of a traction control algorithm and the adopted fatigue life calculation method. This paper gives numerical examples of a rigid-flexible coupled dynamic railway vehicle model subjected to longitudinal forces. Road Environment Percent Occurrence Spectrum (REPOS) load spectrums of the bogie frame were developed from a whole-trip train simulation on a real route. The spectrums are then used to predict locomotive the bogie frame’s fatigue life. The results of the bogie frame fatigue life evaluation performed in this paper show that fatigue lives at the roots of traction rod seats under longitudinal load spectrums are shorter than their fatigue life under vertical load spectrums.
FPSO is widely used during the deep-sea oil and gas exploration operations, for which it is an effective way to keep their position by means of positioning mooring (PM) technology to ensure the long-term reliability of operations, even in extreme seas. Here, a kind of dynamic positioning (DP) controller in terms of structural reliability is presented for the single-point turret-moored FPSOs. Firstly, the mathematical model of the moored FPSO in terms of kinematics and dynamics is established. Secondly, the catenary method is applied to analyze the mooring line dynamics, and mathematical model of one single mooring line is set up based on the catenary equation. Thereafter, mathematical model for the whole turret mooring system is established. Thirdly, a structural reliability index is defined to evaluate the breaking strength of each mooring line. At the same time, control constraints are also considered to design a state feedback controller using the backstepping technique. Finally, a series of simulation tests are carried out for a certain turret-moored FPSO with eight mooring lines. It is shown in the simulation results that the moored FPSO can keep its position well in extreme seas. Besides, the FPSO mooring line tension is reduced effectively to ensure mooring lines safety to a large extent in harsh sea environment.
The LACMTA HR4000 heavy rail vehicle was designed to meet the ASME RT-2 Safety Standard for Structural Requirements for Heavy Rail Transit Vehicles. The crash energy management (CEM) structures designed for this vehicle also provide unique performance characteristics through use of a staged combination of CEM technologies. The resulting design, using easily replaceable components, provides reduced repair costs for lower speed collisions, minimizes the number of cars damaged during a collision, while exceeding the RT-2 standard for safety to the operator. None of the CEM technologies used are novel, but their integrated design provides a unique performance in heavy rail vehicle design.
This paper provides an overview of the CEM design development. First, a general description of the CEM system function is provided, including the various CEM technologies used and how they interact during a collision. Then the 1-dimensional and 3-dimensional nonlinear dynamic models developed for optimizing the design are discussed. The CEM test program performed to demonstrate the system function and validate the modeling is described. Finally, the performance of the CEM system in train-to-train collision analyses is presented. Underframe testing was conducted for validation of the simulations.
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