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In this study, the dynamic characteristics of three different bogie configurations, a conventional Steel bogie (SB), a composite bogie without primary suspension (CB1), and a composite bogie with primary suspensions of conical rubber type (CB2), were compared. The CB1 shows the highest critical speed while the CB2 shows the lowest. The SB configuration showed the highest ride index value while the CB2 showed the lowest. Both of the composite configurations showed better ride comfort index than that of the steel configuration. The trend of the derailment index was opposite to that of the critical speed. In the derailment index measuring test, the CB1 bogie configuration had a 12.3 % higher derailment index than that of the SB. These results show good agreement in overall trends with the simulation results. [ABSTRACT FROM AUTHOR]

Abstract: A fiber-optic distributed sensor system is configured to measure the longitudinal strain distribution of a rail in real time. The system is based on the Brillouin correlation domain analysis (BOCDA), in which the variation of local Brillouin frequency (ν B ) is measured that linearly depends on the strain applied to the optical fiber. In the test measurement, the longitudinal strain distribution along a 2.8m rail is measured under different loading conditions with a spatial resolution of 3.8cm and an accuracy of ±15με. [Copyright &y& Elsevier]

In this study, the crush behaviors of square sandwich composite tubes with woven fabric carbon/epoxy skins and aluminum honeycomb cores with the different honeycomb cell sizes and tube sizes were evaluated. For the evaluation, four different kinds of tubes were fabricated and crushed under quasi-static and dynamic impact loads. The impact tests were carried out using heavy wagons. From the test results, the crushing mode under the dynamic load was changed into more stable collapse than the corresponding static tests. Additionally, the increased bond strength between the honeycomb core and the composite face leaded to a higher energy absorption capability. [ABSTRACT FROM AUTHOR]

Abstract: In this study, the failure modes and energy absorption capabilities of different kinds of circular tubes made of carbon, Kevlar, and carbon–Kevlar hybrid fibers composites with epoxy resin have been evaluated. The relationship between the crushing parameters (specific energy absorption, maximum peak load, mean crushing load) and the material properties for different fibers and patterns was also investigated. The fabric carbon/epoxy tubes had the best energy absorption capability (specific energy absorption of 81.7%). In contrast, the tubes made of Kevlar showed the worst energy absorption capability. Based on the linear regression analysis results, the crushing parameters generally showed good correlation with the compressive strength and shear modulus. In particular, the specific energy absorption of the tubes with the brittle fracture mode revealed the strongest correlation with the compressive strength (R-square value=0.90). [Copyright &y& Elsevier]

When diagnosing the condition of a structure, it is necessary to measure the widths of any existing cracks in the structure. To ensure safety when relying on images of cracks, the selected imaging parameters and processing technology must be well understood. In this study, the effects of the ground sample distance and threshold values on the crack width measurement error are analyzed from a theoretical perspective. Here, the main source of such errors is assumed to be due to the mixed pixel phenomena in the left and right boundary pixels. Thus, a mathematical model is proposed in which the intensity changes in these pixels are computed via an equation. In addition, the relationship between the error and error probability distribution is represented with an equation based on the threshold values and mean error. Upon analysis, it was found that the threshold value that minimizes the error is at the mid-point between the background and foreground, and the probabilistic nature of the error indicates that it is theoretically possible to predict both the error and its probability distribution. The proposed model was validated using artificial images. [ABSTRACT FROM AUTHOR]