Date of Award

Fall 2021

Document Type

Open Access Thesis

Department

Civil and Environmental Engineering

First Advisor

Dimitris Rizos

Abstract

Modern railway tracks worldwide standardize the use of Continuous Welded Rail (CWR) due to its ability to prevent disadvantages associated with rail joints in a track. CWR is laid when the rail is free of thermal stresses, also known as Rail Neutral Temperature (RNT). RNT is controlled in the CWR installation procedure; however, over time, the temperatures deviate from the RNT. The deviation causes significant thermal stresses introduced in the longitudinal direction of the rail, leading to potential failures such as pull-apart and buckling, causing track integrity and safety of train operation. The most significant potential failure is track buckling due to the decrease in RNT over time; therefore, it is important to know the state of stress in the rail at different temperatures and the changes in RNT to maintain the track and prevent track buckling beforehand.

The proposed non-contacting method for this work utilizes stereo vision and 3D Digital Image Correlation (StereoDIC) technology. It is a method that can acquire full-field deformation measurements. The measurements data then can be processed to obtain an RNT estimate and longitudinal stress calculation. Compared to the other existing methods, this method reduces the disadvantages such as system complexity, practicality, reliability, simplicity, and instrumentation demands. Using the novel concept developed from Knopf’s work, this paper furthers provides a preliminary guide for the method’s implementation on a full-scale prototype system in the laboratory followed by initial stages for field testing.

Rights

© 2021, Ellie Yi-Hsien Chao

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