Dr. Allan M Zarembski, Kenza Soufiane (Graduate Student), University of Delaware
Railroad cross-ties (sleepers) are a key component of the track structure and play an important role in the distribution of train loading through the track. Automated cross-tie inspections, which are becoming increasingly significant in the inspection of the cross-ties, are important in planning and optimizing tie replacement. Furthermore, the data these inspections provide on tie condition enable maintenance engineers to better understand the behavior of the ties and their associated life. By using inspection data taken from the same track in different years, it is possible to develop improved tie life models that take into account local conditions. Using these different tie conditions, and the corresponding different periods in the lifespan of a tie, this activity will determine average tie life using mathematical modeling techniques, such as piecewise reconstruction. It will also develop a model that shows how the probability of tie failure grows over time and changes depending on the loss of adjacent support.
The dataset to be used consists of tie inspection data for inspections carried out on the same track during the period 2016 to 2019. Ties are grouped based on their adjacent tie condition. Data analytic tools will be used to predict and model tie life based on support condition, as defined by the condition of adjacent cross-ties. The analysis approaches will be based on the use of tie condition data from two different inspections performed over a span of years.
Implementation of Research Outcomes
Impacts/Benefits of Implementation