Soufiane, Kenza2021-11-042021-11-042021https://udspace.udel.edu/handle/19716/29344Railroad cross-ties are a crucial element of the track structure as they contribute to the distribution of loads through the track. Determining the life of cross-ties, and particularly timber cross-ties is of importance in both design and maintenance decisions and activities. This includes mathematical modelling of the average crosstie life and predicting how different factors affect its lifespan. It also includes the use of automated tie inspections to provide information on ties condition, which in turn allows for the determination of the ties life and the making of decisions on tie maintenance and replacement operations. ☐ This thesis addresses the issue of the use of automated tie condition inspection data to predict and model tie life based on support condition, as defined by the condition of adjacent cross-ties. The thesis presents several analysis approaches, all e based on the use of tie condition data from two different inspections performed over a span of 3 years. The dataset used consisted of tie inspection data from approximately 100,000 crossties), from multiple inspections carried out on the same track during the period 2016 to 2019. ☐ The approach taken is a comprehensive data analysis approach starting with data preprocessing and exploratory data analysis. A macro-analysis was then performed in order to determine the mile-by-mile behavior of ties, followed by a microanalysis that allowed for the study of each individual tie and its degradation behavior. Noting that tie loading was dependent on the condition of adjacent ties on both sides of a given tie, ties were grouped based on their adjacent tie condition and their corresponding loss of adjacent tie support as defined by the Beam on Elastic Foundation theory. In the initial analysis, a simplified formula was developed that described the life reduction as a function of this loss of adjacent tie support. ☐ The second part of the thesis consisted of a more detailed investigation of the tie condition changes over the three years study period. In this analysis a piecewise reconstruction of the average tie life was performed and used to compare the tie degradations rates with respect to loss of adjacent tie support. As such, regression functions were developed for the different support groups, based on the distributions of the different tie condition score transitions from 2016 to 2019 . These functions were then used recursively to predict the tie score change over time. Then, Dijkstra’s algorithm was applied to model each group’s average tie life based on adjacency matrices developed using the tie score transitions. In a third analysis approach, Markov chains were utilized for the determination of the probability of tie failure as a function of loss of support. ☐ The results showed different average tie lives for different support conditions confirming the fact that loss of support contributes significantly to premature tie failure with the higher the loss of support, the shorter the average tie life. Life reduction formulas were then generated based on the three analysis approaches.Adjacent support conditionPremature crosstie failureLoadBridgesThesis12826309042021-08-11en