Simulation of Railway Drainage Asset Service Condition Degradation in the UK Using a Markov Chain–Based Approach

Abstract

UK railway drainage systems are facing increasing challenges due to poor completeness of the asset inventory, long asset life cycles, more intense use of the UK railway system, and a changing climate. It is therefore important for drainage managers to acquire a better understanding of the current and future condition of the drainage assets for which they are responsible. This study presents a Markov model for simulating the potential future service condition of various classes of UK railway drainage assets based on observed historical changes in asset condition. Linear regression analysis was performed on distinct asset groups and the influence of the characteristics of asset construction material, size, shape, and location on the rate of the degradation process was quantified. These results were incorporated with the continuous time Markov chain model to improve the accuracy of the degradation rate prediction for several drainage asset classes. The model is illustrated on a case study of the Network Rail drainage assets showing the minimum number of samples required to make a reliable estimation of the service condition degradation process.