Digital twin-based approach to improve resilience of slab tracks in a warming climate

We are in a warming climate. Predictions indicate that the world is on track for a warming of 1.5 ℃ in the most optimistic situation. This is very bad news for railway slab tracks utilized all around the world, since the intensified extreme heat waves in a warming climate can induce severe slab track failure and cause lethal outcomes like train derailments. Furthermore, the rise in life-cycle carbon emissions due to increased track maintenance workload and material consumption worldwide in a warming climate is estimated to be around 60 million tonnes, which can be used to manufacture about 120 million cars.However, we are not fully prepared to this challenge because of a lack of useful tools to predict track performance and arrange maintenance activities in a warming climate. Thus, this TwinsTrack project aims to contribute to a better understanding of slab tracks' mechanical behavior in a warming climate and practical maintenance strategies to improve their climate adaptability.In this project, the applicant will (i) develop integrated digital twin models of slab tracks for performance prediction in a warming climate; (ii) design various climate-adaptive maintenance measures for slab tracks; (iii) develop a multi-objective optimization approach to select optimal types and design details of maintenance measures to not only maximize the safety of slab tracks, but also ensure their best environmental and economic performance.The outcomes of this TwinsTrack project will not only prepare engineers for the climate crisis but also inform policymakers of the urgent need for action. This will not only reduce the risk of structural-failure-induced accidents but also decrease carbon emissions and maintenance costs of slab tracks by an estimated 20% to 30% in a warming climate.