Multi-defect risk assessment in high-speed rail subgrade infrastructure in China

Abstract This study addresses the escalating risk of high-speed railway (HSR) infrastructure in China, amplified by climate warming, increased rainfall, frequent extreme weather, and geohazard events. Leveraging a georeferenced dataset of recent HSR defects obtained through an extensive literature review, we employ machine learning techniques for a quantitative multi-defect risk assessment. Climatic, geomorphological, geohydrological, and anthropogenic variables influencing HSR subgrade safety are identified and ranked. Climatic factors significantly impact frost damage and mud pumping, while geomorphological variables exhibit greater influence on settlement and uplift deformation defects. Notably, frost damage is prevalent in the northeast and northwest, mud pumping along the southeast coast, and settlement and uplift deformation in the northwest and central areas. The generated comprehensive risk map underscores high-risk zones, particularly the Menyuan Hui Autonomous and Minle County sections of the Lanzhou-Urumqi HSR, emphasizing the need for focused attention and preventive actions to mitigate potential losses and ensure operational continuity.