To enhance the design rationality and material utilisation of heavy-haul railway sleepers, this study takes the widely used type IIIa prestressed concrete sleeper from the Shuohuang railway as a case study. Based on the bi-directional evolutionary structural optimisation (BESO) method, topological solutions are first generated and then explicitly interpreted as strut-and-tie models, leading to two optimised reinforcement schemes (model II and model III). Using Abaqus software, a comparative non-linear finite-element analysis of the mechanical performance between the optimised schemes and the conventional design (model I) was conducted. The results demonstrate that by bending up prestressed tendons, the optimised schemes achieve a more uniform stress distribution in the reinforcement, significantly improve the ultimate bearing capacity (with increases of 13.39% for model II and 24.89% for model III) and exhibit superior crack resistance compared to the conventional design. Moreover, the proposed designs enhance structural efficiency without additional material use, achieving an implicit steel saving of 12–18% and a corresponding carbon dioxide emission reduction of 0.044–0.066 kg CO2-eq per sleeper. This method provides an innovative and intelligent design approach for sleepers, which aligns well with the principles of low carbon dioxide and energy-saving construction, offering practical value for sustainable railway infrastructure development.
Zhang et al. (Wed,) studied this question.