BIM (building information modeling) plays a pivotal role in the construction industry. BIM technology tailored for pipelines offers in-depth semantic information and spatial data, bolstering the utility and implementation of digital twin-associated technologies in both architecture and urban planning. This paper introduces a rendering optimization algorithm rooted in the BSP Tree (Binary Space Partitioning Tree). The algorithm is used to address the challenges of slow loading and poor rendering quality of pipeline BIM models when displayed on the web, which stem from large amounts of model data and complex geometric configurations. Initially, the algorithm delves into the geometric distribution traits of the pipeline BIM model from multiple perspectives, pinpointing the spatial division dimension. Subsequently, it employs an adaptive step size technique for spatial segmentation, harmonizing it with real-world application contexts. Concurrently, any superfluous data that emerge are refined to uphold the structural wholeness of the BIM model. This algorithm is adept at systematically arranging and overseeing the BIM model data. Trial outcomes reveal that the AKDT (Adaptive K-Dimensional Tree) algorithm significantly trims the browser’s initial rendering duration while maintaining the model’s accuracy and semantic uniformity. Moreover, it excels in areas such as rendering frame rate, user interaction responsiveness, and data transmission duration. In essence, the algorithm stands out for its efficiency and precision in rendering pipeline BIM models on web platforms, achieving the desired optimization results.