This study takes the Harbin Company Street Railway Industrial Heritage Area as a case study to explore the application of parametric design in the renovation of small- and medium-sized industrial buildings. Through surveying and collecting data such as rail spacing and truss dimensions, a site information database is established. Based on the Grasshopper platform, a parametric modeling process is developed: using the 1520 mm wide gauge as the basic module, roof surfaces are generated through dynamic trajectory algorithms, followed by morphological adjustment and structural optimization according to functional requirements. The results show that parametric methods can effectively preserve the characteristic elements of industrial heritage, although complex nodes still require supplementation through traditional modeling approaches. This study provides a practical reference for the digital transformation and adaptive reuse of small- and medium-sized railway industrial heritage.

DigitalTransformation of Railway Heritage via Dynamic Trajectory Algorithm: A Case Study of Harbin Company Street Market Parametric Design / Liu, Ying; Yang, Xinyue; Liu, Fangfang; Liang, Xiaoxu. - (2025), pp. 328-332. ( 2025 National Symposium on Teaching and Research in Architectural Digital Technology, China Wuhan (CHI) December 2025).

DigitalTransformation of Railway Heritage via Dynamic Trajectory Algorithm: A Case Study of Harbin Company Street Market Parametric Design

Liang Xiaoxu
2025

Abstract

This study takes the Harbin Company Street Railway Industrial Heritage Area as a case study to explore the application of parametric design in the renovation of small- and medium-sized industrial buildings. Through surveying and collecting data such as rail spacing and truss dimensions, a site information database is established. Based on the Grasshopper platform, a parametric modeling process is developed: using the 1520 mm wide gauge as the basic module, roof surfaces are generated through dynamic trajectory algorithms, followed by morphological adjustment and structural optimization according to functional requirements. The results show that parametric methods can effectively preserve the characteristic elements of industrial heritage, although complex nodes still require supplementation through traditional modeling approaches. This study provides a practical reference for the digital transformation and adaptive reuse of small- and medium-sized railway industrial heritage.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3009869