Abstract: To achieve intelligent generation and dynamic optimization of the process parameters in the construction of tunnels with small cross-sections, aiming to enhance construction safety and efficiency, an intelligent excavation process planning method based on knowledge graphs and graph model inference is proposed. This method addresses the challenges of generalized and differentiated management in configuring the process parameters for cantilever excavator in the construction of tunnels with small cross-sections. Firstly, a structured excavation knowledge graph is designed considering the excavator components, construction environment, and quality control elements. Graph convolutional networks are introduced to achieve semantic fusion and entity alignment of heterogeneous knowledge. Secondly, a scheme deduction mechanism based on rule constraints and similarity computation is proposed. By integrating historical databases and construction boundary conditions, a parameter-adaptive process planning method is established. Subsequently, the excavation process is simulated and a digital twin system employing unreal engine is developed. By integrating the DeepSeek-R1 semantic reasoning model, the system enables structured recognition of construction conditions, process-scheme Q&A, and dynamic optimization. The proposed system was applied and validated in the construction of a water-conveyance tunnel with a small cross-section in the Tingzikou irrigation construction project in Sichuan, China, yielding a tunnel crown settlement within 5 mm and an overbreak/underbreak within 5 cm. Compared to traditional empirical methods, the proposed approach demonstrates remarkable improvements in the intelligent construction-process planning and adaptive optimization of parameters for the excavation of tunnels with small cross-sections, providing novel insights and a feasible technical pathway for the intelligent excavation of such tunnels.

Key words: small cross-section tunnel, cantilever excavation and construction, knowledge graph, process planning, intelligent Q&, A, scenario simulation