Tunnel Rapid AI Classification (TRaiC): An Open-Source Code for 360° Tunnel Face Mapping, Discontinuity Analysis, and RAG-LLM Powered Geo-Engineering Reporting

Accurate and efficient rock mass characterization is critical for geotechnical engineering. To achieve this, the digital rock mass characterization is rapidly growing. traditional tunnel face mapping faces significant challenges, including time-consuming manual processes, subjective geological interpretations, and safety risks for personnel in hazardous underground environments. Recent advances in digital technologies and AI offer opportunities for automation, but existing digital solutions suffer from time-consuming 3D scanning, computationally expensive post-processing, and limited flexibility of system integration. This paper introduces a face mapping solution named Tunnel Rapid AI Classification (TRaiC), which is an open-source MATLAB-based platform that integrates 360° panoramic (single-shot) photography, AI-powered discontinuity detection, 3D textured digital twin generation, rock mass discontinuity characterization, and Retrieval-Augmented Generation with Large Language Models (RAG-LLM) for automated geological interpretation and standardized reporting. TRaiC features a modular eight-stage workflow encompassing a simplified 3D geometric modeling, trace segmentation, 3D joint network analysis, and rock mass classification using RMR, with outputs structured for Geo-BIM integration. Initial performance evaluations demonstrate significant reductions in tunnel data processing and geotechnical expert assessments time. TRaiC produces a lightweight digital twin with a high textural fidelity but simplified geometry, ensuring computational efficiency and superior suitability for Geo-BIM integration. Its open-source nature brings about transparency and reproducibility of research and it constitutes the stepping stone for future research in the field of AI-assisted geotechnical engineering. Significant efforts have been made to name and organize scripts to bring maximum readability and flexibility to understand the functionality of functions, and a graphical user interface is designed to make it easy for the application and make it suitable for beginners, advanced, and experienced users to solve problems or develop it for research.