Tunnel construction using TBM involves various factors that increase risks to the structure, including workers, machinery, operation, structure and surrounding environment. These factors interact in complex ways, making risk management rather complicated and challenging. To achieve a better risk management, state-of-the-art technologies such as knowledge graph (KG) can help manage construction risk by storing, managing and mining risk concepts and construction entities. In the paper, a risk management knowledge graph was created for the TBM hard rock tunnel constructed in West China using Neo4j graph database. Work breakdown tree (WBS) and risk breakdown tree (RBS) were created to subdivide the complex TBM tunnelling process and risk sources. WBS and RBS entities were then integrated into the knowledge graph, making the attributes and relations of various entities clear to engineers. The case study demonstrated that knowledge graph is effective, reliable and advanced in TBM hard rock tunnelling risk management.
Nuclear energy, a prominent source of clean energy, finds widespread application in power production, medical, and industrial sectors. Currently, nuclear power plants generate approximately 10% of the world's electricity, highlighting its significance. Notably, China has undertaken commendable initiatives in developing nuclear energy for power generation, nuclear medicine technology and industrial nuclear radiation processing.
China's progress in nuclear energy industry has brought the challenge of disposing nuclear waste to the forefront. Beishan underground laboratory project in Gansu represents China's pioneering effort towards addressing this problem. As the country's first underground field research and development platform dedicated to high-level waste disposal technology, the project is slated to become the world's largest, most functional, and inclusive underground laboratory upon completion. Its state-of-the-art facilities will provide a crucial testing platform and foundation for tackling the global challenge of geological disposal of high-level waste.
The laboratory is situated in wild Gobi, characterized by geological conditions dominated by slightly weathered granite with a quartz content of 25% to 30%. The platform is situated at a significant depth of 560 meters underground, representing a challenging hard rock project. Given the local construction site's unique features and associated needs, the structural plan comprises a spiral rampway-multi-shaft-two-level flat tunnel, as depicted in Figure 1.
