{"title":"Ontology-driven knowledge graph for decision-making in resilience enhancement of underground structures: Framework and application","authors":"Bin-Lin Gan , Dong-Mei Zhang , Zhong-Kai Huang , Fei-Yu Zheng , Rui Zhu , Wei Zhang","doi":"10.1016/j.tust.2025.106739","DOIUrl":null,"url":null,"abstract":"<div><div>Enhancing the resilience of underground structures for their operation safety amidst complex disasters has become a critical societal issue. However, resilience enhancement decision-making for underground structures mainly depends on practical subjective experience currently, with insufficient integration of ontology knowledge and a clear gap in the availability of efficient and intelligent decision-making models. To address this, this paper presents a novel method for constructing a knowledge graph (KG) based on ontology to enhance the resilience of underground structures. A comprehensive resilience knowledge system considering 10 categories for underground structures is established. This system is built upon resilience quantification analysis, fault tree modeling of resilience insufficiency, and event tree analysis of disaster chain processes. A systematic approach for KG construction, integrating top-down and bottom-up strategies, is then proposed. Additionally, a multi-layered framework of KG for underground structure resilience is developed, comprising application, rule, pattern, and data layers. Resilience-related knowledge is extracted using expert empirical methods, and the data layer is constructed through semantic networks and knowledge fusion. The visualization and field application of the KG are implemented using the Neo4j graph database. Findings of this study substantially advance a methodological foundation for intelligent decision-making in resilience enhancement and safeguarding of underground infrastructures under complex disasters.</div></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":"163 ","pages":"Article 106739"},"PeriodicalIF":6.7000,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tunnelling and Underground Space Technology","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0886779825003773","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Enhancing the resilience of underground structures for their operation safety amidst complex disasters has become a critical societal issue. However, resilience enhancement decision-making for underground structures mainly depends on practical subjective experience currently, with insufficient integration of ontology knowledge and a clear gap in the availability of efficient and intelligent decision-making models. To address this, this paper presents a novel method for constructing a knowledge graph (KG) based on ontology to enhance the resilience of underground structures. A comprehensive resilience knowledge system considering 10 categories for underground structures is established. This system is built upon resilience quantification analysis, fault tree modeling of resilience insufficiency, and event tree analysis of disaster chain processes. A systematic approach for KG construction, integrating top-down and bottom-up strategies, is then proposed. Additionally, a multi-layered framework of KG for underground structure resilience is developed, comprising application, rule, pattern, and data layers. Resilience-related knowledge is extracted using expert empirical methods, and the data layer is constructed through semantic networks and knowledge fusion. The visualization and field application of the KG are implemented using the Neo4j graph database. Findings of this study substantially advance a methodological foundation for intelligent decision-making in resilience enhancement and safeguarding of underground infrastructures under complex disasters.
期刊介绍:
Tunnelling and Underground Space Technology is an international journal which publishes authoritative articles encompassing the development of innovative uses of underground space and the results of high quality research into improved, more cost-effective techniques for the planning, geo-investigation, design, construction, operation and maintenance of underground and earth-sheltered structures. The journal provides an effective vehicle for the improved worldwide exchange of information on developments in underground technology - and the experience gained from its use - and is strongly committed to publishing papers on the interdisciplinary aspects of creating, planning, and regulating underground space.