Knowledge Modeling and Reuse of Concrete Structure Strengthening Solutions for Existing Buildings

Implementing knowledge modelling tools of concrete structure strengthening solutions for existing buildings addresses the urgent needs of urban renewal efforts. This paper thoroughly investigates the application of Natural Language Processing (NLP), and knowledge graphs for organizing and managing complex information related to building strengthening strategies. By developing an ontology model for solutions and supplementing it with methods for generating word vectors and annotating data, this study constructed a comprehensive framework for the management of strengthening solution knowledge. A case study on the partial structural strengthening validated the applicability of the proposed model in facilitating recommendations for similar cases and supporting solution design. This research under-scores the transformative impact of digital technologies and knowledge modelling on the efficiency and quality of urban renewal projects, contributing to the advancement of smart cities. The findings promoted the integration of informatized and intelligent methods in the strategic planning and execution of concrete structure strengthening projects.