Research And Application Of Digital Twin Optimization Strategy For Architectural Design And Building Operation

Digital twinning is the mapping of digital to reality.The optimization of architectural design,the reduction of operating energy consumption,and the realization of carbon reduction goals are driven by digitalization,building digitalization has become a hot research direction in recent years.The complexity in building information makes data collection,management,and utilization difficult,making it difficult for building participants to form effective information transmission among each other,hindering the automatic interaction between the digital twin and the real world,making it challenging to realize data-driven energy conservation and carbon reduction in buildings.Building Information Modeling(BIM)is a medium for building digital twins,which can run through all stages of a building life cycle,from concept,design,and construction to operation and maintenance and final demolition.Semantic web technology plays a vital role in the management and analysis of information.Utilizing the Semantic Web and BIM is an effective method for optimizing data collection and analysis.Therefore,this study combines BIM and Semantic Web to study the optimization method of data collection,management,and utilization of architectural digital twins from the perspective of the life cycle,solve the data sharing problem of architectural digital twins,and assist in the realization of digital twins in the entire life cycle of buildings.The major work and findings are as follows:(1)This study analyzes the application status of information technology in the construction industry and the workflow of BIM.The typical issues of data sharing during digital twining are summarized as the collection and utilization of relevant data in the concept stage,the transition of information in the life cycle,and data usages during building operation.Dimension stage data management.Then,combined with the analysis of the BIM standard Capability Maturity Model(NBIMS-CMM)on the workflow of integrated,real-time service and auxiliary BIM software,research and development schemes are formulated for the conceptual stage,the transition from design and construction to operation and maintenance stage and the problems existing in operation and maintenance stage of BIM Technology.Based on the schemes,this work carries out further studies into digital twin optimizations.(2)This study optimizes the transition of BIM information from the design and construction stage to the operation and maintenance stage.Aiming at the problem of information simplification and standardization in this period,this study simplifies and standardizes BIM based on the Semantic Web.The scheme uses NLP and ontology to standardize the translation of BIM instances and uses knowledge graphs to infer the relationship between instances,thereby automatically building semantic models,but currently,the effective way is to standardize the naming of points in the model.At the same time,this study extends the Brick metadata standard to support Variable Refrigerant Flow(VRF)systems,broadening the coverage of metadata in building systems.(3)This study optimizes the digital twin in the operation and maintenance phase.Aiming at the problems of chaotic data management and data utilization in this period,this study builds a semantic model of buildings and equipment based on metadata,a building management system that provides data indexing.Meantime,this study uses BIM as the carrying platform to standardize the optimization method.The verification of the tool in the operation management of the air conditioning system and the engineering application in Foshan show that the optimization scheme can improve the efficiency of data analysis in the operation and maintenance phase,and the management of building operation data is no longer limited to a single system,but can instantly query and analyze multiple conforming ontologies.The standard building data optimizes data management,improves the speed of data query and analysis,and reduces the energy consumption of building operations.(4)This study optimizes the digital twin in the operation and maintenance phase.Aiming at the problems of chaotic data management and difficult data utilization in this period,this study builds a semantic model of buildings and equipment based on metadata to provide data indexes for building automation systems.Meanwhile,this study uses BIM as the carrying platform to standardize the optimization method.The verification of the tool in the operation management of the air conditioning system and the engineering application in Foshan show that the optimization scheme can improve the efficiency of data analysis in the operation and maintenance phase.The management of building operation data is no longer limited to a single system,but can instantly query and analyze multiple conforming ontologies.The standard building data optimizes data management,improves the speed of data query and analysis,and reduces the energy consumption of building operations.To sum up,based on BIM and Semantic Web,this study conducts research on digital twin optimization strategies for the entire life cycle of buildings,combines building evaluation criteria into BIM to optimize digital twins in the concept stage,and translates BIM defined by rules into standard semantic models to optimize data for operation and maintenance.Phase transition,integrating the semantic web and building an automatic control management system to optimize the digital twin in the operation and maintenance phase,and standardizing the development of the schemes,respectively.This study optimizes digital twins in some stages of the entire life cycle,and the research results provide a theoretical basis for building digital twin optimizations,as well as data support and technical guidance for digital twins to assist buildings in energy conservation and carbon reduction.