Analysis And Application Of Wind Environment During Building Operation And Maintenance Period Based On Multi-scale Modeling And Data-driven Methods

The wind has a significant impact on building personnel,structures,facilities and the environment,and is an important issue to be considered throughout the building lifecycle.At present,although the wind environment analysis technology represented by Computational Fluid Dynamics(CFD)is relatively mature,and a series of analysis software has been developed,most of the software is developed for the building design stage.The current analysis process usually initiates wind environment analysis based on local meteorological statistics and idealized boundary conditions,which is generally static,idealized,inefficient,and has a high professional threshold.However,the building Operation and Maintenance(O&M)process requires management tasks to be real-time,on-site,dynamic,and easy-to-use.As a result,current wind environment analysis methods are difficult to meet the needs of the O&M tasks,and there is still no applicable and suitable wind analysis solution for the O&M process.It is difficult to realize the quantitative and accurate consideration of the building wind environment in the O&M decision-making process,which limits the improvement of the refinement and intelligence level of building O&M management.To address the above problems,this study introduces two core technologies of multiscale numerical simulation and deep learning to improve the existing wind environment analysis methodology,and constructs an original wind environment analysis framework towards the building O&M process based on multi-scale modeling and data-driven methods.Combining the technologies of wind environment data management,data application and platform development,this study proposes a comprehensive solution including theories,technologies,methods and platforms for building wind environment analysis in the O&M period.Firstly,this study summarizes the actual demand of wind information in the O&M phase and investigates the current wind environment analysis theory,and then constructs a theoretical framework for building wind environment analysis in the O&M stage from the aspects of data,models,and applications.To deal with the multi-source,heterogeneous and multi-scale data involved in the analysis process,this study proposes the Building Wind Environment Information Model(BWEIM)which realizes the automatic acquisition,integration and management of the related data,including meteorology data,wind data,buildings and geospatial data.Subsequently,a multi-scale numerical analysis model including the mesoscale meteorology model and the microscale CFD model is constructed to support the wind environment simulation under precise spatial-temporal conditions.The multi-scale model meets the dynamic and on-site analysis requirements in the O&M stage,and realizes the automation of the simulation process through the embedding of expert knowledge.A deep neural networkbased wind environment prediction model is then developed to address the inefficiency problem of the numerical simulation model.And a framework that couples multiscale numerical simulation and deep learning methods is proposed to balance the efficiency and accuracy of wind environment analysis.Concerning three key issues in the O&M process including pollutant dispersion,personnel comfort and building energy consumption,this study proposes the application methods of wind environment information in the O&M decision-making process.At last,on the basis of the abovementioned key technologies,this study develops the wind environment analysis and application platform for the O&M stage.The platform provides comprehensive tools for the O&M decision-making process considering wind factors.The feasibility and reliability of the platform are verified with actual building O&M projects.It is proved that the theory,method,technology and platform proposed in this study can realize the dynamic,efficient,automatic and low-threshold analysis of wind environment under specific meteorological conditions,given time range,and actual urban morphologies.The proposed approach meets the actual needs of building wind environment analysis during the O&M process,and provides a feasible way for the windenvironment-involved intelligent O&M management,which has important research significance and broad application prospects.