Design And Research Of Real-time Dynamic Pre-response Spray System For High-rise Building Fir

High-rise building fires pose a significant threat to human life and property due to their high loads and the variety of flammable materials used in their construction.The complex horizontal and vertical passages within the building make it difficult to predict and control the rapid development of a fire.Existing automatic sprinkler systems for preventing and controlling fires in high-rise buildings are passive and uncontrollable,often failing to keep up with the dynamic development of such fires.Therefore,the research and design of Real-Time Dynamic Pre-Response(RTDPR)systems for controlling high-rise building fires has significant practical implications.First,this article analyzes the theoretical development process of high-rise building fires and explores the disaster characteristics of such fires.The chimney effect and turbulence effect that affect the transmission of smoke in high-rise building fires are also analyzed.A network model of high-rise buildings is established based on graph theory,and the critical channels for the spread of fire smoke are studied using network flow algorithms,specifically identifying corridors and vertical passages.A pre-response strategy based on pre-response vectors is proposed and simulation experiments are carried out using Python,based on a temperature formula that includes a random term.The response times for first-and second-level preresponse were found to be 15.1s and 67.0s,respectively,with an average response temperature error of 26℃ and 57℃,indicating that the pre-response strategy can effectively achieve the function of graded pre-response.Second,based on the pre-response strategy and key elements of the Internet of Things,the RTDPR system is implemented.Database design for the RTDPR system was implemented using MariaDB.API interface development for the RTDPR system was completed using PHP+ Apache,and Vue was used for the user interface.The client development of the RTDPR system has been accomplished using tools such as js and Axios.The various elements of the RTDPR system work together to collect,transmit,process,and store data,while also providing additional functionalities such as command control and system logging.The system’s realtime dynamic pre-response capabilities are particularly evident when dealing with high-rise building fires.Finally,based on the Reynolds similarity criterion,a similar model was constructed to analyze the impact of the RTDPR system on fire smoke in terms of temperature,particle concentration,and visibility.The results show that the RTDPR system can reduce the temperature of fire smoke and affect its temperature distribution.It can also significantly accelerate particle settling in the later stages of a fire.According to the analysis and comparison of response results in the system log,the average response time is 2 seconds,indicating that the RTDPR system has a good rapid response capability.Additionally,two sets of experiments were selected to analyze the system log using Gantt charts to reconstruct the response process of the RTDPR system and ultimately reverse engineer the fire development process.In summary,the RTDPR system’s real-time dynamic pre-response capabilities are particularly effective in dealing with high-rise building fires,which can effectively enhance the fire prevention and control capabilities of such buildings and strengthen the protection of people’s lives and property.