When high-speed fluid flows through throttling components such as elbows,valves,tee joints and orifice plates in pipeline systems,fluid impact load is easy to induce vibration of the pipline,and can even cause damage to the pipeline and its accessories.Conventional pipeline flow-induced vibration analysis carries out the flow field of fluid in the pipe and the coupling calculation of fluid and pipeline flow-solid,which consumes long working hours and is not universal.This article conducts a data-driven neural network method analysis to establish a database of flow characteristics of typical fluid components.Through the neural network method,the calculation of flow induced vibration can be completed in a much shorter time.This method can be used to analyze and calculate the possible vibration conditions of pipelines during the design period and avoid or reduce pipeline vibration by changing the pipeline design.This method can also be applied to the flow induced vibration analysis of pipeline systems in other industries.
关键词
热力发电/核电/流致振动/数据驱动/神经网络/管道
Key words
thermal power generation/nuclear power/flow induced vibration/data driven/neural networks/pipeline
维普
万方数据