Accurate acquisition of the distribution offlow parameters inside the supersonic combustor is of great significance for hypersonicflight control.It is an interesting attempt to introduce a data-driven model to a super...Accurate acquisition of the distribution offlow parameters inside the supersonic combustor is of great significance for hypersonicflight control.It is an interesting attempt to introduce a data-driven model to a supersonic combustor forflowfield prediction.This paper proposes a novel method for predicting theflowfield in a dual-mode combustor.Aflowfield prediction convolutional neural network with multiple branches is built.Numerical investiga-tions for a strut variable geometry combustor have been conducted to obtainflowfield data for training the network as aflowfield prediction model.Richflowfield data are obtained by changing the equivalent ratio,incomingflow condition and geometry of the supersonic combustor.The Mach number distribution can be obtained from the trainedflowfield prediction model using the combustor wall pressure as input with high accuracy.The accuracy offlowfield prediction is discussed in several aspects.Further,the combustion mode detection is im-plemented on the predictionflowfield.展开更多
基金supported by the National Natural Science Foundation of China (Grant No.11972139 and 52125603)the Fundamental Research Funds for the Central Universities (HIT.BRET.2021006 and FRFCU5710094620).
文摘Accurate acquisition of the distribution offlow parameters inside the supersonic combustor is of great significance for hypersonicflight control.It is an interesting attempt to introduce a data-driven model to a supersonic combustor forflowfield prediction.This paper proposes a novel method for predicting theflowfield in a dual-mode combustor.Aflowfield prediction convolutional neural network with multiple branches is built.Numerical investiga-tions for a strut variable geometry combustor have been conducted to obtainflowfield data for training the network as aflowfield prediction model.Richflowfield data are obtained by changing the equivalent ratio,incomingflow condition and geometry of the supersonic combustor.The Mach number distribution can be obtained from the trainedflowfield prediction model using the combustor wall pressure as input with high accuracy.The accuracy offlowfield prediction is discussed in several aspects.Further,the combustion mode detection is im-plemented on the predictionflowfield.
