Firstly, the static and dynamic mathematic model of the Liquid Propellant Rocket Engine of pressure-fed providing system was established in centralized parameter method.
首先采用集中参数法,建立了挤压式供应系统的液体火箭发动机各部件的静态及动态数学模型。
Two-phase turbulent reacting flow model of the internal operating processes in Liquid Rocket Engine (LRE) is set up in non-orthogonal curvilinear coordinates.
建立了任意斜交曲线坐标系下液体火箭发动机(LRE)内部工作过程的气液两相湍流化学反应流模型。
Finally, based on the model data, the neural networks are applied to recognize several fault patterns of the liquid rocket engine.
最后,基于模型数据,应用神经网络识别了液体火箭发动机的几种故障模式。
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