In order to optimize the slit/slot geometry design of a bipropellant pintle injector, the impinging spray development of a pintle injector was numerically investigated. The VOF (volume of fluid) and LES (large eddy simulation) methods were employed for an analysis to capture the gas–liquid interface by means of the AMR (adaptive mesh refinement) method. In those simulation cases, different flowrates, slot numbers, pintle diameters, slot thicknesses and slot shapes were compared for an analysis. In a comparison of visualization and quantification, a high flowrate and large pintle diameter were shown to be more positive features for improving the atomization quality and mixing effect. As for the slot parameters and shape, the spray development was mainly determined by the flow proportion between the slit jet and slot jet. The simulation results indicated that dominant slot jets cause a more dispersed spatial distribution, which is more conducive to the subsequent improvement of combustion efficiency in a limited space. However, an excessive increase in the number of slot jets can weaken the overall atomization quality and mixing effect, so it is suggested to ensure a balance for geometry design optimization.

This article proposes a design method for a valve automatic assembly production line in response to the automation assembly requirements of electric valve products in space propulsion systems and the engineering problems of inaccurate loading force control and low valve measurement accuracy in existing process methods. This method can achieve five assembly processes during the assembly process of electric valves, including pre-tightening force control, valve-core stroke measurement, performance testing, and shell structure welding. The article introduces the design of platform components such as process execution, positioning, and transportation, as well as the design and operation process of workstations. By combining the design of a three-axis motion mechanism, a small turntable, and a robotic arm, the product can achieve professional, positioning, full process automation, and equipment miniaturization design across multiple workstations. Through the design of precise control of loading force and non-contact optical measurement method of moving structure, compared with the original method, the parameters affecting product performance are precisely controlled and the precision is improved. And the multivariable decoupling of valve product performance is realized by this method. Through application verification, this automatic assembly production line can significantly improve the assembly efficiency of electric valve products and solve difficult problems in product engineering.

In order to improve the mixture ratio accuracy of the bipropellant thruster and prolong the service life of a satellite on orbit, a variety of different liquid-flow tests and the final firing test are critical in the production testing process. However, after comparison with a large number of tests data, it was found that the liquid-flow test results were far away from matching the firing-test data without clear regularity, resulting in a qualified rate of mixture ratio of less than 40%. This study developed a BP-RNN (back propagation—recurrent neural network) chain method based on machine learning, which uses multi-dimensional nonlinear parameters to construct the specific dataset after data enhancement. Then, the mapping characteristic of the neural network was used to fit the historical data for the weight analysis and mixture ratio prediction, and effectively improved the qualified rate of the mixture ratio. The back propagation neural network was used to learn the association rules of the 10-dimension characteristic data and the firing test results generated in the historical process of thruster production. Then, the features with high influencing weight were extracted and sorted, so the “many-to-one” mixture ratio prediction was conducted through the subsequent recurrent neural network. The accepted prediction accuracy could reach around 75% after the test data verification. By using this method, most of bipropellant thrusters could directly reach the qualified mixture ratio in the firing test after adjusting the throttle orifice size in the liquid-flow tests. This chain method first bridges the data between the liquid-flow test and the firing test.