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The filling conditions and pipeline characteristics of the aircraft fire extinguishing system determine the pressure of the fire extinguishing cylinder outlet, the discharge quality of the extinguishing agent, and the flow distribution during the discharge process. The simulation model of the fire extinguishing system pipeline of an aircraft was established by Amesim. The influence of filling conditions and pipeline characteristics was studied. It was found that the mass curves of the fire extinguishing agent were similar under filling pressures of 4, 5, and 6 MPa with a filling amount of 5.55 kg. The lower the initial temperature is, the pressure at the outlet of the cylinder decreases, but the emptying time is similar to 1.22 s. The lower the roughness is, the faster the discharge is. Under the ideal smooth pipe (ε = 0 mm), the emptying time of the fire extinguishing cylinder is 0.72 s. When the diameter of the short branch pipe is 10 mm, and the diameter of the long branch pipe is 14 mm, the discharge quality of the two pipes is close. The larger the diameter of the main pipe, the higher the discharge rate. The research results have a certain guiding significance for the pipeline design of certain aircraft.

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In a wind tunnel process, Mach number is the most important parameter. However, it is difficult to measure directly, especially in the multimode operation process, leading to difficulty in process monitoring. Thus, it is necessary to measure the Mach number indirectly by utilizing data-driven methods, and based on which, to monitor the operation status of the wind tunnel process. In this paper, therefore, a multimode wind tunnel flow field system monitoring strategy is proposed. Since the wind tunnel system is a strongly nonlinear system, the kernel partial least squares method, which can efficiently handle the nonlinear regression problem, is utilized. Firstly, the Mach number is predicted utilizing the kernel partial least squares method. Secondly, process monitoring statistics, i.e., the Hotelling T2 statistic and the square prediction error, the SPE statistic, and their control limits, are proposed to be applied to monitor the wind tunnel process on the basis of the prediction of the Mach number. Finally, the Mach number prediction and monitoring strategy are applied to a real process, where mode analysis and division is necessary. After mode division, the single-mode and multimode processes are modeled and predicted, respectively, and both the single-mode and multimode processes are monitored online. Satisfactory results were achieved compared with those of the partial least squares method.