# Dynamic Modeling and Full-Process Simulation of the Core Engine Test Rig Main Test System
## 6 Conclusions  
The modeling and simulation research on the core engine test rig main test system can be concluded as follows:  
(1) The high-precision complex system models reflect the real situation of the physical entities or systems, and its modeling technology is the key technology to realize the digital twins. The modularization modeling approach used in the core engine test rig main test system provides a solution to digital twin modeling. In the dynamic simulation of the whole process in two operating conditions of normal temperature 1400 s and low temperature 1240 s by using the 47-components numerical system, the variation trends of all simulation curves are consistent with those of the test curves. The maximum errors of gas source pressure, exhaust-bypass total temperature, and total pressure under the normal-temperature condition are lower than 4%, 2%, and 12%, respectively; the maximum errors of gas source pressure and exhaust-bypass total temperature under the low-temperature condition are lower than 3% and 2%, respectively; meanwhile, the simulation analysis fully and clearly reveals the dynamic variation process of the system with combining regulation of various valves. These indicate that the simulation models of various components and the established numerical system can be used for virtual test of the test rig in two operating conditions. However, it still needs to further improve accuracy, especially with respect to different operating conditions. (2) A comprehensive solution is provided to the valve-spool/orifice throttling modeling at the system level, which is a key issue of the fluid pipeline system modeling. Vanessa 30,000 valve-spool throttling model is used for the modeling of F9, F10, and F11, the valves with known information in the test rig system; a modeling approach which utilizes system test data to correct the reference-valve throttling model is proposed for those valves with unknown structure and throttling characteristic information. This approach consists of three options, where for F3, the regulator valve with upstream and downstream system test data, HCB high-capacity sleeve regulator valve is selected as reference valve and the calibration-adjusting scheme (Option A) is used for modeling; for F4, the regulator valve only with indirect system test data, HCB valve is used as reference valve and the full-system simulation trial-calibration scheme (Option B) is used for modeling. The variation trendsof the flow-rate simulation curves of engine main line and exhaust bypass in two operating conditions are consistent with those of the test curves, and the maximum error between simulation curves and test curves of the remaining parameters in the two branches is less than 12%, which indicates that the proposed method can solve the modeling problems of various regulator valves in the complex pipeline network system. (3) In practice, both Vanessa 30,000 and HCB are used as reference-valve models separately for the modeling of F3 and F4 so as to assess their validity. Taking F3 as an example, it is found by assessment that the flow-rate simulation results of the two models are the same at the zero opening point, and the difference between the two models with the opening in the range of 0.42-0.63, including the calibration opening point of 0.44, is less than 20%; outside such range, the difference between the two models with the opening in 0.33-0.42 and 0.63-0.94 is less than 20-50%. These indicate that the proposed modeling approach for information-unknown regulator valves has no strict restrictions on the reference valve and has certain versatility. However, it needs to be reassessed based on the corresponding test when used for the opening points outside the permitted error range. At this time, with the accumulation of multi-operating conditions test data, the modeling can use Option C, under which the flow characteristic is obtained by fitting based on the reference-valve throttling flow-rate equation and the test data.