Front Variable Area Bypass Injector (Front-VABI) is a component of the Adaptive Cycle Engine (ACE) with important variable-cycle features. The performance of Front-VABI has a direct impact on the performance and stability of ACE, but the current ACE performance model uses approximate models for Front-VABI performance calculation. In this work, a multi-fidelity simulation based on a de-coupled method is developed which delivers a more accurate calculation of the Front-VABI performance based on Computational Fluid Dynamics (CFD) simulation. This simulation method proposes a form of Front-VABI characteristic and its matching calculation method between it and the ACE performance model, constructs a coupling method between the (2-D) Front-VABI model and the (0-D) ACE performance model. The result shows, when ACE works in triple bypass mode, the approximate model cannot account for the effect of Front-VABI pressure loss on Core Driven Fan Stage (CDFS) design pressure ratio, and the calculated error of high-pressure turbine inlet total temperature is more than 40 K in mode transition condition (the transition operating condition between triple bypass mode and double bypass mode). In double bypass mode, the approximate model can better simulate the performance of Front-VABI by considering the local loss of area expansion. This method can be applied to the performance-optimized design of Front-VABI and the ACE control law design during mode transition.

The alternative working modes and flexible working states are the outstanding features of an adaptive cycle engine, with a proper control schedule design being the only way to exploit the performance of such an engine. However, unreasonable design in the control schedule causes not only performance deterioration but also serious aerodynamic stability problems. Thus, in this work, a hybrid optimization method that automatically chooses the working modes and identifies the optimal and smooth control schedules is proposed, by combining the differential evolution algorithm and the Latin hypercube sampling method. The control schedule architecture does not only optimize the engine steady-state performance under different working modes but also solves the control-schedule discontinuity problem, especially during mode transition. The optimal control schedules are continuous and almost monotonic, and hence are strongly suitable for a control system, and are designed for two different working conditions, i.e., supersonic and subsonic throttling, which proves that the proposed hybrid method applies to various working conditions. The evaluation demonstrates that the proposed control method optimizes the engine performance, the surge margin of the compression components, and the range of the thrust during throttling.