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With uncrewed aircraft systems (UASs) becoming more popular in recent years there is an increasing risk of a midair collision with aircraft for which there are currently no regulations in place. Bird impacts have been thoroughly studied for years and are considered soft body impacts. The bird impact research cannot be directly applied to UAS ingestions since they are hard body impacts. Some recent research has looked into understanding the differences between soft and hard body impacts on aircraft engines. However, this research used primarily unvalidated models for the harsh conditions of an ingestion event, which creates uncertainty in the results. This work intends to fill in this gap in understanding by developing a validated computational model of a UAS for engine ingestion simulations. Part I of this work presented the experimental test plan and experimental results of UAS critical components and full UAS being launched at test articles with representative features of a fan blade. This work discusses the computational modeling completed in LS-DYNA to simulate the physical tests and to update and validate the UAS models. [ABSTRACT FROM AUTHOR]

A variable cycle engine (VCE) is a potential power system for future advanced military and civil aircraft. The involvement of numerous adjustable parameters enables a VCE to meet multiple flight requirements simultaneously; however, it also increases the difficulty of engine design. Global algorithms can be adopted to maximally exploit the performance potential of a VCE while satisfying constraints. However, the optimization of a VCE is a highly constrained and nonlinear problem with high computational cost. In this article, a novel acceleration technique for the global optimization of VCEs is presented. The initial guesses for the iterations of the VCE model were optimized along with the optimization variables to reduce the model call number (MCN). The differential evolution (DE) algorithm was chosen to demonstrate and verify the effectiveness of this acceleration technique. The results show that the technique can significantly reduce the MCN under most conditions without affecting the optimization process. The more rapidly the DE converges, the more significantly the MCN is reduced. In some cases, this technique can help improve the optimization results. Moreover, the technique can be applied to various DE improvement strategies. This technique can also be employed in the performance optimization of other aero engines or similar systems. [ABSTRACT FROM AUTHOR]