Severity assessment of aircraft engine fan blades under airborne collision of unmanned aerial vehicles comparable to bird strike certification standards

Airborne drone collision on commercial manned aircraft has received extensive awareness due to the increasing drone operations in the restricted airspace. In addition, the bird strike certification for aircraft engines is likely to be inadequate for a drone collision with identical kinetic energy du...

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Bibliographic Details
Main Authors: Mohd Hasrizam Che Man, Hu, Liu, Low, Kin Huat
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2022
Subjects:
Online Access:https://hdl.handle.net/10356/155374
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Institution: Nanyang Technological University
Language: English
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Summary:Airborne drone collision on commercial manned aircraft has received extensive awareness due to the increasing drone operations in the restricted airspace. In addition, the bird strike certification for aircraft engines is likely to be inadequate for a drone collision with identical kinetic energy due to the difference in damage levels. Thus, it is important to understand and compare the risk between drones and bird strikes. This study aims to understand the damage severity from bird and drone strikes on the manned commercial aircraft engine. The Finite Element Method (FEM) simulation is adopted to obtain the damage of engine fan blades under the drone collision and bird strikes at different collision positions. The Lagrangian and Smooth Particle Hydrodynamics (SPH) approaches are employed for the drone and bird simulations, respectively. In addition, three different drone and bird weight categories were considered in this study, namely small, medium, and large, to investigate the effect of kinetic energy on the damage of fan blades. Results from the FEM simulation demonstrated that the damage of the engine fan blades due to drone collisions were more severe when comparing bird strikes of the same weight category. The damage severity level was proposed based on the damage of engine fan blades. In the event of a drone ingestion, the damage severity level assists in the identification of potential damage to engine fan blades and its performance.