Finite Element Analysis of Drone Impact on a Rotating Aircraft Engine Fan: Sensitivity to Blade Material and Impact Velocity

An explicit finite element study examined the sensitivity of a rotating aircraft-engine fan to blade material and drone impact velocity. A complete 20-blade rotor and a deformable, equivalent-material quadcopter were modelled in ANSYS/LS-DYNA. Ti-6Al-4V, Ti-6242 and AA2024-T3 blades were assessed at 30, 60 and 100 m/s with an initial fan angular velocity of 283 rad/s. Nine frictional simulations and one Ti-6Al-4V frictionless case at 100 m/s were evaluated using stress, equivalent plastic strain, directional displacement, erosion and energy histories. Ti-6Al-4V produced the lowest maximum blade plastic strain at each velocity; AA2024-T3 values were 11.6–26.9 times greater despite lower equivalent stress. No fan elements were deleted, whereas drone deletion occurred in every case. The maximum-history reduction in surviving-drone kinetic energy increased with velocity, but the highest velocity did not produce the largest plastic strain in every material. Including friction increased maximum plastic strain by a factor of 6.46 in the sensitivity case. The results highlight multi-blade chronology and complementary response measures within the adopted model; local impact convergence and configuration-specific experimental validation were not established.

Authors

Institutions

Publication Details

Journal
Modelling—International Open Access Journal of Modelling in Engineering Science
Published
2026-10-14
DOI
https://doi.org/10.3390/modelling7050224
Primary Topic
High-Velocity Impact and Material Behavior
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Finite Element Analysis of Drone Impact on a Rotating Aircraft Engine Fan: Sensitivity to Blade Material and Impact Velocity

Mertol Tüfekci, Abishek Keshar Khanal
Modelling—International Open Access Journal of Modelling in Engineering Science
High-Velocity Impact and Material Behavior
article

Finite Element Analysis of Drone Impact on a Rotating Aircraft Engine Fan: Sensitivity to Blade Material and Impact Velocity

Mertol Tüfekci, Abishek Keshar Khanal
article en

Abstract

An explicit finite element study examined the sensitivity of a rotating aircraft-engine fan to blade material and drone impact velocity. A complete 20-blade rotor and a deformable, equivalent-material quadcopter were modelled in ANSYS/LS-DYNA. Ti-6Al-4V, Ti-6242 and AA2024-T3 blades were assessed at 30, 60 and 100 m/s with an initial fan angular velocity of 283 rad/s. Nine frictional simulations and one Ti-6Al-4V frictionless case at 100 m/s were evaluated using stress, equivalent plastic strain, directional displacement, erosion and energy histories. Ti-6Al-4V produced the lowest maximum blade plastic strain at each velocity; AA2024-T3 values were 11.6–26.9 times greater despite lower equivalent stress. No fan elements were deleted, whereas drone deletion occurred in every case. The maximum-history reduction in surviving-drone kinetic energy increased with velocity, but the highest velocity did not produce the largest plastic strain in every material. Including friction increased maximum plastic strain by a factor of 6.46 in the sensitivity case. The results highlight multi-blade chronology and complementary response measures within the adopted model; local impact convergence and configuration-specific experimental validation were not established.

Modelling—International Open Access Journal of Modelling in Engineering ScienceVol. 7(5)
University of Hertfordshire (GB)
Openalex Percentile: Top 28%
High-Velocity Impact and Material Behavior
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.