This Website is not fully compatible with Internet Explorer.
For a more complete and secure browsing experience please consider using Microsoft Edge, Firefox, or Chrome

Multidisciplinary Design Optimization of a Composite Aircraft Radome

This paper was produced for the 2019 NAFEMS World Congress in Quebec Canada

Resource Abstract

Radomes protect antennas from structural damage due to wind, precipitation, and bird strikes. In aerospace applications, radomes often double as a nose cone and thus have a significant impact on the aerodynamics of the aircraft. Radomes should be strong enough to endure bird strikes and aerodynamic loads while appearing as transparent as possible to the radar’s signal. We demonstrate how multiple physics model simulations can be used to verify and optimize the structural, aerodynamic, and electromagnetic performance of a nose cone radome. We consider a radome constructed using composite fiberglass plies and a foam core, and coated with an anti-static coating, paint, and primer. A slotted waveguide array is designed at X-band to represent a weather radar antenna. The transmission loss of the radome walls is analyzed using a planar Green’s function approach. An asymptotic technique, Ray-Launching Geometric Optics (RL-GO), is used to accurately simulate the nose cone radome and compute transmission loss, boresight error, and sidelobe performance. Computational Fluid Dynamics (CFD) analysis is used to predict steady state pressures resulting from high speeds (Mach 0.8), which are then mapped to an implicit structural solution to assess buckling using the Finite Element Method (FEM). Structural damage from a “bird strike” is predicted by an explicit structural FEM model where the bird is modeled using Smooth Particle Hydrodynamics (SPH). Multiple physics models (electromagnetics, structural, and bird strike impact) are simulated for multiple composite layup designs using a Modified Extensible Lattice Sequence (MELS) sampling method. Each model is then approximated as a mathematical response surface via a self-selecting regression technique known as Fit Automatically Selected by Training or FAST. These surfaces are combined to perform a Multidisciplinary Design Optimization (MDO). The resulting design is 31% lighter than the original radome and satisfies design requirements from each model, including transmission loss, maximum displacement, minimum buckling factor, and maximum strain. This process can improve the performance and reduce the design time of nose cone radomes.

Document Details

ReferenceNWC_19_206
AuthorHunter. K
LanguageEnglish
TypePaper
Date 18th June 2019
OrganisationAltair
RegionGlobal

Download

Purchase Download

Order RefNWC_19_206 Download
Non-member Price £5.00 | $6.31 | €5.83

Back to Previous Page