Modeling of electromagnetic propagation inside jet engine environment using statistical electromagnetic approach

TL;DR

This paper proposes new methods to model electromagnetic fields in jet engines, which are complex and dynamic environments.

Contribution

The paper introduces two novel approaches for electromagnetic modeling in jet engines: a dynamic system simulation and a statistical excitation method.

Findings

Dynamic system simulation captures blade rotation effects in jet engine electromagnetic modeling.

A statistical excitation method models jet engines as static systems with random excitation.

Results from the static system model match finite element simulations, validating the approach.

Abstract

In this paper, the distribution of the electromagnetic field inside a complex jet engine environment is analyzed using statistical electromagnetics. The jet engine environment is an extremely complex geometry and exhibits random behavior due to the presence of moving metallic parts. This renders traditional analytical and simulation modeling techniques highly inefficient. To address this issue, two different approaches are proposed to model the propagation characteristics of the jet engine environment. The first is an innovative dynamic system approach based on dynamic system simulation which is inspired by the analysis of mechanically stirred reverberation chambers. In the dynamic system simulation the dynamic system, which is characterized by the rotation of a distinct set of blades, is primarily studied through the simulation program. A dimension scaling method is also introduced along with the dynamic system simulation to solve the complex jet engine environment. In the second approach, a novel statistical excitation method is applied to develop an equivalent model for the dynamic jet engine system. The studied jet engine is considered as a static jet engine system without blade rotation (static blades), but with a random excitation.A small signal analysis method is used to integrate the static and dynamic system parameters to generate random excitation characteristics of the static system. The extracted electric field values from the dynamic jet engine simulation environment and the static system field values from the small signal analysis have been analyzed statistically to prove the statistical equality between the two systems. The numerical results of the static system model are presented and verified through comparison with finite element method simulation packages.

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