A New Method to Calculate Induced Current of Thin Wire over Anisotropic Ground under HPM

Cao, Le

doi:10.1155/2019/4270395

Cited by 2 publications

(1 citation statement)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…From the perspective of computational electromagnetism, the HPEMP effect on vehicles is a composite time-domain scattering problem. Numerous numerical approaches have been widely used, such as the Method of Moments (MoM) [6,7], the Finite-Difference Time-Domain (FDTD) method [8][9][10], the Finite Element Method (FEM) [11,12], the Time-Domain Integral Equation (TDIE) method [13,14], and other hybrid methods [15,16]. However, to calculate the coupling between the vehicle and the half-space, most existing algorithms need to use half-space Green's function, which is extremely difficult to derive and calculate, particularly for multi-layered planar medium and rough surfaces.…”

Section: Introductionmentioning

confidence: 99%

High-Power Electromagnetic Pulse Effect Prediction for Vehicles Based on Convolutional Neural Network

et al. 2022

Self Cite

View full text Add to dashboard Cite

This study presents a prediction model for high-power electromagnetic pulse (HPEMP) effects on aboveground vehicles based on convolutional neural networks (CNNs). Since a vehicle is often located aboveground and is close to the air-ground–half-space interface, the electromagnetic energy coupled into the vehicle by the ground reflected waves cannot be ignored. Consequently, the analysis of the vehicle’s HPEMP effect is a composite electromagnetic scattering problem of the half-space and the vehicles above it, which is often analyzed using different half-space numerical methods. However, traditional numerical methods are often limited by the complexity of the actual half-space models and the high computational demands of complex targets. In this study, a prediction method is proposed based on a CNN, which can analyze the electric field and energy density under different incident conditions and half-space environments. Compared with the half-space finite-difference time-domain (FDTD) method, the accuracy of the prediction results was above 98% after completing the training of the CNN network, which proves the correctness and effectiveness of the method. In summary, the CNN prediction model in this study can provide a reference for evaluating the HPEMP effect on the target over a complex half-space medium.

show abstract