Work

Deep operator network prediction method for electromagnetic thrust of linear propulsion electromagnetic energy equipment

Year: 2025

Type: article

Abstract: Linear propulsion electromagnetic energy equipment utilizes the Lorentz force to apply power to the emitter, achieving launch speeds and efficiencies that far surpass those of traditional chemical propulsion technologies. This capability has significant strategic and practical value in both defense and civilian applications. Analyzing and calculating the armature electromagnetic thrust is essential for studying the dynamic characteristics of linear propulsion electromagnetic energy equipment. However, high-speed scenarios often present challenges in obtaining numerical solutions due to “pseudo-oscillation.” To address this issue, we propose a novel prediction method for the armature electromagnetic thrust in linear propulsion electromagnetic energy equipment using deep operator networks. First, a finite element simulation model of the system was developed to generate stable numerical simulation data under varying excitation currents. This model is then used to analyze the dynamic characteristics of the armature electromagnetic thrust and evaluate the stability of the numerical solutions. Based on the simulation data, we introduce a deep operator network-based prediction method for armature electromagnetic thrust. Finally, the prediction performance of the model is validated using linear propulsion electromagnetic energy equipment as a computational example. The results showed that the prediction error for the electromagnetic thrust on the test set was within 1%. After training, the model can calculate the electromagnetic thrust under different excitation currents in a matter of seconds, providing a fresh perspective for analyzing the dynamic characteristics of linear propulsion electromagnetic energy equipment.

Source: AIP Advances

DOI: 10.1063/5.0219041

Authors: Liang Jin, Tianci Ma, Qingxin Yang, Juheng Song

Institutions: Hebei University of Technology, State Key Laboratory of Reliability and Intelligence of Electrical Equipment

Language: English

Topic: Electromagnetic Launch and Propulsion Technology

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,350