AI赋能下高功率微波效应研究趋势简析

A brief analysis of research trends in high-power microwave effects empowered by AI

  • 摘要: 本文梳理了高功率微波效应研究现状,并针对当前效应研究中难以快速开展高精度仿真实验、效应目标失效机理不明晰、实验数据量稀缺及跨学科协同不足等问题,分析论述了将人工智能技术引入高功率微波效应研究后,在加速多物理场耦合仿真、辅助预测损伤传导过程、辅助高功率微波效应高通量实验,以及构建高功率微波大语言模型等方面的应用,旨在推动人工智能在高功率微波效应研究中更好地发挥先导性和引领性作用。特别是在加速多物理场耦合仿真和辅助预测损伤传导过程两个方面,依托人工智能强大的非线性映射能力及多模态数据融合能力,将为高功率微波效应底层机理的揭示提供重要的推动作用。

     

    Abstract:
    Background With the advancement of artificial intelligence (AI) technology, integrating AI into scientific research and leveraging AI tools to empower scientific discovery has emerged as an important trend in the development of scientific research.
    Purpose This paper analyzes and discusses the feasibility of introducing artificial intelligence technology into high-power microwave (HPM) effect research and its enabling role in such research, with the aim of promoting AI to better play its pioneering and leading role in the study of HPM effects.
    Methods The present paper provides a detailed exposition of the applications ensuing from the integration of artificial intelligence into HPM effect research, encompassing the acceleration of multiphysics coupled simulations, assisted prediction of damage conduction processes, facilitation of high-throughput HPM effect experiments, and the development of large language models for HPM, accompanied by specific exemplifications.
    Results Especially with regard to the acceleration of coupled multiphysics simulations and the assisted prediction of damage propagation processes, leveraging artificial intelligence’s robust nonlinear mapping competence and multimodal data fusion capacity will furnish crucial momentum to the elucidation of the underlying mechanisms of HPM effects.
    Conclusions The incorporation of artificial intelligence technology into the study of HPM effects constitutes a significant developmental trend endowed with far-reaching application prospects.

     

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