In recent decades, the use of artificial intelligence (AI) techniques in the field of materials modeling has received significant attention owing to their excellent ability to analyze a vast amount of data and reveal correlations between several complex interrelated phenomena. In this review paper, we summarize recent advances in the applications of AI techniques for numerical modeling of different types of materials. AI techniques such as machine learning and deep learning show great advantages and potential for predicting important mechanical properties of materials and reveal how changes in certain principal parameters affect the overall behavior of engineering materials. Furthermore, in this review, we show that the application of AI techniques can significantly help to improve the design and optimize the properties of future advanced engineering materials. Finally, a perspective on the challenges and prospects of the applications of AI techniques for material modeling is presented.

在最近的几十年里，由于其出色的分析大量数据并揭示几种复杂的相互关联的现象之间的关联的能力，在材料建模领域中使用人工智能（AI）技术受到了广泛的关注。在这篇综述文章中，我们总结了AI技术在不同类型材料的数值建模中的最新应用进展。诸如机器学习和深度学习之类的AI技术在预测材料的重要机械性能方面显示出巨大的优势和潜力，并且揭示了某些主要参数的变化如何影响工程材料的整体性能。此外，在这篇评论中，我们表明，人工智能技术的应用可以极大地帮助改善设计并优化未来先进工程材料的性能。最后，提出了关于将AI技术应用于材料建模的挑战和前景的观点。