As an emerging technology in the era of Industry 4.0, digital twin is gaining
unprecedented attention because of its promise to further optimize process
design, quality control, health monitoring, decision and policy making, and
more, by comprehensively modeling the physical world as a group of
interconnected digital models. In a two-part series of papers, we examine the
fundamental role of different modeling techniques, twinning enabling
technologies, and uncertainty quantification and optimization methods commonly
used in digital twins. This first paper presents a thorough literature review
of digital twin trends across many disciplines currently pursuing this area of
research. Then, digital twin modeling and twinning enabling technologies are
further analyzed by classifying them into two main categories:
physical-to-virtual, and virtual-to-physical, based on the direction in which
data flows. Finally, this paper provides perspectives on the trajectory of
digital twin technology over the next decade, and introduces a few emerging
areas of research which will likely be of great use in future digital twin
research. In part two of this review, the role of uncertainty quantification
and optimization are discussed, a battery digital twin is demonstrated, and
more perspectives on the future of digital twin are shared.

本文旨在探究数字孪生技术在工业 4.0 时代的应用及相关研究，主要通过文献综述和数字孪生建模技术分类探讨数字孪生建模所使用的不同建模技术、建模工具和优化方法，并提供该领域未来发展的趋势和研究方向。