NAVAL

POSTGRADUATE

SCHOOL

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MONTEREY, CALIFORNIA

THESIS

ENHANCING MISSION ENGINEERING

ROUTE SELECTION THROUGH DIGITAL TWIN

DECISION SUPPORT

by

Boon Kien Eugene Lee

September 2021

Thesis Advisor: Douglas L. Van Bossuyt

Co-Advisor: Jason Bickford (NSWC, DOD)

Approved for public release. Distribution is unlimited.

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Untangling the requirements of a Digital Twin

October 2020

关于征求工业数字孪生和工业机器人方面两项团体标准意见的通知

各有关单位：

团体标准《工业数字孪生概念和术语体系》和《工业移动机器人可靠性测试与评定标准》已由起草单位完成征求意见稿和编制说明，现面向社会征求意见并进行网上公示。

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为保证标准质量，请有关单位认真审阅后，填写《团体标准征求意见汇总表》（见附件3），于2024年8月30日之前寄回或以电子邮件的方式反馈至协会秘书处科技质量部。

通讯地址：北京市丰台区广安路9号院1号楼12A18室

邮政编码：100055

联系人：刘明雷，13910132260

电子邮件：Liuml@cameta.org.cn

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亚信科技（中国）有限公司取得一项名为“一种数字孪生实现方法及装置、电子设备、存储介质”，授权公告号 CN118332932B，申请日期为 2024 年 6 月。

本申请公开了一种数字孪生实现方法及装置、电子设备、存储介质，所述方法应用于目标设备，所述方法包括：采集目标设备的当前运行数据；其中，当前运行数据包括当前目标设备自身的运行数据以及目标设备的孪生体的运行数据；调用目标设备中的内生智能模块，利用目标设备的当前运行数据以及历史运行数据，对目标设备的数字孪生模型进行优化，得到当前的目标设备的数字孪生模型；其中，内生智能模块基于人工智能大模型实现；目标设备的数字孪生模型预先通过调用内生智能模块利用目标设备的设备数据构建并训练得到；基于当前的目标设备的数字孪生模型，更新目标设备的孪生体；通过更新后的目标设备的孪生体对目标设备进行模拟，并反馈模拟结果。

安世亚太科技股份有限公司取得一项名为“一种基于数字孪生体的时变频率信号处理系统及方法”，授权公告号 CN115967599B，申请日期为 2022 年 7 月。

本发明涉及一种基于数字孪生体的时变频率信号处理系统及方法，属于数字孪生体技术领域，解决了现有基于时变频率信号的用户接入性能受频率偏移等因素影响较大的问题。该系统包括：信号产生模块，根据真实物理世界中每一用户接入的业务特征，映射得到数字孪生体中相应用户的时变频率信号；输入信号处理模块，将每一用户的时变频率信号分别调制到同一调制频率下，并对调制后的信号分别进行欧拉变换，得到相应用户的欧拉变换信号；信号传递模块，传输所有用户的欧拉变换信号混合形成的信号；输出信号处理模块，进行信号恢复及分数域解调，从分数域解调结果中提取出每一用户的时变频率信号中的频率偏移、并还原出每一用户的时变频率信号。

Connecting the Twins: A Review on Digital Twin Technology & its

Networking Requirements

A Comprehensive Review of Digital Twin - Part 1: Modeling

and Twinning Enabling Technologies

Adam Thelen1, Xiaoge Zhang2, Olga Fink3, Yan Lu4, Sayan Ghosh5, Byeng D.

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Youn6, Michael D. Todd7, Sankaran Mahadevan8, Chao Hu1* and Zhen Hu9*

1Department of Mechanical Engineering, Iowa State University, Ames, 50011, IA, USA.

2Department of Industrial and Systems Engineering, The Hong Kong Polytechnic

University, Kowloon, Hong Kong.

3Intelligent Maintenance and Operations Systems, EPFL, Lausanne, 12309, NY,

Switzerland.

4Information Modeling and Testing Group, National Institute of Standards and

Technology, Gaithersburg, 20877, MD, USA.

5Probabilistic Design and Optimization group, GE Research, Niskayuna, 12309, NY, USA.

6Department of Mechanical Engineering, Seoul National University, Gwanak-gu, 151-742,

Seoul, Republic of Korea.

7Department of Structural Engineering, University of California, San Diego, La Jolla,

92093, CA, USA.

8Department of Civil and Environmental Engineering, Vanderbilt University, Nashville,

37235, TN, USA.

9Department of Industrial and Manufacturing Systems Engineering, University of

Michigan-Dearborn, Dearborn, 48128, MI, USA.

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A Comprehensive Review of Digital Twin - Part 2: Roles of

Uncertainty Quanti cation and Optimization, a Battery

Digital Twin, and Perspectives

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Adam Thelen1, Xiaoge Zhang2, Olga Fink3, Yan Lu4, Sayan Ghosh5, Byeng D.

Youn6, Michael D. Todd7, Sankaran Mahadevan8, Chao Hu1* and Zhen Hu9*

1Department of Mechanical Engineering, Iowa State University, Ames, 50011, IA, USA.

2Department of Industrial and Systems Engineering, The Hong Kong Polytechnic

University, Kowloon, Hong Kong.

3Intelligent Maintenance and Operations Systems, Swiss Federal Institute of Technology

Lausanne, Lausanne, 12309, NY, Switzerland.

4Information Modeling and Testing Group, National Institute of Standards and

Technology, Gaithersburg, 20877, MD, USA.

5Probabilistic Design and Optimization group, GE Research, Niskayuna, 12309, NY, USA.

6Department of Mechanical Engineering, Seoul National University, Gwanak-gu, 151-742,

Seoul, Republic of Korea.

7Department of Structural Engineering, University of California, San Diego, La Jolla,

92093, CA, USA.

8Department of Civil and Environmental Engineering, Vanderbilt University, Nashville,

37235, TN, USA.

9Department of Industrial and Manufacturing Systems Engineering, University of

Michigan-Dearborn, Dearborn, 48128, MI, USA.

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