Towards digital twins: Design of an entity data model in the MuPIF simulation platform

IF 4 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software Pub Date : 2024-08-01 DOI:10.1016/j.advengsoft.2024.103733

Bořek Patzák, Stanislav Šulc, Václav Šmilauer

引用次数: 0

Abstract

This paper describes the design and implementation of a digital twin model in the open-source MuPIF simulation platform. MuPIF enables a user-defined data model based on an ontology or schema to be created. A representation of the data model is generated in a target data management system. The data model, integrated with MuPIF, lets model entities to be linked, and model attributes can be assigned to simulation workflows inputs and outputs. The model is semantically-defined, provides full traceability, and has a web-based API for data discovery.

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迈向数字双胞胎：在 MuPIF 仿真平台中设计实体数据模型

本文介绍了在开源 MuPIF 仿真平台中设计和实施数字孪生模型的情况。MuPIF 可根据本体论或模式创建用户定义的数据模型。数据模型的表示方法在目标数据管理系统中生成。数据模型与 MuPIF 集成后，可以链接模型实体，并将模型属性分配给仿真工作流的输入和输出。该模型是语义定义的，提供完整的可追溯性，并有一个用于数据发现的基于网络的应用程序接口。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Advances in Engineering Software 工程技术-计算机：跨学科应用

CiteScore

7.70

自引率

4.20%

发文量

169

审稿时长

37 days

期刊介绍： The objective of this journal is to communicate recent and projected advances in computer-based engineering techniques. The fields covered include mechanical, aerospace, civil and environmental engineering, with an emphasis on research and development leading to practical problem-solving. The scope of the journal includes: • Innovative computational strategies and numerical algorithms for large-scale engineering problems • Analysis and simulation techniques and systems • Model and mesh generation • Control of the accuracy, stability and efficiency of computational process • Exploitation of new computing environments (eg distributed hetergeneous and collaborative computing) • Advanced visualization techniques, virtual environments and prototyping • Applications of AI, knowledge-based systems, computational intelligence, including fuzzy logic, neural networks and evolutionary computations • Application of object-oriented technology to engineering problems • Intelligent human computer interfaces • Design automation, multidisciplinary design and optimization • CAD, CAE and integrated process and product development systems • Quality and reliability.