Open AccessPublication Frequency:Continuously
The Digital Engineering and Digital Twin (DEDT) is an international peer-reviewed Open Access journal that covers a broad range of topics in the frontier of digital engineering and digital twin to be of interest and use to both academics and practitioners. The journal communicates original contributions primarily in the form of research articles, but also through letters, technical notes, review articles, and editorials. The multidisciplinary nature of the journal is intended to encourage a fruitful exchange of ideas and research outcomes among different engineering specialties.
The journal’s scope spans methods, technologies, and applications of digital engineering and digital twin in different stages of the product’s lifecycle, including design, development, verification, manufacture, acquisition, operation, and maintenance, in a variety of engineering fields such as aerospace, automotive, marine, civil, mechanical, electrical, etc. Integrations and interactions of multi-stage and multi-disciplinary activities, including but not limited to multidisciplinary design analysis and optimization, model-based system engineering, virtual testing, rapid prototype, digital manufacture and assembly, self-awareness and self-control, prognostics and health management, are encouraged. Relevant methods for DEDT, such as physics-based modeling, data-driven modeling, model reduction, model calibration and updating, model adaptation, verification and validation, multi-domain modeling, multi-fidelity modeling, multi-disciplinary simulation, multi-level and multi-scale simulation, model/data fusion, uncertainty quantification, diagnosis and prognosis, risk-based decision-making, and predictive control, are welcomed. Key enabling technologies for DEDT including software development, platform deployment, connection and communication, visualization, as well as other relevant technologies such as the Internet of Things, cloud/edge computing, big data, artificial intelligence, and VR/AR, are also considered.
Starting from July 2023, Digital Engineering and Digital Twin will transition to a continuous publication model, accepted articles will be promptly published online upon completion of the peer review and production processes.
Open Access
ARTICLE
Digital Engineering and Digital Twin, Vol.2, pp. 103-130, 2024, DOI:10.32604/dedt.2024.044545 - 06 May 2024
（This article belongs to the Special Issue: Advances in Methods of Computational Modeling in Engineering Sciences, a Special Issue in Memory of Professor Satya Atluri)
Abstract This paper presents a novel approach to using supervised learning with a shallow neural network to increase the efficiency of the finite element analysis of holes under biaxial load. With this approach, the number of elements in the finite element analysis can be reduced while maintaining good accuracy. The neural network will be used to predict the maximum stress for holes of different configurations such as holes in a finite-width plate (2D), multiple holes (2D), staggered holes (2D), and holes in an infinite plate (3D). The predictions are based on their respective coarse mesh with… More >
Open Access
REVIEW
Digital Engineering and Digital Twin, Vol.2, pp. 79-101, 2024, DOI:10.32604/dedt.2024.047280 - 25 March 2024
（This article belongs to the Special Issue: Advances in Methods of Computational Modeling in Engineering Sciences, a Special Issue in Memory of Professor Satya Atluri)
Abstract A finite element alternating method has been known as a very convenient and accurate method to solve two and three-dimensional crack problems. In this method, a general crack problem is solved by a superposition of two solutions. One is a finite element solution for a finite body without a crack, and the other is an analytical solution for a crack in an infinite body. Since a crack is not considered in a finite element model, generating a model is very simple. The method is especially very convenient for a fatigue crack growth simulation. Over the More >
Open Access
ARTICLE
Digital Engineering and Digital Twin, Vol.2, pp. 49-77, 2024, DOI:10.32604/dedt.2023.044180 - 31 January 2024
（This article belongs to the Special Issue: Advances in Methods of Computational Modeling in Engineering Sciences, a Special Issue in Memory of Professor Satya Atluri)
Abstract This paper mainly considers the formulation and theoretical analysis of the reduced-order numerical method constructed by proper orthogonal decomposition (POD) for nonlocal diffusion problems with a finite range of nonlocal interactions. We first set up the classical finite element discretization for nonlocal diffusion equations and briefly explain the difference between nonlocal and partial differential equations (PDEs). Nonlocal models have to handle double integrals when using finite element methods (FEMs), which causes the generation of algebraic systems to be more challenging and time-consuming, and discrete systems have less sparsity than those for PDEs. So we establish… More >
Open Access
ARTICLE
Digital Engineering and Digital Twin, Vol.2, pp. 33-48, 2024, DOI:10.32604/dedt.2023.044279 - 31 January 2024
（This article belongs to the Special Issue: Advances in Methods of Computational Modeling in Engineering Sciences, a Special Issue in Memory of Professor Satya Atluri)
Abstract In an integrated coal gasification combined cycle plant, cooling pipes are installed in the gasifier reactor and water cooling is executed to avoid reaching an excessively high temperature. To accelerate the design, it is necessary to develop an analysis system that can simulate the cooling operation within the practical computational time. In the present study, we assumed the temperature fields of the cooled object and the cooling water to be governed by the three-dimensional (3D) heat equation and the one-dimensional (1D) convection-diffusion equation, respectively. Although some existing studies have employed similar modeling, the applications have… More >
Open Access
ARTICLE
Digital Engineering and Digital Twin, Vol.2, pp. 1-31, 2024, DOI:10.32604/dedt.2023.044930 - 31 January 2024
Abstract The advent of technology around the globe based on the Internet of Things, Cloud Computing, Big Data, Cyber-Physical Systems, and digitalisation. This advancement introduced industry 4.0. It is challenging to measure how enterprises adopt the new technologies. Industry 4.0 introduced Digital Twins, given that no specific terms or definitions are given to Digital Twins still challenging to define or conceptualise the Digital Twins. Many academics and industries still use old technologies, naming it Digital Twins. This young technology is in danger of reaching the plateau despite the immense benefit to sectors. This paper proposes a… More >
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