Advances in Civil Engineering

Digital Twins in Civil Engineering


Publishing date
01 Mar 2022
Status
Closed
Submission deadline
05 Nov 2021

Lead Editor

1Qingdao University, Qingdao, China

2St. Bonaventure University, Bonaventure, USA

3University of Macedonia, Macedonia, Greece

This issue is now closed for submissions.
More articles will be published in the near future.

Digital Twins in Civil Engineering

This issue is now closed for submissions.
More articles will be published in the near future.

Description

In the construction and civil engineering industries, digital twins are one of the key new technologies used in the Internet of things (IoT). They are usually applied to building information modelling (BIM) technology. Digital twins can create an equivalent virtual entity to physics, which can simulate, analyze, and test physical entities. They can take real data of physics or systems as input. The generated data is used as an output to predict or simulate how the physical object or system has been affected by these inputs.

Digital twins run through different stages of the life cycle of products, including the design stage, manufacturing stage, and service stage. It is widely used in model design, simulation, and virtual debugging. Digital twins have become popular within the process of digital transformation. By 2024, it is estimated that more than 25% of the new digital twins will be adopted as the binding function of the new IoT. Because it can analyze the virtual space and digitally map the interaction with entities, industrial manufacturing and civil engineering can use digital twins to predict the development track of equipment and systems. Therefore, it can greatly improve the situation awareness of businesses. Furthermore, it will guide enterprises to make better decision-making. For instance, businesses with this benefit can have more reasonable maintenance time and a better production scheduling plan.

With the development of the industrial Internet and the connectivity utility of networks, digital twins are connected and complementary in equipment asset management, product life cycle management, and manufacturing process management. The closed loop-based digital twins are formed through the integrated management of raw materials, factory manufacturing, sales, and customer demand. In digital space, a highly accurate digital model is used to describe and simulate the real world. The information collected in the real world is reflected in the digital model and updated with reality. In digital spaces, predictive simulation and visualization are carried out by using models and information. In terms of the business process, digital twins are not only used for modelling. They are also used for the simulation of the whole life cycle. The scope of applying digital twins is broad and is not oriented to specific fields like architecture. Digital twins can be applied to the whole objective world, the universe, and molecular atoms, which can be modelled and simulated in a three-dimensional (3D) way.

The aim of this Special Issue is to bring together original research and review articles discussing the digital twins in civil engineering. We welcome submissions from a wide range of disciplines. However, articles in this Special Issue should focus on the innovation of digital twins to meet the current challenges in civil engineering. Moreover, we welcome research discussing the most effective ways to develop the civil engineering and construction industry rapidly.

Potential topics include but are not limited to the following:

  • Renewal of the construction plan following BIM digital twins in civil engineering
  • Influence of digital twins on physical equipment in construction engineering
  • Intelligent construction with digital twin visualization
  • Design and construction of digital twins supported by artificial intelligence
  • Design and construction of bridge engineering following digital twins
  • Intelligent building construction management based on BIM digital twins
  • Interaction design and planning between virtual and reality-based digital twins
  • Safety emergency and model interconnection in the construction Industry with digital twins
  • Support design of rock tunnel based on digital twins
  • Design and construction of substations based on digital twins

Articles

  • Special Issue
  • - Volume 2022
  • - Article ID 6399515
  • - Research Article

Use of Digital Twins-Based Intelligent Navigation Visual Sensing Technology in Environmental Art Design of Scenic Spots

Chuanbao Sun | Xudong Zhou
  • Special Issue
  • - Volume 2022
  • - Article ID 8273451
  • - Research Article

Research on Intelligent Dispatching System Management Platform for Construction Projects Based on Digital Twin and BIM Technology

Heng Sun | Zhe Liu
  • Special Issue
  • - Volume 2022
  • - Article ID 9311246
  • - Research Article

Digital Visual Sensing Design Teaching Using Digital Twins

Lu Lian | Yao Yan
  • Special Issue
  • - Volume 2022
  • - Article ID 3683216
  • - Research Article

Digital Twins by Physical Education Teaching Practice in Visual Sensing Training System

Xinran Liu | Ji Jiang
  • Special Issue
  • - Volume 2021
  • - Article ID 2801557
  • - Research Article

The Modelling of Digital Twins Technology in the Construction Process of Prefabricated Buildings

Yun Zhou | Xiao Wei | Ying Peng
  • Special Issue
  • - Volume 2021
  • - Article ID 5743387
  • - Research Article

Application of Visual Sensing Image Processing Technology under Digital Twins to the Intelligent Logistics System

Jianjun Miao | Shundong Lan
  • Special Issue
  • - Volume 2021
  • - Article ID 8910274
  • - Research Article

A Theoretical Analysis Method of Spatial Analytic Geometry and Mathematics under Digital Twins

Kaiqi Wang
  • Special Issue
  • - Volume 2021
  • - Article ID 3918524
  • - Research Article

Construction and Application of Recognition Model for Black-Odorous Water Bodies Based on Artificial Neural Network

Zhonghua Xu | Changguo Dai | ... | Lei Jiang
Advances in Civil Engineering
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Acceptance rate42%
Submission to final decision74 days
Acceptance to publication21 days
CiteScore2.600
Journal Citation Indicator0.380
Impact Factor1.843
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Article of the Year Award: Outstanding research contributions of 2021, as selected by our Chief Editors. Read the winning articles.