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Digital Twin Technology in Energy and Environmental Sector

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "B: Energy and Environment".

Deadline for manuscript submissions: 15 May 2024 | Viewed by 6240

Special Issue Editors

School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China
Interests: multiscale simulations; digital twin technology in the energy and environmental sector
CNNC Key Laboratory on Nuclear Reactor Thermal Hydraulics Technology, Nuclear Power Institute of China, Chengdu 610041, China
Interests: digital twin technology; CFD technology; nuclear, thermal, and hydraulic energies
Department of Mechanical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
Interests: multimodal fusion; remote sensing; two-phase cooling
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Guest Editor
Institute of Interdisciplinary Research for Mathematics and Applied Science, School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan 430000, China
Interests: scientific machine learning; uncertainty quantification

Special Issue Information

Dear Colleagues,

We have entered a new digital era. Digital twin technology is promising for applications in building a digital world. Such technology is a virtual representation of a real-world system or process which could be used for many practical purposes, such as system simulation, integration, testing, monitoring, and maintenance. Digital technology application in the energy and environmental sectors is a new, multidisciplinary subject. Multiscale simulation technologies, big data mining, machine learning, sensor, automation, virtual reality, computer vision, etc., are all engaged in this new rising technology.

This Special Issue aims to present and disseminate the most recent advances related to the theory, design, modeling, conception, and application of all types of digital twin technologies in the energy or environmental sectors.

Topics of interest for publication include, but are not limited to, the following:

  • New conceptions of digital twin technology;
  • New conceptions of multiscale simulation using AI algorithms;
  • Machine learning in heat and mass transfer, fluid mechanisms, and thermodynamics;
  • Multiobjective and multiparameter optimization algorithms;
  • VR technology in the energy and environmental sectors;
  • Computer vision in the energy and environmental sectors;
  • Advanced control and monitoring technologies;
  • Physics-informed neural networks;
  • GAN/CNN algorithms in the prediction of multiple physical fields.

Dr. Gui Lu
Dr. Dewen Yuan
Dr. Han Hu
Dr. Xuhui Meng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (6 papers)

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Research

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16 pages, 2819 KiB  
Article
Probabilistic Design Method for Aircraft Thermal Protective Layers Based on Surrogate Models
by Zhongcan Chen, Kai Zhang, Shanshan Zhao, Feng Li, Fengtao Xu and Min Chen
Energies 2024, 17(5), 1051; https://doi.org/10.3390/en17051051 - 23 Feb 2024
Viewed by 436
Abstract
In this study, a probabilistic method was proposed for an aircraft’s thermal protective layers. The uncertainties of material properties, geometric dimensions, and incoming flow environments were considered for the design inputs. To accelerate the design efficiency, Latin hypercube sampling and surrogate models were [...] Read more.
In this study, a probabilistic method was proposed for an aircraft’s thermal protective layers. The uncertainties of material properties, geometric dimensions, and incoming flow environments were considered for the design inputs. To accelerate the design efficiency, Latin hypercube sampling and surrogate models were built based on finite element method calculations to enhance the simulation efficiency. Thus, the Monte Carlo method can be implemented with such a fast simulation method and produce a massive number of samples for the uncertainty quantification and sensitivity analysis, exploring their impact on the back temperature of the thermal protection layer. Compared to the deterministic method with the extreme deviation design, the probabilistic design yields a weight reduction of 15.61%. This indicates that probabilistic design is an efficient approach to enhance the performance of aircraft and reduce the overall weight of the aircraft. The general goal of this study is to provide a new design method for the coating film of thermal protection systems by considering multiple sources of uncertainties. Full article
(This article belongs to the Special Issue Digital Twin Technology in Energy and Environmental Sector)
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20 pages, 3293 KiB  
Article
Comprehensive Evaluation and Scheme Optimization for Power Transmission and Transformation Projects with the Adoption of Carbon Reduction Technologies
by Shuyuan Zhao, Heng Chen, Chengyu Jia, Yinan Wang, Cheng Xin and Xue Jiang
Energies 2024, 17(3), 598; https://doi.org/10.3390/en17030598 - 26 Jan 2024
Viewed by 566
Abstract
To investigate the economic impact of carbon reduction technology on power transmission and transformation projects, carbon reduction technologies adapted to power transmission and transformation projects were investigated, and the evaluation indicator system for cost-benefit in power transmission and transformation projects was established based [...] Read more.
To investigate the economic impact of carbon reduction technology on power transmission and transformation projects, carbon reduction technologies adapted to power transmission and transformation projects were investigated, and the evaluation indicator system for cost-benefit in power transmission and transformation projects was established based on AHP (Analytic Hierarchy Process) and EWM (Entropy Weight Method). Taking 110 kV and 220 kV transmission and transformation projects in a province located in northwest China as an example, a sensitivity analysis was carried out for the weight of each carbon reduction technology. Additionally, based on the evaluation indicator system, eight alternative carbon reduction schemes were proposed, and the net present value and scheme scores were analyzed with TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). The results showed that in the criterion layer of the 110 kV case, the highest proportion of weight is “high-efficiency transformer”, accounting for 34.12%, and in the indicator layer, the highest proportion of weight is “ parasitic losses”, accounting for 12.35%. After conducting error analysis on the 110 kV and 220 kV cases, it was found that the errors were within an acceptable range both in the criterion layer and index layer. Moreover, it is expected to achieve greater economic benefits through lower costs according to Scheme VI, and due to the limitations of carbon reduction technologies and the lack of a relevant policy system, it is difficult to achieve the goal of covering costs with benefits for the eight schemes studied. Full article
(This article belongs to the Special Issue Digital Twin Technology in Energy and Environmental Sector)
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20 pages, 4743 KiB  
Article
A Parametric Physics-Informed Deep Learning Method for Probabilistic Design of Thermal Protection Systems
by Runlin Zhang, Nuo Xu, Kai Zhang, Lei Wang and Gui Lu
Energies 2023, 16(9), 3820; https://doi.org/10.3390/en16093820 - 29 Apr 2023
Viewed by 1306
Abstract
Precise and efficient calculations are necessary to accurately assess the effects of thermal protection system (TPS) uncertainties on aerospacecrafts. This paper presents a probabilistic design methodology for TPSs based on physics-informed neural networks (PINNs) with parametric uncertainty. A typical thermal coating system is [...] Read more.
Precise and efficient calculations are necessary to accurately assess the effects of thermal protection system (TPS) uncertainties on aerospacecrafts. This paper presents a probabilistic design methodology for TPSs based on physics-informed neural networks (PINNs) with parametric uncertainty. A typical thermal coating system is used to investigate the impact of uncertainty on the thermal properties of insulation materials and to evaluate the resulting temperature distribution. A sensitivity analysis is conducted to identify the influence of the parameters on the thermal response. The results show that PINNs can produce quick and accurate predictions of the temperature of insulation materials. The accuracy of the PINN model is comparable to that of a response surface surrogate model. Still, the computational time required by the PINN model is only a fraction of the latter. Considering both computational efficiency and accuracy, the PINN model can be used as a high-precision surrogate model to guide the TPS design effectively. Full article
(This article belongs to the Special Issue Digital Twin Technology in Energy and Environmental Sector)
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13 pages, 3697 KiB  
Article
Investigation of the Vibration Transmission Characteristics of the Aero-Engine Casing System by Rotating Force Exciter
by Jingming Zhao, Xiaolong Hao, Kai Zhang, Yuanyuan Li and Guanghui Zhang
Energies 2023, 16(4), 1873; https://doi.org/10.3390/en16041873 - 14 Feb 2023
Viewed by 1132
Abstract
This work aims to study the dynamic characteristics of an entire aero-engine casing by experiments using a new type of rotating exciter. New vibration sensor layout rules are proposed according to experimental results and vibration transmission characteristics. The vibration response of the aero-engine [...] Read more.
This work aims to study the dynamic characteristics of an entire aero-engine casing by experiments using a new type of rotating exciter. New vibration sensor layout rules are proposed according to experimental results and vibration transmission characteristics. The vibration response of the aero-engine casing is carried out, and the vibration response of different casing measuring points is also studied. The finite element model of the engine casing’s structure is established to obtain the natural frequency of the whole aero-engine casing, which agrees well with the experimental measurement. We find that the vibration acceleration transmission value of the radial measuring point of bearing No. 1, but not the fan sensor, is more suitable for detecting the running state of the fan rotor. In addition, the sensor in the intermediate casing can detect the vibration of the high-pressure rotor. Bolt loosening of the flange has little effect on the vibration transmission characteristics of the casing. This work aims to provide experimental data of whole aero-engine vibration characteristics with a new rotating exciter for the vibration test, which can help optimize the location of the vibration transducer for the engine and the assembly technology design for the whole engine structure. Full article
(This article belongs to the Special Issue Digital Twin Technology in Energy and Environmental Sector)
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Review

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30 pages, 4654 KiB  
Review
Methodology for the Development of Virtual Representations within the Process Development Framework of Energy Plants: From Digital Model to Digital Predictive Twin—A Review
by Martin Hammerschmid, Daniel Cenk Rosenfeld, Alexander Bartik, Florian Benedikt, Josef Fuchs and Stefan Müller
Energies 2023, 16(6), 2641; https://doi.org/10.3390/en16062641 - 10 Mar 2023
Cited by 5 | Viewed by 1692
Abstract
Digital reflections of physical energy plants can help support and optimize energy technologies within their lifecycle. So far, no framework for the evolution of virtual representations throughout the process development lifecycle exists. Based on various concepts of virtual representations in different industries, this [...] Read more.
Digital reflections of physical energy plants can help support and optimize energy technologies within their lifecycle. So far, no framework for the evolution of virtual representations throughout the process development lifecycle exists. Based on various concepts of virtual representations in different industries, this review paper focuses on developing a novel virtual representation framework for the process development environment within the energy sector. The proposed methodology enables the continuous evolution of virtual representations along the process development lifecycle. A novel definition for virtual representations in the process development environment is developed. Additionally, the most important virtual representation challenges, properties, and applications for developing a widely applicable framework are summarized. The essential sustainability indicators for the energy sector are listed to standardize the process evaluation throughout the process development lifecycle. The virtual representation and physical facility development can be synchronized by introducing a novel model readiness level. All these thoughts are covered through the novel virtual representation framework. Finally, the digital twin of a Bio-SNG production route is presented, to show the benefits of the methodology through a use case. This methodology helps to accelerate and monitor energy technology developments through the early implementation of virtual representations. Full article
(This article belongs to the Special Issue Digital Twin Technology in Energy and Environmental Sector)
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Other

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17 pages, 5700 KiB  
Technical Note
DC Active Damper Control Strategy Based on Resonance Suppression Effectiveness Evaluation Method
by Huaying Zhang, Yingxin Wang, Xinyi Zhu, Yonghai Xu and Shun Tao
Energies 2024, 17(2), 480; https://doi.org/10.3390/en17020480 - 18 Jan 2024
Viewed by 508
Abstract
With the complication of the power system, features of the resonance interaction behave diversely and pose a threat to the effectiveness of the resonance suppression strategies. Existing resonance suppression strategies are usually designed for specific scenarios which are in close correlation with the [...] Read more.
With the complication of the power system, features of the resonance interaction behave diversely and pose a threat to the effectiveness of the resonance suppression strategies. Existing resonance suppression strategies are usually designed for specific scenarios which are in close correlation with the impedance frequency-amplitude distribution, and their adaptability under different scenarios is hard to evaluate. In this paper, the resonance suppression domain of a DC distribution network is derived based on the node impedance variation before/after the resonance is suppressed. The derived criterion takes the admittance change of the resonance suppression strategies as variables, and the conservative/ideal suppression domain criteria are defined. On this basis, a method for evaluating the effectiveness of resonance suppression strategies is proposed, which simplifies the evaluation process and avoids a complicated matrix inverse process to each resonance suppression strategy during the system impedance calculation. Furthermore, a DC active damper control strategy based on the resonance suppression strategy evaluation is proposed, and the proposed strategy could suppress resonances under different scenarios by a targeted design of the reshaping admittance parameters. Time domain simulations with a 5-node distribution network are carried out to verify the proposed method. Full article
(This article belongs to the Special Issue Digital Twin Technology in Energy and Environmental Sector)
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