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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (10 December 2021) | Viewed by 7874

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Prof. Dr. Anton A. Zhilenkov

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Department of Control Systems and Informatics, Saint Petersburg State Marine Technical University, Saint Petersburg (ex Leningrad), Russia
Interests: adaptive and robust control; artificial intelligence; FPGA, SoC, embedded systems; machine learning; robotics systems
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Prof. Dr. Sergei Chernyi

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Artificial Intelligence Laboratory, St. Petersburg State Marine Technical University, 190121 Saint Petersburg, Russia
Interests: cyber-physical systems; automatic control; artificial intelligence; maritime
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Special Issue Information

Dear Colleagues,

This Special Issue is devoted to leading articles on the problems of analysis, design, modeling and control of advanced cyber–physical systems for engines and power systems, as well as related problems and areas of scientific and practical research. The transition to the paradigm of cyber–physical systems, a feature of which is the tightly coupled integration and coordination of computing elements, communication components and physical resources, makes it possible to obtain systems with new capabilities for their consumers. In such systems, all elements are interconnected so that they can no longer be considered separately. The study of such systems implies research in the field of embedded computers, control theory, sensor and communication networks, and physical resources. Their joint work must be explored together, and this is what sets this emerging field of research apart. Even more advanced results can be obtained using artificial intelligence and machine learning technologies, decision theory and knowledge discovery. For the design of cyber–physical systems, it is necessary to model, analyze and verify the entire system, as well as its components, to ensure security, performance and fault-tolerance of the system.

Prof. Dr. Anton A. Zhilenkov
Prof. Dr. Sergei Chernyi
Guest Editors

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Keywords

Cyber-physical system
Complex systems
Smart systems
Power system
Engines

Published Papers (4 papers)

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Research

13 pages, 410 KiB

Open AccessArticle

Integrated Estimation of a Cyber-Physical System’s Sustainability

by Elena Schislyaeva, Elena Balashova, Inna Krasovskaya, Olga Saychenko and Elena Palkina

Energies 2022, 15(2), 563; https://doi.org/10.3390/en15020563 - 13 Jan 2022

Cited by 2 | Viewed by 1451

Abstract

Currently, in conditions of Industry 4.0, the use of cyber-physical systems in various fields is becoming widespread. This article is devoted to the problem of estimating CPS sustainability in the context of modern challenges faced by decision makers and IT developers in order to ensure effective proactive business process management using this innovative technology. The purpose of the research is to propose and substantiate a methodology for estimating CPS sustainability to ensure the reliability and strength of its elements, their interrelationships and interaction, as well as the effective functioning and development of this system in conditions of high dynamism and uncertainty of the external environment. In this study, we used methods of integral evaluation, synthesis, expert assessments, dynamic analysis, and systematic approach, and coined the term ‘CPS sustainability’. Our study showed that negative risks, external and internal threats may have a significant adverse impact on CPS sustainability. The reliability of this system should be evaluated on the basis of integrated indicators. The key indicators, reflecting the reliability of maintaining the properties of the CPS in a normal state of its function and further development, were identified. We propose a methodology for estimating CPS sustainability. In general, the presented results form the basis for improving CPS management to increase the effectiveness and efficiency of its functioning and development. Full article

(This article belongs to the Special Issue Advanced Cyber-Physical System for Engines and Power System)

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12 pages, 2300 KiB

Open AccessArticle

Application of Artificial Intelligence Technologies to Assess the Quality of Structures

by Anton Zhilenkov, Sergei Chernyi and Vitalii Emelianov

Energies 2021, 14(23), 8040; https://doi.org/10.3390/en14238040 - 01 Dec 2021

Cited by 9 | Viewed by 1628

Abstract

The timeliness of the complex automated diagnostics of the metal condition for all characteristics has been substantiated. An algorithm for the automation of metallographic quality control of metals is proposed and described. It is based on the use of neural networks for recognizing images of metal microstructures and a precedent method for determining the metal grade. An approach to preliminarily process the images of metal microstructures is described. The structure of a neural network has been developed to determine the quantitative characteristics of metals. The results of the functioning of neural networks for determining the quantitative characteristics of metals are presented. The high accuracy of determining the characteristics of metals using neural networks is shown. Software has been developed for the automated recognition of images of metal microstructures, and for the determination of the metal grade. Comparative results of carrying out metallographic analysis with the developed tools are demonstrated. As a result, there is a significant reduction in the time required for analyzing metallographic images, as well as an increase in the accuracy of determining the quantitative characteristics of metals. The study of this problem is important not only in the metallurgical industry, but also in production, the maritime industry, and other engineering fields. Full article

(This article belongs to the Special Issue Advanced Cyber-Physical System for Engines and Power System)

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23 pages, 7634 KiB

Open AccessArticle

Standard and Modified SST Models with the Consideration of the Streamline Curvature for Separated Flow Calculation in a Narrow Channel with a Conical Dimple on the Heated Wall

by Sergey Isaev, Dmitry Nikushchenko, Alexandr Sudakov, Nikita Tryaskin, Ann Egorova, Leonid Iunakov, Alexandr Usachov and Valery Kharchenko

Energies 2021, 14(16), 5038; https://doi.org/10.3390/en14165038 - 17 Aug 2021

Cited by 4 | Viewed by 1759

Abstract

The testing of the standard and modified SST models of the transfer of shear stresses was carried out on an example of calculating the heat transfer with an intense detached flow around a conical dimple with a slope angle of

45 °

on [...] Read more.

45 °

on the heated wall of a narrow channel. It was shown that the standard turbulence model by Menter SST (MSST) of 2003, widely used in the packages Fluent, CFX, StarCCM+, etc., significantly underestimated the intensity of the return flow. A correction of this model was presented that took into account the influence of the curvature of streamlines within the framework of the Rodi-Leshziner-Isaev (RLI) approach for spatial separated flows. It was found that the predictions for the RLI MSST 2003 were close to the predictions for the original standard MSST 1993, in which the eddy viscosity was calculated using the vorticity modulus. At the same time, the predictions based on the modified one, following Smirnov-Menter (SM) MSST 2003, included in the ANSYS model catalog did not differ too much from the standard MSST 2003. The preference of the MSST modified within the RLI 2003 for calculating the heat transfer in intense separated flows was substantiated. Full article

(This article belongs to the Special Issue Advanced Cyber-Physical System for Engines and Power System)

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22 pages, 1890 KiB

Open AccessArticle

Multiparameter Optimization of Thrust Vector Control with Transverse Injection of a Supersonic Underexpanded Gas Jet into a Convergent Divergent Nozzle

by Vladislav Emelyanov, Mikhail Yakovchuk and Konstantin Volkov

Energies 2021, 14(14), 4359; https://doi.org/10.3390/en14144359 - 19 Jul 2021

Cited by 8 | Viewed by 2161

Abstract

The optimal design of the thrust vector control system of solid rocket motors (SRMs) is discussed. The injection of a supersonic underexpanded gas jet into the diverging part of the rocket engine nozzle is considered, and multiparameter optimization of the geometric shape of the injection nozzle and the parameters of jet injection into a supersonic flow is developed. The turbulent flow of viscous compressible gas in the main nozzle and injection system is simulated with the Reynolds-averaged Navier–Stokes (RANS) equations and shear stress transport (SST) turbulence model. An optimization procedure with the automatic generation of a block-structured mesh and conjugate gradient method is applied to find the optimal parameters of the problem of interest. Optimization parameters include the pressure ratio of the injected jet, the angle of inclination of the injection nozzle to the axis of the main nozzle, the distance of the injection nozzle from the throat of the main nozzle and the shape of the outlet section of the injection nozzle. The location of injection nozzle varies from 0.1 to 0.9 with respect to the length of the supersonic part of the nozzle; the angle of injection varies from 30 to 160 degrees; and the shape of the outlet section of the injection nozzle is an ellipse with an aspect ratio that varies from 0.1 to 1. The computed fluid flow in the combustion chamber is compared with experimental and computational results. The dependence of the thrust as a function of the injection parameters is obtained, and conclusions are made about the effects of the input parameters of the problem on the thrust coefficient. Full article

(This article belongs to the Special Issue Advanced Cyber-Physical System for Engines and Power System)

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