scholarly journals Simulation Models of Production Plants as a Tool for Implementation of the Digital Twin Concept into Production

2020 ◽  
Vol 20 (4) ◽  
pp. 527-533
Author(s):  
Erika Sujová ◽  
Daniela Vysloužilová ◽  
Helena Čierna ◽  
Roman Bambura
Keyword(s):  
Simulation Models ◽  
Digital Twin

Mooring Integrity Management through Digital Twin and Standardized Inspection Data

2021 ◽  
Author(s):  
Shunsaku Matsumoto ◽  
Vivek Jaiswal ◽  
Tadashi Sugimura ◽  
Shintaro Honjo ◽  
Piotr Szalewski
Keyword(s):  
Simulation Models ◽  
Sensitivity Analyses ◽  
Maintenance Cost ◽  
Digital Twin ◽  
Diagnosis And Prognosis ◽  
Twin System ◽  
Physics Simulation ◽  
Integrity Management ◽  
Risk Visualization ◽  
Inspection Data

Abstract This paper presents a concept of a mooring digital twin frameworkand a standardized inspection datatemplate to enable digital twin. The mooring digital twin framework supports real-time and/or on-demand decision making in mooring integrity management, which minimizes the failure risk while reducing operation and maintenance cost by efficient inspection, monitoring, repair, and strengthening. An industry survey conducted through the DeepStar project 18403 identified a standard template for recording inspection data as a high priority item to enable application of the digital twins for integrity management. Further, mooring chain was selected as a critical mooring component for which a standard inspection template was needed. The characteristics of damage/performance prediction with the proposed mooring digital twin framework are (i) to utilize surrogates and/or reduced-order models trained by high-fidelity physics simulation models, (ii) to combine all available lifecycle data about the mooring system, (iii) to evaluate current and future asset conditions in a systematic way based on the concept of uncertainty quantification (UQ). The general and mooring-specific digital twin development workflows are described with the identified essential data, physics models, and several UQ methodologies such as surrogate modeling, local and global sensitivity analyses, Bayesian prediction etc. Also, the proposed digital twin system architecture is summarized to illustrate the dataflow in digital twin development andutilization. The prototype of mooring digital twin dashboard, web-based risk visualization and advisory system, is developed to demonstrate the capability to visualize the system health diagnosis and prognosis and suggest possible measures/solutions for the high-risk components as a digital twin's insight.

Digital Twin-Driven Condition-Based Maintenance

2022 ◽  
pp. 109-136
Author(s):  
Adolfo Crespo del Castillo ◽  
Marco Macchi ◽  
Laura Cattaneo
Keyword(s):  
Real Time ◽  
Industry 4.0 ◽  
Simulation Models ◽  
Condition Based Maintenance ◽  
Industrial Management ◽  
Digital Twin ◽  
Operation And Maintenance ◽  
Twin Models ◽  
Technical Professionals ◽  
Case Development

The world is witnessing an all-level digitalization that guides the industry and business to a restructuration in order to adapt to the new requirements of the surrounding environment. That change also concerns the labour of the technical professionals and their formation. As a consequence of this deep consciousness-raising, this chapter will investigate and develop simulation models based on the current digitalization. The aim of this chapter is the exposition of a real case development of “digital twin” models framed as part of the condition-based maintenance paradigm to improve real-time assets operation and maintenance. This model contributes by providing real-time results that could turn into a basis for the industrial management decisions and place them in the Industry 4.0 paradigm environment.

scholarly journals Digital twin of the management process of field service teams of an electric grid company

2021 ◽  
Vol 2090 (1) ◽  
pp. 012015
Author(s):  
A R Kinzhalieva ◽  
O M Protalinskiy ◽  
A A Khanova ◽  
I O Bondareva
Keyword(s):  
System Dynamics ◽  
Simulation Models ◽  
System Component ◽  
Management Process ◽  
System Dynamics Model ◽  
Dynamics Model ◽  
Electric Grid ◽  
Digital Twin ◽  
Field Service ◽  
Use Of Resources

Abstract Modern electric grid companies are focused on minimum economically feasible costs and are aimed at improving the efficiency of financial and economic activities through the rational use of resources. The digital twin structure is proposed for the management of field service teams in the event of accidents and technological failures in an electric grid company. The digital twin includes an agent model, a system dynamics model, a geographic information system component, and modules with experiments. The description of the simulation model of management of field service teams in the event of accidents and technological failures is formalized, the input and output information on the model components is highlighted, the information is structured, and the scheme of the system dynamics model is created. Experiment designs for the digital twin of the management of field service teams in the event of accidents and technological failures in order to determine the best reliability and cost indicators are developed. The developed approach can be used to create digital twins of the management process of field service teams in the event of accidents and technological failures for various electric grid companies by selecting the parameters of simulation models according to the statistical reports by electric grid companies and connecting the appropriate GIS modules.

scholarly journals Continuous calibration of a digital twin: Comparison of particle filter and Bayesian calibration approaches

2021 ◽  
Vol 2 ◽  
Author(s):  
Rebecca Ward ◽  
Ruchi Choudhary ◽  
Alastair Gregory ◽  
Melanie Jans-Singh ◽  
Mark Girolami
Keyword(s):  
Particle Filter ◽  
Simulation Models ◽  
Bayesian Calibration ◽  
Digital Twin ◽  
Calibration Parameter ◽  
New Methods ◽  
Model Fidelity ◽  
Model Element ◽  
Parameter Values

Abstract Assimilation of continuously streamed monitored data is an essential component of a digital twin; the assimilated data are used to ensure the digital twin represents the monitored system as accurately as possible. One way this is achieved is by calibration of simulation models, whether data-derived or physics-based, or a combination of both. Traditional manual calibration is not possible in this context; hence, new methods are required for continuous calibration. In this paper, a particle filter methodology for continuous calibration of the physics-based model element of a digital twin is presented and applied to an example of an underground farm. The methodology is applied to a synthetic problem with known calibration parameter values prior to being used in conjunction with monitored data. The proposed methodology is compared against static and sequential Bayesian calibration approaches and compares favourably in terms of determination of the distribution of parameter values and analysis run times, both essential requirements. The methodology is shown to be potentially useful as a means to ensure continuing model fidelity.

scholarly journals Development of 2D models of the magnetic field for digital twin technology and generative design of power transformers

Vestnik IGEU ◽  
2020 ◽  
pp. 32-43
Author(s):  
A.I. Tikhonov ◽  
A.V. Stulov ◽  
I.S. Snitko ◽  
A.V. Podobnyj
Keyword(s):  
Power Transformer ◽  
Simulation Models ◽  
3D Models ◽  
Dirichlet Boundary Conditions ◽  
Generative Design ◽  
Matlab Simulink ◽  
Digital Twin ◽  
Digital Twins ◽  
Urgent Task ◽  
Tech Nologies

The development of generative design technologies that solve the problems of structural optimization and digital twins, that is simulation models of devices with at least 95 % accuracy, is an urgent task. These tech-nologies are usually implemented on the basis of 3D models of physical fields, for example, using ANSYS Maxwell or COMSOL Multiphysics packages, which are demanding in terms of computer resources and de-signer skills. However, the sufficient accuracy for transformer digital twins can be achieved using chain and 2D field models. The article aims to develop the models to calculate the transformer with the accuracy and ability to take into account the design features of a particular device, which is characteristic of digital twins. This can be used in generative design of transformers and in the study of their operation modes. The finite element method implemented via the authoring EMLib library which allows calculating magnetic fields in a 2D formulation was used. The simulation methods using the MatLab Simulink SymPowerSystem package were also employed. The assumptions made during the power transformer simulation have been estimated. They include the possibility of using chain and 2D field models without taking into account the steel anisotropy with Dirichlet boundary conditions when calculating the scattering fluxes. 2D field models have been developed for calculating the main flux and scattering fluxes, which are able to form the basis for digital twin technology and generative design of transformers. A simulation model of a transformer implemented in MatLab Simulink has been provided. The possibility of using the models for diagnosing transformer faults has been demonstrated. The simulation results of a transformer with a defect have been presented. The results obtained can be used in the development of transformers to search for optimal designs and to study the results of design decisions without creating prototypes. The findings can also be applied while operating the transformers to assess the damage and failures without dismantling and according to the test results.

scholarly journals Technology for the soft implementing a digital twin into the IoT HVAC control loop

2021 ◽  
Vol 16 (95) ◽  
pp. 33-47
Author(s):  
Aleksey V. Kychkin ◽  
◽  
Oleg V. Gorshkov ◽  
Vladislav A. Selivanov ◽  
Vitaliy A. Pavlov ◽  
...  
Keyword(s):  
Simulation Models ◽  
Ventilation Network ◽  
Control Loop ◽  
Industrial Facilities ◽  
Control Loops ◽  
Digital Twin ◽  
Iot Platform ◽  
Distribution Process ◽  
Dynamic Simulation Model ◽  
Hvac Control

The development of application software for cyber-physical systems of buildings involves the widespread use of Internet of Things (IoT) integration platforms. In practice, the flexible functionality of IoT platforms often leads to additional costs for software enhancement of existing and connection of new units, in particular digital twins. The paper proposes a technological solution for the implementation of a digital twin of the ventilation process in the IoT control loop of heating, ventilation and air conditioning (HVAC) systems for buildings and industrial facilities. The implementation and execution of the digital twin in the form of a dynamic simulation model in the object-oriented modelling language Modelica in the OpenModelica environment is considered. The IoT platform InfluxData, based on the TICK stack, is considered as an example of an integration environment. It is a horizontally-oriented IoT platform that contains the mechanism for collecting data from devices and the InfluxDB time-series database for storing metrics. To integrate simulation models on Modelica with InfluxDB, an OMPython server is proposed. In this case, the integration scripts are executed in the Python language, which as a result extends the traditional capabilities of the IoT platform significantly to the level of a digitally twinned control system. This HVAC control involves adapting control loops by taking into account the dynamics of the air distribution process over the ventilation network, evaluating and compensating for process inertia. The publication was prepared within the framework of the Academic Fund Program at the HSE University in 2020–2021 (grant № 21-04-039).

Correlation of Pore Structure and Permeability by SEM-Image Analysis

1990 ◽  
Vol 48 (1) ◽  
pp. 428-429
Author(s):  
C. A. Callender ◽  
Wm. C. Dawson ◽  
J. J. Funk
Keyword(s):  
Image Analysis ◽  
Pore Structure ◽  
Imaging System ◽  
Pore Space ◽  
Simulation Models ◽  
Image Analyzer ◽  
Imaging Data ◽  
Sem Images ◽  
Thin Sections ◽  
Rock Types

The geometric structure of pore space in some carbonate rocks can be correlated with petrophysical measurements by quantitatively analyzing binaries generated from SEM images. Reservoirs with similar porosities can have markedly different permeabilities. Image analysis identifies which characteristics of a rock are responsible for the permeability differences. Imaging data can explain unusual fluid flow patterns which, in turn, can improve production simulation models.Analytical SchemeOur sample suite consists of 30 Middle East carbonates having porosities ranging from 21 to 28% and permeabilities from 92 to 2153 md. Engineering tests reveal the lack of a consistent (predictable) relationship between porosity and permeability (Fig. 1). Finely polished thin sections were studied petrographically to determine rock texture. The studied thin sections represent four petrographically distinct carbonate rock types ranging from compacted, poorly-sorted, dolomitized, intraclastic grainstones to well-sorted, foraminiferal,ooid, peloidal grainstones. The samples were analyzed for pore structure by a Tracor Northern 5500 IPP 5B/80 image analyzer and a 80386 microprocessor-based imaging system. Between 30 and 50 SEM-generated backscattered electron images (frames) were collected per thin section. Binaries were created from the gray level that represents the pore space. Calculated values were averaged and the data analyzed to determine which geological pore structure characteristics actually affect permeability.

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