• Journal of the Korea Society for Simulation
• /
• v.32 no.3
• /
• pp.33-41
• /
• 2023

As carbon-free has been getting interest, renewable energy sources have been increasing. However, renewable energy is intermittent and variable so it is difficult to predict the produced electrical energy from a renewable energy source. In this study, digital-twin concept is applied to solve difficulties in predicting electrical energy from a renewable energy source. Considering that rotation of wind turbine has high correlation with produced electrical energy, a model which simulates rotation in the drivetrain of a wind turbine is developed. The base of a drivetrain simulation model is set with well-known state equation in mechanical engineering, which simulates the rotating system. Simulation based machine learning is conducted to get unknown parameters which are not provided by manufacturer. The simulation is repeated and parameters in simulation model are corrected after each simulation by optimization algorithm. The trained simulation model is validated with 27 real wind turbine operation data set. The simulation model shows 4.41% error in average compared to real wind turbine operation data set. Finally, it is assessed that the drivetrain simulation model represents the real wind turbine drivetrain system well. It is expected that wind-energy-prediction accuracy would be improved as wind turbine digital twin including the developed drivetrain simulation model is applied.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.5
• /
• pp.935-940
• /
• 2023

Digital-twin technology is emerging as an innovative solution for all industries, including manufacturing and production lines. Therefore, this paper optimizes all the energy used in a biomass plant based on unused resources. We will then implement a digital-twin prototype for biomass plants and evaluate its performance in order to improve the efficiency of plant operations. The proposed digital-twin prototype applies a standard communication platform between the framework and the gateway and is implemented to enable real-time collaboration. and, define the message sequence between the client server and the gateway. Therefore, an interface is implemented to enable communication with the host server. In order to verify the performance of the proposed prototype, we set up a virtual environment to collect data from the server and perform a data collection evaluation. As a result, it was confirmed that the proposed framework can contribute to energy optimization and improvement of operational efficiency when applied to biomass plants.

• Journal of Convergence for Information Technology
• /
• v.10 no.9
• /
• pp.1-7
• /
• 2020

In order to implement a smart factory for manufacturing innovation, more digital twins will be developed and applied gradually. In particular, simulation and optimization of digital twins makes it possible to support critical decision-making like a predictive maintenance of the equipment for manufacturing. In terms of a user perspective, this study suggests the conceptual framework of Digital Twin Management System (DTMS) for supporting the analytical and managerial activities for Digital Twins. We integrate the methods and structure of the area like Manufacturing Engineering, Decision Support Systems, and Optimization for developing the DTMS. The framework suggested in this study shows a typical DSS which consists of dialog management system, model management system and data management system. It also includes Analytical Digital Twins and simulations & optimization module. The framework is being applied in one of the most competitive and complex industrial sector. Also this study is meaningful to suggest a new direction of research.

• Journal of Industrial Convergence
• /
• v.19 no.1
• /
• pp.65-70
• /
• 2021

This study aims to propose specific directions for developing digital twin contents. This aim is achieved by thorough literature review and applying the grounded theory. Based on customers' need analysis, this study suggests the priorities of contents development of digital twins. As a result, complex workflows and dangerous training contents are adequate to be developed. Moreover, large-scale projects such as nuclear powerplants that are hard to build the mock-ups were considered to be effective. This study provides significant information for not only software developers but also clients who desire to reduce training fees and improve the complex workflows. Since these client companies operate based upon multiple complex workflows, this study encourages stakeholders to make effective decisions. This research needs further analysis of current digital twin technology- possibilities and limitations.

• Journal of KIBIM
• /
• v.13 no.1
• /
• pp.1-12
• /
• 2023

The number of old buildings in Korea is increasing. According to a report from the Ministry of Land, Infrastructure and Transport, the proportion of old buildings increased from 29.0% in 2005 to 37.8% in 2009. However, the ratio of repairs to improve usability and improve the environment through problem improvement The proportion of old buildings was 72% in 2010, but decreased to 38% in 2020 and does not exceed 40%. The reason is that the difficulty of remodeling old buildings is more difficult than repairing new ones, and business estimates are difficult to predict. Accurately reflecting the current condition of a building in a repair project has a huge impact on time and budget. Accurate and detailed measurements are essential. Current repair methodologies require a lot of manpower, time and money to remodel an old building. Therefore, it is necessary to improve the remodeling methodology applied in the field. In this study proposed a Digital-Twin-based remodeling process that introduced various digital technologies such as 3D Scanning, BIM, Reverse Engineering, and Digital Fabrictation in consideration of the latest technologies used in recent construction projects. In addition, the process proposed in this study was applied to an actual small-scale building remodeling project and the results were analyzed. In addition, useful basic data were provided for the establishment of plans related to the repair process of buildings in the future.

• Earthquakes and Structures
• /
• v.22 no.5
• /
• pp.503-515
• /
• 2022

This paper presents the development of seismic fragility curves for a precast reinforced concrete bridge instrumented with a structural health monitoring (SHM) system. The bridge is located near an active seismic fault in the Dominican Republic (DR) and provides the only access to several local communities in the aftermath of a potential damaging earthquake; moreover, the sample bridge was designed with outdated building codes and uses structural detailing not adequate for structures in seismic regions. The bridge was instrumented with an SHM system to extract information about its state of structural integrity and estimate its seismic performance. The data obtained from the SHM system is integrated with structural models to develop a set of fragility curves to be used as a quantitative measure of the expected damage; the fragility curves provide an estimate of the probability that the structure will exceed different damage limit states as a function of an earthquake intensity measure. To obtain the fragility curves a digital twin of the bridge is developed combining a computational finite element model and the information extracted from the SHM system. The digital twin is used as a response prediction tool that minimizes modeling uncertainty, significantly improving the predicting capability of the model and the accuracy of the fragility curves. The digital twin was used to perform a nonlinear incremental dynamic analysis (IDA) with selected ground motions that are consistent with the seismic fault and site characteristics. The fragility curves show that for the maximum expected acceleration (with a 2% probability of exceedance in 50 years) the structure has a 62% probability of undergoing extensive damage. This is the first study presenting fragility curves for civil infrastructure in the DR and the proposed methodology can be extended to other structures to support disaster mitigation and post-disaster decision-making strategies.

• Journal of Practical Engineering Education
• /
• v.16 no.1_spc
• /
• pp.1-9
• /
• 2024

The introduction of smart factory digital twins is a concept that has already been proposed to increase productivity in the manufacturing industry through CPS(Cyber Physics System), and has been applied to specific industrial process stages or partially introduced in stages where simulation is required. However, with the recent development of the 4th Industrial Revolution technology, it is receiving attention again along with XR (Extended Reality) technology. However, because there are not many effective cases, this study analyzed the devices, equipment, and technology of the manufacturing process to build a digital twin applying digital threads and synchronized signals and information to control, remote control, and produce intelligent process automation equipment. A platform capable of analyzing information was proposed and developed. Through this, we designed and built an XR content service platform that can support artificial intelligence and developed it to enable control, remote control, and analysis of production information. A possible platform was proposed and developed. We hope that this study will be helpful in conducting research on many cases, and in the future, expanded research on increasing productivity in each part of the process and production is needed through intelligent models.

• Clean Technology
• /
• v.28 no.1
• /
• pp.63-78
• /
• 2022

Electronics industrial wastewater treatment facilities release organic wastewaters containing high concentrations of organic pollutants and more than 20 toxic non-biodegradable pollutants. One of the major challenges of the fourth industrial revolution era for the electronics industry is how to treat electronics industrial wastewater efficiently. Therefore, it is necessary to develop an electronics industrial wastewater modeling technique that can evaluate the removal efficiency of organic pollutants, such as chemical oxygen demand (COD), total nitrogen (TN), total phosphorous (TP), and tetramethylammonium hydroxide (TMAH), by digital twinning an electronics industrial organic wastewater treatment facility in a cyber physical system (CPS). In this study, an electronics industrial wastewater activated sludge model (e-ASM) was developed based on the theoretical reaction rates for the removal mechanisms of electronics industrial wastewater considering the growth and decay of micro-organisms. The developed e-ASM can model complex biological removal mechanisms, such as the inhibition of nitrification micro-organisms by non-biodegradable organic pollutants including TMAH, as well as the oxidation, nitrification, and denitrification processes. The proposed e-ASM can be implemented as a Water Digital Twin for real electronics industrial wastewater treatment systems and be utilized for process modeling, effluent quality prediction, process selection, and design efficiency across varying influent characteristics on a CPS.

• Computational Structural Engineering
• /
• v.31 no.4
• /
• pp.4-11
• /
• 2018

• Journal of Drive and Control
• /
• v.21 no.2
• /
• pp.82-85
• /
• 2024