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A clean solar hydrail, a locomotive operated by solar and hydrogen energy, has received significant attention as an alternative to a current fossil fuel-based locomotive. Nevertheless, the feasibility test of solar hydrail is still challenging since it has not yet been practically developed. Herein, we employed digital twin technology to design and operate solar hydrail and diesel locomotive. 30 years of operation simulation starting from 2021 was conducted based on the data of Gangwon-do, South Korea. It was confirmed that replacing the single diesel locomotive with solar hydrail can provide about 59 % lower net present cost and annual harmful emission reduction of approximately 300 tons. Sensitivity analyses were also conducted to mitigate future uncertainty, and the solar hydrail was a better option than the diesel locomotive in every scenario. This study demonstrates that solar hydrail is the successful substitute for the diesel locomotive currently operated in South Korea. • 30 years of operation was simulated for solar hydrail and diesel locomotive. • Solar hydrail can have $2,026,279 lower NPC than diesel locomotive. • Solar hydrail yearly saves about 300 tons of emissions compared to diesel locomotive. [ABSTRACT FROM AUTHOR]

Digital twin (DT) has been around for many years, but there is no widely accepted standardized tool or method. In this study, system dynamics was proposed as a tool that can be integrated into multi‐scale, multi‐physics, and multi‐disciplinary, which are continuously becoming issues in the DT field. Various heterogeneous data from multiple protocols or platforms could be integrated into one model. Through the five‐step model building process, it was possible to integrate the theories and various models studied in the past. In this study, the operation and maintenance system of ROK Naval ships is implemented as a proposed method. Various physics, scales, and disciplines such as failures of ships, maintenance ability of repair shops, and schedule pressure of mechanics were reflected. It was possible to observe non‐intuitive correlations and potential problems caused by the latent effect of the high‐fidelity DT model. The proposed method is also capable of updating through continuous data calibration or real‐time interworking with external statistical analysis tools. [ABSTRACT FROM AUTHOR]

This paper presents an innovative digital twin dam and watershed management platform, K-Twin SJ, that utilizes real-time data and simulation models to support decision-making for flood response and water resource management. The platform includes a GIS-based geospatial digital twin of the entire Sumjin dam and river water system in Korea, with high-precision geospatial topography and facility information for dams and rivers (watershed area 4913 km2, river length 173 km, and 91 water infrastructures). The platform synchronizes real-time data such as rainfall, dam and river water levels, flow rate, and closed-circuit television (CCTV), and incorporates three hydraulic and hydrological simulation models for efficient dam operation considering the river conditions. AI technology is also used to predict the river water level and suggest optimal dam discharge scenarios. Additionally, the platform includes a geotechnical safety evaluation module for river levees, advanced drone monitoring for dams and rivers, and an AI CCTV video surveillance function. The digital-twin-based platform supports efficient decision-making for smart flood responses and contributes to reducing flooding damage and optimal operation through better smart water management. [ABSTRACT FROM AUTHOR]

• We propose a participatory modeling framework in the context of urban pluvial floods. • A trade-off between the detail of digital twin and the level of citizen participation. • We identify four components of optimal participatory modeling that can create synergy. • A case study presenting every modeling framework without real participant recruitment. The recent advancement in digital twin technology, which creates virtual replicas of real-world processes, offers an interactive testbed for understanding and predicting environmental changes. As pluvial flood damage escalates globally in urban areas, there remains a gap in understanding the most effective collaboration between governments and local residents for sustainable flood risk management. To address this gap, we develop a participatory framework for urban pluvial flood modeling, incorporating open source software, virtual reality, minimum viable product, and gamification components. This framework engages citizens in every phase of the participatory modeling process, from input data preparation, through hydrological model construction, to model verification, and experiments. We present a case study on the recurring pluvial flood damages in South Korea's Gangnam region, demonstrating the practical implications of an interactive, web-based crowdsourcing platform to leverage community engagement and local knowledge. The results underscore the evidence of a proactive role for citizens, not merely as recipients of disaster information but as key contributors collaborating with a range of stakeholders in stormwater management and modeling. Combining digital twin technology with citizen participation can empower informed decision-making and collective actions in the evolving digital era, leading to a disaster-resilient community. [ABSTRACT FROM AUTHOR]

With the expansion of digital transformation based on new technologies, the digital twin bureaucracy (DTB) emerges as a distinct type of 21st-century bureaucracy. The digital twin bureaucracy is defined as a digital replica of the bureaucracy in the physical world. Although the digital twin is formed based on new information and communication technology and physical bureaucracy data, it will control the physical bureaucracy through autonomous decision-making on matters of public affairs. Feedback from the physical world serve as input and update to the digital twin in this cyclical course of interactions. This study explores the technological figures and benefits of the digital twin bureaucracy based on a case analysis of the Sejong City Digital Twin Project in South Korea. It also compares the characteristics of the DTB and those of Max Weber's "ideal-type" bureaucracy. Based on this theoretical and empirical analysis, the paper presents the challenges and concerns of building the DTB. [ABSTRACT FROM AUTHOR]

In this paper, a digital twin-based assessment framework is proposed to determine which energy-saving technologies and strategies will work best in existing buildings. The proposed framework is based on a digital twin that integrates the existing building's hardware system, the building's operational schedule database, and a probabilistic model of occupant behavior. A digital model was constructed based on field measurements and database integration for a case study involving nine university buildings and 55 classrooms. As a result, in the classrooms involved in the case study, the lighting was turned on in the absence of occupants for an average of 10.7 h a day. The results indicate that it is very important to turn off the lights after the last hour of use in university classrooms in South Korea and that it is possible to reduce power consumption by more than 60% by employing an off strategy involving a passive infrared sensor or manager. Additionally, LED lighting in most classrooms is over-designed, which indicates that 46% of the energy consumed can be saved by adjusting the luminance level to an appropriate range. [ABSTRACT FROM AUTHOR]

The digital twin (DT) model is the key to enabling DT-enabled applications and services by mathematically expressing the physics, dynamics, and indoor environment of a target building. However, the DT model may provide substandard performance owing to various operational uncertainties; as such, in-situ calibration is essential in building operations. This study proposed a neural network-based nonintrusive calibration (NNNC) method for a DT prediction model. A field application study was conducted on a prediction model developed for a district heating substation serving real residential buildings in Korea. The case study demonstrated (1) the operational uncertainty of the prediction model and (2) the dependence of the calibration accuracies on different indirect calibration approaches. The NNNC method showed a better calibration accuracy for the target prediction model than existing Bayesian inference-based nonintrusive calibration. Specifically, NNNC, using a correction function with a multi-layer perceptron, reduced the prediction model errors by 38.6% and 34.7% for bias and random errors, respectively. The results demonstrate the effectiveness of NNNC in DT-enabled building operations. Therefore, the NNNC ensured the applicability and reliability of the prediction model. • A neural network-based nonintrusive calibration (NNNC) is proposed for a prediction model. • A field application showed prediction model errors in building operations. • The effectiveness of NNNC is discussed. • NNNC contributes to in-situ digital twinning. [ABSTRACT FROM AUTHOR]

[Display omitted] • This study proposes simultaneous in-situ calibration for multiple physical and virtual sensors. • Field application shows virtual sensor errors in building operation. • The importance and effectiveness of simultaneous in-situ calibration are discussed. • Simultaneous in-situ calibration contributes to the virtual sensing-driven digital twins. Digital twin-enabled building operations heavily rely on a building sensor network to collect operational data. Virtual sensing, in combination with physical sensors, has great potential in establishing a reliable and informative sensing environment. However, physical sensors can experience hardware errors or systematic errors due to the working environment within building systems. Virtual sensors are also subject to their model uncertainties arising from input physical sensor errors and changes in system operations. These virtual sensor errors have a negative effect on the in-situ calibration accuracy of corresponding physical sensors. To address these issues, this study proposes a simultaneous in-situ calibration (SIC) method designed to calibrate multiple physical and virtual sensors with varying errors in the context of digital twins. The SIC problem is mathematically formulated, including two types of distance functions (direct and indirect) and defining correction functions to calibrate various types of virtual sensors (such as backup, validation, replacement/virtualization, and observation sensors). Importantly, the proposed method tackles the challenges posed by the unknown calibration environment in operational systems. A field application study was conducted for two physical sensors and three different virtual sensors operating in a district heating substation serving real residential buildings in Korea. The case study shows how the different calibration accuracies for each sensor depend on the calibration approaches, such as physical-targeted (existing Case 1), virtual-targeted (existing Case 2), and simultaneous calibration (novel Case 3). Under the simultaneous errors, only Case 3 satisfied the reference accuracy for all sensors. Specifically, the average MAEs in Case 3 were improved by approximately 79.3%, 75.3%, 63.9%, and 87.5% for the target physical sensor, backup virtual sensor, virtualized sensor, and validation virtual sensor, respectively, compared to the accuracies before calibration. These results demonstrate the importance and effectiveness of simultaneous in-situ calibration of physical and virtual sensors in digital twin-enabled building operations. The proposed calibration can contribute to the synchronization of physical and virtual building systems, thus achieving reliable and informative virtual sensing-driven digital twins. [ABSTRACT FROM AUTHOR]

• Integration of BIM and GIS for detailed representation of test bed. • Digital twin model creation through field surveys and UAV-based imaging. • Generation of 3D models containing information on agricultural infrastructures. • Web-based visualization in three dimensions at their real-world locations. • A pop-up window in Cesium displays details of agricultural infrastructures. Geographic Information Systems (GIS) are currently used in agriculture to represent various farming-related geographical information. While prior research has highlighted the potential of GIS in visualizing agricultural data, it still faces limitations in terms of model quality, interaction capabilities, and representing detailed topographic information, particularly in hydrological structures like culverts, irrigation systems, and drainage facilities. A method integrating Building Information Modeling (BIM) concepts with GIS is proposed to overcome these limitations. To achieve this, information on agricultural infrastructure in beneficiary areas was collected through field surveys and photos captured by Unmanned Aerial Vehicle (UAV). Subsequently, a digital twin model was created with various characteristics and information about agricultural hydraulic structures such as land shape, sluices, and channels of the entire beneficiary area of the test bed (Heungeop reservoir in the City of Wonju, Gangwon Province, South Korea) based on this information. A web-based geographic information visualization platform (Cesium) was integrated with the concepts of BIM to check the information associated with the selected 3D agricultural infrastructure models in a pop-up window. The proposed method overcomes the limitations of existing GIS information representation by enabling a detailed depiction of the agricultural environment. It allows for an intuitive understanding of information such as structural features, details of the material, history of maintenance, year of completion, etc., on agricultural infrastructure through a pop-up window, providing a foundation for research on efficient management and planning. [ABSTRACT FROM AUTHOR]

Use of digital twins is becoming a global trend according to Gartner, the United Nations Committee of Experts on Global Geospatial Information Management (UN-GGIM) and the Centre for Digital Built Britain (CDBB). In line with this trend, South Korea has applied digital twins to land systems. To this end, a pilot project has been performed in Jeonju city. This study reviews digital twins and land conceptually and analyses the case in Jeonju. Conceptually, in terms of effective policy decision support, digital twins and land have shared characteristics, encompassing physical land, virtual land, and land-related data. The case of Jeonju city has been reviewed in terms of the relationship between digital twins and land. In the process of collection and renewal of data from physical land, systematic data-management systems and collaboration among related departments and/or persons in charge are important. In terms of processing for digitalization in the virtual space, sufficient budget and human resource management have been identified as important elements. As for analysis and simulation conducted in the virtual space, trust in the model of analysis and simulation needs to be developed through verification and job rotation in the civil service; without proper transfer of duties and responsibilities, this could be an obstacle. In the process of decision-making with regard to physical land, social issues that could be caused by digital technologies need to be carefully considered. Last but not least, legal and institutional support is required. In order to improve the case of Jeonju city, the establishment of a digital twin committee with appropriate authority under the mayor is recommended, because single departments tend to have difficulty in dealing with diverse issues. • Digital twins and land are composed of physical land, virtual land, and land-related data. • In the process of the collection and renewal of data from physical land, establishing a systematic data-management system and collaboration among related departments and/or persons in charge are important. • In terms of processing for digitalization, sufficient budget and human resource management have been identified as important elements. • As for analysis and simulation, trust in the model of analysis and simulation needs to be built, keeping in mind that job rotation in the civil service without proper transfer of duties and responsibilities could be an obstacle. • In the process of decision-making, social issues that could be caused by digital technologies need to be carefully considered. [ABSTRACT FROM AUTHOR]