| publications-4811 |
Article |
2024 |
He Y.; Ding Y.; Zhu Q.; Wu H.; Guo Y.; Wang Q.; Zhou R. |
Reliable simulation analysis for high-temperature inrush water hazard based on the digital twin model of tunnel geological environment |
Tunnelling and Underground Space Technology |
10.1016/j.tust.2024.106110 |
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In complex mountainous terrains, tunnel construction faces unique challenges from high-temperature water inrush hazards, a systemic risk arising from the interplay of stress, seepage, and temperature fields. Traditional simulation methods, focusing on isolated disaster scenarios, fall short in addressing the multifaceted nature of these risks due to geological ambiguity and data incompleteness. Digital twin technology presents an effective solution to these challenges; however, its core challenge lies in how to utilize digital twin technology for data-model-co-driven simulation analysis of coupled multi-physical fields in situations of incomplete data. This paper introduces a digital twin paradigm for the simulation analysis of water inrush, which significantly enhances efficiency and accuracy through the integration of advanced machine learning and finite element analysis techniques. Specifically, this is achieved by combining a high-precision geological modeling method based on Gaussian Processes (GP) with a parameter calibration method through Gaussian Process-Differential Evolution (GP-DE) back-analysis. Firstly, a voxel structure is utilized to integrate the multi-field attribute features of the tunnel environment. Secondly, through the integration of multi-source advanced geological prediction data, we construct a dynamic digital twin model of the tunnel environment leveraging machine learning techniques. To overcome the issue of low modeling accuracy, the GP is employed, enhancing the exploitation of latent information within multi-source geophysical data. Lastly, we utilize the GP-DE back-analysis method to calibrate the parameters of the tunnel environment, thereby enhancing the precision and reliability of water inrush simulations. The method has been validated through application to a section of an ultra-high-temperature water inrush tunnel in China, featuring a burial depth of 230 meters. The accuracy of the method is corroborated by the monitoring data from the tunnel, supporting dynamic optimization design and safety prevention measures during construction. Β© 2024 Elsevier Ltd |
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| publications-4812 |
Article |
2024 |
Kim M.; Shim J.Y.; Lim S.; Lee H.; Kwon S.C.; Hong S.; Ryu S. |
Reduction of greenhouse gas emissions by optimizing the textile dyeing process using digital twin technology |
Fashion and Textiles |
10.1186/s40691-024-00384-w |
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Owing to global warming and pollution concerns, reducing the environmental footprint of the textile and fashion industry has received considerable attention. Within this industry, the dyeing and finishing processes contribute significantly to greenhouse gas emissions and water pollution. This study introduces an innovative approach to address these challenges by leveraging digital twin technology to optimize the textile dyeing process. A smart analysis module was developed to continuously monitor and analyze the dyeing parameters in real time to implement control actions to automatically reduce the process duration. Integrated with this module, a digital twin of the dyeing machine enabled the real-time monitoring of energy consumption and process parameters. A case study comparing the traditional dyeing process with the optimized process was conducted. The results showed that dyeing time was reduced by ~Β 17.5% without compromising dyeing quality. Energy consumption and greenhouse gas emissions were also reduced by ~Β 12.1% when using the optimized process. This study offers a practical and sustainable option for textile dyeing, particularly for small and medium-sized enterprises. Β© The Author(s) 2024. |
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| publications-4813 |
Article |
2024 |
Iliev I.K.; Filimonova A.A.; Chichirov A.A.; Chichirova N.D.; Kangalov P.G. |
Computational and Experimental Research on the Influence of Supplied Gas Fuel Mixture on High-Temperature Fuel Cell Performance Characteristics |
Energies |
10.3390/en17112452 |
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Currently, the process of creating industrial installations is associated with digital technologies and must involve the stage of developing digital models. It is also necessary to combine installations with different properties, functions, and operational principles into a single system. Some tasks require the use of predictive modeling and the creation of β€_x009c_digital twinsβ€_x009d_. The main processes during the fuel cell modeling involve electrochemical transformations as well as the movement of heat and mass flows, including monitoring and control processes. Numerical methods are utilized in addressing various challenges related to fuel cells, such as electrochemical modeling, collector design, performance evaluation, electrode microstructure impact, thermal stress analysis, and the innovation of structural components and materials. A digital model of the membrane-electrode unit for a solid oxide fuel cell (SOFC) is presented in the article, incorporating factors like fluid dynamics, mass transfer, and electrochemical and thermal effects within the cell structure. The mathematical model encompasses equations for momentum, mass, mode, heat and charge transfer, and electrochemical and reforming reactions. Experimental data validates the model, with a computational mesh of 55 million cells ensuring numerical stability and simulation capability. Detailed insights on chemical flow distribution, temperature, current density, and more are unveiled. Through a numerical model, the influence of various fuel types on SOFC efficiency was explored, highlighting the promising performance of petrochemical production waste as a high-efficiency, low-reagent consumption fuel with a superior fuel utilization factor. The recommended voltage range is 0.6–0.7 V, with operating temperatures of 900–1300 K to reduce temperature stresses on the cell when using synthesis gas from petrochemical waste. The molar ratio of supplied air to fuel is 6.74 when operating on synthesis gas. With these parameters, the utilization rate of methane is 0.36, carbon monoxide CO is 0.4, and hydrogen is 0.43, respectively. The molar ratio of water to synthesis gas is 2.0. These results provide an opportunity to achieve electrical efficiency of the fuel cell of 49.8% and a thermal power of 54.6 W when using synthesis gas as fuel. It was demonstrated that a high-temperature fuel cell can provide consumers with heat and electricity using fuel from waste from petrochemical production. Β© 2024 by the authors. |
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| publications-4814 |
Article |
2024 |
Shehadeh A.; Alshboul O.; Arar M. |
Enhancing Urban Sustainability and Resilience: Employing Digital Twin Technologies for Integrated WEFE Nexus Management to Achieve SDGs |
Sustainability (Switzerland) |
10.3390/su16177398 |
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This research explores the application of digital twin technologies to progress the United Nations’ Sustainable Development Goals (SDGs) within the water-energy-food-environment (WEFE) nexus management in urban refugee areas. The study in Irbid Camp utilizes a detailed 3D Revit model combined with real-time data and community insights processed through advanced machine learning algorithms. An examination of 450 qualitative interviews indicates an 80% knowledge level of water conservation practices among the community but only 35% satisfaction with the current management of resources. Predictive analytics forecast a 25% increase in water scarcity and an 18% surge in energy demand within the next ten years, prompting the deployment of sustainable solutions such as solar energy installations and enhanced rainwater collection systems. By simulating resource allocation and environmental impacts, the digital twin framework helps in planning urban development in line with SDGs 6 (Clean Water and Sanitation), 7 (Affordable and Clean Energy), 11 (Sustainable Cities and Communities), and 12 (Responsible Consumption and Production). This investigation highlights the capacity of digital twin technology to improve resource management, increase community resilience, and support sustainable urban growth, suggesting its wider implementation in comparable environments. © 2024 by the authors. |
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| publications-4815 |
Review |
2024 |
Cairone S.; Hasan S.W.; Choo K.-H.; Lekkas D.F.; Fortunato L.; Zorpas A.A.; Korshin G.; Zarra T.; Belgiorno V.; Naddeo V. |
Revolutionizing wastewater treatment toward circular economy and carbon neutrality goals: Pioneering sustainable and efficient solutions for automation and advanced process control with smart and cutting-edge technologies |
Journal of Water Process Engineering |
10.1016/j.jwpe.2024.105486 |
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Wastewater treatment plants (WWTPs) play a crucial role in ensuring a safe environment by effectively removing contaminants and minimizing pollutant discharges. Compliance with stringent regulations and the search for sustainable treatment processes pose new challenges and provide opportunities for innovative solutions. These solutions include using wastewater as a resource to recover value-added by-products, such as clean water, renewable energy, and nutrients, while optimizing energy consumption and reducing operating costs without compromising treatment performance. To drive continuous innovation in wastewater treatment, the integration of advanced treatment technologies with robust monitoring and control systems is imperative. This review explores advancements in automation and advanced process control within WWTPs. In this context, technologies such as Internet of Things (IoT), cloud computing, big data analytics, artificial intelligence (AI), blockchain, robotics, drones, virtual/augmented reality (VR/AR), and digital twin are identified as promising tools for developing innovative, smart, and efficient monitoring and control systems. While the integration of these tools offers many benefits, further research is essential to optimize their performance and cost-effectiveness. A detailed overview of the current and future applications of these advanced tools and smart systems is provided, emphasizing their strengths, limitations, and opportunities for future research and improvements. Β© 2024 The Authors |
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| publications-4816 |
Article |
2024 |
Wu B.; Wei Q.; Li X.; Kou Y.; Lu W.; Ge H.; Guo X. |
A four-dimensional digital twin framework for fatigue damage assessment of semi-submersible platforms and practical application |
Ocean Engineering |
10.1016/j.oceaneng.2024.117273 |
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In the dynamic and challenging environment of deep-water operations, structural integrity is of paramount importance, particularly given the harsh and ever-evolving conditions these assets endure. This often results in significant fatigue damage, a primary concern in ocean engineering. Recent advancements in digital technologies, notably the concept of the digital twin, have revolutionized this field, significantly enhancing the intelligence and efficiency of structural operation and maintenance. This paper presents an innovative four-dimensional digital twin framework, meticulously designed for the fatigue damage assessment of semi-submersible platforms. We provide an in-depth examination of the critical technologies pertinent to each dimension and elucidate the intricate interplay of data flow amongst them. A key highlight of this study is the introduction of an advanced stress twinning methodology. This novel approach adeptly integrates real-time monitoring data with the results of high-fidelity numerical simulations. To validate the applicability and efficacy of this framework, it was implemented on a deep-water semi-submersible platform in the South China Sea. The application involved comprehensive fatigue damage assessments, demonstrating the framework's practical utility and potential as a transformative tool in the realm of ocean engineering. Β© 2024 Elsevier Ltd |
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| publications-4817 |
Article |
2024 |
Uchimiya M. |
Big data-driven water research towards metaverse |
Water Science and Engineering |
10.1016/j.wse.2024.02.001 |
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Although big data is publicly available on water quality parameters, virtual simulation has not yet been adequately adapted in environmental chemistry research. Digital twin is different from conventional geospatial modeling approaches and is particularly useful when systematic laboratory/field experiment is not realistic (e.g., climate impact and water-related environmental catastrophe) or difficult to design and monitor in a real time (e.g., pollutant and nutrient cycles in estuaries, soils, and sediments). Data-driven water research could realize early warning and disaster readiness simulations for diverse environmental scenarios, including drinking water contamination. Β© 2024 |
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| publications-4818 |
Article |
2024 |
Sharifi A.; Tarlani Beris A.; Sharifzadeh Javidi A.; Nouri M.; Gholizadeh Lonbar A.; Ahmadi M. |
Application of artificial intelligence in digital twin models for stormwater infrastructure systems in smart cities |
Advanced Engineering Informatics |
10.1016/j.aei.2024.102485 |
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Digital twins provide insights into physical objects by serving as advanced virtual representations. Their sensors capture detailed information about an object's functionality through their use of various sensors. It is possible to gain a deep understanding of the object's performance and potential areas for improvement by collecting data, which includes metrics such as energy output, temperature, and weather conditions. Digital twins are becoming important in a variety of research and industrial application sectors as production lines and processes become more digitalized and as improved data analysis techniques such as machine learning and enhanced visualization techniques are used. There is no unified definition of the digital twin concept in scientific literature, which results in imprecise applications and the weakening of its terminology. However, this study demonstrates how digital twin models can be applied to urban drainage systems. As a result, this highlights the relatively novel use of digital twins within the field of urban water system engineering. Our review of the language, practices, and directions in smart stormwater management provides a framework to organize and comprehend the current research landscape while highlighting crucial areas for future research. Our results demonstrate that there is near-unanimous agreement within the literature that smart technology has been, or will be, advantageous for stormwater management. However, while some progress has been made in terms of quantity management, maturity in water quality management has not yet been achieved. This study examines the scientific literature on digital twins in the application of artificial intelligence for smart city stormwater infrastructure systems, specifically focusing on urban drainage systems. A demonstration of the workflow and features of current digital twin applications in urban drainage systems is also presented, providing valuable insights and guidance for future research and development in this field. Β© 2024 Elsevier Ltd |
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| publications-4819 |
Article |
2024 |
Wen X.; Zhang J.; Ong M.C.; Kniat A. |
Comparative study of numerical modelling and experimental investigation for vessel-docking operations |
Marine Structures |
10.1016/j.marstruc.2024.103680 |
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A comparative study between numerical modelling and experimental investigation is performed to validate the developed numerical method for simulating floating dock operations with a vessel on board. Both model-scale and full-scale experimental tests are performed on floating docks with a vessel on board, and the draughts using draught meters, floating positions and bending of the floating dock are measured. The present numerical method is proposed based on a quasi-static assumption during vessel-docking operations. A static analysis model is built to determine the static response of a floating dock under a specific ballast water distribution based on a hydrostatic force model and a Newton-Raphson method. A bending model is proposed to calculate the deflection of the floating dock along the longitudinal direction. Results of the mode-scale tests show that the draught measurements and the floating positions of the dock and vessel predicted using the present numerical method agree well with the corresponding experimental results. It proves the accuracy of the present numerical method for simulating vessel-docking operations. Moreover, a well-designed ballast plan enables successful de-ballasting operations on the model-scale dock, even in the event of one to three pump failures. The comparison of the deflection changes of the floating dock in the field test measurements further proves the accuracy of the present bending model. Therefore, the validated numerical model tested on both model-scale and full-scale docks provides a reliable foundation for creating digital twin of floating docks in shipyards. Β© 2024 The Authors |
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| publications-4820 |
Article |
2024 |
Ge Q.; Zhu C.; Hu J.; Feng G.; Huang X.; Cheng X. |
A Study on the Construction and Evaluation of the Water Resource Reutilization System for Farmland Diversion and Drainage |
Water (Switzerland) |
10.3390/w16162289 |
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Water is an essential resource for both rural and agricultural areas; it can be wisely distributed and used in the field to protect daily life, production, the natural environment, and the safety and stability of regional drainage and flood control systems. Our research selected a typical plains rural river network area with agriculture as the main industry to investigate the most effective method of farmland diversion and drainage. We comprehensively planned and transformed the water system flow, water conservation engineering, and the ecological environment in the irrigation area through the reutilization system. The reutilization system’s operation and scheduling design is implemented for four specific periods: the water replenishment cycle, agricultural irrigation, agricultural drainage and the rainy period of the flood season. The research period ranges from 2020 to 2023 after the completion of the system. We used monitoring, the recording of hydraulic equipment parameters and data collection to evaluate the balance of water supply and demand in the study area. At the same time, we have tracked and evaluated the four aspects of water quality enhancement, water conservation and flood control, and agricultural irrigation. The results show that the total agricultural water consumption decreased by 2.9%, and the amount of water saved increased by 9.6%. The current segment creates the rivers’ embankment standards. With a 92% irrigation guarantee rate, the current section forms and the embankment standards of the rivers satisfy the design storage volume and the flood level of one in twenty years. The water quality of all the rivers in the area has decreased by 5~10% compared to the average concentration prior to establishment. This study verifies the comprehensive effect and the suitability of the system by comparing the before and after effects, and provides a scientific basis for the method of efficient recycling and utilization of water resources in the rural plains river network area; we also propose the guidance of increasing the digital twin control and long-term operation mechanism to ensure the long-term stable operation of the technology. © 2024 by the authors. |
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