| publications-4831 |
Conference paper |
2024 |
KallesΓΈe C.S.; Wisniewski R. |
Cyber-attack and Fault Detection using a Digital Twin of the Controller Software |
IFAC-PapersOnLine |
10.1016/j.ifacol.2024.07.200 |
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Local control units typically control large infrastructures such Water Distribution Networks (WDN's). This control setup makes the system robust both to failures and cyber-attacks. However, today's trend is to connect the local controllers to a Supervisory Control And Data Acquisition system (SCADA), which gives access to all local control parameters. This means that, intentionally or unintentionally, access to the SCADA will provide access to the entire control system. Here, we propose a cyber-attack observer that is based on a copy of the control software. This observer can detect manipulations to the local controller settings and thereby determine malicious attacks through SCADA. We call the software copy a Digital Twin of the controller software. Moreover, the collected data for the cyber-attack observer is also used for burst detection in the WDN zone. The algorithm is tested on a simulation of a WDN with consumption data profiles derived from real-life consumption data. Β© 2024 The Authors. This is an open access article under the CC BY-NC-ND license. |
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| publications-4832 |
Review |
2024 |
Ferreira C.S.S.; Soares P.R.; Guilherme R.; Vitali G.; Boulet A.; Harrison M.T.; Malamiri H.; Duarte A.C.; Kalantari Z.; Ferreira A.J.D. |
Sustainable Water Management in Horticulture: Problems, Premises, and Promises |
Horticulturae |
10.3390/horticulturae10090951 |
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Water is crucial for enduring horticultural productivity, but high water-use requirements and declining water supplies with the changing climate challenge economic viability, environmental sustainability, and social justice. While the scholarly literature pertaining to water management in horticulture abounds, knowledge of practices and technologies that optimize water use is scarce. Here, we review the scientific literature relating to water requirements for horticulture crops, impacts on water resources, and opportunities for improving water- and transpiration-use efficiency. We find that water requirements of horticultural crops vary widely, depending on crop type, development stage, and agroecological region, but investigations hitherto have primarily been superficial. Expansion of the horticulture sector has depleted and polluted water resources via overextraction and agrochemical contamination, but the extent and significance of such issues are not well quantified. We contend that innovative management practices and irrigation technologies can improve tactical water management and mitigate environmental impacts. Nature-based solutions in horticultureβ€”mulching, organic amendments, hydrogels, and the likeβ€”alleviate irrigation needs, but information relating to their effectiveness across production systems and agroecological regions is limited. Novel and recycled water sources (e.g., treated wastewater, desalination) would seem promising avenues for reducing dependence on natural water resources, but such sources have detrimental environmental and human health trade-offs if not well managed. Irrigation practices including partial root-zone drying and regulated deficit irrigation evoke remarkable improvements in water use efficiency, but require significant experience for efficient implementation. More advanced applications, including IoT and AI (e.g., sensors, big data, data analytics, digital twins), have demonstrable potential in supporting smart irrigation (focused on scheduling) and precision irrigation (improving spatial distribution). While adoption of technologies and practices that improve sustainability is increasing, their application within the horticultural industry as a whole remains in its infancy. Further research, development, and extension is called for to enable successful adaptation to climate change, sustainably intensify food security, and align with other Sustainable Development Goals. Β© 2024 by the authors. |
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| publications-4833 |
Article |
2024 |
Feng F.; Liu Z.; Shi G.; Mo Y. |
An Effective Digital Twin Modeling Method for Infrastructure: Application to Smart Pumping Stations |
Buildings |
10.3390/buildings14040863 |
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Digital twin technology has evolved from a theoretical concept to practical application, facilitating seamless data exchange between virtual and physical domains. Although there has been progress, the infrastructure industry, which is recognized for its intricate nature and the need for timely action, is still in the first phases of digital twin advancement. A significant obstacle in this field is the absence of established definitions and modeling standards, which impede the precise depiction of infrastructure systems. To address these challenges, this paper proposes a high-precision digital twin modeling method tailored for pumping stations. The method focuses on two key scenarios: first, we construct an overall digital twin model that contains both physical entities and operational processes of pumping stations; second, we design a modeling process applicable to pumping stations by analyzing the deficiencies of the existing standard system. Additionally, we selected the East–West Water Transfer Project in China as a case study to demonstrate the high-precision digital twin model of a pumping station. This model will include essential components, such as the modeling of pumping stations, the operational processes of pumping stations, and the modeling of system operation analysis. Serving as the database for the digital twin, it can complete the automatic inspection of the pumping station, optimization of scheduling, prediction and regulation of energy and carbon emissions, and visualization of results for display and other applications. The model realized the benefits of 100% automatic inspection rate, reduction of eight corresponding operating personnel, and comprehensive cost saving of RMB 2.25 million. The objective of this research is to narrow the divide between theoretical concepts and real-world implementations by pushing the boundaries of digital twin modeling and offering valuable insights for its utilization in the infrastructure industry. It establishes the foundation for progress in the field of digital twin technology in the specific context of intricate infrastructure projects. This project aims to improve the practicality of digital twin technology in real-world situations, namely in the infrastructure industry. © 2024 by the authors. |
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| publications-4834 |
Article |
2024 |
Wang H.; Guo Y.; Li L.; Li S. |
Development of AI-based process controller of sour water treatment unit using deep reinforcement learning |
Journal of the Taiwan Institute of Chemical Engineers |
10.1016/j.jtice.2024.105407 |
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Background: Due to the variability in the feedstock conditions and the nonlinearity of the sour water stripping process, determining the optimal operating conditions for Sour Water Treatment Unit (SWTU) is a huge challenge. Methods: In this study, we propose an AI-Based Process Controller (AIPC) for optimizing the SWTU, combining deep reinforcement learning (DRL) and expert knowledge. A surrogate model of an industrial SWTU digital twin was developed to serve as the environment for DRL. A reward function was designed and compared with others for evaluation. A method for seamless switching was devised to guarantee uninterrupted device operation by preventing any interference from the policy network. Significant Findings: In contrast to the alternative control schemes, the AIPC not only demonstrates superior performance in mitigating overshooting and enhancing setpoint tracking precision but achieves a reduction in stripping steam usage. The proposed method has great potential in the field of real-time optimization. Β© 2024 Taiwan Institute of Chemical Engineers |
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| publications-4835 |
Conference paper |
2024 |
Zhang L.; Yang M.; Fan Z.; Kong X.; Zhang J. |
Jining City Si River Digital Twin Watershed Management Platform Construction Practice |
ACM International Conference Proceeding Series |
10.1145/3685088.3685137 |
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In order to further enhance the flood prevention and disaster mitigation capacity of the Jining Si River basin and the ability to guarantee the supply of water resources, the use of digital twins, big data, cloud computing and other new technologies, starting from the construction of BIM + GIS digital twin big scene, to water conservancy projects as a unit, to the river as a pulse, to the core of the watershed, to carry out the construction of the Jining Si River Digital Twin Basin Management Platform practice, to create the national digital twin basin prototype. Aiming at the current water conservancy business, there are low precision data substrate, data update is not timely, insufficient departmental linkage and other pain points, from the data fusion, results show, model coupling, institutional mechanism innovation, common sharing and common defense and other aspects of the exploration breakthroughs, in order to provide ideas for reference and case support for the digital twin river basin management platform in other similar areas. Β© 2024 ACM. |
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| publications-4836 |
Article |
2024 |
Guo J.; Zheng X.; Wang Z.; Yang B.; Fu X.; Ma H.; Zhu J. |
Intelligent practice and prospects of water flooding development technology in Daqing Placanticline oilfield; [大庆长ε_x009e_£ζ²Ήη”°ζ°΄ι©±εΌ€ε_x008f_‘ζ_x008a_€ζ_x009c_―智能ε_x008c_–ε®_x009e_θ·µδΈ_x008e_展ζ_x009c_›] |
Petroleum Geology and Oilfield Development in Daqing |
10.19597/J.ISSN.1000-3754.202403008 |
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Digital transition and intelligent development are necessary paths for upgrading levels and improving quality and efficiency of mature oilfields. Application progress and significant achievements of AI techniques in waβƒ ter flooding development in Daqing Placanticline oilfield are presentedοΌ_x008c_with particular emphasis on positive effect of key techniques of intelligent well logging interpretationοΌ_x008c_reservoir prediction by intelligent well-seismic tieοΌ_x008c_water injection optimization adjustment based on data miningοΌ_x008c_and intelligent optimization of stimulation wells and reserβƒ voirs in enhancing efficiencyοΌ_x008c_effectiveness and economic benefits of oilfield development. Through technological inβƒ novationοΌ_x008c_natural decline rate by water flooding in Daqing Placanticline oilfield is controlled to <7%οΌ_x008c_and annual water cut increase is controlled to less than 0.2 percentage pointsοΌ_x008c_realizing high-level and high-quality oilfield deβƒ velopment in late stage of ultra-high water cut. On this basisοΌ_x008c_intelligent development direction of water flooding technology is prospectedοΌ_x008c_suggesting that application of large language models should be accelerated for oil and gasοΌ_x008c_research and development of real-time dynamic monitoring techniques should be enhancedοΌ_x008c_and techniques of digital twin modelsοΌ_x008c_intelligent plan design and smart injection-production optimization should be adoptedοΌ_x008c_so as to promote higher-level intelligent transform of oilfield development. Β© 2024 Editorial Department of Petroleum Geology and Oilfield Development in Daqing. All rights reserved. |
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| publications-4837 |
Review |
2024 |
Li Q.; Ma Z.; Li J.; Li W.; Li Y.; Yang J. |
Overview of the Research Status of Intelligent Water Conservancy Technology System |
Applied Sciences (Switzerland) |
10.3390/app14177809 |
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A digital twin is a new trend in the development of the current smart water conservancy industry. The main research content of intelligent water conservancy is clarified. This paper first summarizes and combs the relevant system architecture of smart water conservancy, and puts forward a smart water conservancy framework based on digital twins, highlighting the characteristics of virtual and real interaction, and symbiosis of the water conservancy twin platform. Secondly, the status quo of intelligent water conservancy β€_x009c_sky, air, ground and waterβ€_x009d_ integrated monitoring technology, big data and artificial intelligence, model platform technology, knowledge graph and security technology is analyzed. From the perspective of application, the research progress of each technology in water security, water resources and hydraulic engineering is reviewed. Although the construction of smart water conservancy has made remarkable progress, it still faces many challenges such as data governance, technology integration and innovation, and standardization. In view of these challenges, this paper puts forward a series of countermeasures, and looks forward to the future development direction of intelligent water conservancy. Β© 2024 by the authors. |
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| publications-4838 |
Article |
2024 |
Zhang H.; Dai Y.; Zhang S. |
A review of Regional Earth System Model development; [ε_x008c_Ίε_x009f__x009f_ε_x009c_°ηƒη³»η»_x009f_模εΌ_x008f_η ”η©¶θΏ›ε±•] |
Transactions of Atmospheric Sciences |
10.13878/j.cnki.dqkxxb.20240124012 |
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An accurate understanding of Earth system change mechanisms and predicting their impacts relies on the development of Earth system models. Compared to global models, Regional Earth System Models (RESMs) concentrate more on medium-to small-scale processes and their regional impacts within specific areas, featuring higher spatial resolution and more detailed physical processes.RESMs enable coupled simulations of multi-layered Earth interactions,thereby enhancing the ability to reproduce,analyze,and forecast extreme climate events.Consequently, the development and application of RESMs hold significant scientific and practical importance for addressing various climate change-related challenges and assisting in prediction and decision-making across multiple fields, including disaster prevention and mitigation, water resources management, agriculture, energy, environmental conservation, and resource exploitation.The concept of RESMs was initially proposed by Giorgi around 1995.Over the past three decades,their development has primarily followed two approaches. The first approach, known as independent development, involves coupling regional weather/climate models with specialized models tailored to specific application goals. This method aims to broaden the application scope of regional models in specific fields based on reliable atmospheric, land surface, and oceanic descriptions. Typically, specialized models are directly coupled with regional weather/climate models, resulting in relatively simple model structures and limited functions. Representative models include WRF-Hydro, PFWRF, WRF-HMS, RegCM-FVCOM, CWRF-FVCOM, WRF-Crop, WRF-CMAQ,and WRF-Chem.The second approach,holistic integration, seeks to construct a comprehensive model of coupled multi-sphere processes for digital twin regional Earth systems.This approach aims to create a unified and coordinated framework that emphasizes deep integration among various models. Such an approach not only requires technical compatibility among the models but also demands theoretical and methodological innovations to better simulate and understand the complex dynamics and interactions within Earth systems.Representative models of this approach include RegCM-ES,TerrSysMP,ROM,and R-CESM.Irrespective of the development approach,RESMs exhibit the following common characteristics; (i) Multilayer coupling: RESMs provide a more detailed representation and online coupling of land surface and ocean processes compared to regional weather/climate models. They integrate biogeochemical, hydrological, human activity, and atmospheric chemistry processes, enabling a comprehensive understanding and simulation of the dynamic relationships among various Earth system components. Through the use of couplers, RESMs achieve flux coupling and interactions across different spatiotemporal scales, thereby enhancing the precision of simulations of natural cycles and the impacts of human activities on these cycles, (ii) Higher spatial resolution;RESMs can simulate small-scale processes, explicitly representing atmospheric convection, boundary layer processes, oceanic me-soscale eddies,complex vegetation structures on land surfaces,and changes in land use.These capabilities lead to more accurate simulations and predictions of extreme weather and climate events and their effects on local environments^ iii) Integration of data assimilation: The initial state in RESMs involves multiple processes across different layers,and the initial value of any variable can influence the entire model.Assimilating observational data from multiple sources and layers into the model' s initial state not only reduces the initial errors of related processes but also minimizes error propagation throughout the entire system, thereby shortening the model' s spin-up time and enhancing simulation accuracy.In light of the overview provided, this study advocates for the integration of interdisciplinary research efforts through open-source collaboration to expedite the development of RESMs in China. There is an urgent need to conduct interdisciplinary research utilizing the newly established model, with a particular focus on interactions a-mong multi-layer and multi-scale processes. Additionally, efforts should be directed towards establishing a regional digital twin platform for monitoring and early warning based on high-resolution RESMs.Such platform could play a crucial role in disaster prevention and mitigation in critical regions and support vital decision-making processes. Β© 2024 Editorial Department of Transactions of Atmospheric Sciences. All rights reserved. |
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| publications-4839 |
Review |
2024 |
Bains A.; Sridhar K.; Dhull S.B.; Chawla P.; Sharma M.; Sarangi P.K.; Gupta V.K. |
Circular bioeconomy in carbon footprint components of nonthermal processing technologies towards sustainable food system: A review |
Trends in Food Science and Technology |
10.1016/j.tifs.2024.104520 |
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Background: The environmental impact in terms of the number of greenhouse gases released due to human activities is measured by the method known as carbon footprint. This method is used to assess and quantify the contribution of individual organizations, products, or processes to the global climate. The environmental impact of processing throughout its life cycle is evaluated by a comprehensive method known as life cycle assessment. Sustainability criteria assessment and utilization of sustainability indicators are important to conduct circularity in research. Effective food supply chain management plays an essential role in achieving sustainability goals and increasing food safety. Scope and approach: The present review highlights the evaluation of carbon footprint by methods such as nonthermal techniques, artificial intelligence, and machine learning. Artificial intelligence and machine learning include the use of electronic sensors, digital twin technology, and the current version system to evaluate the quality and organoleptic conditions. These methods result in optimizing energy and resource consumption and promote sustainability. Key findings and conclusion: This review emphasizes that nonthermal processing technologies and artificial intelligence demonstrate significant potential in reducing energy use, water consumption, and greenhouse gas emissions, thereby contributing to the sustainability goals of the circular bioeconomy. Furthermore, AI-driven technologies offer promising solutions for monitoring agricultural outputs, optimizing supply chains, and reducing waste. Therefore, adopting these technologies within the framework of the circular bioeconomy not only offers a viable pathway toward a more sustainable food system but also aligns with global sustainability objectives by promoting resource efficiency and reducing waste. Β© 2024 Elsevier Ltd |
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| publications-4840 |
Article |
2024 |
Moradi F.; Abbaspour Asadollah S.; Pourvatan B.; Moezkarimi Z.; Sirjani M. |
CRYSTAL framework: Cybersecurity assurance for cyber-physical systems |
Journal of Logical and Algebraic Methods in Programming |
10.1016/j.jlamp.2024.100965 |
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We propose CRYSTAL framework for automated cybersecurity assurance of cyber-physical systems (CPS) at design-time and runtime. We build attack models and apply formal verification to recognize potential attacks that may lead to security violations. We focus on both communication and computation in designing the attack models. We build a monitor to check and manage security at runtime and use a reference model, called Tiny Digital Twin, in detecting attacks. The Tiny Digital Twin is an abstract behavioral model that is automatically derived from the state space generated by model checking during design-time. Using CRYSTAL, we are able to systematically model and check complex coordinated attacks. In this paper we discuss the applicability of CRYSTAL in security analysis and attack detection for different case studies, Temperature Control System (TCS), Pneumatic Control System (PCS), and Secure Water Treatment System (SWaT). We provide a detailed description of the framework and explain how it works in different cases. Β© 2024 The Authors |
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