| publications-4971 |
Review |
2024 |
Okenyi V.; Bodaghi M.; Mansfield N.; Afazov S.; Siegkas P. |
A review of challenges and framework development for corrosion fatigue life assessment of monopile-supported horizontal-axis offshore wind turbines |
Ships and Offshore Structures |
10.1080/17445302.2022.2140531 |
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Digital tools such as machine learning and the digital twins are emerging in asset management of offshore wind structures to address their structural integrity and cost challenges due to manual inspections and remote sites of offshore wind farms. The corrosive offshore environments and salt-water effects further increase the risk of fatigue failures in offshore wind turbines. This paper presents a review of corrosion fatigue research in horizontal-axis offshore wind turbines (HAOWT) support structures, including the current trends in using digital tools that address the current state of asset integrity monitoring. Based on the conducted review, it has been found that digital twins incorporating finite element analysis, material characterisation and modelling, machine learning using artificial neural networks, data analytics, and internet of things (IoT) using smart sensor technologies, can be enablers for tackling the challenges in corrosion fatigue (CF) assessment of offshore wind turbines in shallow and deep waters. Β© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. |
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| publications-4972 |
Review |
2024 |
Hassoun A.; AΓ―t-Kaddour A.; Dankar I.; Safarov J.; Ozogul F.; Sultanova S. |
The Significance of Industry 4.0 Technologies in Enhancing Various Unit Operations Applied in the Food Sector: Focus on Food Drying |
Food and Bioprocess Technology |
10.1007/s11947-024-03465-2 |
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Food unit operations refer to the engineering processes involved in transforming raw materials into desirable food products, taking into account the main laws and principles that govern the physical, chemical, and biochemical changes related to these processes. Drying is one of the most common unit operations used in the food sector to reduce food water content, thereby extending shelf-life, reducing weight and volume, and decreasing inventory and transportation costs. Traditionally, food materials are dried using conventional methods, such as natural solar drying and hot air drying. However, recent years have witnessed the introduction of several emerging technologies (e.g., infrared drying, microwave drying, and freeze drying) that have promising potential to overcome challenges, such as uneven drying, poor sensory properties and nutrient loss, and large energy consumption. More interestingly, recent developments and advancements in digital, physical, and biological technologies, spurred by the Fourth Industrial Revolution (Industry 4.0), have significantly impacted various food manufacturing operations, including food drying. Growing evidence shows that diverse Industry 4.0 technologies (notably artificial intelligence, the Internet of Things, smart sensors, digital twins, and big data) can be harnessed to improve the modelling, monitoring, prediction, and optimization of various parameters in food drying. These technological advancements are not only accelerating the pace of innovation but also enhancing process efficiency and overall performance in intelligent food drying, ushering in the era of β€_x009c_Food Drying 4.0.β€_x009d_ Β© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. |
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| publications-4973 |
Conference paper |
2024 |
Magaisa E.; Michell K.; Moghayedi A. |
Technological Innovation for Improving Energy and Water Consumption Efficiency and Sustainability on Government Buildings in South Africa: A Comprehensive Review of Literature |
Lecture Notes in Civil Engineering |
10.1007/978-3-031-35399-4_4 |
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Low operational efficiency and sustainability characterise South African government buildings, which partly emanates from lack of innovation in the South African public sector. As a result, inefficiency and lack of sustainability in the use of energy and water are major challenges, consequently affecting sustainability in buildings and causing detrimental effects to the environment. It is therefore imminent that the South African government adopts innovative technologies that ameliorate the public built environment. The goal of this paper is therefore to understand, from a critical review of literature, how harnessing technological innovation can improve operational efficiency and sustainability in energy use and water consumption in government buildings in South Africa. Careful selection of the most appropriate scholarly sources was done, which were then appraised to understand how the different latest technologies can be utilised and how they can be helpful in improving efficiency and sustainability in energy use and water consumption in buildings. The internet of things, digital twin, big data analytics and smart meters, were identified to be useful in improving efficiency and sustainability in energy and water consumption in buildings, whilst also improving indoor environmental quality. The result would be reducing the cost of energy and water management in South African Government buildings, and elimination of the energy and water crisis in South Africa, as well as minimisation of harm to the environment. Β© 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG. |
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| publications-4974 |
Article |
2024 |
Zhang C.; Zhang S.; Yu M.; Soo H.J.; Law Y.Z.; Chen W.K.; Yeo C.K.; Cai M.; How B.V.E.; Santo H.; Magee A.R.; Si M. |
Model tests of a stiffness-similar jack-up, Part 2: In-place and hull-in-water conditions |
Marine Structures |
10.1016/j.marstruc.2023.103528 |
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This paper, Part 2 of a series, presents a comprehensive study involving ocean basin model tests of a novel stiffness-similar jack-up structure. The objective is to generate a high-quality dataset for the development of structural digital twins. The focus is on the model test design and selected results for in-place and hull-in-water conditions. The generic jack-up model was instrumented with strategically placed sensors on the hull, legs, leg-to-hull connections, and spudcan modules. The novel use of polycarbonate for the jack-up legs ensures stiffness similarity, enabling the use of strain gauges to derive axial member forces. Boundary forces were meaningfully measured, because of the representative modelling of the foundation and leg-to-hull connection fixity. The test cases encompassed long-crested waves, including conditions with and without current. In addition, oblique waves were modelled by rotating the entire jack-up model. Both extreme and operating scenarios were considered. In operating scenarios, the dynamic responses of the jack-up structure were found primarily governed by structural resonance, while wave frequency responses became comparable in extreme scenarios. For extreme scenarios, dynamic wind loads, consistently Froude-scaled to the model scale, were applied using a servomotor in the presence of random waves. Comparisons between results with and without the applied dynamic wind loads revealed noticeable differences in damping characteristics. The hull-in-water condition exhibited significantly larger motion and structural responses, emphasising its criticality in jack-up operations. The findings underscore the importance of considering the hull-in-water condition in the analysis and operation of jack-up structures. Β© 2023 Elsevier Ltd |
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| publications-4975 |
Article |
2023 |
Shukla A.; Matharu P.S.; Bhattacharya B. |
Design and development of a continuous water quality monitoring buoy for health monitoring of river Ganga |
Engineering Research Express |
10.1088/2631-8695/ad0d40 |
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Real-time monitoring of water quality in the river Ganga and other Indian rivers is crucial to determining its suitability for drinking and other usages across the seasons and round the clock. For this, a structurally strong and hydrostatically stable floating observation center is required to house all the sensors and related equipment. This paper explains the design process for such a buoy platform that can house an array of water quality sensors powered by hybrid energy harvesting systems. Sensors are connected to a wireless sensor network (WSN) system that transfers data to a web-based platform, where we can monitor and analyze our data for the purpose of hazard prediction. Computational analysis has been carried out for the observatory body to ascertain its structural integrity and hydrostatic stability at small and large angles of inclination. The buoy design is based on various requirements specific to Indian rivers at different locations from the mid-course to the confluence. It is important that the system be modular and portable for use in a constantly changing river/water environment. A full-scale functional prototype has been developed, and field testing has been carried out to bring out the efficacy of the proposed system. Also, the WSN system collected real-time water quality data that have been validated with laboratory-based experiments. The establishment of a network of low-cost river/water health monitoring system will further initiate the large-scale data collection and help create digital twins of the Indian rivers. Β© 2023 IOP Publishing Ltd |
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| publications-4976 |
Conference paper |
2024 |
Wei Z.; Xie L.; Zhang W.; Liu J.; Fan M.; Yi F. |
Research and Application of Digital Twin in the Field of Hydropower Stations |
Proceedings - 2024 9th Asia Conference on Power and Electrical Engineering, ACPEE 2024 |
10.1109/ACPEE60788.2024.10532306 |
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The national '14th Five-Year Plan' on the construction of intelligent water conservancy clearly requires the construction of an intelligent water conservancy system to enhance the ability to measure and report water clarity and intelligent scheduling, and to make full use of the new generation of information technology such as the Internet of Things, big data and digital twins. The main task of smart water conservancy construction is to build a digital twin basin to achieve integrated development and safety. To this end, the digital twin platform in this paper covers the entire process of reservoir digital scene construction, simultaneous monitoring of dam safety and rainfall, real-time forecasting, automatic feedback analysis, online safety judgement, early warning, and dam safety decision support. The system collects the characteristics of dam settlement, inclination, water pressure and dam shape, and through the acquisition, collation and analysis of all kinds of information, it makes dam safety evaluation, controls the safe operation of dams, verifies the accuracy of calculation parameters, the practicability of the calculation method, and the correctness of the feedback construction method, and helps the management personnel to make accurate and fast disaster warning forecasts to protect the people's life and property safety. In addition, this paper also researches the 'four pre' functions required for the construction of digital twin watersheds, i.e., prediction, early warning, pre-control and planning, and puts forward suggestions for a perfect business application system and network security protection system. Β© 2024 IEEE. |
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| publications-4977 |
Article |
2023 |
Wang Y.; Kang M.; Liu Y.; Li J.; Xue K.; Wang X.; Du J.; Tian Y.; Ni Q.; Wang F.-Y. |
Can Digital Intelligence and Cyber-Physical-Social Systems Achieve Global Food Security and Sustainability? |
IEEE/CAA Journal of Automatica Sinica |
10.1109/JAS.2023.123951 |
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Plants sequester carbon through photosynthesis and provide primary productivity for the ecosystem. However, they also simultaneously consume water through transpiration, leading to a carbon-water balance relationship. Agricultural production can be regarded as a form of carbon sequestration behavior. From the perspective of the natural-social-economic complex ecosystem, excessive water usage in food production will aggravate regional water pressure for both domestic and industrial purposes. Hence, achieving a harmonious equilibrium between carbon and water resources during the food production process is a key scientific challenge for ensuring food security and sustainability. Digital intelligence (DI) and cyber-physical-social systems (CPSS) are emerging as the new research paradigms that are causing a substantial shift in the conventional thinking and methodologies across various scientific fields, including ecological science and sustainability studies. This paper outlines our recent efforts in using advanced technologies such as big data, artificial intelligence (AI), digital twins, metaverses, and parallel intelligence to model, analyze, and manage the intricate dynamics and equilibrium among plants, carbon, and water in arid and semiarid ecosystems. It introduces the concept of the carbon-water balance and explores its management at three levels: the individual plant level, the community level, and the natural-social-economic complex ecosystem level. Additionally, we elucidate the significance of agricultural foundation models as fundamental technologies within this context. A case analysis of water usage shows that, given the limited availability of water resources in the context of the carbon-water balance, regional collaboration and optimized allocation have the potential to enhance the utilization efficiency of water resources in the river basin. A suggested approach is to consider the river basin as a unified entity and coordinate the relationship between the upstream, midstream and downstream areas. Furthermore, establishing mechanisms for water resource transfer and trade among different industries can be instrumental in maximizing the benefits derived from water resources. Finally, we envisage a future of agriculture characterized by the integration of digital, robotic and biological farming techniques. This vision aims to incorporate small tasks, big models, and deep intelligence into the regular ecological practices of intelligent agriculture. Β© 2014 Chinese Association of Automation. |
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| publications-4978 |
Article |
2024 |
Alamri S.; Usman I.; Alvi S. |
Agent Based Modelling in Digital Twins for Household Water Consumption Forecasting; [Modelowanie agentowe w cyfrowych bliΕΊniakach do prognozowania zuΕΌycia wody w gospodarstwach domowych] |
Przeglad Elektrotechniczny |
10.15199/48.2024.01.33 |
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The continuous increase in urban population due to migration of mases from rural areas to big cities has set urban water supply under serious stress. Urban water resources face scarcity of available water quantity, which ultimately effects the water supply. It is high time to address this challenging problem by taking appropriate measures for the improvement of water utility services linked with better understanding of demand side management (DSM), which leads to an effective state of water supply governance. We propose a dynamic framework for preventive DSM that results in optimization of water resource management. This paper uses Agent Based Modeling (ABM) with Digital Twin (DT) to model water consumption behavior of a population and consequently forecast water demand. DT creates a digital clone of the system using physical model, sensors, and data analytics to integrate multi-physical quantities. By doing so, the proposed model replicates the physical settings to perform the remote monitoring and controlling jobs on the digital format, whilst offering support in decision making to the relevant authorities. Β© 2024 Wydawnictwo SIGMA-NOT. All rights reserved. |
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| publications-4979 |
Article |
2023 |
Ma Y.; Li Q.; Zhang J.; Liu Z.; Guo F.; Wang Y. |
Synergistic optimization model of sintering ore allocation cost and energy consumption based on PSO–VIKOR; [ε_x009f_ΊδΊ_x008e_ PSO–VIKOR η_x009a_„烧结ι…_x008d_η_x009f_Ώζζ_x009c_¬δΈ_x008e_能耗ε_x008d__x008f_ε_x008c_δΌε_x008c_–模ε_x009e_‹] |
Gongcheng Kexue Xuebao/Chinese Journal of Engineering |
10.13374/j.issn2095-9389.2022.08.30.004 |
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As one of the major energy-consuming processes in steel production, sintering accounts for approximately 10% of the total energy consumption of steel production. The energy consumed in the sintering process is mainly attributed to solid fuels. Additionally, in traditional sintering, optimized ore–fuel ratio is usually determined by experience, which fails to achieve a dynamic balance between raw material type and sintering process combustion consumption. In this study, we first analyze the complex physicochemical reaction processes, such as the decomposition of crystalline water, combustion of solid fuels, and oxidation and reduction of iron oxides in the sintering process, to understand the energy flow of the sintering process. We then set empirical parameters according to an actual sintering site, and we finally establish a sintering energy–mass balance model. Subsequently, the sintering energy balance constraint is embedded on the basis of the existing constraints of chemical composition, alkalinity, raw material ratio, etc. Additionally, the cost of sintering raw material is taken as the optimization target, after which a sintering batching model based on sintering energy balance is constructed; the penalty function method is used to transform the constrained problem into an unconstrained one; finally, the actual furnace charge structure of a certain steel plant is solved by using the particle swarm algorithm (PSO) to realize completely automatic dosing of sintering iron ore, flux and fuel. The simulation results show that the optimized sintering ore allocation based on the proposed PSO algorithm-led optimal sintering ore allocation model results in a suitable fuel ratio and increased energy efficiency of the sintering process. The optimal sintering ore allocation method is a compromise of various conflicting objectives; therefore, the solved ore allocation scheme is taken as the object, and the four indicators TFe, cost, S content, and solid fuel usage are integrated; additionally, the weights of each indicator are objectively obtained by using the entropy weight method according to the dispersion degree of data and information entropy of each indicator, under the principle of considering the balance of group benefit maximization and individual regret minimization. The VIKOR (Multicriteria optimization and compromise solution) method is used for compromise ranking and preference of the scheme. The final results confirm that the proposed PSO–VIKOR sintering ore allocation optimization model achieves energy saving and emission reduction in the sintering process while considering the sintering cost and quality, which is expected to help in low-carbon green development and sustainable evolution of sintering in iron and steel enterprises and achieve the double carbon target. © 2023 Science Press. All rights reserved. |
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| publications-4980 |
Article |
2023 |
Raman G.; Mathur A. |
AICrit: A Design-Enhanced Anomaly Detector and Its Performance Assessment in a Water Treatment Plant |
Applied Sciences (Switzerland) |
10.3390/app132413124 |
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Critical Infrastructure Security Showdown 2021β€”Online (CISS2021-OL) represented the fifth run of iTrust’s international technology assessment exercise. During this event, researchers and experts from the industry evaluated the performance of technologies designed to detect and mitigate real-time cyber-physical attacks launched against the operational iTrust testbeds and digital twins. Here, we summarize the performance of an anomaly detection mechanism, named AICrit, that was used during the exercise. AICrit utilizes the plant’s design to determine the models to be created using machine learning, and hence is referred to as a β€_x009c_design-enhancedβ€_x009d_ anomaly detector. The results of the validation in this large-scale exercise reveal that AICrit successfully detected 95.83% of the 27 launched attacks. Our analysis offers valuable insights into AICrit’s efficiency in detecting process anomalies in a water treatment plant under a continuous barrage of cyber-physical attacks. Β© 2023 by the authors. |
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