| publications-5191 |
Article |
2022 |
Bahlawan H.; Ferraro N.; Gambarotta A.; Losi E.; Manservigi L.; Morini M.; Saletti C.; Ruggero Spina P.; Venturini M. |
Detection and identification of faults in a District Heating Network |
Energy Conversion and Management |
10.1016/j.enconman.2022.115837 |
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District Heating Networks (DHNs) are composed of numerous pipes that can be threatened by faults that affect DHN operation and management. Thus, reliable diagnostic methodologies are essential to identify DHN health state and hinder DHN malfunctioning and performance deterioration. To this purpose, a novel diagnostic approach that couples a DHN simulation model with an optimization algorithm for detecting and identifying both thermal and hydraulic faults, i.e., water leakages, anomalous heat and pressure losses, is presented in this paper. In the current paper, the novel diagnostic approach is challenged at evaluating the health state of the DHN of the campus of the University of Parma, where different faults are artificially implanted, by using a digital twin of the DHN. The faulty datasets account for both single and multiple faults, as well as different fault types and causes. The novel diagnostic approach proves to correctly detect and identify all simulated faults, by also correctly estimating their magnitude even in the most challenging scenarios. Β© 2022 Elsevier Ltd |
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| publications-5192 |
Article |
2022 |
Banyay G.A.; Palamara M.J.; Preston J.N.; Smith S.D. |
Mechanics Informed Neutron Noise Monitoring to Perform Remote Condition Assessment for Reactor Vessel Internals |
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering |
10.1115/1.4054444 |
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The use of neutron noise analysis in pressurized water reactors to detect and diagnose degradation represents the practice of pro-active structural health monitoring for reactor vessel internals. Recent enhancements to this remote condition monitoring and diagnostic computational framework quantify the sensitivity of the structural dynamics to different degradation scenarios. This methodology leverages benchmarked computational structural mechanics models and machine learning methods to enhance the interpretability of neutron noise measurement results. The novelty of the methodology lies not in the particular technologies and algorithms but our amalgamation into a holistic computational framework for structural health monitoring. Recent experience revealed the successful deployment of this methodology to pro-actively diagnose different degradation scenarios, thus enabling prognostic asset management for reactor structures. This article is available in the ASME Digital Collection at https://doi.org/10.1115/1.4054444. Β© 2022 American Society of Mechanical Engineers. |
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| publications-5193 |
Article |
2022 |
LΓΌnser H.; Hartmann M.; Desmars N.; Behrendt J.; Hoffmann N.; Klein M. |
The Influence of Characteristic Sea State Parameters on the Accuracy of Irregular Wave Field Simulations of Different Complexity |
Fluids |
10.3390/fluids7070243 |
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The accurate description of the complex genesis and evolution of ocean waves, as well as the associated kinematics and dynamics is indispensable for the design of offshore structures and the assessment of marine operations. In the majority of cases, the water-wave problem is reduced to potential flow theory on a somehow simplified level. However, the nonlinear terms in the surface boundary conditions and the fact that they must be fulfilled on the unknown water surface make the boundary value problem considerably complex. Hereby, the contrary objectives with respect to a very accurate representation of reality and numerical efficiency must be balanced wisely. This paper investigates the influence of characteristic sea state parameters on the accuracy of irregular wave field simulations of different complexity. For this purpose, the high-order spectral method was applied and the underlying Taylor series expansion was truncated at different orders so that numerical simulations of different complexity can be investigated. It is shown that, for specific characteristic sea state parameters, the boundary value problem can be significantly reduced while providing sufficient accuracy. Β© 2022 by the authors. |
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| publications-5194 |
Article |
2022 |
Wei Z.; Wang L.; Sun S.C.; Li B.; Guo W. |
Graph Layer Security: Encrypting Information via Common Networked Physics |
Sensors |
10.3390/s22103951 |
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The proliferation of low-cost Internet of Things (IoT) devices has led to a race between wireless security and channel attacks. Traditional cryptography requires high computational power and is not suitable for low-power IoT scenarios. Whilst recently developed physical layer security (PLS) can exploit common wireless channel state information (CSI), its sensitivity to channel estimation makes them vulnerable to attacks. In this work, we exploit an alternative common physics shared between IoT transceivers: the monitored channel-irrelevant physical networked dynamics (e.g., water/oil/gas/electrical signal-flows). Leveraging this, we propose, for the first time, graph layer security (GLS), by exploiting the dependency in physical dynamics among network nodes for information encryption and decryption. A graph Fourier transform (GFT) operator is used to characterise such dependency into a graph-bandlimited subspace, which allows the generation of channel-irrelevant cipher keys by maximising the secrecy rate. We evaluate our GLS against designed active and passive attackers, using IEEE 39-Bus system. Results demonstrate that GLS is not reliant on wireless CSI, and can combat attackers that have partial networked dynamic knowl-edge (realistic access to full dynamic and critical nodes remains challenging). We believe this novel GLS has widespread applicability in secure health monitoring and for digital twins in adversarial radio environments. Β© 2022 by the authors. Licensee MDPI, Basel, Switzerland. |
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| publications-5195 |
Article |
2022 |
Shirangi M.G.; Aragall R.; Osgouei R.E.; May R.; Furlong E.; Dahl T.G.; Thompson C.A. |
Development of Digital Twins for Drilling Fluids: Local Velocities for Hole Cleaning and Rheology Monitoring |
Journal of Energy Resources Technology, Transactions of the ASME |
10.1115/1.4054463 |
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In this work, we present our advances to develop and apply digital twins for drilling fluids and associated wellbore phenomena during drilling operations. A drilling fluid digital twin is a series of interconnected models that incorporate the learning from the past historical data in a wide range of operational settings to determine the fluids properties in real-time operations. Our specific focus is on prediction of cuttings bed thickness along the wellbore in hole cleaning and prediction of high-pressure high-temperature (HPHT) rheological properties (in downhole conditions). In both applications, we present procedures to develop accurate digital twins for prediction of drilling fluid properties in real-time drilling operations. In the hole cleaning application, we develop accurate computational fluid dynamics (CFD) models to capture the effects of rotation, eccentricity, and bed height on local fluid velocities above cuttings bed. We then run 55,000 CFD simulations for a wide range of operational settings to generate training data for machine learning. For rheology monitoring, thousands of lab experiment records are collected as training data for machine learning. In this case, the HPHT rheological properties are determined based on rheological measurement in the American Petroleum Institute (API) condition (14.7 psi and 150 Β°F) together with the fluid type and composition data. We compare the results of the application of several machine learning algorithms to represent CFD simulations (for hole cleaning) and lab experiments (for monitoring HPHT rheological properties). Rotating cross-validation method is applied to ensure accurate and robust results. In both cases, models from the gradient boosting and the artificial neural network algorithms provided the highest accuracy (about 0.95 in terms of R2) for test datasets. With developments presented in this paper, the hole cleaning calculations can be performed in real time, and the HPHT rheological properties of drilling fluids can be estimated at the rig site avoiding the need to wait for the laboratory experimental results. Copyright Β© 2022 by ASME. |
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| publications-5196 |
Article |
2022 |
Chen W.D.; Hasanien H.M.; Chua K.J. |
Towards a digital twin approach – Experimental analysis and energy optimization of a multi-bed adsorption system |
Energy Conversion and Management |
10.1016/j.enconman.2022.116346 |
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An adsorption chiller system is one of the most promising technologies that utilize waste thermal energy to simultaneously produce cooling and potable water. However, the energy utilization optimization and detection of desiccant's sorption capacity degradation are two unresolved issues that have severely impeded the development and commercial applications of adsorption chiller technologies. This study is pioneered to develop a digital twin platform specifically designed for an experimental four-bed two-evaporator adsorption chiller system prototype. Leveraging this platform, system monitoring, performance prediction, and optimization functions are achieved. Relying on the monitoring function, the digital twin can detect the capacity degradation of desiccant-coated heat exchangers. By employing the prediction and optimization functions, the application performance of the adsorption chiller system under varying ambient and load conditions can be simulated and optimized under real-time operating conditions. Additionally, this work projects a first-time experimental parametric study analysis for a four-bed two-evaporator adsorption chiller system prototype under a heat recovery scheme that considers fourteen operating parameters. Key results revealed that COPth reaches 0.68 when the cycle time is 2240 s. Case studies also showed that the adsorption chiller system can yield significant energy-saving performance for climatic conditions in Malaysia and Saudi Arabia. The proposed digital twin optimization method demonstrates that COPth is enhanced by 8.5 %, 9.5 %, and 8.5 %, respectively. In contrast to the conventional method, optimizing the adsorption chiller's performance through the digital twin platform enables a reduction of the annual electricity consumption by up to 10.3 %. Β© 2022 Elsevier Ltd |
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| publications-5197 |
Article |
2022 |
Huang Z.F.; Soh K.Y.; Islam M.R.; Chua K.J. |
Digital twin driven life-cycle operation optimization for combined cooling heating and power-cold energy recovery (CCHP-CER) system |
Applied Energy |
10.1016/j.apenergy.2022.119774 |
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Natural gas is expected to be the dominant fossil fuel in the coming decades. Improving the sustainability of natural gas usage is imperative to achieving a low-carbon society. This study proposes a combined cooling, heating, and power incorporating cold energy recovery (CCHP-CER) system to utilize both heat and cold energies of liquified natural gas (LNG) in a cascade way. The system is comprised of four subsystems, namely, gas turbine, water-lithium bromide absorption chiller, hot water heat exchanger, and cold energy recovery unit. A digital twin approach is applied to this system for real-time and life-cycle operational optimization. The cascade forward neural network (CFNN) is employed to construct the virtual representation while a parameter-free intelligent algorithm is adopted to seek the optimal operating parameters. Key results from this study revealed that incorporating the cold energy recovery (CER) unit produces additional electricity and cooling effect, bringing a 0.72 % improvement in the average daily primary energy saving rate (PESR). The digital twin-based optimization process updates the optimal operation parameters in time when the system suffers degradation. Consequently, the degradation performance is alleviated by the living parameters. Compared to static model-based optimization, the digital twin-based optimization improves the daily PESR by 2.23 %, 0.35 %, and 1.53 % during respective winter, summer, and transition days, particularly when the compressor and turbine of the gas turbine suffer degraded efficiency of β’2 %. Β© 2022 Elsevier Ltd |
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| publications-5198 |
Article |
2022 |
Jiang Y.; Shen X.; LΓΌ H.; Zhang C. |
Construction and Simulation of Operation Digital Twin Model for Alkaline Water Electrolyzer; [碱性电解槽θΏθ΅_x008c_特性数ε—εη”_x009f_模ε_x009e_‹ζ_x009e_„ε»Ίε_x008f__x008a_δ»Ώη_x009c__x009f_] |
Diangong Jishu Xuebao/Transactions of China Electrotechnical Society |
10.19595/j.cnki.1000-6753.tces.210501 |
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Digital twin technology based on sensing technology, Internet of Things technology and simulation modeling technology has become an advanced and feasible new technology that realizes the simulation comparison and deduction evaluation of real-state of physical entities through the integration of physical model and data-driven model. The alkaline water electrolyzer is a key device in the electrolysis hydrogen production system. Therefore, constructing its working characteristic model through digital twin technology to realize the application in characteristic simulation and state evaluation, is of great significance to not only the informatization and digitization of electrolyzer and but also the optimization of renewable energy power generation and hydrogen production system. Based on the characteristics test of alkaline water electrolyzer, combined with the working mechanism of hydrogen production system of the alkaline water electrolyzer, this paper establishes the digital twin model of the alkaline water electrolyzer impedance characteristic; Then, based on the established data-driven models, the characteristic parameters such as the total voltage, total current, and cell temperature will be selected as the observation variables. The data-driven model and the electrochemical mechanism model will be integrated to construct the digital twin system of alkaline water electrolyzer operating characteristics. Finally, based on Matlab/Simulink, the simulation of the digital twin model of alkaline water electrolyzer is realized, including the simulation model of the temperature rise, power regulation, hydrogen production efficiency and separator characteristics. Β© 2022, Electrical Technology Press Co. Ltd. All right reserved. |
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| publications-5199 |
Article |
2022 |
Gourbesville P.; Ma Q. |
Smart river management: What is next? |
River |
10.1002/rvr2.13 |
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The growing complexity of the competition among uses and the emerging understanding of the synergy effects within the catchments and the rivers have underlined the need for information on various aspects of water: precipitations, discharges, velocities, and water depths are some of the basic characteristics that need to be studied for developing a management strategy that can identify and balance the various uses, ensure conservation of resources, and mitigate the potential effect of extreme events. At present, technical innovation provides the possibility to perform measurements on the field, to produce the needed information, and to move to a new paradigm for the management of rivers. This study analyzes the concept of smart river management that emerged recently with the wide spread of Information Technologies (IT) solutions and development of a new generation of sensors based on internet of things architecture. The analysis demonstrates that a holistic approach is needed for efficient management of rivers. The use of Information and Communication Technologies solutionsΒ can provide a real added value, but important efforts must be engaged for identifying key activities in the various domains that can benefit from the digital transformation. At the same time, this study introduces the paradigm of a river information system that encompasses the various activities taking place around the rivers and ensures gradual integration of the various IT components in a consistent environment that provides support to the many users of rivers. To achieve this objective, the current situation requires formalization of a roadmap and the need to address the various activities in a systematic way. Within this long-term process, the digital twins concept represents a step toward the target water information system and has generated interest among professional communities. Β© 2022 The Authors. River published by Wiley-VCH GmbH on behalf of China Institute of Water Resources and Hydropower Research (IWHR). |
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| publications-5200 |
Article |
2022 |
Wang H.; Huang H.; Bi W.; Ji G.; Zhou B.; Zhuo L. |
Deep and ultra-deep oil and gas well drilling technologies: Progress and prospect |
Natural Gas Industry B |
10.1016/j.ngib.2021.08.019 |
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In the period of β€_x009c_13th Five-Year Planβ€_x009d_, domestic deep and ultra-deep oil/gas well drilling technologies were developed quickly and a great number of technological achievements were obtained by means of continuous researches, including: (1) high-end devices, such as automatic drilling rig, managed pressure drilling, logging, cementing and completion technology, high-torque top drive system, and deep-well coiled tubing operation unit; (2) advanced tools, such as vertical drilling tool, non-planar tooth bit, high-strength expandable tubular, high-temperature, high-torque and long-life screw rod, torsion impact tool, synergistic damping based rock breaking tool, measurement while drilling tool, and safety monitoring tool; (3) core additives, such as temperature-resistance high-density oil based drilling fluid, high-performance water based drilling fluid, ductile cement slurry, and self-healing cement slurry; (4) life-cycle wellbore integrity technology system. Nevertheless, oil and gas well drilling and completion still faces severe challenges, including deep (great burial depth), steep (large formation dip), narrow (narrow pressure window), thick (thick gravel layer, salt bed and other complex intervals), difficult (complex multi-pressure system, abundant complex accidents and poor drillability) and high (high temperature, high pressure and high acid). Facing these challenges, the following suggestions are proposed. The key to the oil and gas reserve and production increase during the 14th Five-Year Plan and afterwards is till deep and ultra-deep layers. And it is necessary to focus on above mentioned geological difficulties to research key core technologies, such as automatic and intelligent drilling equipment, ultra-high temperature wellbore working fluid, pre-exploration while drilling and digital twin well construction, so as to realize the iterative upgrading of traditional superior technologies and improve the ability to drill deep and ultra-deep wells safely, quickly and optimally. In conclusion, during the 13th Five-Year Plan, China exceeded America in the number of ultra-deep wells for the first time and its well depth stepped up to a new stage of 8000 m, which plays an important role in supporting the development of deep oil and gas exploration and development and improving the market competitiveness of drilling and completion. Β© 2022 Sichuan Petroleum Administration |
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