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Fast prediction of rain erosion in wind turbine blades using a data-based computational tool

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Journal of Hydrodynamics 2024年第3期36卷 504-518页

作者： Juan m.Gimenez Sergio R.Idelsohn eugenio Oñate Centre Internacional de mètodes Numèrics en enginyeria(CImNe) Edifici C1 Campus Nord UPC C/Gran CapitàS/NBarcelonaSpain

Wind turbines(WTs)face a high risk of failure due to environmental factors like erosion,particularly in high-precipitation areas and offshore *** this paper we introduce a novel computational tool for the fast prediction of rain erosion damage on WT blades that is useful in operation and maintenance decision making *** approach is as follows:Pseudo-Direct Numerical Simulation(P-DNS)simulations of the droplet-laden flow around the blade section profile are employed to build a high-fidelity data set of impact statistics for potential operating *** this database as training data,a machine learning-based surrogate model provides the feature of the impact pattern over the 2-D section for given wind and rain *** this information,a fatigue-based model estimates the remaining lifetime and erosion damage for both homogeneous and coating-substrate blade *** prediction is done by quantifying the accumulated droplet impact energy and evaluating operative conditions over time periods for which the weather at the installation site is *** this work,we describe the modules that compose the prediction method,namely the database creation,the training of the surrogate model and their coupling to build the prediction ***,the method is applied to predict the remaining lifetime and erosion damage to the blade sections of a reference *** evaluate the reliability of the tool,several site locations(offshore,coastal,and inland),the coating material and the coating thickness of the blade are *** few minutes we are able to estimate erosion after many years of *** results are in good agreement with field observations,showing the promise of the new rain erosion prediction approach.

关键词： Wind turbine blades leading edge erosion fatigue Pseudo-Direct Numerical Simulation(P-DNS) machine learning eblader

The importance of increasing primary vaccinations against COVID-19 in europe

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Infectious Disease modelling 2024年第1期9卷 1-9页

作者： Pierre-Yves Boelle eugenio Valdano Sorbonne Universite INSERMInstitut Pierre Louis d’Epidemiologie et de Sante PubliqueF75012ParisFrance

In the european Union,mass vaccination against COVID-19 staved off the strict restrictions that had characterized early epidemic ***,vaccination campaigns are focusing on booster doses,and primary vaccinations have all but ***,52 million european adults are *** investigated if reaching the still unvaccinated population in future vaccination campaigns would substantially decrease the current burden of COVID-19,which is *** focused on vaccination homophily,whereby those who are unvaccinated are mostly in contact with other unvaccinated,making COVID-19 circulation *** quantified vaccination homophily and estimated its impact on COVID-19 *** used an online survey of 1,055,286 people from 22 european countries during early *** computed vaccination homophily as the association between reported vaccination status and perceived vaccination uptake among one's own social contacts,using a case-referent design and a hierarchical logistic *** used this information in an analysis of the COVID-19 reproduction ratio to determine the impact of vaccine homophily in *** homophily was present and strong everywhere:the average odds ratio of being vaccinated for a 10-percentage-point increase in coverage among contacts was 1.66(95%CI=(1.60,1.72)).Homophily was positively associated with the strictness of COVID-19-related restrictions in 2020(Pearson=0.49,P=.03).In the countries studied,12%-to-18%of the reproduction ratio would be attributable to vaccine *** vaccination homophily may curb the reproduction ratio substantially even to the point of preventing recurrent epidemic *** addition to boosting those already vaccinated,increasing primary vaccination should remain a high priority in future vaccination campaigns,to reduce vaccination homophily:this combined strategy may decrease COVID-19 burden.

关键词： COVID-19 Vaccination campaign Reproduction ratio Vaccination homophily Survey europe

A High-Order Localized Artificial Diffusivity Scheme for Discontinuity Capturing on 1D Drift-Flux models for Gas-Liquid Flows

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Advances in Applied mathematics and mechanics 2024年第1期16卷 47-74页

作者： Adyllyson H.Nascimento eugenio S.Rosa Department of energy School of Mechanical EngineeringUniversity of CampinasCampinasBrazil

A computational code is developed for the numerical solution of onedimensional transient gas-liquid flows using drift-flux models,in isothermal and also with phase change *** these two-phase models,classical upwind schemes such as Roe-and Godunov-type schemes are generally difficult to derive and expensive to use,since there are no treatable analytic expressions for the Jacobian matrix,eigenvalues and eigenvectors of the system of *** the other hand,the highorder compact finite difference scheme becomes an attractive alternative on these occasions,as it does not make use of any wave propagation information from the system of *** present paper extends the localized artificial diffusivity method for high-order compact finite difference schemes to solve two-phase flows with *** numerical method has simple formulation,straightforward implementation,low computational cost and,most importantly,*** numerical methodology proposed is validated by solving several numerical examples given in the *** simulations are sixth-order accurate and it is shown that the proposed numerical method provides accurate approximations of shock waves and contact *** is an essential property for simulations of realistic mass transport problems relevant to operations in the petroleum industry。

关键词： Compressible two-phase flows drift-flux model localized artificial diffusivity highorder numerical methods

Spatial and temporal patterns of forest fires in the Central monte:relationships with regional climate

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ecological Processes 2024年第1期13卷 66-79页

作者： Pablo eugenio Villagra erica Cesca Leandro manuel Alvarez Silvia Delgado Ricardo Villalba Instituto Argentino de Nivología Glaciología y Ciencias Ambientales–CONICeT-CCT mendoza Facultad de Ciencias Agrarias Universidad Nacional de Cuyo

Background Natural and anthropogenic wildfires burn large areas of arid and semi-arid forests with significant socio-economic and environmental impacts. Fire regimes are controlled by climate, vegetation type, and anthropogenic factors such as ignition sources and human-induced disturbances. Projections of climate and land-use change suggest that these controlling factors will change, altering fire regimes in the near future. In the southern Central monte, mendoza, Argentina, the factors that modulate the fire temporal and spatial variability are poorly understood. We reconstructed the fire history of southeast of mendoza from 1984 to 2023 and investigated the relationships between fire extent and climate variability at seasonal and interannual scales. Burned areas were determined using Google earth engine by processing Landsat 5-Tm, Landsat 7-eTm+, and Landsat 8-OLI-TIRS sensor *** The region exhibited high spatial and temporal variability in fire occurrence, being a mosaic of areas with different fire histories and recovery times. Between 1985 and 2023, fire recurrence ranged from sites unburned to sites with up to 14 fires. The occurrence of large fires was strongly favored by a combination of a year with abundant spring–early summer precipitation, which favors fuel accumulation, followed by a year of low spring–early summer precipitation. Precipitation and burnt area showed a very pronounced 6–7 year cycle, suggesting a dominant climatic control on fire *** Fire distribution in southeastern mendoza forests is not homogeneous, resulting in a mosaic of patches with different fire histories. This heterogeneity may be related to vegetation patterns and land use. The temporal variability of fires is strongly influenced by climate variability, which would promote fuel production and subsequent drying. Large fires are concentrated in periods of high interannual precipitation variability. Climate change scenarios predict an increase in tem

关键词： Fire recurrence Fire mapping Recovery time Climate Dry forest Wildfire

Time and Space efficient multi-model Convolution Vision Transformer for Tomato Disease Detection from Leaf Images with Varied Backgrounds

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Computers, materials & Continua 2024年第4期79卷 117-142页

作者： Ankita Gangwar Vijaypal Singh Dhaka Geeta Rani Shrey Khandelwal ester Zumpano eugenio Vocaturo Department of Computer and Communication engineering Manipal University JaipurJaipurIndia Department of IoT and Intelligent Systems Manipal University JaipurJaipurIndia Department of Computer engineering ModellingElectronics and Systems(DIMES)University of CalabriaRende(Cosenza)Italy National Research Council Institute of Nanotechnology(NANOTEC)Rende(Cosenza)Italy

A consumption of 46.9 million tons of processed tomatoes was reported in 2022 which is merely 20%of the total *** increase of 3.3%in consumption is predicted from 2024 to *** are also rich in iron,potassium,antioxidant lycopene,vitamins A,C and K which are important for preventing cancer,and maintaining blood pressure and glucose ***,tomatoes are globally important due to their widespread usage and nutritional *** face the high demand for tomatoes,it is mandatory to investigate the causes of crop loss and minimize *** are one of the major causes that adversely affect crop yield and degrade the quality of the tomato *** leads to financial losses and affects the livelihood of ***,automatic disease detection at any stage of the tomato plant is a critical *** learning models introduced in the literature show promising results,but the models are difficult to implement on handheld devices such as mobile phones due to high computational costs and a large number of ***,most of the models proposed so far work efficiently for images with plain backgrounds where a clear demarcation exists between the background and leaf ***,the existing techniques lack in recognizing multiple diseases on the same *** address these concerns,we introduce a customized deep learning-based convolution vision transformer *** achieves an accuracy of 93.51%for classifying tomato leaf images with plain as well as complex backgrounds into 13 *** requires a space storage of merely 5.8 mB which is 98.93%,98.33%,and 92.64%less than stateof-the-art visual geometry group,vision transformers,and convolution vision transformermodels,*** training time of 44 min is 51.12%,74.12%,and 57.7%lower than the above-mentioned ***,it can be deployed on(Internet of Things)IoT-enabled devices,drones,or mobile devices to assist farmers in the real-time monitoring of tomato *** p

关键词： Tomato disease transformer deep learning mobile devices

Virtual Transmission Solution Based on Battery energy Storage Systems to Boost Transmission Capacity

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Journal of modern Power Systems and Clean energy 2024年第2期12卷 466-474页

作者： matías Agüero Jaime Peralta eugenio Quintana Victor Velar Anton Stepanov Hossein Ashourian Jean mahseredjian Roberto Cárdenas Coordinador eléctrico Nacional SantiagoChile PGSTech Montreal Canada ecole Polytechnique de montréal Montréal Canada University of Chile Santiago Chile Ieee

The increasing penetration of variable renewable energy(VRe)generation along with the decommissioning of conventional power plants in Chile,has raised several operational challenges in the Chilean National Power Grid(NPG),including transmission congestion and VRe *** mitigate these limitations,an innovative virtual transmission solution based on battery energy storage systems(BeSSs),known as grid booster(GB),has been proposed to increase the capacity of the main 500 kV corridor of the *** paper analyzes the dynamic performance of the GB using a wide-area electromagnetic transient(emT)model of the *** GB project,composed of two 500 mVA BeSS units at each extreme of the 500 kV corridor,allows increasing the transmission capacity for 15 min during N-1 contingencies,overcoming transmission limitations under normal operation conditions while maintaining system stability during *** dynamic behavior of the GB is also analyzed to control power flow as well as voltage *** results show that the GB is an effective solution to allow greater penetration of VRe generation while maintaining system stability in the NPG.

关键词： Battery energy storage system(BeSS) grid booster transient stability voltage stability electromagnetic transient(emT)

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Trio in a Triangle

China Today 2024年第2期73卷 21-23页

作者： eugenio BReGOLAT 不详

europe should use its moderating power to prevent *** from spiralling into open confrontation.W HeReVeR we look,understanding and cooperation among states is indispensable,be it to keep peace in the world,maintain economic progress or confront global challenges beginning with climate change and ending with artificial *** between the two great powers of our time,the United States and China,is of the essence.

关键词： peace maintain artificial

enhanced quantum resources via two distant atom-cavity systems under the influence of atomic dissipation

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Communications in Theoretical Physics 2024年第2期76卷 62-73页

作者： m Setodeh Kheirabady m K Tavassoly m Rafeie e Ghasemian Laser and Optics Group Faculty of PhysicsYazd UniversityYazd 89195-741Iran Department of electrical engineering Faculty of Intelligent Systems Engineering and Data SciencePersian Gulf UniversityBushehrIran

Quantum resources such as entanglement and coherence are the holy grail for modern quantum technologies. Although the unwanted environmental effects tackle quantum information processing tasks, suprisingly these key quantum resources may be protected and even enhanced by the implementation of some special hybrid open quantum systems. Here, we aim to show how a dissipative atom-cavity-system can be accomplished to generate enhanced quantum *** do so, we consider a couple of dissipative cavities, where each one contains two effective two-level atoms interacting with a single-mode cavity field. In practical applications, a classical laser field may be applied to drive each atomic subsystem. After driving the system, a Bell-state measurement is performed on the output of the system to quantify the entanglement and coherence. The obtained results reveal that the remote entanglement and coherence between the atoms existing inside the two distant cavities are not only enhanced, but can be stabilized, even under the action of dissipation. In contrast, the local entanglement between two atoms inside each dissipative cavity attenuates due to the presence of unwanted environmental ***, the local coherence may show the same behavior as the remote ***, the system provides the steady state entanglement in various interaction regimes,particularly in the strong atom-cavity coupling and with relatively large detuning. more interestingly, our numerical analyses demonstrate that the system may show a memory effect due to the fact that the death and revival of the entanglement take place during the interaction. Our proposed model may find potential applications for the implementation of long distance quantum networks. In particular, it facilitates the distribution of quantum resources between the nodes of large-scale quantum networks for secure communication.

关键词： remote entanglement and coherence atomic dissipation steady state entanglement Bell-statemeasurement

Novel Framework for an Intrusion Detection System Using multiple Feature Selection methods Based on Deep Learning

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Tsinghua Science and Technology 2024年第4期29卷 948-958页

作者： A.e.m.eljialy mohammed Yousuf Uddin Sultan Ahmad Department of Information Systems College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabiaand also with University Center for Research and Development(UCRD)Department of Computer Science and EngineeringChandigarh UniversityPunjabIndia

Intrusion detection systems (IDSs) are deployed to detect anomalies in real time. They classify a network’s incoming traffic as benign or anomalous (attack). An efficient and robust IDS in software-defined networks is an inevitable component of network security. The main challenges of such an IDS are achieving zero or extremely low false positive rates and high detection rates. Internet of Things (IoT) networks run by using devices with minimal resources. This situation makes deploying traditional IDSs in IoT networks unfeasible. machine learning (mL) techniques are extensively applied to build robust IDSs. many researchers have utilized different mL methods and techniques to address the above challenges. The development of an efficient IDS starts with a good feature selection process to avoid overfitting the mL model. This work proposes a multiple feature selection process followed by classification. In this study, the Software-defined networking (SDN) dataset is used to train and test the proposed model. This model applies multiple feature selection techniques to select high-scoring features from a set of features. Highly relevant features for anomaly detection are selected on the basis of their scores to generate the candidate dataset. multiple classification algorithms are applied to the candidate dataset to build models. The proposed model exhibits considerable improvement in the detection of attacks with high accuracy and low false positive rates, even with a few features selected.

关键词： random forest feature selection decision tree software-defined network logistic regression intrusion detection system XGB classifier AdaBoost