Quantifying the Role of the Eddy Transfer Coefficient in Simulating the Response of the Southern Ocean Meridional Overturning Circulation to Enhanced Westerlies in a Coarse-resolution Model

This study assesses the capability of a coarse-resolution ocean model to replicate the response of the Southern Ocean Meridional Overturning Circulation(MOC) to intensified westerlies,focusing on the role of the eddy transfer coefficient(κ).κ is a parameter commonly used to represent the velocities induced by unresolved eddies.Our findings reveal that a stratification-dependent κ,incorporating spatiotemporal variability,leads to the most robust eddy-induced MOC response,capturing 82% of the reference eddy-resolving simulation.Decomposing the eddy-induced velocity into its vertical variation(VV) and spatial structure(SS) components unveils that the enhanced eddy compensation response primarily stems from an augmented SS term,while the introduced VV term weakens the response.Furthermore,the temporal variability of the stratification-dependent κ emerges as a key factor in enhancing the eddy compensation response to intensified westerlies.The experiment with stratification-dependent κ exhibits a more potent eddy compensation response compared to the constant κ,attributed to the structure of κ and the vertical variation of the density slope.These results underscore the critical role of accurately representing κ in capturing the response of the Southern Ocean MOC and emphasize the significance of the isopycnal slope in modulating the eddy compensation mechanism.

Lift-Off Effect of Koch and Circular Differential Pickup Eddy Current Probes

A flexible or planar eddy current probe with a differential structure can suppress the lift-off noise during the inspection of defects.However,the extent of the lift-off effect on differential probes,including different coil structures,varies.In this study,two planar eddy current probes with differential pickup structures and the same size,Koch and circular probes,were used to compare lift-off effects.The eddy current distributions of the probes perturbed by 0°and 90°cracks were obtained by finite element analysis.The analysis results show that the 90°crack can impede the eddy current induced by the Koch probe even further at relatively low lift-off distance.The peak-to-peak values of the signal output from the two probes were compared at different lift-off distances using finite element analysis and experimental methods.In addition,the effects of different frequencies on the lift-off were studied experimentally.The results show that the signal peak-to-peak value of the Koch probe for the inspection of cracks in 90°orientation is larger than that of the circular probe when the lift-off distance is smaller than 1.2 mm.In addition,the influence of the lift-off distance on the peak-to-peak signal value of the two probes was studied via normalization.This indicates that the influence becomes more evident with an increase in excitation frequency.This research discloses the lift-off effect of differential planar eddy current probes with different coil shapes and proves the detection merit of the Koch probe for 90°cracks at low lift-off distances.

Shallow Convection Dataset Simulated by Three Different Large Eddy Models

Shallow convection plays an important role in transporting heat and moisture from the near-surface to higher altitudes,yet its parameterization in numerical models remains a great challenge,partly due to the lack of high-resolution observations.This study describes a large eddy simulation(LES)dataset for four shallow convection cases that differ primarily in inversion strength,which can be used as a surrogate for real data.To reduce the uncertainty in LES modeling,three different large eddy models were used,including SAM(System for Atmospheric Modeling),WRF(Weather Research and Forecasting model),and UCLA-LES.Results show that the different models generally exhibit similar behavior for each shallow convection case,despite some differences in the details of the convective structure.In addition to grid-averaged fields,conditionally sampled variables,such as in-cloud moisture and vertical velocity,are also provided,which are indispensable for calculation of the entrainment/detrainment rate.Considering the essentiality of the entraining/detraining process in the parameterization of cumulus convection,the dataset presented in this study is potentially useful for validation and improvement of the parameterization of shallow convection.

The Predictability Limit of Oceanic Mesoscale Eddy Tracks in the South China Sea

Employing the nonlinear local Lyapunov exponent (NLLE) technique, this study assesses the quantitative predictability limit of oceanic mesoscale eddy (OME) tracks utilizing three eddy datasets for both annual and seasonal means. Our findings reveal a discernible predictability limit of approximately 39 days for cyclonic eddies (CEs) and 44 days for anticyclonic eddies (AEs) within the South China Sea (SCS). The predictability limit is related to the OME properties and seasons. The long-lived, large-amplitude, and large-radius OMEs tend to have a higher predictability limit. The predictability limit of AE (CE) tracks is highest in autumn (winter) with 52 (53) days and lowest in spring (summer) with 40 (30) days. The spatial distribution of the predictability limit of OME tracks also has seasonal variations, further finding that the area of higher predictability limits often overlaps with periodic OMEs. Additionally, the predictability limit of periodic OME tracks is about 49 days for both CEs and AEs, which is 5-10 days higher than the mean values. Usually, in the SCS, OMEs characterized by high predictability limit values exhibit more extended and smoother trajectories and often move along the northern slope of the SCS.

Frontogenesis and Frontolysis of a Cold Filament Driven by the Cross-Filament Wind and Wave Fields Simulated by a Large Eddy Simulation

The variations of the frontogenetic trend of a cold filament induced by the cross-filament wind and wave fields are studied by a non-hydrostatic large eddy simulation. Five cases with different strengths of wind and wave fields are studied.The results show that the intense wind and wave fields further break the symmetries of submesoscale flow fields and suppress the levels of filament frontogenesis. The changes of secondary circulation directions—that is, the conversion between the convergence and divergence of the surface cross-filament currents with the downwelling and upwelling jets in the filament center—are associated with the inertial oscillation. The filament frontogenesis and frontolysis caused by the changes of secondary circulation directions may periodically sharpen and smooth the gradient of submesoscale flow fields.The lifecycle of the cold filament may include multiple stages of filament frontogenesis and frontolysis.

Seasonal variation of mesoscale eddy intensity in the global ocean

Mesoscale eddies are a prominent oceanic phenomenon that plays an important role in oceanic mass transport and energy conversion.Characterizing by rotational speed,the eddy intensity is one of the most fundamental properties of an eddy.However,the seasonal spatiotemporal variation in eddy intensity has not been examined from a global ocean perspective.In this study,we unveil the seasonal spatiotemporal characteristics of eddy intensity in the global ocean by using the latest satellite-altimetry-derived eddy trajectory data set.The results suggest that the eddy intensity has a distinct seasonal variation,reaching a peak in spring while attaining a minimum in autumn in the Northern Hemisphere and the opposite in the Southern Hemisphere.The seasonal variation of eddy intensity is more intense in the tropical-subtropical transition zones within latitudinal bands between 15°and 30°in the western Pacific Ocean,the northwestern Atlantic Ocean,and the eastern Indian Ocean because baroclinic instability in these areas changes sharply.Further analysis found that the seasonal variation of baroclinic instability precedes the eddy intensity by a phase of 2–3 months due to the initial perturbations needing time to grow into mesoscale eddies.

Quantitative analysis and prediction of the sound field convergence zone in mesoscale eddy environment based on data mining methods

The mesoscale eddy(ME)has a significant influence on the convergence effect in deep-sea acoustic propagation.This paper use statistical approaches to express quantitative relationships between the ME conditions and convergence zone(CZ)characteristics.Based on the Gaussian vortex model,we construct various sound propagation scenarios under different eddy conditions,and carry out sound propagation experiments to obtain simulation samples.With a large number of samples,we first adopt the unified regression to set up analytic relationships between eddy conditions and CZ parameters.The sensitivity of eddy indicators to the CZ is quantitatively analyzed.Then,we adopt the machine learning(ML)algorithms to establish prediction models of CZ parameters by exploring the nonlinear relationships between multiple ME indicators and CZ parameters.Through the research,we can express the influence of ME on the CZ quantitatively,and achieve the rapid prediction of CZ parameters in ocean eddies.The prediction accuracy(R)of the CZ distance(mean R:0.9815)is obviously better than that of the CZ width(mean R:0.8728).Among the three ML algorithms,Gradient Boosting Decision Tree has the best prediction ability(root mean square error(RMSE):0.136),followed by Random Forest(RMSE:0.441)and Extreme Learning Machine(RMSE:0.518).

Zooplankton community response to eddy during dinoflagellate Noctiluca scintillans blooms off Pakistan,northern Arabian Sea

Eddies are major elements of ocean dynamics that affect ocean production.Understanding their effects on plankton distribution may help understand the dynamics of harmful phytoplankton blooms.Previous studies on the effects of eddies in the northern Arabian Sea have primarily focused on the zooplankton community,and few have observed zooplankton dynamics during winter blooms of Noctiluca scintillans.We investigated zooplankton community structure and the related environmental variability during a N.scintillans bloom that was affected by an eddy in February 2018.The sampling stations were deployed at eddy core and eddy edge distinguished in salinity,temperature,and velocity.Results show that N.scintillans bloomed at the eddy core with high-velocity currents induced by warm eddies that moved from eddy core to eddy edge.As a result,blooms significantly changed the zooplankton community structure.Non-bloom stations had higher zooplankton diversity than bloom stations.Zooplankton at non-bloom stations were dominated by either tunicates or copepods,such as Thalia democratica and Pleuromamma gracilis.In addition to the influence of N.scintillans blooms,the velocity of eddy currents was a crucial factor on the similarities in the zooplankton community composition between eddy edge and eddy core.Moreover,the lower abiotic factors in bloom area contribute to the structuring of the zooplankton community during N.scintillans blooms.

Faster AMEDA-A Hybrid Mesoscale Eddy Detection Algorithm

Identification of ocean eddies from a large amount of ocean data provided by satellite measurements and numerical simulations is crucial,while the academia has invented many traditional physical methods with accurate detection capability,but their detection computational efficiency is low.In recent years,with the increasing application of deep learning in ocean feature detection,many deep learning-based eddy detection models have been developed for more effective eddy detection from ocean data.But it is difficult for them to precisely fit some physical features implicit in traditional methods,leading to inaccurate identification of ocean eddies.In this study,to address the low efficiency of traditional physical methods and the low detection accuracy of deep learning models,we propose a solution that combines the target detection model Faster Region with CNN feature(Faster R-CNN)with the traditional dynamic algorithm Angular Momentum Eddy Detection and Tracking Algorithm(AMEDA).We use Faster R-CNN to detect and generate bounding boxes for eddies,allowing AMEDA to detect the eddy center within these bounding boxes,thus reducing the complexity of center detection.To demonstrate the detection efficiency and accuracy of this model,this paper compares the experimental results with AMEDA and the deep learningbased eddy detection method eddyNet.The results show that the eddy detection results of this paper are more accurate than eddyNet and have higher execution efficiency than AMEDA.

Large Eddy Simulation of Vertical Structure and Size Density of Deep Layer Clouds

In a convective scheme featuring a discretized cloud size density, the assumed lateral mixing rate is inversely proportional to the exponential coefficient of plume size. This follows a typical assumption of-1, but it has unveiled inherent uncertainties, especially for deep layer clouds. Addressing this knowledge gap, we conducted comprehensive large eddy simulations and comparative analyses focused on terrestrial regions. Our investigation revealed that cloud formation adheres to the tenets of Bernoulli trials, illustrating power-law scaling that remains consistent regardless of the inherent deep layer cloud attributes existing between cloud size and the number of clouds. This scaling paradigm encompasses liquid, ice, and mixed phases in deep layer clouds. The exponent characterizing the interplay between cloud scale and number in the deep layer cloud, specifically for liquid, ice, or mixed-phase clouds, resembles that of shallow convection,but converges closely to zero. This convergence signifies a propensity for diminished cloud numbers and sizes within deep layer clouds. Notably, the infusion of abundant moisture and the release of latent heat by condensation within the lower atmospheric strata make substantial contributions. However, this role in ice phase formation is limited. The emergence of liquid and ice phases in deep layer clouds is facilitated by the latent heat and influenced by the wind shear inherent in the middle levels. These interrelationships hold potential applications in formulating parameterizations and post-processing model outcomes.

Development and Application of a Power Law Constitutive Model for Eddy Current Dampers

Eddy current dampers (ECDs) have emerged as highly desirable solutions for vibration control due to theirexceptional damping performance and durability. However, the existing constitutive models present challenges tothe widespread implementation of ECD technology, and there is limited availability of finite element analysis (FEA)software capable of accurately modeling the behavior of ECDs. This study addresses these issues by developing anewconstitutivemodel that is both easily understandable and user-friendly for FEAsoftware. By utilizing numericalresults obtained from electromagnetic FEA, a novel power law constitutive model is proposed to capture thenonlinear behavior of ECDs. The effectiveness of the power law constitutive model is validated throughmechanicalproperty tests and numerical seismic analysis. Furthermore, a detailed description of the application process ofthe power law constitutive model in ANSYS FEA software is provided. To facilitate the preliminary design ofECDs, an analytical derivation of energy dissipation and parameter optimization for ECDs under harmonicmotionis performed. The results demonstrate that the power law constitutive model serves as a viable alternative forconducting dynamic analysis using FEA and optimizing parameters for ECDs.

Observing eddy dye patches induced by shear instabilities in the surf zone on a plane beach

The effects of surf zone eddy generated by alongshore currents on the deformation and transport of dye are still poorly understood,and related tracer release experiments are lacking.Therefore,a tracer release laboratory experiment was conducted under monochromatic,unidirectional incident waves with a large incident angle(30°)on a plane beach with a 1:100 slope in a large wave basin.A charge-coupled device suspended above the basin recorded the dye patch image.The evolution of eddy dye patch was observed and the transport and diffusion were analyzed based on the collected images.Subsequently,a linear instability numerical model was adopted to calculate the perturbation velocity field at the initial stage.The observation and image processing results show that surf zone eddy patches occurred and were separated from the original dye patches.Our numerical analysis results demonstrate that the structure of the perturbation velocity field is consistent with the experimental observations,and that the ejection of eddy patches shoreward or offshore may be ascribed to the double vortex.

Eddy current quantitative evaluation of high-speed railway contact wire cracks based on neural network

Purpose–The purpose of this study is to study the quantitative evaluation method of contact wire cracks by analyzing the changing law of eddy current signal characteristics under different cracks of contact wire of high-speed railway so as to provide a new way of thinking and method for the detection of contact wire injuries of high-speed railway.Design/methodology/approach–Based on the principle of eddy current detection and the specification parameters of high-speed railway contact wires in China,a finite element model for eddy current testing of contact wires was established to explore the variation patterns of crack signal characteristics in numerical simulation.A crack detection system based on eddy current detection was built,and eddy current detection voltage data was obtained for cracks of different depths and widths.By analyzing the variation law of eddy current signals,characteristic parameters were obtained and a quantitative evaluation model for crack width and depth was established based on the back propagation(BP)neural network.Findings–Numerical simulation and experimental detection of eddy current signal change rule is basically consistent,based on the law of the selected characteristics of the parameters in the BP neural network crack quantitative evaluation model also has a certain degree of effectiveness and reliability.BP neural network training results show that the classification accuracy for different widths and depths of the classification is 100 and 85.71%,respectively,and can be effectively realized on the high-speed railway contact line cracks of the quantitative evaluation classification.Originality/value–This study establishes a new type of high-speed railway contact wire crack detection and identification method,which provides a new technical means for high-speed railway contact wire injury detection.The study of eddy current characteristic law and quantitative evaluation model for different cracks in contact line has important academic value and practical significance,and it has certain guiding significance for the detection technology of contact line in high-speed railway.

MAPOD Analysis in Eddy Current Testing of Flaws Considering Multiple Response Signals and Multiple Flaw Parameters

The reliability of the eddy current testing (ECT) in flaw detection is quantitatively evaluated by theprobability of detection (POD). Precise and efficient modeling of POD gives direction for the implement of ECTon sites to avoid false or missing flaw detection. Traditional POD analysis focuses on single uncertain factor orsingle response signal with limited credibility in engineering. This paper considers multiple response signals andmultiple flaw parameters to perform POD. The flaw length, the flaw depth, the coil impedance, and the magneticflux density are comprehensively studied under various lift-off distances. A finite element model (FEM) of ECT isestablished and verified with experiments to obtain sufficient simulation data for discrete POD modeling. Thecontinuous POD function is then fitted based on the discrete values to show the superiority of integrating multiplefactors. A comparison with conventional POD analysis further demonstrates the higher reliability of ECT flawdetection considering multiple flaw parameters and multiple response signals, especially for small flaws.

Absolute Wall Thickness Measurement of Conducting Plates Using Pulsed Eddy Currents

The method using pulsed eddy currents to determine the thickness of a conduction plate is extended to enable the simultaneous measurement of the plate thickness and material properties. For optimal performance, a probe must be designed depending on the thickness range that should be accessible. The need for a calibration of the material properties of a conducting plate to enable the measurement of its thickness has been removed. All that is needed is a probe with known dimensions and suitable hardware to create a current pulse and measure a transient magnetic induction.

A Perspective on the Evolution of Atmospheric Blocking Theories:From Eddy-Mean flow Interaction to Nonlinear Multiscale Interaction

In this paper,we first review the research advancements in blocking dynamics and highlight the merits and drawbacks of the previous theories of atmospheric blocking.Then,the dynamical mechanisms of atmospheric blocking are presented based on a nonlinear multi-scale interaction(NMI)model.Previous studies suggested that the eddy deformation(e.g.,eddy straining,wave breaking,and eddy merging)might lead to the formation and maintenance of atmospheric blocking.However,the results were speculative and problematic because the previous studies,based on the time-mean eddy-mean flow interaction model,cannot identify the causal relationship between the evolution of atmospheric blocking and the eddy deformation.Based on the NMI model,we indicate that the onset,growth,maintenance,and decay of atmospheric blocking is mainly produced by the spatiotemporal evolution of pre-existing upstream synoptic-scale eddies,whereas the eddy deformation is a concomitant phenomenon of the blocking formation.The lifetime of blocking is mainly determined by the meridional background potential vorticity gradient(PVy)because a small PVyfavors weak energy dispersion and strong nonlinearity to sustain the blocking.But the zonal movement of atmospheric blocking is associated with the background westerly wind,PVy,and the blocking amplitude.Using this NMI model,a bridge from the climate change to sub-seasonal atmospheric blocking and weather extremes might be established via examining the effect of climate change on PVy.Thus,it is expected that using the NMI model to explore the dynamics of atmospheric blocking and its change is a new direction in the future.

Seasonal variation of the shape and location of the Luzon cold eddy

Using observational data from multiple satellites,we studied seasonal variations of the shape and location of the Luzon cold eddy(LCE)northwest of Luzon Island.The shape and location of the LCE have obvious seasonal variations.The LCE occurs,develops,and disappears from December to April of the next year.During this period,the shape of the LCE changed from a flat ellipse to a circular ellipse,and the change in shape can be reflected by the increase of the ellipticity of the LCE from 0.16 to 0.82.The latitude of center location of the LCE changes from 17.4°N to 19°N,and the change in latitude can reach 1.6°.Further study showed that seasonal variation of the northeast monsoon intensity leads to the change in the shape and location of the LCE.The seasonal variation of the LCE shape can significantly alter the spatial distribution of the thermal front and chlorophyll a northwest of the Luzon Island by geostrophic advection.

Three-Dimensional Climatological Structures of the Arabian Sea Eddies and Eddy-Induced Flux

This study explores the spatial structure and transport characteristics of eddies in the Arabian Sea(AS)using Argo profiles and satellite measurements.The majority of eddies occur in the northern AS,especially along its northeastern boundary.In contrast,the western AS had a relatively higher eddy kinetic energy compared to the eastern part.Particularly,the strongest energetic eddies were present in the Somali Current system.The composite results revealed the evident thermohaline anomalies caused by cyclonic eddies(CEs)and anticyclonic eddies(AEs)in the upper 300m layers.The anomalous temperature structure within CEs and AEs showed a dominant dipole structure in the near-surface layer and a monopole structure below,with maximum temperature anomalies of approximately−0.8℃and+1.0℃located at depths of 100–150m,respectively.The composited salinity structures for CEs and AEs exhibited monopole vertical structures and sandwich-like patterns.For AEs,large positive salinity anomalies occurred at subsurface layers of 60–180 m with a peak value of about 0.07,and weak negative values were observed above 60m and below 180 m.A similar vertical structure but with an opposite sign operates for CEs.The composited CE and AE caused an equatorward salt flux with values of−8.1×10^(4)and−2.2×10^(4)kg s^(−1),respectively.CEs caused an equatorward heat flux of−7.7×10^(11)W,and AEs induced a poleward flux of 1.5×1011 W.

High-sensitivity phase imaging eddy current magneto-optical system for carbon fiber reinforced polymers detection

This paper proposed a high-sensitivity phase imaging eddy current magneto-optical (PI-ECMO) system for carbon fiber reinforced polymer (CFRP) defect detection. In contrast to other eddy current-based detection systems, the proposed system employs a fixed position excitation coil while enabling the detection point to move within the detection region. This configuration effectively mitigates the interference caused by the lift-off effect, which is commonly observed in systems with moving excitation coils. Correspondingly, the relationship between the defect characteristics (orientation and position) and the surface vertical magnetic field distribution (amplitude and phase) is studied in detail by theoretical analysis and numerical simulations. Experiments conducted on woven CFRP plates demonstrate that the designed PI-ECMO system is capable of effectively detecting both surface and internal cracks, as well as impact defects. The excitation current is significantly reduced compared with traditional eddy current magneto-optical (ECMO) systems.

Model Predictive Control Coupled with Artificial Intelligence for Eddy Current Dynamometers

The recent studies on Artificial Intelligence(AI)accompanied by enhanced computing capabilities supports increasing attention into traditional control methods coupled with AI learning methods in an attempt to bringing adap-tiveness and fast responding features.The Model Predictive Control(MPC)tech-nique is a widely used,safe and reliable control method based on constraints.On the other hand,the Eddy Current dynamometers are highly nonlinear braking sys-tems whose performance parameters are related to many processes related vari-ables.This study is based on an adaptive model predictive control that utilizes selected AI methods.The presented approach presents an updated the mathema-tical model of an Eddy Current Dynamometer based on experimentally obtained system operational data.Finally,the comparison of AI methods and related learn-ing performances based on the assessment technique of mean absolute percentage error(MAPE)issues are discussed.The results indicate that Single Hidden Layer Neural Network(SHLNN),General Regression Neural Network(GRNN),Radial Basis Network(RBNN),Neuro Fuzzy Network(ANFIS)coupled MPC have quite satisfying performances.The presented results indicate that,amongst them,GRNN appears to provide the best performance.