bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamic Investigations between Two- and Three-bladed Wind Turbines with Various Yaw, Tilt and Cone Angles
Authors: Martínez Vivas A I , Kim T
Published: June 2022

Tilt and cone are included in wind turbine design to increase tower clearance. Yaw misalignments take place often during turbine operation. The combined effects of these parameters modify the relative wind speed experienced by wind turbine blades, thereby altering the turbine’s dynamics. Consequently, power and loads, key design considerations, are affected. In the absence of exhaustive research available on this topic, this paper provides a quantitative analysis on the impact of tilt, cone and yaw on power and loads. The DTU 10MW Reference Wind Turbine and its two-bladed equivalent are evaluated. The results are obtained using the aeroelastic code HAWC2. It is demonstrated that the ultimate and fatigue loads are greater in the two-bladed than in the three-bladed model during operations. Tilt, cone and ±10º yaw reduce the annual energy production by up to 1%. These three parameters generally increase ultimate and fatigue loads. However, the relationship between these parameters and their impact on the bending moments of both wind turbines is complex, and the results are configuration dependent. It is concluded that the combination of these three parameters must be included as part of the design load examination of any target wind turbine.
Development of a Vulnerability Map of Wind Turbine Power Converters
Authors: Tartt K , Kazemi-Amiri A , Nejad A R , McDonald A , Carroll J
Published: June 2022

With the amount of turbines that are already installed and that are planned to be installed in order to meet all the carbon emission objectives set by Governments worldwide, a means of producing a way to determine and highlight weak links or components that are more likely to fail would be extremely beneficial. One way to do this is via vulnerability maps. This paper looks at producing a vulnerability map for the power converter of a wind turbine using maintenance reports. The vulnerability map is a useful means to identify which sub-systems/components to consider when determining lifetime extension of wind turbine drivetrains. All the components that were either replaced or repaired are grouped together to determine their failure rates. Their rates are then ranked from highest to lowest and each component that makes up a typical power converter diagram coloured according to its failure rate, from red for the highest, through to orange, yellow and green for the lowest. The results show that there are three clear components that failed more often than the rest. An additional analysis looks at whether the location of the turbines alter the vulnerability map and this is confirmed. Although the same three components have the highest failure rates, their values change according to which country they are installed.
Aerodynamic Devices to Reduce/Suppress Vortex Induced Vibrations on a Wind Turbine Tower: A Review
Authors: Krishnappa Likith , Sander Aljoscha , Thoben Klaus-Dieter
Published: June 2022

The flow of air over a cylinder at sufficiently high Reynolds number (Re) leads to the formation of vortices. The vortices formed undergoes the process of shedding, exerting lift and drag forces onto the cylinder causing the cylinder to oscillate. These oscillations are termed as Vortex Induced Vibrations (VIV). VIV’s can induce very high fatigue loads onto the structure, leading to its failure. Hence, the suppression/mitigation of these VIV’s is of utmost importance in practical situations. Vortex suppression techniques such as active, passive or compound techniques can be used for the same. This paper focuses on providing a brief overview on the available passive techniques with particular interest in the flow modification, flow separation control devices and their implementation on a wind turbine tower. From this study, it was observed that most of the experimental research related to the testing of the flow modification devices were carried out in a flow channel with water as the flow medium. Therefore, their effectiveness on a wind turbine tower is questionable. However, flow separation control devices were tested in air but these devices have been tested at different Re and therefore their effectiveness cannot be comprehensively compared. The paper concludes by giving a brief overview of the work that will be carried out in the future to tackle this particular problem.
Finite Element Model to Predict the Impact of Wrinkles on Wind Turbine Blades
Authors: Mendonça Heloisa Guedes , Mikkelsen Lars Pilgaard , Branner Kim
Published: June 2022

Among the manufacturing defects of wind turbine blades, wrinkles are critical to the blade performance, affecting the structural integrity. Therefore, this paper introduces three-dimensional numerical models of laminates representative of a wind turbine blade with artificial wrinkles. The models are verified against static tension-compression experimental tests of laminates embedded with two types of wrinkles. The results show a good correlation between numerical prediction and experimentally obtained stiffness behaviour. The outcome of this analysis proves the validity of the numerical modelling strategy applied to evaluate the behaviour of laminates with wrinkles for a static loading situation.
State observer for the deformation state of wind turbine blades based on inertial measurements
Authors: Luthe J , Su Y , Ehret J , Zierath J , Woernle C
Published: June 2022

The design of wind turbines is based on conservative load assumptions compared to the actual load conditions at the designated erection site. As a consequence, structural reserves are very likely at the end of the turbine’s approved life time. To safely exploit these structural reserves, a continuous, model-based fatigue monitoring of the individual wind turbine is necessary. Direct strain measurements are possible at accessible locations only and, moreover, have limited long-term stability. Therefore, an indirect, model-based estimation of structural deformations is proposed that relies on integrated motion measurement with only a minimal number of robust inertial sensors. Tests on a small-scale structural test rig of a wind turbine prove the feasibility of the concept.
Model-free control of the dynamic lift of a wind turbine blade section: experimental results
Authors: Michel Loïc , Neunaber Ingrid , Mishra Rishabh , Braud Caroline , Plestan Franck , Barbot Jean-Pierre , Boucher Xavier , Join Cédric , Fliess Michel
Published: June 2022

This work addresses the problem of developing control algorithms for the control of the aerodynamic lift of wind turbine blades using air injection, taking into account disturbances caused by turbulent perturbations. For this, a test bench is used where the lift of a 2D blade section in a wind tunnel can be controlled by a set of micro-jets close to the trailing edge. Through a continuous, local identification of the lift variations a model-free control that does not need any prior knowledge of the system is proposed. It allows the control of the flow of the micro-jets and stabilizes the lift around a tracking reference. The ability of the proposed control algorithm to track the lift reference when subjected to external perturbations, i.e., gusts, is discussed. In particular, this work demonstrates that the lift can be set to particular values using the proposed control strategy, and can be re-stabilized to pre-gust lift conditions. Experimental results illustrate globally the feasibility of such a control.
Wind Turbine Power Curve Modelling using Gaussian Mixture Copula, ANN Regressive and BANN
Authors: Lázaro Roberto , Yürüşen Nurseda Y. , Melero Julio J.
Published: June 2022

In terms of monitoring wind turbine performance, the power curve plays a key role and it is a valuable indicator of the wind turbine’s condition as it allows the identification of anomalies related to production. On the other hand, by calculating a typical reference curve of the machine, it is possible to calculate losses and estimate its performance. A suitable model that characterises the power curve can benefit the estimated production of a wind turbine or wind farm. The most widely used models to characterise power curves are based on 2-variable models (wind speed and power). The power curve is affected by different exogenous variables (such as temperature, wind direction or turbulence intensity) that must be taken into account in the characterisation of the power curve. Consequently, the working conditions of the wind turbine are different depending on the site, and multivariable models that can take these variables into account are required. Currently new models and alternatives are emerging. This study will evaluate the performance of multivariate models based on Gaussian mixture copula model (GMCM), Regressive artificial neural Networks (ANN) and Bayesian artificial neural networks (BANN) in terms of power curve characterisation and power estimation. The results will be compared to the most common methods such as the manufacturer power curve and historical power curve, which is generated using the the bins method. Taking advantage of the benefits of neural networks (NN), particular types of NN have been considered to provide the value of uncertainty in the estimation of power.
Mechanical sensitivity analysis of strain gauge configurations in the main shaft of wind turbines
Authors: Bacaicoa J , Iriarte X , Aginaga J , Plaza A
Published: June 2022

Wind turbines are reaching their remaining useful life, thus it is important to guarantee the well status of its components. A common way to check the status is to measure the loads on the Low Speed Shaft with strain gauges, but not always are bonded perfectly. In this work a sensitivity analysis of strain gauge configurations is carried out, where the influence of geometric and material parameters, and misplacement and misalignment parameters is analyzed. An analytical model for a single gauge was developed, obtaining a relation between the exerted loads and the strain measured by the strain gauge. By means of Taylor approximations the estimated loads were approached in order to have into account the influence of the uncertainty of parameters. Results shown that the sensitivities with respect to the geometric and material parameters did not depend on the secondary loads while in the sensitivities with respect to the gauge bonding parameters the cross-talk effect was present. In order to obtain realistic numerical results, a horizontal-axis NREL 5-MW wind turbine was simulated in OpenFAST with two wind-speed scenarios. The uncertainty of the estimated loads by the strain gauge configurations was calculated.
Efficient Loads Surrogates for Waked Turbines in an Array
Authors: Shaler Kelsey , Jasa John , Barter Garrett E.
Published: June 2022

Accurately and efficiently predicting wind turbine structural loading is a crucial step in wind farm design. Without considering structural loading, wind farm optimization could negatively impact turbine fatigue and ultimate loads, especially for waked and partially waked turbines, which could result in higher maintenance costs and reduced turbine lifetime. However, predicting turbine loads throughout an array is a costly step, as these quantities require time-accurate results across long time histories, which is often intractable for large array optimization. Therefore, surrogate models that link array spacing to load outputs are often used, but the surrogates are then unique to the inflow conditions and array configurations in the training library. This work develops surrogate models for many wind turbine load outputs based solely on rotor plane velocity measurements, with no required input about array configuration or freestream inflow parameters. Surrogate models were constructed for many turbine quantities of interest (QoI), considering mean, standard deviation, ultimate, and fatigue loads. In general, most QoI statistics were accurately captured, as measured by predicted vs. actual correlation coefficient, confirming the suitability of the approach. Temporal mean values of the QoI required only temporal mean measurements of the rotor plane inflow velocity. However, accurate prediction of temporal standard deviation, ultimate, and fatigue values of QoI also required temporal standard deviations of the rotor plane velocity field. Poor surrogate performance was observed when too many correlated inputs were used, such as multiple velocity components. If the fewest inflow parameters are used to construct the surrogates, the average correlation coefficient value for all output QoI statistics is 0.89. Surrogates for standard deviations and damage equivalent loads (DELs) of turbine QoIs generally had lower accuracy and tower-base and shaft load channels posed the most difficult to capture accurately. The results suggest that these surrogates could be easily paired with analytic wake models, which are frequently used for pre-construction wind farm array optimization, to account for turbine loading in addition to power production. By including the optimal inflow conditions, the surrogate accuracy can improve to an average correlation coefficient value for all output QoI statistics of 0.92. This work has established the ability to build accurate surrogates for mean, standard deviation, ultimate load, and DEL turbine QoI values based on the rotor plane inflow velocity, and identified which inflow conditions lead to greater surrogate accuracy.
Probabilistic surrogates for flow control using combined control strategies
Authors: Debusscher Charles Marie J , Göçmen Tuhfe , Andersen Søren Juhl
Published: June 2022

Wind farm flow control (WFFC) is a promising technology for improving wind farm operation and design. The presented study focuses on the combination of the two most prominent WFFC strategies, yaw-based wake-steering and axial induction control via constant blade pitch, for maximising the wind farm power production with and without a load constraint. The optimisation is performed via data-driven polynomial-based probabilistic surrogate models, calibrated through a range of LES and aeroelastic simulations for a 2-turbine setup. The results indicate the yaw-based wake-steering to be the driving mechanism to increase the wind farm power production, particularly when loads are not considered. However, axial induction is seen beneficial for load alleviation, especially in close spacings. Overall, the analyses highlight the potential of combined WFFC strategies for power optimisation in a safety-critical system and provides a probabilistic approach for data-driven multi-objective farm flow control.
Study of the influence of met-ocean data in fatigue loads calculations of a floating offshore wind turbine
Authors: Lizarraga-Saenz Ion , Artal-García Jesús , Martín-San-Román Raquel , Vittori Felipe , Azcona-Armendáriz José
Published: June 2022

The design of a floating offshore wind turbine (FOWT) requires the computation of loads with time domain simulations that depend heavily on the metocean conditions of the site. Guidelines, such as IEC 61400-3, recommend the use of scatter tables with the combined probability of the significant wave height (Hs) and peak period (Tp) as a function of the mean wind speed. Nevertheless, at early engineering phases it may be difficult to obtain the adequate environmental wind-wave data where both parameters are correlated for the site of interest. The main objective of this work is to assess the influence of neglecting or not the correlation between wind speed and wave data in the resulting fatigue Damage Equivalent Load (DEL) for different FOWT components. The analysis is performed through the comparison of the fatigue loads obtained for correlated and non correlated wind-wave data. Results show that fatigue loads are very similar for both data sets at the rotor loads, and present slight differences, at mooring tensions and tower base. The use of a simpler metocean data, where wave height and period occurrences are given independently of the wind speed, might be a sufficient solution for initial fatigue load estimations.
Power curve measurement of a floating offshore wind turbine with a nacelle-based lidar
Authors: Özinan Umut , Liu Dexing , Adam Raphaël , Choisnet Thomas , Cheng Po Wen
Published: June 2022

Understanding the power performance of floating offshore wind turbines is essential for the economics of floating wind, which requires reliable wind speed measurements. This work investigates the use of nacelle-based lidar technology for power curve measurement of a floating offshore wind turbine. In a five-month long measurement campaign, a nacelle-based lidar was installed on top of a 2MW floating offshore wind turbine. It was used to reconstruct the wind field including a carrier-to-noise ratio threshold filter, an availability filter and a hard target filter for the one hertz line of sight measurements. The quality of lidar wind speed estimations were compared to nacelle-based sonic anemometer measurements in terms of their linear correlation and root mean squared error of ten minute averages. The correlation of rotor averaged wind speed estimation of lidar and sonic wind speed measurements showed a 0.97 coefficient of determination. Variability of correlation is investigated in terms of nacelle excitations to identify the uncertainty related to the use of nacelle lidars for floating wind applications. Findings show that the quality of correlation decreased with higher nacelle excitations, which are caused by both wind and waves. Consequently, wind speed estimations were used for power curve measurement to investigate the qualification of using a nacelle-based lidar for such an application. Although lidar measurements showed higher scatter, they provided a reasonable wind speed estimate and a similar power curve to sonic measurements.
Shell buckling simulations of suction buckets with stochastic and deterministic imperfection forms
Authors: Böhm Manuela , Schaumann Peter
Published: June 2022

Suction buckets are large shell structures that have become a prominent alternative to pile foundations for bottom-fixed and floating offshore wind turbines. They are embedded by applying negative pressure, which leads to a high risk of structural buckling during the installation. The prediction of the buckling strength of such large shells is subject to uncertainty, since it depends significantly on the initial geometric imperfections resulting from the fabrication process. The aim of this work is to understand and reduce uncertainties in the determination of the buckling pressure. Previous work on suction buckets revealed that the choice of a representative imperfection form and amplitude is very challenging and has not yet been solved in a generalized manner. In this work, a stochastic modeling approach is introduced, which considers more realistic imperfection patterns. This approach is compared to widely established imperfection forms such as buckling mode affine imperfections and analytically described weld depressions. The generated imperfection patterns are applied to geometrically and materially nonlinear finite element models and the buckling pressures are calculated. By quantifying the impact of different imperfection forms and amplitudes, uncertainties can be reduced, and design optimization and cost minimization are enabled.
Modified Constitutive Relation Error for Multi-Physics Wind Turbine Calibration
Authors: Roussel A. , Capaldo M. , Chamoin L. , Argaud J.-P.
Published: June 2022

Asbtract. Despite the availability of massive operation datasets, numerous uncertain parameters linger in offshore wind modeling. We propose an identification procedure based on reliability of information coming from both modeling and measurements. The procedure is constructed from the modified Constitutive Relation Error concept, which considers measurement noise and model uncertainties. This concept is extended to a multi-physics context involving nonlinear fluid-structure interactions. Several constitutive laws are assumed unreliable and relaxed for comparison with data and safe identification.
Multi-Physical Simulation Toolchain for the Prediction of Acoustic Emissions of Direct Drive Wind Turbines
Authors: Cardaun Martin , Mülder Christoph , Decker Thomas , Dilba Boris , Duda Tobias , Schelenz Ralf , Jacobs Georg , Hameyer Kay , Keuchel Sören
Published: June 2022

To address the acoustic behaviour of wind turbines, particularly tonalities, in an early design stage, accurate simulation toolchains have to be developed. In this work a novel simulation approach for the prediction of tonalities of direct drive wind turbines is presented. Comprehensive work is carried out in the fields of electromagnetic force excitation, structural sound transfer and radiation as well as airborne sound propagation. The developed methods are combined to a simulation toolchain to formulate a multi-physical system model of a direct drive wind turbine in order to predict tonal sound behaviour. These methods will be presented and discussed in detail in the course of this work. First, the approach, integrating the electromagnetic airgap forces of the large generator into a multi body simulation model of the mechanical turbine, is explained and validated with test bench measurements. Following, the modeling of the respective mbs is presented which calculates the resulting surface velocities. This model is solved in the time domain to account for the interaction between the external loads that are highly nonlinear and low-frequency and the high-frequency excitation forces of the generator. Subsequently, the methods for calculating the airborne sound emission in the vincinity of the turbine resulting from the surface velocities are discussed.
A surrogate model of offshore wind farm support structures for wind farm design and financial valuation
Authors: McWilliam Michael K. , Friis-Møller Mikkel , Pollini Nicolò , Dykes Katherine , Jensen Morten
Published: June 2022

In the preliminary phases of offshore wind farm development, very little information on project design are available for supporting financial valuation and site design. In this work, we develop a surrogate model for offshore wind support structure mass for input to techno-economic analysis that is based on a small set of input parameters. Using reference turbines and a broad set of met-ocean conditions, a large design spaced is developed from which a sampling of conditions is used to estimate the dimensions and mass of monopile support structures. The results are parameterized using statistical methods to create a functional model of costs relative to high-level site and technical inputs. To preserve the transparency of the model input-output relationships, a statistical surrogate model is used based on quadratic functions of the inputs. Overall, the rated power and rotor diameter of the turbine has the greatest influence on the mass, followed by the specific power. The water depth was the next most important environmental parameter, followed by wave period. The full surrogate model captures 98.5% of the variance of the monopile mass as a function of the above inputs. We present results related to monopile foundations, but the methodology is flexible and can be applied also in the case of other types of support structures.
Wind farm layout and unconstrained hub height optimization using genetic algorithms applied to different power densities
Authors: Kirchner-Bossi Nicolas , Porté-Agel Fernando
Published: June 2022

LES and wind tunnel studies have shown significant benefit when allowing turbines (T) in a wind farm to adopt different heights. This work presents two new genetic algorithms (GA) that perform wind farm layout optimization (WFLO) involving continuous and top-unconstrained Z-coordinate (XYZ-WFLO), applied to different power densities (PD) and using Horns Rev 1 as case study. One provides each turbine the possibility to adopt any height (XYZInd
). The other is a self-adaptive GA allowing turbines to automatically cluster into a fixed number of maximum heights (XYZClus). When considering 80T, compared to the baseline the levelized cost of energy (LCOE) is reduced up to 2.3% (XYZInd
), vs. a 0.88% improvement obtained through XY-WFLO. XYZClus
shows performances close to XYZInd even with just 2 Z-clusters (2%), which can entail a more feasible solution for the industry. The allowance for different heights exerts the main role in the performance improvement, in contrast to merely allowing turbines to increase their height. Results considering different PD yield the optimum XYZ-WFLO performance through 70T (2.5% LCOE decrease), while XY-WFLO provides best results considering 60T (1.5%). This indicates that the most efficient XYZ-WFLO solution also allows for bigger power productions. The benefit of XYZ-WFLO against XY-WFLO increases with PD. The optimized solutions arrange turbines into very few different heights, whose amount is positively related to PD. Finally, it is verified that the solutions attained reproduce the vertically staggered patterns proposed in conceptual studies (LES, wind tunnel).
Stability analysis of vortex-induced vibrations on wind turbines
Authors: Riva Riccardo , Horcas Sergio G. , Sørensen Niels N. , Grinderslev Christian , Pirrung Georg R.
Published: June 2022

A parked wind turbine can be subjected to large yaw angles, which causes vortex shedding. Under some particular inflow conditions, the interaction between the shed vorticity and the blade structure could lead to Vortex-Induced Vibrations (VIV). VIV are an instability where the response grows until it reaches a limit cycle oscillation. In this paper, we will focus on this last part of the response. We will see that the shedding makes the aeroelastic system linear time-periodic, and study its stability with Floquet theory. We will use high-fidelity simulations of different inflow conditions, and quantify the stability of the system using a model-free approach.
Aeroelastic Stability Analysis of a Quad-Rotor Wind Turbine
Authors: Ferede Etana , Stillman Alexander , Gandhi Farhan
Published: June 2022

This paper presents the aeroelastic stability analysis of a quad-rotor wind turbine and identifies modes with low damping that are otherwise not present on a single-rotor wind turbine. The non-linear dynamics of a wind turbine model in SIMPACK, without considering wind shear and tower shadow, is linearized around a steady-state; followed by MBC transformation resulting in LTI model. Standard eigenvalue analysis of LTI model is carried out to capture the natural frequency and damping of a quad-rotor wind turbine as a function of wind speed. Results show that several modes with low damping (besides the low damping modes observed on a single-rotor wind turbines) are identified where the damping ratio is less than 1% over the entire operation range.
High Wind Speed Performance of AeroMINE at Pilot-Scale
Authors: Houchens B C , Marian D V , Pol S , Westergaard C H
Published: June 2022

AeroMINEs consist of a mirrored pair of foils that have no external moving parts. A low-pressure region is created between the foils. The foils are hollow and the low-pressure side skins contain orifices (air-jets) that allow air to flow from the interior of the foil to the exterior flow, driven by the suction between the mirrored pair. This flow is ducted to an internal turbine and generator, producing electricity. A series of pilot-scale field (1-m chord) demonstrations were performed on AeroMINEs. These included both low wind speed tests (<5 m/s) and high wind speed tests (>9 m/s) at the Sandia National Laboratories Scaled Wind Farm Technology site in Lubbock, Texas, USA. Here the performance in high wind speed conditions is studied while varying the air-jet area. An efficiency of 25%, or 42% of Betz limit, was achieved for the maximum air-jet area.
Real-world development challenges of the Clarkson University 3 meter ducted wind turbine
Authors: Visser Kenneth D.
Published: June 2022

The enticing viability of ducted turbines continues to be demonstrated around the world, both numerically and experimentally, however real-world implementation of this technology has historically been a challenge. Promising wind tunnel results for a 2.5 meter rotor ducted turbine model at Clarkson University have led to the construction of a 3 meter prototype test bed, installed on the Clarkson campus. An overview of the development process and the resulting experimental performance measurements on the 3 meter unit is presented. Construction of a prototype for field tests, including component selection, fabrication details of the structure, and selection of downstream electronics is reviewed. Performance results from various system implementations and lessons learned are compared. The turbine demonstrated Cpt efficiencies, based on the duct area, of up to 0.45.
Numerical Study using RANS model to Predict Loading of a Wind Turbine Blade with a Trailing Edge Flap
Authors: Jami R , Samara F , Johnson D A
Published: June 2022

A numerical study was conducted with a 3D steady state Computational Fluid Dynamics (CFD) model using k-ω SST at SATP conditions for air. The mesh geometry is based on a S833 airfoil with a trailing edge flap to predict the lift and moment loads. This airfoil is representative of a wind turbine blade. A set of static CFD simulation cases were conducted with a free stream velocity of 29 m/s at an angle of attack (α) between -4° and 20°. A trailing edge flap is also present on the airfoil which was operated between an angle (αf) of -20° and 20°. The airfoil has a chord of 178 mm with the trailing edge flap covering 20% of the length and chord-based Reynolds number of 350,000. The CFD results were compared against an experimental study performed in a closed-loop wind tunnel at the University of Waterloo. The wind tunnel has a contraction ratio of 9:1 and a cross section of 0.61 m square. The experimental data showed that lift forces increased at a larger angle of attack and larger downward flap angle up until stall. Moment on the blade is relatively constant regardless of the angle of attack, however, increases significantly with upward flap angle. The CFD results showed very similar results in both the lift and moment coefficient, with all angle configurations having over 90% agreeability excluding α near +/- 20°.
Ground effect for ducted wind turbines: A computational study
Authors: Sheshadri Shraddha M. , Dighe Vinit V.
Published: June 2022

Ducted wind turbines (DWTs) can take the advantage of ground effect (GE) when installed close to urban areas. To this aim, a parametric study to investigate the aerodynamic performance of DWTs in relation to three different ground distances are investigated. The flow around a commercial DWT model using a simplified duct actuator disc (AD) model based on Reynolds Averaged Navier-Stokes (RANS) equations is performed. The results indicate that DWTs placed close to the ground will lead to increased mass flow rate the turbine plane, and thereby improving the aerodynamic performance. However, the additional ground force leads to an asymmetric flow-field at the turbine plane, which will ultimately induce unsteady forces on the DWT system. The present analysis will serve as a strong recommendation to address siting issues for DWT manufacturers.
On Theoretical Foundations of Human and Robot Vision
Authors: Wang Yingxu
Published: June 2022

A set of cognitive, neurological, and mathematical theories for human and robot vision has been recognized that encompasses David Hubel’s hypercolumn vision theory (The Nobel Prize in Physiology or Medicine 1981 [1]) and Dennis Gabor’s wavelet filter theory (The Nobel Prize in Physics 1971 [2]). This keynote lecture presents a theoretical framework of the Cognitive Vision Theory (CVT) [3-6] and its neurological and mathematical foundations. A set of Intelligent Mathematics (IM) [7-13] and formal vision theories developed in my laboratory is introduced encompassing Image Frame Algebra (IFA) [3], Visual Semantic Algebra (VSA) [4], and the Spike Frequency Modulation (SFM) theory [5]. IM is created for enabling cognitive robots to gain autonomous vision cognition capability supported by Visual Knowledge Bases (VKBs). Paradigms and case studies of robot vision powered by CVTs and IM will be demonstrated. The basic research on CVTs has led to new perspectives to human and robot vision for developing novel image processing applications in AI, neural networks, image recognitions, sequence learning, computational intelligence, self-driving vehicles, unmanned systems, and robot navigations.
Research on Comprehensive Evaluation Method of Radar
Authors: Duanyang Shi , Qiang Lin , Bing Hu , Xinyu Yan
Published: June 2022

Aiming at the difficult problem of radar equipment evaluation caused by complex structure and many influencing factors, a comprehensive evaluation method of radar is proposed. This paper starts with the concept, elements and steps of comprehensive evaluation, and introduces the process of comprehensive evaluation in detail. The types of index weighting methods and the historical process of evaluation methods at home and abroad are summarized. According to the practical working experience, the radar comprehensive evaluation index system is constructed, and combining the characteristics of subjective and objective weighting methods, the combined subjective and objective weighting model is designed. On the basis of analysing the results of various evaluation methods, a combination model of evaluation results is constructed. The radar equipment is evaluated according to the scoring data of experts on the supportability of radar equipment. The effectiveness of the method is verified by an example.
A Brief Analysis of the Development of Chinese Virtual Idol Industry Empowered by 5G+Motion Capture Technology——Taking the Virtual Idol Group A-SOUL as an Example
Authors: Wang Y. Q.
Published: June 2022

A-SOUL, a virtual idol girl group, debuted in December 2020, and in just one year, it has turned around from a very poor reputation to become the most influential subculture IP in China today. virtual idols are real people performing in virtual spaces on the internet using virtual images, and the superior motion capture technology, visual design, and 5G network are the key reasons why A-SOUL has been able to stand out from the crowd of virtual anchors. A-SOUL’s superior motion capture technology, visual design, and 5G network are what make it stand out from the crowd of virtual hosts. This paper will use A-SOUL as an example to analyze the current situation, dilemmas, and future development trends of virtual anchor technology in China, and explore the possibilities of virtual idols as an opportunity to drive technological and social change in China.
Score-CAM++: Class Discriminative Localization with Feature Map Selection
Authors: Chen Yifan , Zhong Guoqiang
Published: June 2022

In recent years, explaining convolutional neural networks (CNN) has received increasing attention since it helps to build humans’ trust on CNNs by exposing their inference basis. In this field, generating intuitive saliency maps that highlight the input regions most related to model decisions is one of the popular approaches. Building on a state-of-the-art saliency method named Score-CAM, we propose Score-CAM++ to generate better saliency maps with higher efficiency (when compared to Score-CAM). Different from Score-CAM, which adopts all the feature maps in target layer to produce saliency maps, we propose the “feature map selection” operation to select the feature maps that capture the “positive” information (i.e., the features whose increment in intensity leads to an increase in target score). Then the selected feature maps are up-sampled as masks to perturb the input and compute the weights of the corresponding feature maps. Finally, the linear combination of the weighted feature maps forms the saliency map. Compared with Score-CAM, the experiments based on VGG-16 show that our method saves 25%-30% of the time when generating saliency maps. Meanwhile, our conducted evaluations, both subjective and objective, show that our method provides better visual explanations when compared to the previous saliency methods.
Supervised Contrastive Representation Embedding Based on Transformer for Few-Shot Classification
Authors: Wu Jianxin , Tian Xiangtao , Zhong Guoqiang
Published: June 2022

Few-shot learning as an emerging problem has attracted intensive attention in the data-limited situations of Computer Vision. Recently, massive works concentrate on exploiting meta learning to improve performance of recognition. However, most of them overlook the intra-class and inter-class relationships within the support set during episodic training, which are significant and important for the tasks of downstream. To tackle this problem, we present an efficient supervised contrastive representation embedding for few-shot classification. Specially, (1) we employ Swin Transformer as the backbone to replace CNN architecture in order to explore the huge potential of transformer-based backbone for the field of few-shot learning. (2) We introduce supervised contrastive loss to meta learning to take good advantage of extremely limited relations for the first time. Combined the classifier based on metric learning, extensive experiments have demonstrated the efficiency of the representation embedding. We conduct experiments and establish competitive results on two widely-used few-shot classification benchmarks: Fewshot-CIFAR 100 (FC-100) and MiniImageNet.
Classification of Epileptic Brain Signals of College Students Based on Deep Learning
Authors: Zhang Fuchun , Qi Lei , Li Meng , Wang Baiyang , Yang Yue , Zheng Guiyue
Published: June 2022

Epilepsy, as a common nervous system disease in the world, urgently needs effective methods for diagnosis and treatment. Scalp electroencephalogram (EEG) contains a lot of physiological and pathological information, which plays a very important role in the diagnosis of brain diseases such as epilepsy. At present, the clinical analysis of EEG signal is mainly based on the clinician’s visual analysis, which makes the clinician’s task heavy, and there is no quantitative standard for the analysis results. Therefore, the automatic classification of epileptic EEG signals has great potential in current clinical application. Based on the deep learning VGG16 convolutional neural network model, a method for automatic detection of seizure signals is proposed in this paper. Firstly, the samples are preprocessed, then enter the VGG16 convolutional neural network model for training, and finally input the validation set for validation. The experimental results indicate that this model can distinguish the pre-ictal EEG, interictal EEG and ictal EEG.
Deep Face-Swap Model Combining Attention Mechanism and CycleGAN
Authors: Liu Kai , Li Bicheng , Li Jiale
Published: June 2022

Deep face swapping is a hot field in computer vision, which uses deep learning technology to replace the face in the original image while keeping other contents unchanged. To solve the problem of discontinuities across the blending boundaries in existing mainstream deepfake methods, we propose a face swapping model combining attention mechanism and CycleGAN. Firstly, a generator incorporating the attention module is used to obtain the generated graph. Then, the discriminator based on PatchGAN is used to discriminate if the graph is synthesized. Finally, the least square loss and SmoothL1 loss are used to improve the loss function. Experimental results manifest that our method reduces the difference by 0.43 in facial region and increases the similarity by 0.56 in background region. The model we proposed can improve the quality of face swapping images effectively, and enrich the existing face swapping methods, which has great significance for both generation and detection of deep face swapping research.
Image Segmentation of Endoscopic Cataract Based on Semantic Segmentation
Authors: Chen Jingshi , Ye Haili , Yin Huayi , Wang Da-Han , Li Jianmin
Published: June 2022

Medical imaging technology has become one of the indispensable computer-assisted intervention methods in clinical disease diagnosis and treatment, including identifying and locating lesion areas, detecting and segmenting tissue and organ lesions in different modalities. The wide application of medical image analysis in clinical examination and medical auxiliary diagnosis has effectively improved the diagnostic efficiency of doctors. In this paper, we propose a novel and effective model to achieve semantic segmentation of cataract datasets. This model uses the self-supervised method BYOL for parameter pre-training, which improves the model’s ability to extract image consistency features. In addition, we have added a lightweight Coordinate attention mechanism to the backbone network to enable the model to independently learn the correlation between the channel and the space and enhance the ability of network feature expression. Experiments are conducted on the cataract endoscopy fine-grained segmentation data set, showing the effectiveness of the proposed method for segment the organs and surgical instruments in the cataract surgical microscope image, which demonstrates the accuracy and robustness of the proposed method.
Branching pattern of flexible trees for environmental load mitigation
Authors: Ojo Oluwafemi , Shoele Kourosh
Published: June 2022

Wind-induced stress is the primary mechanical cause of tree failures. Among different factors, the branching mechanism plays a central role in the stress distribution and stability of trees in windstorms. A recent study showed that Leonardo da Vinci’s original observation, stating that the total cross section of branches conserved across branching nodes is the optimal configuration for resisting wind-induced damage in rigid trees, is correct. However, the breaking risk and the optimal branching pattern of trees are also a function of their reconfiguration capabilities and the processes they employ to mitigate high wind-induced stress hotspots. In this study, using a numerical model of rigid and flexible branched trees, we explore the role of flexibility and branching patterns of trees in their reconfiguration and stress mitigation capabilities. We identify the robust optimal branching mechanism for an extensive range of tree flexibility. Our results show that the probability of a tree breaking at each branching level from the stem to terminal foliage strongly depends on the cross section changes in the branching nodes, the overall tree geometry, and the level of tree flexibility. Three response categories have been identified: the stress concentration in the main trunk, the uniform stress level through the tree’s height, and substantial stress localization in the terminal branches. The reconfigurability of the tree determines the dominant response mode. The results suggest a very similar optimal branching law for both flexible and rigid trees wherein uniform stress distribution occurs throughout the tree’s height. An exception is the very flexible branched plants in which the optimal branching pattern deviates from this prediction and is strongly affected by the reconfigurability of the tree.
Detailed microwave absorption performance of BaFe12O19 nano-hexaplates with a large variety of thicknesses
Authors: Thi Kim Yen Nguyen , Tuan Nguyen Quy , Trinh Ngoc Dat , Son Le Vu Truong , Dang Ngoc Toan , Thi Le Anh , Tran Nguyen Tien , Tran Ngo
Published: June 2022

We successfully prepared BaFe12O19 (BaM) nano-hexaplates using the co-precipitation method followed by heat treatment. The hexaplate-like grain size varied in the range of 50–200 nm, while its crystalline size was ∼46 nm. Before investigating microwave absorption, structural and magnetic properties were studied by x-ray diffraction, Raman scattering, and a vibrating sample magnetometer. The structural studies showed a pure phase of BaM, while the magnetic studies revealed a ferro/ferrimagnetic behaviour with M
s = 59.93 emu g−1, M
r = 32.49 emu g−1, and H
c = 5.16 kOe. Microwave dissipation features were systemically investigated for device thickness of 0.25–10 mm with a measured frequency range of 2–16 GHz. The study showed that the BaFe12O19 sample could absorb more than 99.9% of the incident microwave in the 12–14 GHz frequency range for 6.5 mm thickness. The effective absorption bandwidth was also fairly large, as ∼3 GHz in this frequency range. The microwave dissipation features of BaM in this work were better than pure BaM ones in other studies and relatively comparable with BaM-based microwave absorbers. The magnetic loss originated from natural resonance, while the dielectric loss resulted from multi-interface, interface, and dipolar polarization. Overall, the BaFe12O19 sample in this study could be used as a promising microwave absorber in the Ku waveband.
Nilpotent varieties in symmetric spaces and twisted affine Schubert varieties
Authors: Hong Jiuzu , Korkeathikhun Korkeat
Published: June 2022

We relate the geometry of Schubert varieties in twisted affine Grassmannian and the nilpotent varieties in symmetric spaces. This extends some results of Achar–Henderson in the twisted setting. We also get some applications to the geometry of the order 2 nilpotent varieties in certain classical symmetric spaces.
Differences in Fine Particle Exposure and Estimated Pulmonary Ventilation Rate with Respect to Work Tasks of Wildland Firefighters at Prescribed Burns: A Repeated Measures Study
Authors: Adetona Anna M , Adetona Olorunfemi , Chartier Ryan T , Paulsen Michael H , Simpson Christopher D , Rathbun Stephen L , Naeher Luke P
Published: June 2022

Wildland firefighters (WLFFs) are exposed to a mixture of chemicals found in wildland fire smoke and emissions from nonwildland-fuel smoke sources such as diesel. We investigated compositional differences in exposure to particulate matter and explored differences in ventilation rate and potential inhaled dose relative to the work tasks of WLFFs. Repeated measures on ten professional and two volunteer firefighters were collected on prescribed burn and nonburn days. Personal monitoring consisted of real-time and gravimetric fine particulate matter (PM2.5), carbon monoxide (CO), and accelerometer measurements to estimate ventilation rate and potential dose of PM2.5. The fine particulate matter was analyzed for levoglucosan (LG) and light absorbing carbon as a surrogate for black carbon (BC). Breathing zone personal exposure concentrations of PM2.5, LG, BC, and CO were higher on burn days (P < 0.05). Differences in exposure concentrations were observed between burn day tasks (P < 0.05) with firefighters managing fire boundaries (holders) being exposed to higher CO and LG concentrations and less BC concentrations than those conducting lighting (lighters). While no statistical difference in PM2.5 exposure measures was observed between the two tasks, holders in the study tended to be exposed to higher PM2.5 concentrations (~1.4×), while lighters tended to have more inhaled amounts of PM2.5 (~1.3×). Our findings demonstrate possible diversity in the sources of particulate matter exposure at the fireline and suggest the potential importance of using dose as a metric of inhalation exposure in occupational or other settings.