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Статті в журналах з теми "Dynamic stall prediction"
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Ekaterinaris, John A., and Max F. Platzer. "Computational prediction of airfoil dynamic stall." Progress in Aerospace Sciences 33, no. 11-12 (April 1998): 759–846. http://dx.doi.org/10.1016/s0376-0421(97)00012-2.
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Carr, Lawrence W. "Progress in analysis and prediction of dynamic stall." Journal of Aircraft 25, no. 1 (January 1988): 6–17. http://dx.doi.org/10.2514/3.45534.
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Liu, Xiong, Cheng Lu, Shi Liang, Ajit Godbole, and Yan Chen. "Improved dynamic stall prediction of wind turbine airfoils." Energy Procedia 158 (February 2019): 1021–26. http://dx.doi.org/10.1016/j.egypro.2019.01.247.
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Richter, K., A. Le Pape, T. Knopp, M. Costes, V. Gleize, and A. D. Gardner. "Improved Two-Dimensional Dynamic Stall Prediction with Structured and Hybrid Numerical Methods." Journal of the American Helicopter Society 56, no. 4 (October 1, 2011): 1–12. http://dx.doi.org/10.4050/jahs.56.042007.
Повний текст джерелаАнотація:
A joint comprehensive validation activity on the structured numerical method elsA and the hybrid numerical method TAU was conducted with respect to dynamic stall applications. To improve two-dimensional prediction, the influence of several factors on the dynamic stall prediction was investigated. The validation was performed for three deep dynamic stall test cases of the rotor blade airfoil OA209 against experimental data from two-dimensional pitching airfoil experiments, covering low-speed and high-speed conditions. The requirements for spatial discretization and for temporal resolution in elsA and TAU are shown. The impact of turbulence modeling is discussed for a variety of turbulence models ranging from one-equation Spalart–Allmaras-type models to state-of-the-art, seven-equation Reynolds stress models. The influence of the prediction of laminar/turbulent boundary layer transition on the numerical dynamic stall simulation is described. Results of both numerical methods are compared to allow conclusions to be drawn with respect to an improved prediction of dynamic stall.
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Abhishek, A., Shreyas Ananthan, James Baeder, and Inderjit Chopra. "Prediction and Fundamental Understanding of Stall Loads in UH-60A Pull-Up Maneuver." Journal of the American Helicopter Society 56, no. 4 (October 1, 2011): 1–14. http://dx.doi.org/10.4050/jahs.56.042005.
Повний текст джерелаАнотація:
This paper isolates the physics governing the aerodynamics and structural dynamics of UH-60A rotor in an unsteady maneuvering flight and proposes a hypothesis for the mechanism of advancing blade stall observed during pull-up maneuvers. The advancing blade stall observed during the Counter 11029 pull-up maneuver is in addition to the two conventional dynamic stall events observed on the retreating side of the blade. Both lifting-line as well as computational fluid dynamics analyses predict all three stall cycles with calculated deformations. The advancing blade transonic stall, observed from revolution 12 onward, is a twist stall triggered by 5/rev elastic twist deformation that increases the angle of attack beyond the static stall limit, resulting in shock-induced flow separation culminating in stall. The 5/rev elastic twist is triggered by the two retreating blade stalls from previous revolution, which are separated by 1/5th rev. The accurate prediction of both stall cycles on retreating blade holds the key to prediction of advancing blade stall. In analysis, advancing blade stall is triggered by a correct combination of control angles and 5/rev elastic twist.
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Shi, Zheyu, Kaiwen Zhou, Chen Qin, and Xin Wen. "Experimental Study of Dynamical Airfoil and Aerodynamic Prediction." Actuators 11, no. 2 (February 2, 2022): 46. http://dx.doi.org/10.3390/act11020046.
Повний текст джерелаАнотація:
Dynamic stall is a critical limiting factor for airfoil aerodynamics and a challenging problem for active flow control. In this experimental study, dynamic stall was measured by high-frequency surface pressure tapes and pressure-sensitive paint (PSP). The influence of the oscillation frequency was examined. Dynamic mode decomposition (DMD) with time-delay embedding was proposed to predict the pressure field on the oscillating airfoil based on scattered pressure measurements. DMD with time-delay embedding was able to reconstruct and predict the dynamic stall based on scattered measurements with much higher accuracy than standard DMD. The reconstruction accuracy of this method increased with the number of delay steps, but this also prolonged the computation time. In summary, using the Koopman operator obtained by DMD with time-delay embedding, the future dynamic pressure on an oscillating airfoil can be accurately predicted. This method provides powerful support for active flow control of dynamic stall.
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Xiaohua, Li, Zheng Guo, Grecov Dana, and Zhongxi Hou. "Efficient reduced-order modeling of unsteady aerodynamics under light dynamic stall conditions." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 6 (May 10, 2018): 2141–51. http://dx.doi.org/10.1177/0954410018773628.
Повний текст джерелаАнотація:
In this research, a reduced-order modeling is developed to predict the unsteady aerodynamic forces under light dynamic stall conditions at low-speed regimes. The filtered white Gaussian noise is selected as input signals for computational fluid dynamics solver in order to generate training data, containing the information of reduced frequency and amplitude. Because of the time history influences, the reduced-order modeling combines the Kriging function and recurrence framework together in this approach. An airfoil NACA0012 undergoing pitching motions with different reduced frequency, amplitude, and mean angle of attack is designed to illustrate the methodology. The developed model can predict the lift, drag, and moment coefficients in seconds on a single-core computer processor. To reduce the prediction errors between reduced-order modeling predictions and computational fluid dynamics simulations, the aerodynamic loads in static conditions are applied as initial inputs. The predictions via the proposed approach are in agreement with the results using a high precision computational fluid dynamics solver over the designed ranges of amplitude and reduced frequency, which is suitable for engineering applications, such as fluid-structure interaction, and aircraft design optimizations.
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Adema, Niels, Menno Kloosterman, and Gerard Schepers. "Development of a second-order dynamic stall model." Wind Energy Science 5, no. 2 (May 15, 2020): 577–90. http://dx.doi.org/10.5194/wes-5-577-2020.
Повний текст джерелаАнотація:
Abstract. Dynamic stall phenomena carry the risk of negative damping and instability in wind turbine blades. It is crucial to model these phenomena accurately to reduce inaccuracies in predicting design driving (fatigue and extreme) loads. Some of the inaccuracies in current dynamic stall models may be due to the fact that they are not properly designed for high angles of attack and that they do not specifically describe vortex shedding behaviour. The Snel second-order dynamic stall model attempts to explicitly model unsteady vortex shedding. This model could therefore be a valuable addition to a turbine design software such as Bladed. In this paper the model has been validated with oscillating aerofoil experiments, and improvements have been proposed for reducing inaccuracies. The proposed changes led to an overall reduction in error between the model and experimental data. Furthermore the vibration frequency prediction improved significantly. The improved model has been implemented in Bladed and tested against small-scale turbine experiments at parked conditions. At high angles of attack the model looks promising for reducing mismatches between predicted and measured (fatigue and extreme) loading, leading to possible lower safety factors for design and more cost-efficient designs for future wind turbines.
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Haans, Wouter, Tonio Sant, Gijs van Kuik, and Gerard van Bussel. "Stall in Yawed Flow Conditions: A Correlation of Blade Element Momentum Predictions With Experiments." Journal of Solar Energy Engineering 128, no. 4 (July 16, 2006): 472–80. http://dx.doi.org/10.1115/1.2349545.
Повний текст джерелаАнотація:
Yawed flow conditions introduce unsteady loads in a wind turbine that affect generated power quality and fatigue life. An unsteady phenomenon of special concern is dynamic stall, due to the significant load fluctuations associated with it. Although the assumptions underlying blade element momentum (BEM) models are totally inadequate in yawed flow conditions, these models, modified with engineering models, are still widely used in industry. It is therefore relevant to assess the capabilities of BEM models in predicting the location of dynamic stall on the blade for a rotor in yawed flow conditions. A rotor model is placed in an open jet wind tunnel and tested in yawed flow conditions. The locations of dynamic stall on the blade of a rotor model as a function of the blade position are observed. Two experimental techniques are used; tufts glued to the blade and hot-film anemometry in the near wake. The results from the two techniques are compared and possible causes for differences are identified. Furthermore, the rotor model in yaw is modeled with a simple BEM model, utilizing a Gormont dynamic stall model. The regions of dynamic stall on the blades predicted by the BEM model are compared with the experimental results. The BEM model seems capable of a crude prediction of the dynamic stall locations found for the rotor model in yawed flow conditions.
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Ericsson, L. E., and J. P. Reding. "Fluid mechanics of dynamic stall part II. Prediction of full scale characteristics." Journal of Fluids and Structures 2, no. 2 (March 1988): 113–43. http://dx.doi.org/10.1016/s0889-9746(88)80015-x.
Повний текст джерелаДисертації з теми "Dynamic stall prediction"
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Heberling, Brian. "A Numerical Analysis on the Effects of Self-Excited Tip Flow Unsteadiness and Upstream Blade Row Interactions on the Performance Predictions of a Transonic Compressor." University of Cincinnati / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin150479438822623.
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Choudhry, Amanullah. "Unsteady separation control on wind turbine blades." Thesis, 2015. http://hdl.handle.net/2440/101653.
Повний текст джерелаАнотація:
Dynamic stall is one of the primary causes of unsteady loads on wind turbine blades. The process can be instigated by a multitude of factors, common in wind turbine operating environments, such as inflow turbulence, wind gusts and sustained yaw misalignment. The unsteady separation due to dynamic stall can lead to excessive loads, much larger than the design loads for the turbine, and vibrations in the blade, leading to fatigue damage. Furthermore, massive flow separations can lead to performance losses for the turbines. Therefore, it is of utmost importance to devise methods to control the unsteady separation on wind turbines and to reduce its impact on the performance and structural integrity of the system. Dynamic stall on wind turbine blades is initiated by a rapid variation in wind speed and direction. However, no viable methods are available that could reliably predict the occurrence of unsteady separation for wind turbines. Therefore, in the present research, an analytical method has been developed and validated against well-known test cases to quickly and reliably deduce the variations in the sectional angles of attack, based on the variability of wind speed and direction of the oncoming flow. The concept of limiting reduced frequency as a precursor for unsteady separation is proposed in this initial study. Furthermore, it is illustrated, using high-quality wind data, that unsteady separation principally exists near the root regions of turbine blades where thick airfoil sections are generally used. Further research was conducted to determine the effects of wakes on the occurrence of dynamic stall. For this study, the mean and turbulent wind conditions in the wake were acquired through Large Eddy Simulation of a wind turbine wake performed at the University of Adelaide. The data was used to determine the influence of wakes on the occurrence of dynamic stall on wind turbines operating in the wake of an upstream turbine. It was shown that the primary cause of large unsteady loads on downstream wind turbines is the rapid variation in the wind direction. It is emphasized that the model can be used during wind turbine design phase to determine the regions of the blade where the dynamic stall control is necessary. After determining the occurrence of dynamic stall on the turbine blades under normal operating conditions, the second objective of the present research was to gain a deeper insight into the dynamic stall process, particularly the lift characteristics of thick airfoils under unsteady separation. Experiments were conducted to understand the non-linear lift behavior of the airfoil during dynamic stall at constant pitch rates. It was shown that the thickening of the boundary layer during pitch-up resulted in an apparent increase in the thickness and camber of the airfoil. It is, furthermore, proposed that the primary dynamic stall vortex also increases the effective camber of the airfoil. This results in the sudden increase in the lift-slope when the vortex is formed. This effect was further demonstrated using numerical simulations of the thick NACA 0021 airfoil at low turbulence levels. During steady-state operation, a long separation bubble on the airfoil surface was found to be responsible for the increased lift-slope, greater than the theoretical maximum, and the abrupt stalling behavior of the foil. It was proposed that this long separation bubble was responsible for an apparent increase in the airfoil’s camber. Furthermore, removing the bubble, through an artificial increase in turbulence, degraded the lift-to-drag ratio of the airfoil. However, due to the absence of the bubble, the steady-state stall angle of attack was significantly increased. This study, therefore, illustrated that apparent changes in thickness and camber of the airfoil during dynamic stall process are principally responsible for the non-linear lift behavior. It was observed, in the experiments, that an increase in the reduced frequency or the Reynolds number resulted in the increase in the strength of the primary dynamic stall vortex. It was also observed that the stall intensity of the airfoil undergoing unsteady separation is also dictated by the primary vortex. Therefore, an increase in the reduced frequency or the Reynolds number resulted in increased stall intensity. Hence, in order to improve the post-stall lift behavior of the airfoil, it is necessary to modify the primary dynamic stall vortex. This can be accomplished by reducing the strength of the vortex and delaying its formation on the airfoil by minimizing the reversed flow accumulation that leads to the formation of the vortex. In order to propose appropriate control methodologies for dynamic stall on wind turbine blades, literature survey illustrated that the required control would need to be implemented passively, near the leading edge of the airfoil. It was, furthermore, observed that the control methodologies need to be deployed before the formation of the dynamic stall vortex in order to affect the post-stall behavior of the foil. Finally, the required control needs to influence the flow field to a large extent to diminish the effects of the vortex. Therefore, three different methods were proposed to control the dynamic stall process. These included streamwise vortices generated using leading edge vortex generators, spanwise-vortices generated using a novel concept of a thin elevated wire affixed at the leading edge, and a cavity on the upper surface of the airfoil. It is demonstrated through experiment that all three methods influence the formation of the dynamic stall vortex during unsteady separation. However, the methods that promoted enhanced mixing, namely the vortex generators and the elevated wire, were observed to favorably reduce the excessive lift associated with the primary vortex structure. It was also observed that the stall intensity was significantly reduced for these methods since the strength of the primary dynamic stall vortex was significantly reduced. It was, furthermore, illustrated that these methods aid in the lift recovery after separation, leading to reduced stall intensity and post-stall load fluctuations. On the other hand, the cavity was observed to consistently delay the unsteady separation. However, the primary vortex structure was not affected to large degree and, therefore, the stall intensity was similar to the baseline airfoil. Out of these three methods, it is proposed that the vortex generators and the novel elevated wire concept can be used to control the process of dynamic stall on wind turbine blades. These methods are not only easier to implement on existing blades, but also improve the steady-state performance of the airfoil through sustained lift and reduced drag, even at high angles of attack. The research presented in this thesis aims to improve the unsteady stalling conditions of wind turbine blades. This is accomplished by minimizing the primary dynamic stall vortex lift generated during pitchup and reducing the abrupt lift-decay after separation. The thesis presents a comprehensive review of dynamic stall on wind turbine blades as well as investigates previous attempts in controlling the unsteady separation. The new research conducted in the thesis has been presented in the form of journal manuscripts, arranged in an order that will assist the development of ideas. The research as a whole provides renewed insight into dynamic stall control on wind turbine blades.Thesis (Ph.D.) (Research by Publication) -- University of Adelaide, School of Mechanical Engineering, 2015.
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Boersma, Pieter. "A NUMERICAL FLUTTER PREDICTOR FOR 3D AIRFOILS USING THE ONERA DYNAMIC STALL MODEL." 2018. https://scholarworks.umass.edu/masters_theses_2/692.
Повний текст джерелаАнотація:
To be able to harness more power from the wind, wind turbine blades are getting longer. As they get longer, they get more flexible. This creates issues that have until recently not been of concern. Long flexible wind turbine blades can lose their stability to flow induced instabilities such as coupled-mode flutter. This type of flutter occurs when increasing wind speed causes a coupling of a bending and a torsional mode, which create limit cycle oscillations that can lead to blade failure. To be able to make the design of larger blades possible, it is important to be able to predict the critical flutter and post critical flutter behaviors of wind turbine blades.
Most numerical research concerning coupled-mode wind turbine is focused on predicting the critical flutter point, and less focused on the post critical behavior. This is because of the mathematical complexities associated with the coupled, nonlinear wind turbine blade systems. Here, a numerical model is presented that predicts the critical flutter velocity and post critical flutter behavior for 3D airfoils with third order structural nonlinearities. The numerical model can account for the attached flow and separated flow region by using the ONERA dynamic stall model. By retaining higher-order structural nonlinearities, lateral and torsional displacements can be predicted, which makes it possible to use this model in the future to control wind turbine blade flutter. Furthermore, by using a dynamic stall model to simulate the flow, the solver is able to predict accurate limit cycle oscillations when the effective angle of attack is larger than the stall angle.
The coupled, nonlinear equations of motion are two coupled nonlinear PDEs and are determined using Hamilton’s principle. In order to solve the equations of motion, they are discretized using the Galerkin technique into a set of ODEs. The motion of the airfoil is used as an input to ONERA. The airfoil is sectioned with the lateral position and angle of attack known as well as the velocity and acceleration of the section at an instance of time. This information is used by ONERA to calculate lift and moment coefficients for each section which are then used to calculate the total lift and moment forces of the airfoil. Then, a Fortran code solves the system by using Houbolt’s finite difference method.
A theoretical NACA 0012 airfoil has been designed to define the parameters used by the equations of motion. Third bending and first torsional coupling occurs after the critical flutter point and dynamic lift and moment coefficients were observed. Dynamic stall was also observed at wind velocities farther away from the bifurcation point. Bifurcation diagrams, time histories, and phase planes have been created that represent the flutter behavior.
Книги з теми "Dynamic stall prediction"
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Elazar, Yekutiel. A mapping of the viscous flow behavior in a controlled diffusion compressor cascade using laser doppler velocimetry and preliminary evaluation of codes for the prediction of stall. Monterey, California: Naval Postgraduate School, 1988.
Знайти повний текст джерелаЧастини книг з теми "Dynamic stall prediction"
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Jones, K. D., and M. F. Platzer. "On the Prediction of Dynamic Stall Onset on Airfoils in Low Speed Flow." In Unsteady Aerodynamics and Aeroelasticity of Turbomachines, 797–812. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5040-8_52.
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Alessi, Lucia, and Roberto Savona. "Machine Learning for Financial Stability." In Data Science for Economics and Finance, 65–87. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66891-4_4.
Повний текст джерелаАнотація:
AbstractWhat we learned from the global financial crisis is that to get information about the underlying financial risk dynamics, we need to fully understand the complex, nonlinear, time-varying, and multidimensional nature of the data. A strand of literature has shown that machine learning approaches can make more accurate data-driven predictions than standard empirical models, thus providing more and more timely information about the building up of financial risks. Advanced machine learning techniques provide several advantages over empirical models traditionally used to monitor and predict financial developments. First, they are able to deal with high-dimensional datasets. Second, machine learning algorithms allow to deal with unbalanced datasets and retain all of the information available. Third, these methods are purely data driven. All of these characteristics contribute to their often better predictive performance. However, as “black box” models, they are still much underutilized in financial stability, a field where interpretability and accountability are crucial.
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Harbola, Shubhi, Martin Storz, and Volker Coors. "Augmented Reality for Windy Cities: 3D Visualization of Future Wind Nature Analysis in City Planning." In iCity. Transformative Research for the Livable, Intelligent, and Sustainable City, 241–50. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92096-8_15.
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AbstractEffective government management, convenient public services, and sustainable industrial development are achieved by the thorough utilization and management of green, renewable resources. The research and the study of meteorological data and its effect on devising renewable solutions as a replacement for nonrenewable ones is the motive of researchers and city planners. Sources of energy like wind and solar are free, green, and popularly being integrated into sustainable development and city planning to preserve environmental quality. Sensor networks have become a convenient tool for environmental monitoring. Wind energy generated through the use and maintenance of wind turbines requires knowledge of wind parameters such as speed and direction for proper maintenance. An augmented reality (AR) tool for interactive visualization and exploration of future wind nature analyses for experts is still missing. Existing solutions are limited to graphs, tabular data, two-dimensional space (2D) maps, globe view, and GIS tool designed for the desktop and not adapted with AR for easy, interactive mobile use. This work aims to provide a novel AR-based mobile supported application (App) that serves as a bridge between three-dimensional space (3D) temporal wind dataset visualization and predictive analysis through machine learning (ML). The proposed development is a dynamic application of AR supported with ML. It provides a user interactive designed approach, presenting a multilayered infrastructure process accessed through a mobile AR platform that supports 3D visualization of temporal wind data through future wind analysis. Thus, a novel AR visualization App with the prediction of wind nature using ML algorithms would provide city planners with advanced knowledge of wind conditions and help in easy decision-making with interactive 3D visualization.
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Traveset, Anna, and David M. Richardson. "Plant invasions: the role of biotic interactions - an overview." In Plant invasions: the role of biotic interactions, 1–25. Wallingford: CABI, 2020. http://dx.doi.org/10.1079/9781789242171.0001.
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Abstract Diverse biotic interactions between non-native plant species and other species from all taxonomic groups are crucial mediators of the dynamics of plant invasions. This chapter reviews the key hypotheses in invasion ecology that invoke biotic interactions to explain aspects of plant invasion dynamics. We examine the historical context of these hypotheses and assess the evidence for accepting or rejecting their predictions. Most hypotheses invoke antagonistic interactions, mainly competition, predation, herbivory interactions and the role of pathogens. Only in the last two decades have positive (facilitative/mutualistic) interactions been explicitly included in invasion biology theory (as in ecological theory in general). Much information has accumulated in testing hypotheses relating to biotic resistance and Enemy Release Theory, although many of the emerging generalizations are still contentious. There is growing consensus that other drivers of plant invasion success, such as propagule pressure and disturbance, mediate the outcome of biotic interactions, thereby complicating our ability to make predictions, but these have rarely been assessed in both native and adventive ranges of non-native invasive species. It is also widely acknowledged that biogeographic comparisons, more than common garden experiments, are needed to shed light on many of the contradictory results. Contrasting findings have also emerged in exploring the roles of positive interactions. Despite strong evidence that such interactions are crucial in many communities, more work is needed to elucidate the factors that influence the relative importance of positive and negative interactions in different ecosystems. Different types of evidence in support of invasional meltdown have emerged for diverse habitats and across spatial scales. In light of increasing evidence that biotic indirect effects are crucial determinants of the structure, dynamics and evolution of ecological communities, both direct and indirect interactions involving native and non-native species must be considered to determine how they shape plant invasion patterns and the ecological impacts of non-native species on recipient communities. Research that examines both biotic interactions and the factors that mediate their strength and alter interaction outcomes is needed to improve our ability to predict the effects of novel interactions between native and non-native species, and to envisage how existing invaded communities will respond to changing environmental conditions. Many opportunities exist for manipulating biotic interactions as part of integrated control strategies to reduce the extent, density and impacts of non-native plant invasions. These include the introduction of species from the native range of the non-native plant for biological control, diverse manipulations of plant - herbivore interactions and many types of interaction to enhance biotic resistance and steer vegetation recovery following non-native plant control.
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Ekaterinaris, J. A., and M. F. Platzer. "Effects of Turbulence Modeling and Transition on the Numerical Prediction of Dynamic Stall." In Engineering Turbulence Modelling and Experiments, 707–16. Elsevier, 1996. http://dx.doi.org/10.1016/b978-0-444-82463-9.50074-5.
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Brahimi, Tayeb, and Ion Paraschivoiu. "Aerodynamic Analysis and Performance Prediction of VAWT and HAWT Using CARDAAV and Qblade Computer Codes." In Entropy and Exergy in Renewable Energy [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.96343.
Повний текст джерелаАнотація:
Wind energy researchers have recently invited the scientific community to tackle three significant wind energy challenges to transform wind power into one of the more substantial, low-cost energy sources. The first challenge is to understand the physics behind wind energy resources better. The second challenge is to study and investigate the aerodynamics, structural, and dynamics of large-scale wind turbine machines. The third challenge is to enhance grid integration, network stability, and optimization. This chapter book attempts to tackle the second challenge by detailing the physics and mathematical modeling of wind turbine aerodynamic loads and the performance of horizontal and vertical axis wind turbines (HAWT & VAWT). This work underlines success in the development of the aerodynamic codes CARDAAV and Qbalde, with a focus on Blade Element Method (BEM) for studying the aerodynamic of wind turbines rotor blades, calculating the induced velocity fields, the aerodynamic normal and tangential forces, and the generated power as a function of a tip speed ration including dynamic stall and atmospheric turbulence. The codes have been successfully applied in HAWT and VAWT machines, and results show good agreement compared to experimental data. The strength of the BEM modeling lies in its simplicity and ability to include secondary effects and dynamic stall phenomena and require less computer time than vortex or CFD models. More work is now needed for the simulation of wind farms, the influence of the wake, the atmospheric wind flow, the structure and dynamics of large-scale machines, and the enhancement of energy capture, control, stability, optimization, and reliability.
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Vu, Trieu Minh, Reza Moezzi, Jindrich Cyrus, Jaroslav Hlava, and Michal Petru. "Autonomous Vehicle Tracking Based on Non-Linear Model Predictive Control Approach." In Applications of Computational Science in Artificial Intelligence, 74–131. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-9012-6.ch005.
Повний текст джерелаАнотація:
Autonomous driving vehicles are developing rapidly; however, the control systems for autonomous driving vehicles tracking smoothly in high speed are still challenging. This chapter develops non-linear model predictive control (NMPC) schemes for controlling autonomous driving vehicles tracking on feasible trajectories. The optimal control action for vehicle speed and steering velocity is generated online using NMPC optimizer subject to vehicle dynamic and physical constraints as well as the surrounding obstacles and the environmental side-slipping conditions. NMPC subject to softened state constraints provides a better possibility for the optimizer to generate a feasible solution as real-time subject to online dynamic constraints and to maintain the vehicle stability. Different parameters of NMPC are simulated and analysed to see the relationships between the NMPC horizon prediction length and the weighting values. Results show that the NMPC can control the vehicle tracking exactly on different trajectories with minimum tracking errors and with high comfortability.
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Hasan, Mohamad K., and Xuegang (Jeff) Ban. "A Link-Node Nonlinear Complementarity Model for a Multiclass Simultaneous Transportation Dynamic User Equilibria." In Transportation Systems and Engineering, 370–92. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-8473-7.ch018.
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Static transportation network equilibrium models have evolved from traditional sequential models to simultaneous (combined) models, and then to the multiclass simultaneous models to improve prediction of traffic flow. Most Dynamic Traffic Assignment (DTA) models, however, still deal only with the trip assignment step (traveler route choice) that is one of several steps in the transportation planning process. In this paper, the authors combine a dynamic link-node based discrete-time Nonlinear Complementarity Problem (NCP) DTA model with a static Multiclass Simultaneous Transportation Equilibrium Model (MSTEM) in a unified dynamic link-node based discrete-time NCP Dynamic Multiclass Simultaneous Transportation Equilibrium Model (DMSTEM) model. The new model improves the prediction process and eliminates inconsistencies that arise when the DTA or Dynamic Traffic Assignment with Departure Time (DTA-DT) is embedded in a more comprehensive transportation planning framework. An iterative solution algorithm for the proposed DMSTEM model is proposed by solving several relaxed NCPs in each iteration of the algorithm.
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Ancarani, Alessandro, and Carmela Di Mauro. "The Human Side of Supply Chains." In Supply Chain Innovation for Competing in Highly Dynamic Markets, 290–314. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-60960-585-8.ch019.
Повний текст джерелаАнотація:
The adoption of the behavioural approach for the study of OM and Supply Chain Management is still fairly novel. However, there is evidence that in order to improve supply chain management it is crucial to develop models that correctly describe human behaviour. Failure to account for behavioural components such as risk perception, time effects and social interaction may lead to models that are biased in their predictions. This chapter reviews extant behavioural research relevant to supply chain risk management. In particular, its implications for supply chain management are outlined, and opportunities for future developments of theory that is robust to behavioural effects are identified.
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Wernsdorfer, Mark, and Ute Schmid. "From Streams of Observations to Knowledge-Level Productive Predictions." In Human Behavior Recognition Technologies, 268–81. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-3682-8.ch013.
Повний текст джерелаАнотація:
The benefit to be gained by Ambient Assisted Living (AAL) systems depends heavily on the successful recognition of human intentions. Important indicators for specific intentions are behavior and situational context. Once a sequence of actions can be associated with a specific intention, assistance may be provided by anticipating the next individual step and supporting the human in its execution. The authors present a combination of Sequence Abstraction Networks (SAN) and IGOR to guarantee early and impartial predictions with a powerful detection for symbolic regularities. They first generate a hierarchy of abstract action sequences, where individual contexts represent subgoals or minor intentions. Afterwards, they enrich this hierarchy by recursive induction. An example scenario is presented where a table needs to be set for several guests. It turns out that correct predictions can be made while still executing the observed sequence for the first time. Support can therefore be completely individual to the person being assisted but nonetheless be very dynamic and quick in anticipating the next steps.
Тези доповідей конференцій з теми "Dynamic stall prediction"
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CARR, L. "Dynamic stall progress in analysis and prediction." In 12th Atmospheric Flight Mechanics Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1985. http://dx.doi.org/10.2514/6.1985-1769.
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Gao, Haotian, Mingjun Wei, and John Hrynuk. "Data-Driven ROM for the Prediction of Dynamic Stall." In 2018 Fluid Dynamics Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2018. http://dx.doi.org/10.2514/6.2018-3094.
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Reisenthel, Patrick. "Towards a semi-analytic tool for the prediction of dynamic stall." In 32nd Aerospace Sciences Meeting and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1994. http://dx.doi.org/10.2514/6.1994-537.
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Vieira, Bernardo A. O., and Mark D. Maughmer. "An Evaluation of Dynamic Stall Onset Prediction Methods for Rotorcraft Airfoil Design." In 51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2013. http://dx.doi.org/10.2514/6.2013-1093.
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Jones, K. D., and M. F. Platzer. "A Fast Method for the Prediction of Dynamic Stall Onset on Turbomachinery Blades." In ASME 1997 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/97-gt-101.
Повний текст джерелаАнотація:
A computational approach is described for the rapid and systematic prediction and evaluation of the onset of dynamic stall due to rapid incidence changes or unsteady pitch or plunge motions. The method combines an unsteady, two-dimensional panel code with a two-dimensional boundary layer code. The panel code provides incompressible, inviscid flowfields about arbitrary airfoils undergoing prescribed motions. The boundary layer code computes laminar, transitional and turbulent regimes, with transition onset predicted by Michel’s criterion. Presented results demonstrate that the delay in dynamic stall onset is directly related to the dynamic pressure lag, in agreement with previous Navier-Stokes simulations, but in apparent disagreement with several aspects of the ‘moving wall’ analogy suggested in the past as an explanation for delayed dynamic stall onset.
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Schreck, S., and M. Robinson. "Blade Three-Dimensional Dynamic Stall Response to Wind Turbine Operating Condition." In ASME/JSME 2003 4th Joint Fluids Summer Engineering Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/fedsm2003-45362.
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To further reduce the cost of wind energy, future turbine designs will continue to migrate toward lighter and more flexible structures. Thus, the accuracy and reliability of aerodynamic load prediction has become a primary consideration in turbine design codes. Dynamically stalled flows routinely generated during yawed operation are powerful and potentially destructive, as well as complex and difficult to model. As a prerequisite to aerodynamics model improvements, wind turbine dynamic stall must be characterized in detail and thoroughly understood. In the current study, turbine blade surface pressure data and local inflow data acquired by the NREL Unsteady Aerodynamics Experiment during the NASA Ames wind tunnel experiment were analyzed. The dynamically stalled, vortex dominated flow field responded in systematic fashion to variations in wind speed, turbine yaw angle, and radial location, forming the basis for more thorough comprehension of wind turbine dynamic stall and improved modeling.
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Mishra, Asitav, Shreyas Ananthan, and James Baeder. "Coupled CFD/CSD Prediction of the Effects of Trailing Edge Flaps on Rotorcraft Dynamic Stall Alleviation." In 47th AIAA Aerospace Sciences Meeting including The New Horizons Forum and Aerospace Exposition. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2009. http://dx.doi.org/10.2514/6.2009-891.
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Kasibhotla, Venkata Ravishankar, and Danesh Tafti. "Dynamic Stall Simulation of Flow Over NACA0012 Airfoil at 1 Million Reynolds Number." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-50827.
Повний текст джерелаАнотація:
The paper is concerned with the prediction and analysis of dynamic stall of flow past a pitching NACA0012 airfoil at 1 million Reynolds number based on the chord length of the airfoil and at reduced frequency of 0.25 in a three dimensional flow field. The turbulence in the flow field is resolved using large eddy simulations with the dynamic Smagorinsky model at the sub grid scale. The development of dynamic stall vortex, shedding and reattachment as predicted by the present study are discussed in detail. This study has shown that the downstroke phase of the pitching motion is strongly three dimensional and is highly complex, whereas the flow is practically two dimensional during the upstroke. The lift coefficient agrees well with the measurements during the upstroke. However, there are differences during the downstroke. The computed lift coefficient undergoes a sharp drop during the start of the downstroke as the convected leading edge vortex moves away from the airfoil surface. This is followed by a recovery of the lift coefficient with the formation of a secondary trailing edge vortex. While these dynamics are clearly reflected in the predicted lift coefficient, the experimental evolution of lift during the downstroke maintains a fairly smooth and monotonic decrease in the lift coefficient with no lift recovery. The simulations also show that the reattachment process of the stalled airfoil is completed before the start of the upstroke in the subsequent cycle due to the high reduced frequency of the pitching cycle.
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Batther, Jagdeep, and Seongkyu Lee. "Investigation of Dynamic Stall Leading-Edge Flow Features at a Low Transitional Reynolds Number." In Vertical Flight Society 78th Annual Forum & Technology Display. The Vertical Flight Society, 2022. http://dx.doi.org/10.4050/f-0078-2022-17472.
Повний текст джерелаАнотація:
The unsteady laminar separation and subsequent dynamic stall vortex (DSV) formation is investigated on a NACA 0012 airfoil section subject to a constant pitch rate motion using Delayed Detached Eddy Simulations (DDES) in NASA's OVERFLOW 2.3 solver. This study focuses on the complex flow features during the initial DSVformation and analyzes the distinct mechanisms from which the vortex is formed. It is shown that DDES accurately predicts the bursting of a laminar separation bubble (LSB), which triggers the onset of a DSV. In parallel to studying the feasibility of DDES in terms of capturing distinct flow features compared to Large Eddy Simulation (LES) results, a turbulence model study is also carried out, analyzing the influence of stateof-the-art turbulent and transition models on the DSV formation and subsequent stall onset. These include the fully turbulent Spalart Allmaras (SA) turbulence model and three different transition models: SA Coder Amplification Factor Transport (AFT), SA Medida-Baeder ? ? �Re?t , and the Shear Stress Transport (SST) Langtry-Menter ? ? �Re?t . It is found that the Coder SA AFT model provides the closest results with LES and the SST Langtry-Menter model predicts the earlier on set of the DSV. The fully turbulent model shows an abrupt development of a turbulent separation bubble and the under-prediction of the lift coefficient at lower angles of attack. At higher angles of attack, after the collapse of the separation bubble, all the models provide similar trends with each other and LES results.
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Guo, Jin, Jun Hu, Xuegao Wang, and Rong Xu. "A Three-Dimensional Unsteady Through-Flow Model for Rotating Stall in Axial Compressors." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-16186.
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Abstract Rotating stall is a natural limit to the stable operating range of compressors due to the inverse pressure gradient of viscous gas. Effective prediction of compressor stall boundary is an important guarantee for the successful development of aeroengine. In this paper, a three-dimensional unsteady through-flow model based on body force theory is developed to reflect the dynamic stall process of multistage axial compressors with acceptable computational costs. The influence of blade geometric parameters is fully considered in blade force source terms. The source terms are related to the attack angle and Mach number of the blade inlet using the deviation angle and loss model in the through-flow theory. Meanwhile, the temporal lag response of the source terms to the upstream flow conditions is taken into account. Therefore, it can be utilized for predicting the off-design performance and rotating stall characteristics of multistage axial compressors. The developed model is validated on a two-stage low-speed axial compressor. The calculated performance line and stall cell speed are in agreement with the experimental results. The unsteady flow behavior of the compressor during stall is presented by the model. The results indicate that the developed model has the potential to be applied to the preliminary evaluation of compressor stability in design stage.
Звіти організацій з теми "Dynamic stall prediction"
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BARKHATOV, NIKOLAY, and SERGEY REVUNOV. A software-computational neural network tool for predicting the electromagnetic state of the polar magnetosphere, taking into account the process that simulates its slow loading by the kinetic energy of the solar wind. SIB-Expertise, December 2021. http://dx.doi.org/10.12731/er0519.07122021.
Повний текст джерелаАнотація:
The auroral activity indices AU, AL, AE, introduced into geophysics at the beginning of the space era, although they have certain drawbacks, are still widely used to monitor geomagnetic activity at high latitudes. The AU index reflects the intensity of the eastern electric jet, while the AL index is determined by the intensity of the western electric jet. There are many regression relationships linking the indices of magnetic activity with a wide range of phenomena observed in the Earth's magnetosphere and atmosphere. These relationships determine the importance of monitoring and predicting geomagnetic activity for research in various areas of solar-terrestrial physics. The most dramatic phenomena in the magnetosphere and high-latitude ionosphere occur during periods of magnetospheric substorms, a sensitive indicator of which is the time variation and value of the AL index. Currently, AL index forecasting is carried out by various methods using both dynamic systems and artificial intelligence. Forecasting is based on the close relationship between the state of the magnetosphere and the parameters of the solar wind and the interplanetary magnetic field (IMF). This application proposes an algorithm for describing the process of substorm formation using an instrument in the form of an Elman-type ANN by reconstructing the AL index using the dynamics of the new integral parameter we introduced. The use of an integral parameter at the input of the ANN makes it possible to simulate the structure and intellectual properties of the biological nervous system, since in this way an additional realization of the memory of the prehistory of the modeled process is provided.