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1
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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2
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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3
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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4
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.
5
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.
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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.
6
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.
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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.
7
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.
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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.
8
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.
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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.
9
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.
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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.
10
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.
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Gan, Xu Sheng, Xue Qin Tang, and Hai Long Gao. "Research on Stall Aerodynamics Modeling Based on WNN Trained by AFS-PSO Hybrid Algorithm from Flight Data." Applied Mechanics and Materials 602-605 (August 2014): 3173–76. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.3173.
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To accurately depict the dynamic characteristics for aircraft stall by aerodynamic model, a Wavelet Neural Network (WNN) stall aerodynamic modeling method based on Particle Swarm Optimization (PSO) algorithm and Artificial Fish Swarm (AFS) algorithm is proposed. Numerical examples show that the proposed method has a good prediction precision, and it is also effective and feasible to build the aerodynamic model from flight data for aircraft stall.
12
Choi, Seongim, Anubhav Datta, and Juan J. Alonso. "Prediction of Helicopter Rotor Loads Using Time-Spectral Computational Fluid Dynamics and an Exact Fluid–Structure Interface." Journal of the American Helicopter Society 56, no. 4 (October 1, 2011): 1–15. http://dx.doi.org/10.4050/jahs.56.042001.
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The objectives of this paper are to introduce time-spectral computational fluid dynamics (CFD) for the analysis of helicopter rotor flows in level flight and to introduce an exact fluid–structure interface for coupled CFD/computational structural dynamics (CSD) analysis. The accuracy and efficiency of time-spectral CFD are compared with conventional time-marching computations. The exact interface is equipped with an exact delta coupling procedure that bypasses the requirement for sectional airloads. Predicted loads are compared between time-spectral and time-marching CFD using both interfaces and validated using UH-60A flight data for high-vibration and dynamic stall conditions. It is concluded that time-spectral CFD can indeed predict rotor performance and peak-to-peak structural loads efficiently, and hence, open opportunity for blade shape optimization. The vibratory and dynamic stall loads, however, require a large number of time instances, which reduces its efficiency. The exact interface and delta procedure allow coupling to be implemented for arbitrary grids and advanced structural models exactly, without the requirement for two-dimensional sectional airloads.
13
Lin, Peng, Cong Wang, and Min Wang. "Bifurcation Predication in Axial Compressors with Nonuniform Inflow via Deterministic Learning." International Journal of Bifurcation and Chaos 27, no. 10 (September 2017): 1750159. http://dx.doi.org/10.1142/s0218127417501590.
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The nonlinear dynamics of fluid instabilities such as rotating stall and surge in axial compressors are typically modeled as subcritical Hopf bifurcations with hysteresis. The bifurcation prediction provides an effective approach to avoid the occurrence of compressor’s instability. In this paper, based on a fluid dynamic model developed recently, a stall precursor detection approach employing deterministic learning (DL) is proposed for bifurcation predication in axial compressors with nonuniform inflow. The stall precursor near the bifurcation can be obtained as the throttle area parameter approaches its critical (or bifurcation) value. Firstly, the system dynamics underlying normal and stall precursor are locally approximated accurately through DL. The obtained knowledge of dynamics is stored in constant radial basis function (RBF) networks. Secondly, a bank of estimators is built up using the stored constant RBF networks to represent the learning normal and stall precursor patterns. By comparing each estimator with a test system, the average [Formula: see text] norms of the residuals are taken as the measure of the dynamical differences between the test system and the learning patterns. The occurrence of stall precursor as a bifurcation predication signal can be rapidly detected according to the smallest residual principle. Finally, simulation results are given to show the effectiveness of stall precursor detection approach.
14
Schreck, S., and M. Robinson. "Blade Three-Dimensional Dynamic Stall Response to Wind Turbine Operating Condition." Journal of Solar Energy Engineering 127, no. 4 (June 30, 2005): 488–95. http://dx.doi.org/10.1115/1.2035706.
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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. The current study analyzed turbine blade surface pressure data and local inflow data acquired by the NREL Unsteady Aerodynamics Experiment during the NASA Ames wind tunnel experiment. Analyses identified and characterized two key dynamic stall processes, vortex initiation and vortex convection, across a broad parameter range. Results showed that both initiation and convection exhibited pronounced three-dimensional kinematics, which responded in systematic fashion to variations in wind speed, turbine yaw angle, and radial location.
15
Wang, Xu, Jiaqing Kou, and Weiwei Zhang. "A new dynamic stall prediction framework based on symbiosis of experimental and simulation data." Physics of Fluids 33, no. 12 (December 2021): 127119. http://dx.doi.org/10.1063/5.0075083.
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16
Pierce, K., and A. C. Hansen. "Prediction of Wind Turbine Rotor Loads Using the Beddoes-Leishman Model for Dynamic Stall." Journal of Solar Energy Engineering 117, no. 3 (August 1, 1995): 200–204. http://dx.doi.org/10.1115/1.2847783.
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The Beddoes-Leishman model for unsteady aerodynamics and dynamic stall has recently been implemented in YawDyn, a rotor analysis code developed at the University of Utah for the study of yaw loads and motions of horizontal axis wind turbines. This paper presents results obtained from validation efforts for the Beddoes model. Comparisons of predicted aerodynamic force coefficients with wind tunnel data and data from the combined experiment rotor are presented. Also, yaw motion comparisons with the combined experiment rotor are presented. In general the comparisons with the measured data are good, indicating that the model is appropriate for the conditions encountered by wind turbines.
17
Liu, Xiong, Shi Liang, Gangqiang Li, Ajit Godbole, and Cheng Lu. "An improved dynamic stall model and its effect on wind turbine fatigue load prediction." Renewable Energy 156 (August 2020): 117–30. http://dx.doi.org/10.1016/j.renene.2020.04.040.
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Sadeghi, Hamed, Mahmoud Mani, and S. M. Hossein Karimian. "Unsteady wake measurements behind an airfoil and prediction of dynamic stall from the wake." Aircraft Engineering and Aerospace Technology 82, no. 4 (July 6, 2010): 225–36. http://dx.doi.org/10.1108/00022661011082704.
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19
Wang, Pengzhong, Lu Wang, Xiaming Kong, Dazhuan Wu, and Bin Huang. "Influence of relative thickness on static and dynamic stall characteristics and prediction of airfoils." Ocean Engineering 271 (March 2023): 113690. http://dx.doi.org/10.1016/j.oceaneng.2023.113690.
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20
Pei, Binbin, Haojun Xu, Yuan Xue, Wei Chen, and Anwei Shen. "In-flight icing risk prediction and management in consideration of wing stall." Aircraft Engineering and Aerospace Technology 90, no. 1 (January 2, 2018): 24–32. http://dx.doi.org/10.1108/aeat-06-2015-0147.
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Purpose The purpose of this work is to develop an in-flight icing risk assessment methodology by quantification of changing flight dynamic characteristics under icing conditions. Design/methodology/approach This paper develops an approach for the quantitative assessment of flight risk under icing conditions. Using the six degree-of-freedom simulation model, the icing effects model is used to obtain the extreme values of the key parameters relevant to fight safety, allowing calculation of accident probability based on extreme value theory. The risk portion of the flight risk index is designed to account for different levels of flight risk and to provide criteria to allow pilots’ decision-making. Numerical examples are carried out by a series of simulated elevator overshoots of various levels and different distributions of ice accretion to compare the risk index under different icing conditions. Findings Case results show that the proposed methodology is able to analyze conditions of different severity and distribution of icing and assess quantitatively how these different parameters affect flight safety. Practical implications The quantification of flight risk in icing conditions demonstrated here can be applied to provide an objective and intuitive instrument to facilitate decisions by the aircrew or air traffic controller, especially prior to the aircraft entering into areas with adverse meteorological conditions. Originality/value Existing flight risk assessments under icing conditions are typically guided by aerodynamic changes, ice accumulation process or the subjective feeling of the pilot. Here, it is proposed to use the probability of flight risk event to measure different icing intensity levels in a quantitative way. This quantitative metric combines the alteration of aerodynamic characteristics, flight dynamic characteristics and limitation of critical parameters, providing a new and comprehensive viewpoint to measure in-flight icing risk. This may be a promising and more reasonable way to assess the risk.
21
Bangga, Galih, and Herman Sasongko. "Dynamic Stall Prediction of a Pitching Airfoil using an Adjusted Two-Equation URANS Turbulence Model." Journal of Applied Fluid Mechanics 10, no. 1 (January 1, 2017): 1–10. http://dx.doi.org/10.18869/acadpub.jafm.73.238.26391.
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Liu, Pengyin, Guohua Yu, Xiaocheng Zhu, and Zhaohui Du. "Unsteady aerodynamic prediction for dynamic stall of wind turbine airfoils with the reduced order modeling." Renewable Energy 69 (September 2014): 402–9. http://dx.doi.org/10.1016/j.renene.2014.03.066.
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Colding-Jorgensen, J. "Prediction of Rotor Dynamic Destabilizing Forces in Axial Flow Compressors." Journal of Fluids Engineering 114, no. 4 (December 1, 1992): 621–25. http://dx.doi.org/10.1115/1.2910076.
Повний текст джерелаАнотація:
It has been shown by Thomas (1958) and Alford (1965), that axial flow turbo-machinery is subject to rotor dynamic destabilizing gas forces produced by the circumferential variation of blade-tip clearance when the rotor is whirling. However, the magnitude and direction of these forces have yet to be clarified. For example, it is still uncertain, under which circumstances the rotor whirl direction will be forward, and when it will be backward, with respect to the rotation. In the present paper, a simple analysis of the perturbed flow in an axial compressor stage with whirling rotor is presented, based on the actuator disc analysis of Horlock and Greitzer (1983), and the gas force on the rotor is calculated on this basis. It appears that in the normal operation range of an axial compressor, the whirl direction is predicted to be forward always. Backward whirl is predicted to take place only at very low flow rates, well below the normally expected stall limit. Experimentally, forces were indeed found in direction of backward whirl for low flow rates, and in direction of forward whirl for high flow rates, in the results reported by Vance and Laudadio (1984), as analyzed by Ehrich (1989). While this experimental evidence supports the present theory qualitatively, a direct comparison of the measured and predicted destabilizing force has yet to be carried out.
24
Persico, Giacomo, Andrea G. Sanvito, and Vincenzo Dossena. "Quantification of the Dynamic-stall Model Uncertainty in the Performance Prediction of Vertical Axis Wind Turbines." Journal of Physics: Conference Series 1618 (September 2020): 052071. http://dx.doi.org/10.1088/1742-6596/1618/5/052071.
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Mitchell, Samuel, Iheanyichukwu Ogbonna, and Konstantin Volkov. "Aerodynamic Characteristics of a Single Airfoil for Vertical Axis Wind Turbine Blades and Performance Prediction of Wind Turbines." Fluids 6, no. 7 (July 13, 2021): 257. http://dx.doi.org/10.3390/fluids6070257.
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The design of wind turbines requires a deep insight into their complex aerodynamics, such as dynamic stall of a single airfoil and flow vortices. The calculation of the aerodynamic forces on the wind turbine blade at different angles of attack (AOAs) is a fundamental task in the design of the blades. The accurate and efficient calculation of aerodynamic forces (lift and drag) and the prediction of stall of an airfoil are challenging tasks. Computational fluid dynamics (CFD) is able to provide a better understanding of complex flows induced by the rotation of wind turbine blades. A numerical simulation is carried out to determine the aerodynamic characteristics of a single airfoil in a wide range of conditions. Reynolds-averaged Navier–Stokes (RANS) equations and large-eddy simulation (LES) results of flow over a single NACA0012 airfoil are presented in a wide range of AOAs from low lift through stall. Due to the symmetrical nature of airfoils, and also to reduce computational cost, the RANS simulation is performed in the 2D domain. However, the 3D domain is used for the LES calculations with periodical boundary conditions in the spanwise direction. The results obtained are verified and validated against experimental and computational data from previous works. The comparisons of LES and RANS results demonstrate that the RANS model considerably overpredicts the lift and drag of the airfoil at post-stall AOAs because the RANS model is not able to reproduce vorticity diffusion and the formation of the vortex. LES calculations offer good agreement with the experimental measurements.
26
Arabgolarcheh, Alireza, Sahar Jannesarahmadi, Ernesto Benini, and Luca Menegozzo. "Numerical Study of a Horizontal Wind Turbine under Yaw Conditions." Mathematical Problems in Engineering 2021 (August 30, 2021): 1–17. http://dx.doi.org/10.1155/2021/9978134.
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Over recent years, considerable attention has been devoted to the optimization of energy production in wind farms, where yaw angles can play a significant role. In order to quantify and maximize such potential power, the simulation of wakes is vital. In the present study, an actuator line model code was implemented in the OpenFOAM flow solver. A tip treatment was applied to involve the tip effect induced by the pressure equalization from the suction and pressure sides. The Leishman–Beddoes dynamic stall (LB-DS) model modified by Sheng et al. was employed to consider the dynamic stall phenomenon. The developed ALM-CFD solver was validated for the NREL Phase VI wind turbine reference case. The solver was then used in simulating the yawed wind turbine, and power variation was compared with UBEM and CFD. Overall, according to the obtained data, the coupled solver compared well with CFD. There was an improvement in terms of prediction of the phase delay that is due to the dynamic stall. However, there was still negligible overestimation in deep stall conditions. Based on the obtained results, it is suggested that the reduction of power output follows a cosine to the power of X function of the yaw angle. In terms of visualizing wake, the results demonstrated that the current ALM code was satisfying enough to simulate skewed wake and vortices trajectory. The effect of advancing and retreating blade was captured. It was found that yaw led to the concentration of the induced velocity downstream, resulting in a lower velocity deficit on a broader area, which is essential for wind farm optimization.
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Zanon, Alessandro, Pietro Giannattasio, and Carlos J. Simão Ferreira. "Wake modelling of a VAWT in dynamic stall: impact on the prediction of flow and induction fields." Wind Energy 18, no. 11 (August 11, 2014): 1855–74. http://dx.doi.org/10.1002/we.1793.
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Lui, Hugo F. S., and William R. Wolf. "Construction of reduced-order models for fluid flows using deep feedforward neural networks." Journal of Fluid Mechanics 872 (June 14, 2019): 963–94. http://dx.doi.org/10.1017/jfm.2019.358.
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We present a numerical methodology for construction of reduced-order models (ROMs) of fluid flows through the combination of flow modal decomposition and regression analysis. Spectral proper orthogonal decomposition is applied to reduce the dimensionality of the model and, at the same time, filter the proper orthogonal decomposition temporal modes. The regression step is performed by a deep feedforward neural network (DNN), and the current framework is implemented in a context similar to the sparse identification of nonlinear dynamics algorithm. A discussion on the optimization of the DNN hyperparameters is provided for obtaining the best ROMs and an assessment of these models is presented for a canonical nonlinear oscillator and the compressible flow past a cylinder. Then the method is tested on the reconstruction of a turbulent flow computed by a large eddy simulation of a plunging airfoil under dynamic stall. The reduced-order model is able to capture the dynamics of the leading edge stall vortex and the subsequent trailing edge vortex. For the cases analysed, the numerical framework allows the prediction of the flow field beyond the training window using larger time increments than those employed by the full-order model. We also demonstrate the robustness of the current ROMs constructed via DNNs through a comparison with sparse regression. The DNN approach is able to learn transient features of the flow and presents more accurate and stable long-term predictions compared to sparse regression.
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Wang, Liang, Liying Li, and Song Fu. "A comparative study of DES type methods for mild flow separation prediction on a NACA0015 airfoil." International Journal of Numerical Methods for Heat & Fluid Flow 27, no. 11 (November 6, 2017): 2528–43. http://dx.doi.org/10.1108/hff-07-2016-0263.
Повний текст джерелаАнотація:
Purpose The purpose of this paper is to numerically investigate the mildly separated flow phenomena on a near-stall NACA0015 airfoil, by using Detached-Eddy Simulation (DES) type methods. It includes a comparison of different choices of underlying Reynolds-averaged Navier–Stokes model as well as subgrid-scale stress model in Large-Eddy simulation mode. Design/methodology/approach The unsteady flow phenomena are simulated by using delayed DES (DDES) and improved DDES (IDDES) methods, with an in-house computational fluid dynamics solver. Characteristic frequencies in different flow regions are extracted using fast Fourier transform. Dynamic mode decomposition (DMD) method is applied to uncover the critical dynamic modes. Findings Among all the DES type methods investigated in this paper, only the Spalart–Allmaras-based IDDES captures the separation point as measured in the experiments. The classical vortex-shedding and the shear-layer flapping modes for airfoil flows with shallow separation are also found from the IDDES results by using DMD. Originality/value The value of this paper lies in the assessment of five different DES-type models through the detailed investigation of the Reynolds stresses as well as the separation and reattachment.
30
Brahimi, M. T., A. Allet, and I. Paraschivoiu. "Aerodynamic Analysis Models for Vertical-Axis Wind Turbines." International Journal of Rotating Machinery 2, no. 1 (1995): 15–21. http://dx.doi.org/10.1155/s1023621x95000169.
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This work details the progress made in the development of aerodynamic models for studying Vertical-Axis Wind Turbines (VAWT's) with particular emphasis on the prediction of aerodynamic loads and rotor performance as well as dynamic stall simulations. The paper describes current effort and some important findings using streamtube models, 3-D viscous model, stochastic wind model and numerical simulation of the flow around the turbine blades. Comparison of the analytical results with available experimental data have shown good agreement.
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Le, Hieu Thi Hong, Cong Chi Nguyen, and Trong Huu Luong. "Performance prediction of Darrieus vertical axis wind turbines using double multiple stream-tube model." Science and Technology Development Journal 18, no. 4 (December 30, 2015): 153–61. http://dx.doi.org/10.32508/stdj.v18i4.1001.
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Horizontal and vertical axis wind turbines (HAWTs and VAWTs) are two main kinds of wind turbines, which are the most popular way to catch energy from the wind. By comparison, VAWTs have some advantages, but they also have the complexity in aerodynamics that needs a deep investigation. A code is developed based on Double multiple stream-tube and corrections of the dynamic stall for Darrieus VAWTs. It is capable of estimating the output power versus different operating conditions defined by the tipspeed- ratio. The code is also validated with experimental data of many SANDIA Darrieus VAWT turbines.
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Zhang, Mingming, Jia Zhang, Anping Hou, Aiguo Xia, and Wei Tuo. "Dynamic System Modeling of a Hybrid Neural Network with Phase Space Reconstruction and a Stability Identification Strategy." Machines 10, no. 2 (February 9, 2022): 122. http://dx.doi.org/10.3390/machines10020122.
Повний текст джерелаАнотація:
Focusing on the identification of dynamic system stability, a hybrid neural network model is proposed in this research for the rotating stall phenomenon in an axial compressor. Based on the data fusion of the amplitude of the spatial mode, the nonlinear property is well characterized in the feature extraction of the rotating stall. This method of data processing can effectively avoid the inaccurate recognition of single or multiple measuring sensors only depending on pressure. With the analysis on the spatial mode, a chaotic characteristic was shown in the development of the amplitude with the first-order spatial mode. With the prerequisite of revealing the essence of this dynamic system, a hybrid radial basis function (RBF) neural network was adopted to represent the properties of the system by artificial intelligence learning. Combining the advantages of the methods of K-means and Gradient Descent (GD), the Chaos–K-means–GD–RBF fusion model was established based on the phase space reconstruction of the chaotic sequence. Compared with the two methods mentioned above, the calculation accuracy was significantly improved in the hybrid neural network model. By taking the strategy of global sample entropy and difference quotient criterion identification, a warning of inception can be suggested in advance of 12.3 revolutions (296 ms) with a multi-step prediction before the stall arrival.
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Chávez-Modena, M., J. L. Martínez, J. A. Cabello, and E. Ferrer. "Simulations of Aerodynamic Separated Flows Using the Lattice Boltzmann Solver XFlow." Energies 13, no. 19 (October 2, 2020): 5146. http://dx.doi.org/10.3390/en13195146.
Повний текст джерелаАнотація:
We present simulations of turbulent detached flows using the commercial lattice Boltzmann solver XFlow (by Dassault Systemes). XFlow’s lattice Boltzmann formulation together with an efficient octree mesh generator reduce substantially the cost of generating complex meshes for industrial flows. In this work, we challenge these meshes and quantify the accuracy of the solver for detached turbulent flows. The good performance of XFlow when combined with a Large-Eddy Simulation turbulence model is demonstrated for different industrial benchmarks and validated using experimental data or fine numerical simulations. We select five test cases: the Backward-facing step the Goldschmied Body the HLPW-2 (2nd High-Lift Prediction Workshop) full aircraft geometry, a NACA0012 under dynamic stall conditions and a parametric study of leading edge tubercles to improve stall behavior on a 3D wing.
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Tu, Baofeng, Xinyu Zhang, Jun Hu, Ming Zhong, and Bing Xiong. "Analysis Methods for Aerodynamic Instability Detection on a Multistage Axial Compressor." International Journal of Aerospace Engineering 2021 (August 18, 2021): 1–14. http://dx.doi.org/10.1155/2021/8893792.
Повний текст джерелаАнотація:
In order to detect the aerodynamic instability of a multistage axial compressor more accurately and earlier, the harmonic Fourier mean amplitude analysis method and heterotopic variance analysis method are developed. The dynamic instability prediction performance of the two methods is studied on a low-speed and a high-speed two-stage axial compressor. The harmonic Fourier mean amplitude analysis method is suitable for predicting the aerodynamic instability of a multistage axial compressor in the form of a rotating stall. Compared with the traditional harmonic Fourier analysis methods, the harmonic Fourier mean amplitude analysis method can capture the detail of the pressure signal more accurately and it can effectively prevent instability misjudgment. The heterotopic variance analysis method is developed based on the conventional variance analysis method, and it can be used to distinguish whether the compressor is in the rotating stall or the surge state. The heterotopic variance analysis method can predict the aerodynamic instability ahead of the harmonic Fourier mean amplitude analysis method, and fewer circumferential measuring points were employed. The layout of the measuring points also influences the detection of the aerodynamic instability of the compressor. The aerodynamic instability of the high-speed axial compressor can be predicted earlier by employing measuring points at the compressor outlet.
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Bose, Neil, and Peter S. K. Lai. "Experimental Performance of a Trochoidal Propeller with High-Aspect-Ratio Blades." Marine Technology and SNAME News 26, no. 03 (July 1, 1989): 192–201. http://dx.doi.org/10.5957/mt1.1989.26.3.192.
Повний текст джерелаАнотація:
Open-water experiments were done on a model of a cycloidal-type propeller with a trochoidal blade motion. This propeller had three blades with an aspect ratio of 10. These experiments included the measurement of thrust and torque of the propeller over a range of advance ratios. Tests were done for forward and reverse operation, and at zero speed (the bollard pull condition). Results from these tests are presented and compared with: a multiple stream-tube theoretical prediction of the performance of the propeller; and a prediction of the performance of a single blade of the propeller, oscillating in heave and pitch, using unsteady small-amplitude hydrofoil theory with corrections for finite amplitude motion, finite span, and frictional drag. At present, neither of these theories gives a completely accurate prediction of propeller performance over the whole range of advance ratios, but a combination of these approaches, with an allowance for dynamic stall of the blades, should lead to a reliable simple theory for overall performance prediction. Application of a propeller of this type to a small ship is discussed. The aim of the design is to produce a lightly loaded propeller with a high efficiency of propulsion.
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Sanvito, Andrea, Vincenzo Dossena, and Giacomo Persico. "Formulation, Validation, and Application of a Novel 3D BEM Tool for Vertical Axis Wind Turbines of General Shape and Size." Applied Sciences 11, no. 13 (June 24, 2021): 5874. http://dx.doi.org/10.3390/app11135874.
Повний текст джерелаАнотація:
Low order models based on the Blade Element Momentum (BEM) theory exhibit modeling issues in the performance prediction of Vertical Axis Wind Turbines (VAWT) compared to Computational Fluid Dynamics, despite the widespread engineering practice of such methods. The present study shows that the capability of BEM codes applied to VAWTs can be greatly improved by implementing a novel three-dimensional set of high-order corrections and demonstrates this by comparing the BEM predictions against wind-tunnel experiments conducted on three small-scale VAWT models featuring different rotor design (H-shaped and Troposkein), blade profile (NACA0021 and DU-06-W200), and Reynolds number (from 0.8×105 to 2.5×105). Though based on the conventional Double Multiple Stream Tube (DMST) model, the here-presented in-house BEM code incorporates several two-dimensional and three-dimensional corrections including: accurate extended polar data, flow curvature, dynamic stall, a spanwise-distributed formulation of the tip losses, a fully 3D approach in the modeling of rotors featuring general shape (such as but not only, the Troposkein one), and accounting for the passive effects of supporting struts and pole. The detailed comparison with experimental data of the same models, tested in the large-scale wind tunnel of the Politecnico di Milano, suggests the very good predictive capability of the code in terms of power exchange, torque coefficient, and loads, on both time-mean and time-resolved basis. The peculiar formulation of the code allows including in a straightforward way the usual spanwise non-uniformity of the incoming wind and the effects of skew, thus allowing predicting the turbine operation in a realistic open-field in presence of the environmental boundary layer. A systematic study on the operation of VAWTs in multiple environments, such as in coastal regions or off-shore, and highlighting the sensitivity of VAWT performance to blade profile selection, rotor shape and size, wind shear, and rotor tilt concludes the paper.
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Pirrung, Georg R., Helge A. Madsen, and Scott Schreck. "Trailed vorticity modeling for aeroelastic wind turbine simulations in standstill." Wind Energy Science 2, no. 2 (November 20, 2017): 521–32. http://dx.doi.org/10.5194/wes-2-521-2017.
Повний текст джерелаАнотація:
Abstract. Current fast aeroelastic wind turbine codes suitable for certification lack an induction model for standstill conditions. A trailed vorticity model previously used as an addition to a blade element momentum theory based aerodynamic model in normal operation has been extended to allow computing the induced velocities in standstill. The model is validated against analytical results for an elliptical wing in constant inflow and against standstill measurements from the NREL/NASA Phase VI unsteady experiment. The extended model obtains good results in the case of the elliptical wing but underpredicts the steady loading for the Phase VI blade in attached flow. The prediction of the dynamic force coefficient loops from the Phase VI experiment is improved by the trailed vorticity modeling in both attached flow and stall in most cases. The exception is the tangential force coefficient in stall, where the codes and measurements deviate and no clear improvement is visible. This article also contains aeroelastic simulations of the DTU 10 MW reference turbine in standstill at turbulent inflow with a fixed and idling rotor. The influence of the trailed vorticity modeling on the extreme flapwise blade root bending moment is found to be small.
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Li, Jun, Jun Hu, and Chenkai Zhang. "Experimental investigation of the tip leakage flow in a low-speed multistage axial compressor." Science Progress 103, no. 3 (July 2020): 003685042095107. http://dx.doi.org/10.1177/0036850420951070.
Повний текст джерелаАнотація:
Casing pressure measurements and Stereoscopic Particle-Image Velocimetry (SPIV) measurements are used together to characterize the behavior of the rotor tip leakage flow at both the design and near-stall conditions in a low-speed multistage axial compressor. A three-dimensional Navier-Stokes solver is also performed for the multistage compressor and the prediction of tip leakage flow is compared with SPIV data and casing dynamic static pressure data. During the experiment 10 high-frequency Kulite transducers are mounted in the outer casing of the rotor 3 to investigate the complex flow near the compressor casing and Fourier analyses of the dynamic static pressure on the casing of the rotor 3 are carried out to investigate the tip leakage flow characteristics. At the same time, the two CCD cameras are arranged at the same side of the laser light sheet, which is suitable for investigating unsteady tip leakage flow in the multistage axial compressor. The SPIV measurements identify that the tip leakage flow exists in the rotor passage. The influence of tip leakage flow leads to the existence of low axial velocity region in the rotor passage and the alternating regions of positive and negative radial velocity indicates the emergence of tip leakage vortex (TLV). The trajectory of the tip leakage vortex moves from the suction surface toward the pressure surface of adjacent blade, which is aligned close to the rotor at the design point (DP). However, the tip leakage vortex becomes unstable and breaks down at the near-stall point (NS), making the vortex trajectory move upstream in the rotor passage and causing a large blockage in the middle of the passage.
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Pylypenko, O. V., O. N. Nikolayev, N. V. Khoriak, S. I. Dolgopolov, and I. D. Bashliy. "Current problems in the low-frequency dynamics of liquid-propellant rocket propulsion systems." Technical mechanics 2021, no. 3 (October 12, 2021): 9–22. http://dx.doi.org/10.15407/itm2021.03.009.
Повний текст джерелаАнотація:
One of the key problems in liquid-propellant rocket engine (LPRE) design is to provide the stability of LPRE working processes, in particular low-frequency stability. In LPRE experimental tryout, every so often there occur situations where the development of divergent oscillations set up in some of the LPRE loops or units results in contingencies: exceeding the engine ultimate strength, pump stall, chamber ignition, etc. Such contingencies may lead to grave consequences, including engine and bench equipment failure. Because of this, mathematical simulation is one of the main tools that allow one to predict he dynamic performance of an LPRE both in its steady operation and in transients and its startup operation features at the design and tryout stage. This paper overviews and analyzes scientific publications for the past 15 years concerned with the study of the dynamics and low-frequency stability of advanced LPREs and units thereof along different lines. This analysis made it possible to identify problems in low-frequency stability prediction and assurance for liquid-propellant rocket propulsion systems (LPRPSs) under design, to cover new research results (experimental and theoretical) on the origination and development of all-engine low-frequency oscillations and low-frequency oscillations in LPRPS systems and units and to identify new approaches to the mathematical simulation and study of low-frequency processes in LPRPSs and promising lines of investigation. The man lineы of the analysis are as follows: the low-frequency dynamics of cavitating inducer-equipped centrifugal pumps and LPRE gas paths, LPRE thrust control problems, the interaction of launch vehicle airframe longitudinal oscillations with low-frequency processes in the sustainer LPRPS, dynamic processes during an LPRE startup/shutdown, and low-frequency in-chamber oscillations.
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Jebakumar, S. K., Abhay A. Pashilkar, and N. Sundararajan. "A Novel Design Approach for Low Speed Recovery of High Performance Fighter Aircraft." Defence Science Journal 72, no. 4 (August 26, 2022): 505–15. http://dx.doi.org/10.14429/dsj.72.17821.
Повний текст джерелаАнотація:
In this paper, a novel design approach for low-speed recovery of a high-performance fighter aircraft is presented. It is shown that the phugoid mode has an important bearing on the problem of low-speed departure. Based on the analysis of the phugoid mode trajectories, a novel low-speed protection algorithm is presented in this paper. The proposed low speed recovery is achieved in three phases. The first phase consists of detecting the incipient departure followed in the second phase by the application of suitable recovery controls and finally the third phase ends with the transfer of controls to the pilot. The design of the first and the third phase consist of choosing the correct trigger conditions which ensures safe recovery of the aircraft in all conditions. The proposed Automatic low speed recovery is triggered when the aircraft trajectory crosses a fixed boundary in the region spanned by the dynamic pressure and its rate of decrease. It is observed that this boundary is approximately a straight line, implying that it is equivalent to a forward prediction in time to indicate when the aircraft will reach the lowest controllable airspeed. This Automatic Low Speed Recovery with Forward Prediction (ALSR-FP) algorithm is found to be simpler than other existing design methods and effective in preventing low speed departure for a variety of pilot inputs that result in the aircraft losing airspeed leading to stall. In the second phase control inputs are chosen to align the velocity vector to the direction of local gravity. The recovery phase is considered complete after the aircraft reaches the dynamic pressure which is approximately 10 % higher than the minimum dynamic pressure for control. Performance of the ALSR-FP is demonstrated using the high-performance fighter aircraft ADMIRE model which has a delta wing configuration, canards and multiple redundant controls. It is also shown that the proposed algorithm can be easily implemented on board for any other fighter and civil aircraft.
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Xu, B. F., T. G. Wang, Y. Yuan, and J. F. Cao. "Unsteady aerodynamic analysis for offshore floating wind turbines under different wind conditions." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 373, no. 2035 (February 28, 2015): 20140080. http://dx.doi.org/10.1098/rsta.2014.0080.
Повний текст джерелаАнотація:
A free-vortex wake (FVW) model is developed in this paper to analyse the unsteady aerodynamic performance of offshore floating wind turbines. A time-marching algorithm of third-order accuracy is applied in the FVW model. Owing to the complex floating platform motions, the blade inflow conditions and the positions of initial points of vortex filaments, which are different from the fixed wind turbine, are modified in the implemented model. A three-dimensional rotational effect model and a dynamic stall model are coupled into the FVW model to improve the aerodynamic performance prediction in the unsteady conditions. The effects of floating platform motions in the simulation model are validated by comparison between calculation and experiment for a small-scale rigid test wind turbine coupled with a floating tension leg platform (TLP). The dynamic inflow effect carried by the FVW method itself is confirmed and the results agree well with the experimental data of a pitching transient on another test turbine. Also, the flapping moment at the blade root in yaw on the same test turbine is calculated and compares well with the experimental data. Then, the aerodynamic performance is simulated in a yawed condition of steady wind and in an unyawed condition of turbulent wind, respectively, for a large-scale wind turbine coupled with the floating TLP motions, demonstrating obvious differences in rotor performance and blade loading from the fixed wind turbine. The non-dimensional magnitudes of loading changes due to the floating platform motions decrease from the blade root to the blade tip.
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Sanders, A. J. "Nonsynchronous Vibration (NSV) due to a Flow-Induced Aerodynamic Instability in a Composite Fan Stator." Journal of Turbomachinery 127, no. 2 (April 1, 2005): 412–21. http://dx.doi.org/10.1115/1.1811091.
Повний текст джерелаАнотація:
This paper describes the identification and prediction of a new class of nonsynchronous vibration (NSV) problem encountered during the development of an advanced design composite fan stator for an aircraft engine application. Variable exhaust nozzle testing on an instrumented engine is used to map out the NSV boundary, with both choke- and stall-side instability zones present that converge toward the nominal fan operating line and place a limit on the high-speed operating range. Time-accurate three-dimensional viscous CFD analyses are used to demonstrate that the NSV instability is being driven by dynamic stalling of the fan stator due to unsteady shock-boundary layer interaction. The effects of downstream struts in the front frame of the engine are found to exasperate the problem, with the two fat service struts in the bypass duct generating significant spatial variations in the stator flow field. Strain gage measurements indicate that the stator vanes experiencing the highest vibratory strains correspond to the low static pressure regions of the fan stator assembly located approximately 90 degrees away from the two fat struts. The CFD analyses confirm the low static pressure sectors of the stator assembly are the passages in which the flow-induced NSV instability is initiated due to localized choking phenomena. The CFD predictions of the instability frequency are in reasonable agreement with the strain gage data, with the strain gage data indicating that the NSV response occurs at a frequency approximately 25% below the frequency of the fundamental bending mode. The flow patterns predicted by the CFD analyses are also correlated with the results of an engine flow visualization test to demonstrate the complex nature of the flow field.
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Avanzi, Filippo, Francesco De Vanna, Yin Ruan, and Ernesto Benini. "Design-Assisted of Pitching Aerofoils through Enhanced Identification of Coherent Flow Structures." Designs 5, no. 1 (February 14, 2021): 11. http://dx.doi.org/10.3390/designs5010011.
Повний текст джерелаАнотація:
This study discusses a general framework to identify the unsteady features of a flow past an oscillating aerofoil in deep dynamic stall conditions. In particular, the work aims at demonstrating the advantages for the design process of the Spectral Proper Orthogonal Decomposition in accurately producing reliable reduced models of CFD systems and comparing this technique with standard snapshot-based models. Reynolds-Averaged Navier-Stokes system of equations, coupled with k−ω SST turbulence model, is used to produce the dataset, the latter consisting of a two-dimensional NACA 0012 aerofoil in the pitching motion. Modal analysis is performed on both velocity and pressure fields showing that, for vectored values, a proper tuning of the filtering process allows for better results compared to snapshot formulations and extract highly correlated coherent flow structures otherwise undetected. Wider filters, in particular, produce enhanced coherence without affecting the typical frequency response of the coupled modes. Conversely, the pressure field decomposition is drastically affected by the windowing properties. In conclusion, the low-order spectral reconstruction of the pressure field allows for an excellent prediction of aerodynamic loads. Moreover, the analysis shows that snapshot-based models better perform on the CFD values during the pitching cycle, while spectral-based methods better fit the loads’ fluctuations.
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Lyu, Xiaozhong, Cuiqing Jiang, Yong Ding, Zhao Wang, and Yao Liu. "Sales Prediction by Integrating the Heat and Sentiments of Product Dimensions." Sustainability 11, no. 3 (February 11, 2019): 913. http://dx.doi.org/10.3390/su11030913.
Повний текст джерелаАнотація:
Online word-of-mouth (eWOM) disseminated on social media contains a considerable amount of important information that can predict sales. However, the accuracy of sales prediction models using big data on eWOM is still unsatisfactory. We argue that eWOM contains the heat and sentiments of product dimensions, which can improve the accuracy of prediction models based on multiattribute attitude theory. In this paper, we propose a dynamic topic analysis (DTA) framework to extract the heat and sentiments of product dimensions from big data on eWOM. Ultimately, we propose an autoregressive heat-sentiment (ARHS) model that integrates the heat and sentiments of dimensions into the benchmark predictive model to forecast daily sales. We conduct an empirical study of the movie industry and confirm that the ARHS model is better than other models in predicting movie box-office revenues. The robustness check with regard to predicting opening-week revenues based on a back-propagation neural network also suggests that the heat and sentiments of dimensions can improve the accuracy of sales predictions when the machine-learning method is used.
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Halabi, Susan, Cai Li, and Sheng Luo. "Developing and Validating Risk Assessment Models of Clinical Outcomes in Modern Oncology." JCO Precision Oncology, no. 3 (December 2019): 1–12. http://dx.doi.org/10.1200/po.19.00068.
Повний текст джерелаАнотація:
The identification of prognostic factors and building of risk assessment prognostic models will continue to play a major role in 21st century medicine in patient management and decision making. Investigators often are interested in examining the relationship among host, tumor-related, and environmental variables in predicting clinical outcomes. We distinguish between static and dynamic prediction models. In static prediction modeling, variables collected at baseline typically are used in building models. On the other hand, dynamic predictive models leverage the longitudinal data of covariates collected during treatment or follow-up and hence provide accurate predictions of patients’ prognoses. To date, most risk assessment models in oncology have been based on static models. In this article, we cover topics related to the analysis of prognostic factors, centering on factors that are both relevant at the time of diagnosis or initial treatment and during treatment. We describe the types of risk prediction and then provide a brief description of the penalized regression methods. We then review the state-of-the art methods for dynamic prediction and compare the strengths and limitations of these methods. Although static models will continue to play an important role in oncology, developing and validating dynamic models of clinical outcomes need to take a higher priority. A framework for developing and validating dynamic tools in oncology seems to still be needed. One of the limitations in oncology that may constrain modelers is the lack of access to longitudinal biomarker data. It is highly recommended that the next generation of risk assessments consider longitudinal biomarker data and outcomes so that prediction can be continually updated.
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Moroz, N. E., D. V. Sidorov, and M. A. Sonnov. "Application of digital twins to predict rock-bump hazard of drift pillars." Mining Industry Journal (Gornay Promishlennost), no. 3/2022 (July 1, 2022): 93–98. http://dx.doi.org/10.30686/1609-9192-2022-3-93-98.
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Drift pillars are used to protect haulage tunnels from the effects of formation pressure and ingress of the caved rock mass. At the same time, leaving pillars made up of fragile ores exposed to significant compressive stresses poses a risk of dynamic formation pressure. Due to the design features of the mining method and safety regulations, it is not possible to access the drift pillar from the rising side, which limits the ability to make a meaningful instrumental forecast of the rock-bump hazard. Therefore, it is advisable to use digital twins to predict the rock-bump hazard of the drift pillars. The article describes the experience gained by the VNIMI Institute in using the PRESS 3D URAL dedicated software (Polygore LLC, St. Petersburg) and the FIDESYS software package (Fidesys, Moscow) for a comprehensive assessment of the stress-and-strain state and rock-bump hazardous condition of the drift pillar. The first stage included numerical evaluation of the natural tectonic stress field using the PRESS 3D URAL software. At the second stage, an assessment of the man-made stress-and-strain state of the rock mass and the ore drift pillar was performed using the FIDESYS software package during underground mining with the heading-and-stall method. The final stage involved a prediction of the rock-bump hazard of the ore pillar using data on the ore strength properties.
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Ma, Junwei, Xiaoxu Niu, Huiming Tang, Yankun Wang, Tao Wen, and Junrong Zhang. "Displacement Prediction of a Complex Landslide in the Three Gorges Reservoir Area (China) Using a Hybrid Computational Intelligence Approach." Complexity 2020 (January 28, 2020): 1–15. http://dx.doi.org/10.1155/2020/2624547.
Повний текст джерелаАнотація:
Displacement prediction of reservoir landslide remains inherently uncertain since a complete understanding of the complex nonlinear, dynamic landslide system is still lacking. An appropriate quantification of predictive uncertainties is a key underpinning of displacement prediction and mitigation of reservoir landslide. A density prediction, offering a full estimation of the probability density for future outputs, is promising for quantification of the uncertainty of landslide displacement. In the present study, a hybrid computational intelligence approach is proposed to build a density prediction model of landslide displacement and quantify the associated predictive uncertainties. The hybrid computational intelligence approach consists of two steps: first, the input variables are selected through copula analysis; second, kernel-based support vector machine quantile regression (KSVMQR) is employed to perform density prediction. The copula-KSVMQR approach is demonstrated through a complex landslide in the Three Gorges Reservoir Area (TGRA), China. The experimental study suggests that the copula-KSVMQR approach is capable of construction density prediction by providing full probability density distributions of the prediction with perfect performance. In addition, different types of predictions, including interval prediction and point prediction, can be derived from the obtained density predictions with excellent performance. The results show that the mean prediction interval widths of the proposed approach at ZG287 and ZG289 are 27.30 and 33.04, respectively, which are approximately 60 percent lower than that obtained using the traditional bootstrap-extreme learning machine-artificial neural network (Bootstrap-ELM-ANN). Moreover, the obtained point predictions show great consistency with the observations, with correlation coefficients of 0.9998. Given the satisfactory performance, the presented copula-KSVMQR approach shows a great ability to predict landslide displacement.
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Badjate, Sanjay L., and Sanjay V. Dudul. "Novel FTLRNN with Gamma Memory for Short-Term and Long-Term Predictions of Chaotic Time Series." Applied Computational Intelligence and Soft Computing 2009 (2009): 1–21. http://dx.doi.org/10.1155/2009/364532.
Повний текст джерелаАнотація:
Multistep ahead prediction of a chaotic time series is a difficult task that has attracted increasing interest in the recent years. The interest in this work is the development of nonlinear neural network models for the purpose of building multistep chaotic time series prediction. In the literature there is a wide range of different approaches but their success depends on the predicting performance of the individual methods. Also the most popular neural models are based on the statistical and traditional feed forward neural networks. But it is seen that this kind of neural model may present some disadvantages when long-term prediction is required. In this paper focused time-lagged recurrent neural network (FTLRNN) model with gamma memory is developed for different prediction horizons. It is observed that this predictor performs remarkably well for short-term predictions as well as medium-term predictions. For coupled partial differential equations generated chaotic time series such as Mackey Glass and Duffing, FTLRNN-based predictor performs consistently well for different depths of predictions ranging from short term to long term, with only slight deterioration after k is increased beyond 50. For real-world highly complex and nonstationary time series like Sunspots and Laser, though the proposed predictor does perform reasonably for short term and medium-term predictions, its prediction ability drops for long term ahead prediction. However, still this is the best possible prediction results considering the facts that these are nonstationary time series. As a matter of fact, no other NN configuration can match the performance of FTLRNN model. The authors experimented the performance of this FTLRNN model on predicting the dynamic behavior of typical Chaotic Mackey-Glass time series, Duffing time series, and two real-time chaotic time series such as monthly sunspots and laser. Static multi layer perceptron (MLP) model is also attempted and compared against the proposed model on the performance measures like mean squared error (MSE), Normalized mean squared error (NMSE), and Correlation Coefficient (r). The standard back-propagation algorithm with momentum term has been used for both the models.
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Fu, Chen, C. Patrick Bounds, Christian Selent, and Mesbah Uddin. "Turbulence modeling effects on the aerodynamic characterizations of a NASCAR Generation 6 racecar subject to yaw and pitch changes." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 14 (February 10, 2019): 3600–3620. http://dx.doi.org/10.1177/0954407019826475.
Повний текст джерелаАнотація:
The characterization of a racecar’s aerodynamic behavior at various yaw and pitch configurations has always been an integral part of its on-track performance evaluation in terms of lap time predictions. Although computational fluid dynamics has emerged as the ubiquitous tool in motorsports industry, a clarity is still lacking about the prediction veracity dependence on the choice of turbulence models, which is central to the prediction variability and unreliability for the Reynolds Averaged Navier–Stokes simulations, which is by far the most widely used computational fluid dynamics methodology in this industry. Subsequently, this paper presents a comprehensive assessment of three commonly used eddy viscosity turbulence models, namely, the realizable [Formula: see text] (RKE), Abe–Kondoh–Nagano [Formula: see text], and shear stress transport [Formula: see text], in predicting the aerodynamic characteristics of a full-scale NASCAR Monster Energy Cup racecar under various yaw and pitch configurations, which was never been explored before. The simulations are conducted using the steady Reynolds Averaged Navier–Stokes approach with unstructured trimmer cells. The tested yaw and pitch configurations were chosen in consultation with the race teams such that they reflect true representations of the racecar orientations during cornering, braking, and accelerating scenarios. The study reiterated that the prediction discrepancies between the turbulence models are mainly due to the differences in the predictions of flow recirculation and separation, caused by the individual model’s effectiveness in capturing the evolution of adverse pressure gradient flows, and predicting the onset of separation and subsequent reattachment (if there be any). This paper showed that the prediction discrepancies are linked to the computation of the turbulent eddy viscosity in the separated flow region, and using flow-visualizations identified the areas on the car body which are critical to this analysis. In terms of racecar aerodynamic performance parameter predictions, it can be reasonably argued that, excluding the prediction of the %Front prediction, shear stress transport is the best choice between the three tested models for stock-car type racecar Reynolds Averaged Navier–Stokes computational fluid dynamics simulations as it is the only model that predicted directionally correct changes of all aerodynamic parameters as the racecar is either yawed from the 0° to 3° or pitched from a high splitter-ground clearance to a low one. Furthermore, the magnitude of the shear stress transport predicted delta force coefficients also agreed reasonably well with test results.
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Husnayain, Atina, Eunha Shim, Anis Fuad, and Emily Chia-Yu Su. "Predicting New Daily COVID-19 Cases and Deaths Using Search Engine Query Data in South Korea From 2020 to 2021: Infodemiology Study." Journal of Medical Internet Research 23, no. 12 (December 22, 2021): e34178. http://dx.doi.org/10.2196/34178.
Повний текст джерелаАнотація:
Background Given the ongoing COVID-19 pandemic situation, accurate predictions could greatly help in the health resource management for future waves. However, as a new entity, COVID-19’s disease dynamics seemed difficult to predict. External factors, such as internet search data, need to be included in the models to increase their accuracy. However, it remains unclear whether incorporating online search volumes into models leads to better predictive performances for long-term prediction. Objective The aim of this study was to analyze whether search engine query data are important variables that should be included in the models predicting new daily COVID-19 cases and deaths in short- and long-term periods. Methods We used country-level case-related data, NAVER search volumes, and mobility data obtained from Google and Apple for the period of January 20, 2020, to July 31, 2021, in South Korea. Data were aggregated into four subsets: 3, 6, 12, and 18 months after the first case was reported. The first 80% of the data in all subsets were used as the training set, and the remaining data served as the test set. Generalized linear models (GLMs) with normal, Poisson, and negative binomial distribution were developed, along with linear regression (LR) models with lasso, adaptive lasso, and elastic net regularization. Root mean square error values were defined as a loss function and were used to assess the performance of the models. All analyses and visualizations were conducted in SAS Studio, which is part of the SAS OnDemand for Academics. Results GLMs with different types of distribution functions may have been beneficial in predicting new daily COVID-19 cases and deaths in the early stages of the outbreak. Over longer periods, as the distribution of cases and deaths became more normally distributed, LR models with regularization may have outperformed the GLMs. This study also found that models performed better when predicting new daily deaths compared to new daily cases. In addition, an evaluation of feature effects in the models showed that NAVER search volumes were useful variables in predicting new daily COVID-19 cases, particularly in the first 6 months of the outbreak. Searches related to logistical needs, particularly for “thermometer” and “mask strap,” showed higher feature effects in that period. For longer prediction periods, NAVER search volumes were still found to constitute an important variable, although with a lower feature effect. This finding suggests that search term use should be considered to maintain the predictive performance of models. Conclusions NAVER search volumes were important variables in short- and long-term prediction, with higher feature effects for predicting new daily COVID-19 cases in the first 6 months of the outbreak. Similar results were also found for death predictions.