Wind turbine aerodynamic measurements using a scanning lidar.
Abstract not provided.
Kelley, Christopher Lee↗
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Results for “AERODYNAMICS”
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Model reduction for hypersonic aerodynamics via conservative LSPG projection and hyper-reduction
High-speed aerospace engineering applications rely heavily on computational fluid dynamics (CFD) models for design and analysis due to the expense and difficulty of flight tests and experiments. This reliance on CFD models necessitates performing accurate and reliable uncertainty quantification (UQ) of the CFD models. However, it is very computationally expensive to run CFD for hypersonic flows due to the fine grid resolution required to capture the strong shocks and large gradients that are typically present. Furthermore, UQ approaches are “many-query” problems requiring many runs with a wide range of input parameters. One way to enable computationally expensive models to be used in such many-query problems is to employ projection-based reduced-order models (ROMs) in lieu of the (high-fidelity) full-order model. In particular, the least-squares Petrov–Galerkin (LSPG) ROM (equipped with hyper-reduction) has demonstrated the ability to significantly reduce simulation costs while retaining high levels of accuracy on a range of problems including subsonic CFD applications. This allows computationally inexpensive LSPG ROM simulations to replace the full-order model simulations in UQ studies, which makes this many-query task tractable, even for large-scale CFD models. This work presents the first application of LSPG to a hypersonic CFD application. In particular, we present results for LSPG ROMs of the HIFiRE-1 in a three-dimensional, turbulent Mach 7.1 flow, showcasing the ability of the ROM to significantly reduce computational costs while maintaining high levels of accuracy in computed quantities of interest.
Fluid Dynamics↗
Enhanced Data Efficiency Using Deep Neural Networks and Gaussian Processes for Aerodynamic Design Optimization
Adjoint-based optimization methods are attractive for aerodynamic shape design primarily due to their computational costs being independent of the dimensionality of the input space and their ability to generate high-fidelity gradients that can then be used in a gradient-based optimizer. This makes them very well suited for high-fidelity simulation based aerodynamic shape optimization of highly parametrized geometries such as aircraft wings. However, the development of adjoint-based solvers involve careful mathematical treatment and their implementation require detailed software development. Furthermore, they can become prohibitively expensive when multiple optimization problems are being solved, each requiring multiple restarts to circumvent local optima. In this work, we propose a machine learning enabled, surrogate-based framework that replaces the expensive adjoint solver, without compromising on predicting predictive accuracy. Specifically, we first train a deep neural network (DNN) from training data generated from evaluating the high-fidelity simulation model on a model-agnostic design of experiments on the geometry shape parameters. The optimum shape may then be computed by using a gradient-based optimizer coupled with the trained DNN. Subsequently, we also perform a gradient-free Bayesian optimization, where the trained DNN is used as the prior mean. We observe that the latter framework (DNN-BO) improves upon the DNN-only based optimization strategy for the same computational cost. Overall, this framework predicts the true optimum with very high accuracy, while requiring far fewer high-fidelity function calls compared to the adjoint-based method. Furthermore, we show that multiple optimization problems can be solved with the same machine learning model with high accuracy, to amortize the offline costs associated with constructing our models. Our methodology finds applications in the early stages of aerospace design. (C) 2021 Published by Elsevier Masson SAS.
Renganathan, S. Ashwin↗
Aerodynamic levitator for in situ x-ray structure measurements on high temperature and molten nuclear fuel materials
An aerodynamic levitator with carbon dioxide laser beam heating was integrated with a hermetically sealed controlled atmosphere chamber and sample handling mechanism. The system enabled containment of radioactive samples and control of the process atmosphere chemistry. The chamber was typically operated at a pressure of approximately 0.9 bars to ensure containment of the materials being processed. Samples 2.5-3 mm in diameter were levitated in flowing gas to achieve containerless conditions. Levitated samples were heated to temperatures of up to 3500 °C with a partially focused carbon dioxide laser beam. Sample temperature was measured using an optical pyrometer. The sample environment was integrated with a high energy (100 keV) x-ray synchrotron beamline to enable in situ structure measurements to be made on levitated samples as they were heated, melted, and supercooled. The system was controlled from outside the x-ray beamline hutch by using a LabVIEW program. Measurements have been made on hot solid and molten uranium dioxide and binary uranium dioxide-zirconium dioxide compositions.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Sandia Parallel Aerodynamics Reentry Code (SPARC) -- the Future of Production and Research Aerodynamics [Brief]
The Sandia Parallel Aerodynamics and Reentry Code (SPARC) is described.
42 ENGINEERING↗
Multifidelity Uncertainty Quantification with Applications in Wind Turbine Aerodynamics: Preprint
The propagation of input uncertainty through engineering models allows designers to better understand the range of possible outcomes resulting from design decisions. This could lead to greater trust between modelers and stakeholders in the wind energy industry. In this study, we apply multilevel-multifidelity Monte Carlo sampling to flow over an airfoil, assuming uncertainty in the inflow conditions, and characterize the associated computational savings compared to standard Monte Carlo approaches. The truth model is provided by an airfoil simulation with a very fine computational time step, and auxiliary lower-level models are provided by simulations with coarser time steps. Reynolds-averaged Navier Stokes and detached eddy simulations are used to obtain two different model fidelities. The primary quantity of interest for this analysis is the lift force, which is examined for a range of angles of attack. We launch an initial set of 'trial' samples to determine the optimal allocation of model evaluations, and these trial evaluations are used to inform a larger sampling effort. Using the multilevel-multifidelity approach, we achieve roughly an order of magnitude variance reduction in expected lift as compared to the standard Monte Carlo approach with an equivalent computational cost.
17 WIND ENERGY↗
Output-based adaptive aerodynamic simulations using convolutional neural networks
Not provided.
Computer Science↗
Discretization error control for constrained aerodynamic shape optimization
Not provided.
Computer Science↗
Remote optical wind detection and aerodynamic control system for ground vehicle
An aerodynamic control system for a ground vehicle comprises a LiDAR module including at least one LiDAR sensor configured to obtain wind data upstream of the ground vehicle; a computing device; an aerodynamic device controller; and an aerodynamic device including a control surface. The computing device is configured to receive the wind data from the LiDAR module and generate output signals based on the wind data. The aerodynamic device controller is configured to receive the output signals from the computing device and generate control signals to control the aerodynamic device to adjust aerodynamic properties of the ground vehicle based at least in part the wind data. Changes to the configuration of the control surface may include increasing or decreasing a deflection angle of the at least one aerodynamic device. The aerodynamic device may include, e.g., a pneumatically actuated aerodynamic device or an electro-mechanically actuated aerodynamic device.
Damon, Kenneth H.↗
The Unsteady Aerodynamics Module For FAST8
The new modularization framework of FAST v.8 (Jonkman 2013) was accompanied by a complete overhaul of the aerodynamics routines. AeroDyn is an aerodynamics module comprised of four submodels: rotor wake/induction, blade airfoil aerodynamics, tower influence on the blade nodes, and tower drag. Throughout the software overhaul, several improvements to the original theoretical treatments were achieved, including more accurate skewed-wake and unsteady airfoil aerodynamics, and the possibility of modeling highly flexible and curved blades. Under asymmetric conditions, such as wind shear, yawed, and tilted flow, the individual blade elements undergo variations in angle of attack that lead to unsteady aerodynamics phenomena, which can no longer be captured through the static airfoil lift and drag look-up tables. This document covers the main theory and the organization of the modularization framework of the new unsteady aerodynamics submodule (UAM)1, which includes unsteady aerodynamics under attached flow conditions and dynamic stall. The UAM can be called by either blade element momentum theory (only interface discussed in this report), or other future wake models (e.g., dynamic blade element momentum theory, or generalized dynamic wake).
17 WIND ENERGY↗
Bayesian inference of nonlinear unsteady aerodynamics from aeroelastic limit cycle oscillations
A Bayesian model selection and parameter estimation algorithm is applied to investigate the influence of nonlinear and unsteady aerodynamic loads on the limit cycle oscillation (LCO) of a pitching airfoil in the transitional Reynolds number regime. At small angles of attack, laminar boundary layer trailing edge separation causes negative aerodynamic damping leading to the LCO. The fluid–structure interaction of the rigid, but elastically mounted, airfoil and nonlinear unsteady aerodynamics is represented by two coupled nonlinear stochastic ordinary differential equations containing uncertain parameters and model approximation errors. Several plausible aerodynamic models with increasing complexity are proposed to describe the aeroelastic system leading to LCO. The likelihood in the posterior parameter probability density function (pdf) is available semi-analytically using the extended Kalman filter for the state estimation of the coupled nonlinear structural and unsteady aerodynamic model. The posterior parameter pdf is sampled using a parallel and adaptive Markov Chain Monte Carlo (MCMC) algorithm. The posterior probability of each model is estimated using the Chib–Jeliazkov method that directly uses the posterior MCMC samples for evidence (marginal likelihood) computation. The Bayesian algorithm is validated through a numerical study and then applied to model the nonlinear unsteady aerodynamic loads using wind-tunnel test data at various Reynolds numbers.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Aerodynamic Sensitivities over Separable Shape Tensors
Here, we present a comprehensive aerodynamic sensitivity analysis of airfoil parameterization informed by separable shape tensors. This parameterization approach uniquely benefits the design process by isolating various well-studied shape characteristics, such as airfoil thickness, and providing a well-regulated low-dimensional parameter domain for aerodynamic designs. Exploring the aerodynamic sensitivities of this novel parameterization can provide valuable insights for more robust designs and future manufacturing efforts. We construct a data-driven parameter space of airfoils using principal geodesic analysis of separable shape tensors informed by a curated database containing almost 20,000 suitable engineering airfoils. Analyzing the shape reconstruction error and the maximum mean discrepancy between joint distributions of aerodynamic quantities, we study the dimensionality of the learned parameter space. This simple numerical experiment demonstrates a dramatic dimension reduction that retains design effectiveness and promotes regularity of the shape representations. Finally, we generate new airfoils and use the HAM2D Reynolds-averaged Navier–Stokes solver to predict lift, drag, and moment coefficients. We compute multiple sensitivity metrics to quantify and assert the consistency of parameter influence on the aerodynamic quantities. We also explore low-dimensional polynomial ridge approximations to motivate physical intuitions and offer explanations of the approximated sensitivities.
17 WIND ENERGY↗
The influence of time dependent flight and maneuver velocities and elastic or viscoelastic flexibilities on aerodynamic and stability derivatives
The advent of new structural concepts employing composites in primary load carrying aerospace structures in UAVs, MAVs, Boeing 787s, Airbus A380s, etc., necessitates the inclusion of flexibility as well as viscoelasticity in static structural and aero-viscoelastic analyses. Differences and similarities between aeroelasticity and aero-viscoelasticity have been investigated in [2]. An investigation is undertaken as to the dependence and sensitivity of aerodynamic and stability derivatives to elastic and viscoelastic structural flexibility and as to time dependent flight and maneuver velocities. Longitudinal, lateral and directional stabilities are investigated. It has been a well established fact that elastic lifting surfaces are subject to loss of control effectiveness and control reversal at certain flight speeds, which depend on aerodynamic, structural and material properties [5]. Such elastic analyses are extended to linear viscoelastic materials under quasi-static, dynamic, and sudden and gradual loading conditions. In elastic wings one of the critical static parameters is the velocity at which control reversal takes place (V{sub REV}{sup E}). Since elastic formulations constitute viscoelastic initial conditions, viscoelastic reversal may occur at speeds V{sub REV<}{sup ≧}V{sub REV}{sup E}, but furthermore does so in time at 0 < t{sub REV} ≤ ∞. The influence of the twin effects of viscoelastic and elastic materials and of variable flight velocities on longitudinal, lateral, directional and spin stabilities are also investigated. It has been a well established fact that elastic lifting surfaces are subject to loss of control effectiveness and control reversal at certain flight speeds, which depend on aerodynamic, structural and material properties [5]. Such elastic analyses are here extended to linear viscoelastic materials under quasi-static, dynamic, and sudden and gradual loading conditions. In elastic wings the critical parameter is the velocity at which control reversal takes place (V{sub REV}{sup E}). Since elastic formulations constitute viscoelastic initial conditions, viscoelastic reversal may occur at speeds V{sub REV<}{sup ≧}V{sub REV}{sup E}, but furthermore does so in time at 0 < t{sub REV} ≤ ∞. This paper reports on analytical analyses and simulations of the effects of flexibility and time dependent material properties (viscoelasticity) on aerodynamic derivatives and on lateral, longitudinal, directional and spin stability derivatives. Cases of both constant and variable flight and maneuver velocities are considered. Analytical results for maneuvers involving constant and time dependent rolling velocities are analyzed, discussed and evaluated. The relationships between rolling velocity p and aileron angular displacement β as well as control effectiveness are analyzed and discussed in detail for elastic and viscoelastic wings. Such analyses establish the roll effectiveness derivatives (∂[p(t)])/(V{sub ∞}∂β(t)) . Similar studies involving other stability and aerodynamic derivatives are also undertaken. The influence of the twin effects of viscoelastic and elastic materials and of variable flight, rolling, pitching and yawing velocities on longitudinal, lateral and directional are also investigated. Variable flight velocities, encountered during maneuvers, render the usually linear problem at constant velocities into a nonlinear one.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Dynamic inflow and unsteady aerodynamics models for modal and stability analyses in OpenFAST
This work presents two aerodynamic models that are used to perform modal and stability analyses of wind turbines. Including aerodynamic effects in stability analyses is important to capture aerodynamic inertia, stiffness, and damping. The two models consist of a dynamic inflow model based on Øye’s model and an unsteady aerodynamics model based on a simplified Beddoes-Leishman dynamic stall model. Both models are written in a continuous-time state-space form, which is the form needed to perform linearizations within OpenFAST. In this article, we present the new models, perform some simple verifications against HAWC2 results, and then perform stability analyses. We investigate the contribution of the aerodynamic effects on the turbine modes, particularly the flapwise modes, which are the most affected. Because of the development presented in this work, Campbell diagrams accounting for dynamic stall and dynamic wake effects were generated for the first time using OpenFAST.
17 WIND ENERGY↗
Aerodynamic Sensitivity of a Novel Data-Driven Airfoil Shape Representation Framework
We explore the aerodynamic implications of a novel data-driven separable shape tensor framework used to represent discrete airfoil shapes. In this study, we construct a data-driven parameter space defined by separable shape tensors and informed by tens of thousands of distinct airfoils. We use this design space to generate new airfoil designs to study parametric sensitivities with respect to various aerodynamic responses. We use a HAM2D RANS solver to approximate the lift, drag, and moment coefficients for the generated airfoils at two different angles-of-attack. We analyze the robustness and sensitivities of using the separable shape tensor design space by examining the coverage of the aerodynamic response space, uncovering low-dimensional polynomial ridge approximations, and computing various sensitivity metrics. The results show that the data-driven design space produce significant variation in target aerodynamic quantities and facilitate highly accurate approximations (R^2 > 0.96) of one- and two-dimensional structures in each aerodynamic response. This further reduces the effective dimension to enable simplified design and optimization tasks.
aerodynamics↗
Aerodynamic measurements on wind turbines
This article reviews the aerodynamic measurement programs on wind turbines that have been performed in the last decades. It is largely based on results from four projects carried out under auspices of the International Energy Agency (IEA), which are denoted as IEA Tasks 14, 18, 20, and 29. The aim of these projects was to collect and analyze aerodynamic measurements on five field facilities (IEA Tasks 14 and 18), the National Renewable Energy Laboratory Phase VI turbine placed in the large NASA Ames wind tunnel (IEA Task 20), and the Mexico turbine placed in the Large Low Speed Facility of the German Dutch Wind tunnel DNW (IEA Task 29). Other experimental programs with an important aerodynamic content are touched upon as well. Research areas for which these measurements have led to important progress are identified. The progress is illustrated with analyses on these experiments. It is shown that detailed aerodynamic measurements are an absolute necessity for the validation and improvement of wind turbine design codes, where it is also concluded that the amount of measurement data which has been produced until now is still far too limited.
17 WIND ENERGY↗
PyFly: A fast, portable aerodynamics simulator
Here, we present a fast, user-friendly implementation of a potential flow solver based on the unsteady vortex lattice method (UVLM), namely PyFly. UVLM computes the aerodynamic loads applied on lifting surfaces while capturing the unsteady effects such as the added mass forces, the growth of bound circulation, and the wake while assuming that the flow separation location is known a priori. This method is based on discretizing the body surface into a lattice of vortex rings and relies on the Biot–Savart law to construct the velocity field at every point in the simulated domain. We introduce the pointwise approximation approach to simulate the interactions of the far-field vortices to overcome the computational burden associated with the classical implementation of UVLM. The computational framework uses the Python programming language to provide an easy to handle user interface while the computational kernels are written in Fortran. The mixed language approach enables high performance regarding solution time and great flexibility concerning easiness of code adaptation to different system configurations and applications. The computational tool predicts the unsteady aerodynamic behavior of multiple moving bodies (e.g., flapping wings, rotating blades, suspension bridges) subject to incoming air. The aerodynamic simulator can also deal with enclosure effects, multi-body interactions, and B-spline representation of body shapes. Finally, we simulate different aerodynamic problems to illustrate the usefulness and effectiveness of PyFly.
97 MATHEMATICS AND COMPUTING↗
Aerodynamic characterization of two tandem wind turbines under yaw misalignment control using actuator line model
Yaw control has proven to be promising in alleviating the wake effects that plague the efficiency of wind farms. In this work, the actuator line modeling (ALM) method is adopted to simulate the flows over two tandem turbines distanced by 3–7 rotor diameters, with the yaw angle of the upstream rotor varying from γ 1 = 0° to 50°. The aim is to provide a comprehensive aerodynamic characterization of this simple wind farm under yaw misalignment control. With increasing yaw angle, the power generated by the downstream rotor increases, compensating the power loss in the upstream rotor, and resulting in significantly higher total power of the two turbines than that without yaw control. The maximum power output is achieved as the upstream wake of the yawed rotor is redirected away from the downstream rotor plane. Behind the downstream rotor, the secondary steering phenomenon is observed, where the wake is also redirected from the centerline. The use of the actuator line model also reveal unsteady aerodynamic characteristics that cannot be captured by lower-fidelity models. For the upstream rotor, the yaw misalignment results in time-varying change in the local angle of attack on the blade, giving rise to unsteady loading. The downstream rotor is partially submerged in the deflected wake incurred by the yawed upstream rotor. As the blade revolves into and out of the wake deficit, the blade experiences cyclic loading, leading to even stronger fluctuations in the aerodynamic loads than the upstream rotor. These analysis provides a comprehensive understanding of the yaw control effects on the two tandem rotors from the perspectives of aerodynamic performance, wake profiles, and unsteady characteristics. In conclusion, the insights gained from the present study can aid the design of collective yaw control strategies of wind farms, and lay the foundation for assessing the fatigue damage associated with yaw misalignment.
17 WIND ENERGY↗