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This study compared the efficacy of the actuator line and actuator surface models in carrying out large-eddy simulations of a utility-scale wind turbine. A large-eddy simulation with the actuator surface and line models was employed to study the wake flow and power production of the turbine. While both the actuator models were employed for the blade representation, the nacelle was modeled using the actuator surface approach. Both of the actuator models demonstrated agreement in the mean velocity field, power production, and turbulence kinetic energy of the wake flow. Comparing the wake flow, power production, and turbulence kinetic energy results, it was found that the mean discrepancy between the two models was 0.6 % , 0.3 % , and 2.3 % , respectively. Despite the minor discrepancies, both actuator models accurately captured the hub vortex in the wake of the nacelle, evidenced by an energy peak in wind speed spectra at f / f ω ≈ 0.34 . [ABSTRACT FROM AUTHOR]

A framework characterizing the degradation of wind turbines for use in multiple-input damage-aware farm control is suggested. The focus is on the fatigue damage of the powertrain (drivetrain + generator) system, but the methodology may be extended to other components. A database of steady-state damage analyses for different operating conditions (average wind speeds, turbulence levels, power demands, and yaw misalignment angles) using aero-hydro-servo-elastic simulations is first generated. Then, a weighted damage index based on probabilistic long-term fatigue damage analysis of the powertrain system components is suggested and used to represent degradation at the farm level for control purposes. The focus is on curtailed conditions where the farm controller dispatches power commands to individual turbines in order to track a demanded power reference (rather than seeking to maximize power) at the farm level. As a secondary objective, the controller seeks to mitigate degradation through a smart combination of power commands and yaw offset angles, making use of the weighted degradation index. The potential of the proposed approach is demonstrated through a case study on the TotalControl Reference Wind Power Plant in a FLORIS-based simulation framework. The proposed farm controller is compared with the conventional one without damage mitigation feature and with damage mitigation but without yaw angle as the control input. It is found that combining yawing and downregulation effectively slows down degradation on the main bearing and powertrain as a whole. [ABSTRACT FROM AUTHOR]

We present a large-eddy simulation framework capable of control co-design of large wind turbines, coupling the turbulent flow environment with blade aeroelastics and turbine controllers. The geometry and aerodynamics of the rotor blades and the turbine nacelle are parameterized using an actuator surface model. The baseline collective pitch control and individual pitch control (IPC) algorithms, consisting of a single-input, single-output proportional–integral controller and two integral controllers, respectively, are incorporated into the simulation framework. Furthermore, a second-order model based on the Euler–Bernoulli beam theory is implemented to describe the blade deformation. Simulations are carried out to investigate the impact of collective and individual pitch control strategies on the deflection of turbine blades. Our results show that the IPC reduces the blade tip deflection fluctuations in the out-of-plane direction, while the fluctuations of the blade tip deflection along the in-plane direction are barely affected by the IPC. Furthermore, the blade out-of-plane deformation fluctuation is underestimated by the one-way coupling approach compared to the two-way coupling approach. The findings of this study reveal the importance of advanced control systems in reducing the dynamic loads on wind turbine blades and underscore the potential of control co-design to reduce the levelized cost of wind energy. [ABSTRACT FROM AUTHOR]

Vegetation can have an appreciable impact on the hydrodynamics and scour potential in natural rivers, but this effect is generally unaccounted for in high-fidelity computational fluid dynamic models. In this study, we have incorporated trees into the flow domain using two different approaches to study the hydrodynamics of the American River in Northern California under flood conditions. In the first approach, we resolved numerous trees as discrete objects. The second method incorporated a vegetation model into our in-house numerical model to treat the vegetation as a momentum sink along the banks. The flood flow of both cases was modeled using the large-eddy simulation. The computed hydrodynamics results of the cases were compared with a baseline case, which did not include any trees. Although both the tree-resolving and vegetation model approaches compared well with one another with respect to the flow field, they significantly altered the computed river flow dynamics and bed shear stress near the banks and the midwidth of the river compared with that of the no-tree case. Both methods that accounted for the resistance of the trees obtained lower and higher bed shear stresses and velocities along the banks and the midwidth of the river, respectively, than that of the baseline case. This research identified the important role that vegetation plays in natural rivers and provided researchers and engineers with the conceptual tools needed to incorporate vegetation into numerical models to improve the accuracy of the model results. [ABSTRACT FROM AUTHOR]

The coronavirus disease outbreak of 2019 has been causing significant loss of life and unprecedented economic loss throughout the world. Social distancing and face masks are widely recommended around the globe to protect others and prevent the spread of the virus through breathing, coughing, and sneezing. To expand the scientific underpinnings of such recommendations, we carry out high-fidelity computational fluid dynamics simulations of unprecedented resolution and realism to elucidate the underlying physics of saliva particulate transport during human cough with and without facial masks. Our simulations (a) are carried out under both a stagnant ambient flow (indoor) and a mild unidirectional breeze (outdoor), (b) incorporate the effect of human anatomy on the flow, (c) account for both medical and non-medical grade masks, and (d) consider a wide spectrum of particulate sizes, ranging from 10 µm to 300 µm. We show that during indoor coughing some saliva particulates could travel up to 0.48 m, 0.73 m, and 2.62 m for the cases with medical grade, non-medical grade, and without facial masks, respectively. Thus, in indoor environments, either medical or non-medical grade facial masks can successfully limit the spreading of saliva particulates to others. Under outdoor conditions with a unidirectional mild breeze, however, leakage flow through the mask can cause saliva particulates to be entrained into the energetic shear layers around the body and transported very fast at large distances by the turbulent flow, thus limiting the effectiveness of facial masks. [ABSTRACT FROM AUTHOR]

One‐way nested mesoscale to microscale simulations of an onshore wind farm have been performed nesting the Weather Research and Forecasting (WRF) model and our in‐house high‐resolution large‐eddy simulation code (UTD‐WF). Each simulation contains five nested WRF domains, with the largest domain spanning the north Texas Panhandle region with a 4 km resolution, while the highest resolution (50 m) nest simulates microscale wind fluctuations and turbine wakes within a single wind farm. The finest WRF domain in turn drives the UTD‐WF LES higher‐resolution domain for a subset of six turbines at a resolution of ∼5 m. The wind speed, direction, and boundary layer profiles from WRF are compared against measurements obtained with a met‐tower and a scanning Doppler wind LiDAR located within the wind farm. Additionally, power production obtained from WRF and UTD‐WF are assessed against supervisory control and data acquisition (SCADA) system data. Numerical results agree well with the experimental measurements of the wind speed, direction, and power production of the turbines. UTD‐WF high‐resolution domain improves significantly the agreement of the turbulence intensity at the turbines location compared with that of WRF. Velocity spectra have been computed to assess how the nesting allows resolving a wide range of scales at a reasonable computational cost. A domain sensitivity analysis has been performed. Velocity spectra indicate that placing the inlet too close to the first row of turbines results in an unrealistic peak of energy at the rotational frequency of the turbines. Spectra of the power production of a single turbine and of the cumulative power of the array have been compared with analytical models. [ABSTRACT FROM AUTHOR]

Game development is commonly seen as a collaborative effort, with teams cooperating on the same project. Nowadays, a variety of cloud-based services have shown the benefits of performing tasks in real-time collaboration with others. In this article, we present a system for collaborative game level editing. We model this problem as a special instance of merging labeled directed acyclic graphs. We propose an algorithm that guarantees that the shared game level is always coherent between edits, both hierarchically and semantically. We establish real-time collaboration by initiating merges automatically and by augmenting the game editor interface to allow users to monitor all others edits in real time. We validate our algorithm by merging complex edits and large game levels. We further validate the collaborative workflow by running a user study with expert game developers, showing that our system works well and collaborative workflows are beneficial to game development. [ABSTRACT FROM AUTHOR]

Large eddy simulations (LES) of the flow past a wind turbine with and without tower and nacelle have been performed at 2 tip speed ratios (TSR [ABSTRACT FROM AUTHOR]

Large-eddy simulations of the flow past an array of three aligned turbines have been performed. The study is focused on below rated (Region 2) wind speeds. The turbines are controlled through the generator torque gain, as usually done in Region 2. Two operating strategies are considered: (i) preset individual optimum torque gain based on a model for the power coefficient (baseline case) and (ii) real-time optimization of torque gain for maximizing each individual turbine power capture during operation. The real-time optimization is carried out through a model-free approach, namely, extremum-seeking control. It is shown that ESC is capable of increasing the power production of the array by 6.5% relative to the baseline case. The extremum-seeking control reduces the torque gain of the downstream turbines, thus increasing the angular speed of the blades. This results in improved aerodynamics near the tip of the blade that is the portion contributing mostly to the torque and power. In addition, an increase in angular speed leads to a larger entrainment in the wake, which also contributes to provide additional available power downstream. It is also shown that the tip speed ratio may not be a reliable performance indicator when the turbines are in waked conditions. This may be a concern when using optimal parameter settings, determined from isolated turbine models, in applications with waked turbines. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Tangles are a form of structured pen-and-ink 2D art characterized by repeating, recursive patterns. We present a method to procedu-rally generate tangle drawings, seen as recursively split sets of arbitrary 2D polygons with holes, with anisotropic and non-stationary features. We formally model tangles with group grammars, an extension of set grammars, that explicitly handles the grouping of shapes necessary to represent tangle repetitions. We introduce a small set of expressive geometric and grouping operators, showing that they can respectively express complex tangles patterns and sub-pattern distributions, with relatively simple grammars. We also show how users can control tangle generation in an interactive and intuitive way. Throughout the paper, we show how group grammars can, in few tens of seconds, produce a wide variety of patterns that would take artists hours of tedious and time-consuming work. We then validated both the quality of the generated tangles and the efficiency of the control provided to the users with a user study, run with both expert and non-expert users. [ABSTRACT FROM AUTHOR]

Current modeling packages have polished interfaces for editing polygonal meshes, where artists work individually on each mesh. A variety of recent cloud-based services have shown the benefits of editing documents in real-time collaboration with others. In this paper, we present a system for collaborative editing of low-polygonal and subdivision mesh models. We cast collaborative editing as a special instance of distributed version control. We support concurrent editing by robustly sharing and merging mesh version histories in real-time. We store and transmit mesh differences efficiently by encoding them as sequences of primitive editing operations. We enable collaboration by merging and detecting conflicts. We extend this model letting artists adapt others' editing histories by retargeting sequences of editing operations to new parts of the mesh with potentially different topology. We tested our algorithms by editing meshes with up to thousand edits, in collaborative editing sessions lasting a few hours, and by retargeting sequences of several hundred edits. We found the proposed system to be reliable, fast and scaling well with mesh complexity. We demonstrate that our merge algorithm is more robust than prior work. We further validated the proposed collaborative workflow with a user study where MeshHisto was consistently preferred over other alternatives for collaborative workflows. [ABSTRACT FROM AUTHOR]

A convolutional neural network (CNN) autoencoder model has been developed to generate 3D realizations of time-averaged velocity in the wake of the wind turbines at the Sandia National Laboratories Scaled Wind Farm Technology (SWiFT) facility. Large-eddy simulations (LES) of the SWiFT site are conducted using an actuator surface model to simulate the turbine structures to produce training and validation datasets of the CNN. The simulations are validated using the SpinnerLidar measurements of turbine wakes at the SWiFT site and the instantaneous and time-averaged velocity fields from the training LES are used to train the CNN. The trained CNN is then applied to predict 3D realizations of time-averaged velocity in the wake of the SWiFT turbines under flow conditions different than those for which the CNN was trained. LES results for the validation cases are used to evaluate the performance of the CNN predictions. Comparing the validation LES results and CNN predictions, we show that the developed CNN autoencoder model holds great potential for predicting time-averaged flow fields and the power production of wind turbines while being several orders of magnitude computationally more efficient than LES. [ABSTRACT FROM AUTHOR]

The cover image, by Christian Santoni et al., is based on the Research Article Effect of tower and nacelle on the flow past a wind turbine, DOI: 10.1002/we.2130. [ABSTRACT FROM AUTHOR]