Bidadi, Shreyas B.; Brazell, Michael B.; Brunhart-Lupo, Nicholas B.; Henry de Frahan, Marc T.; Lee, Dong H.; Hu, Jonathan J.; Melvin, Jeremy M.; Mullowney, Paul M.; Vijayakumar, Ganesh V.; Moser, Robert D.; Rood, Jon R.; Sakievich, Philip S.; Sharma, Ashesh S.; Williams, Alan B.; Sprague, Michael A.
The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines, capturing the thin boundary layers, and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources.
The Jet Propulsion Laboratory has a keen interest in exploring icy moons in the solar system, particularly Jupiter's Europa. Successful exploration of the moon's surface includes planetary protection initiatives to prevent the introduction of viable organisms from Earth to Europa. To that end, the Europa lander requires a Terminal Sterilization Subsystem (TSS) to rid the lander of viable organisms that would potentially contaminate the moon's environment. Sandia National Laboratories has been developing a TSS architecture, relying heavily on computational models to support TSS development. Sandia's TSS design approach involves using energetic material to thermally sterilize lander components at the end of the mission. A hierarchical modeling approach was used for system development and analysis, where simplified systems were constructed to perform empirical tests for evaluating energetic material formulation development and assist in developing computational models with multiple tiers of physics fidelity. Computational models have been developed using multiple Sandia-native computational tools. Three experimental systems and corresponding computational models have been developed: Tube, Sub-Box Small, and Sub-Box Large systems. This paper presents an explanation of the application context of the TSS along with an overview description of a small portion of the TSS development from a modeling and simulation perspective, specifically highlighting verification, validation, and uncertainty quantification (VVUQ) aspects of the modeling and simulation work. Multiple VVUQ approaches were implemented during TSS development, including solution verification, calibration, uncertainty quantification, global sensitivity analysis, and validation. This paper is not intended to express the design results or parameter values used to model the TSS but to communicate the approaches used and how the results of the VVUQ efforts were used and interpreted to assist system development.
The complexity and associated uncertainties involved with atmospheric-turbine-wake interactions produce challenges for accurate wind farm predictions of generator power and other important quantities of interest (QoIs), even with state-of-the-art high-fidelity atmospheric and turbine models. A comprehensive computational study was undertaken with consideration of simulation methodology, parameter selection, and mesh refinement on atmospheric, turbine, and wake QoIs to identify capability gaps in the validation process. For neutral atmospheric boundary layer conditions, the massively parallel large eddy simulation (LES) code Nalu-Wind was used to produce high-fidelity computations for experimental validation using high-quality meteorological, turbine, and wake measurement data collected at the Department of Energy/Sandia National Laboratories Scaled Wind Farm Technology (SWiFT) facility located at Texas Tech University's National Wind Institute. The wake analysis showed the simulated lidar model implemented in Nalu-Wind was successful at capturing wake profile trends observed in the experimental lidar data.
An implicit, low-dissipation, low-Mach, variable density control volume finite element formulation is used to explore foundational understanding of numerical accuracy for large-eddy simulation applications on hybrid meshes. Detailed simulation comparisons are made between low-order hexahedral, tetrahedral, pyramid, and wedge/prism topologies against a third-order, unstructured hexahedral topology. Using smooth analytical and manufactured low-Mach solutions, design-order convergence is established for the hexahedral, tetrahedral, pyramid, and wedge element topologies using a new open boundary condition based on energy-stable methodologies previously deployed within a finite-difference context. A wide range of simulations demonstrate that low-order hexahedral- and wedge-based element topologies behave nearly identically in both computed numerical errors and overall simulation timings. Moreover, low-order tetrahedral and pyramid element topologies also display nearly the same numerical characteristics. Although the superiority of the hexahedral-based topology is clearly demonstrated for trivial laminar, principally-aligned flows, e.g., a 1x2x10 channel flow with specified pressure drop, this advantage is reduced for non-aligned, turbulent flows including the Taylor–Green Vortex, turbulent plane channel flow (Reτ395), and buoyant flow past a heated cylinder. With the order of accuracy demonstrated for both homogenous and hybrid meshes, it is shown that solution verification for the selected complex flows can be established for all topology types. Although the number of elements in a mesh of like spacing comprised of tetrahedral, wedge, or pyramid elements increases as compared to the hexahedral counterpart, for wall-resolved large-eddy simulation, the increased assembly and residual evaluation computational time for non-hexahedral is offset by more efficient linear solver times. Finally, most simulation results indicate that modest polynomial promotion provides a significant increase in solution accuracy.
Power production of the turbines at the Department of Energy/Sandia National Laboratories Scaled Wind Farm Technology (SWiFT) facility located at the Texas Tech University’s National Wind Institute Research Center was measured experimentally and simulated for neutral atmospheric boundary layer operating conditions. Two V27 wind turbines were aligned in series with the dominant wind direction, and the upwind turbine was yawed to investigate the impact of wake steering on the downwind turbine. Two conditions were investigated, including that of the leading turbine operating alone and both turbines operating in series. The field measurements include meteorological evaluation tower (MET) data and light detection and ranging (lidar) data. Computations were performed by coupling large eddy simulations (LES) in the three-dimensional, transient code Nalu-Wind with engineering actuator line models of the turbines from OpenFAST. The simulations consist of a coarse precursor without the turbines to set up an atmospheric boundary layer inflow followed by a simulation with refinement near the turbines. Good agreement between simulations and field data are shown. These results demonstrate that Nalu-Wind holds the promise for the prediction of wind plant power and loads for a range of yaw conditions.