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This viewgraph presentation discusses unsteady flow simulations for a turbopump intended for a reusable launch vehicle (RLV). The simulation process makes use of computational grids and parallel processing. The architecture of the parallel computers used is discussed, as is the scripting of turbopump simulations.
A series of overset grids was generated in response to the 3rd AIAA CFD Drag Prediction Workshop (DPW-III) which preceded the 25th Applied Aerodynamics Conference in June 2006. DPW-III focused on accurate drag prediction for wing/body and wing-alone configurations. The grid series built for each configuration consists of a coarse, medium, fine, and extra-fine mesh. The medium mesh is first constructed using the current state of best practices for overset grid generation. The medium mesh is then coarsened and enhanced by applying a factor of 1.5 to each (I,J,K) dimension. The resulting set of parametrically equivalent grids increase in size by a factor of roughly 3.5 from one level to the next denser level. CFD simulations were performed on the overset grids using two different RANS flow solvers: CFL3D and OVERFLOW. The results were post-processed using Richardson extrapolation to approximate grid converged values of lift, drag, pitching moment, and angle-of-attack at the design condition. This technique appears to work well if the solution does not contain large regions of separated flow (similar to that seen n the DLR-F6 results) and appropriate grid densities are selected. The extra-fine grid data helped to establish asymptotic grid convergence for both the OVERFLOW FX2B wing/body results and the OVERFLOW DPW-W1/W2 wing-alone results. More CFL3D data is needed to establish grid convergence trends. The medium grid was utilized beyond the grid convergence study by running each configuration at several angles-of-attack so drag polars and lift/pitching moment curves could be evaluated. The alpha sweep results are used to compare data across configurations as well as across flow solvers. With the exception of the wing/body drag polar, the two codes compare well qualitatively showing consistent incremental trends and similar wing pressure comparisons.
Two different grid methodologies are studied for application to DSMC simulations about reusable launch vehicles. One method uses an unstructured, tetrahedral grid while the other uses a structured, variable-resolution Cartesian grid. The relative merits of each method are discussed in terms of accuracy, computational efficiency, and overall ease of use. Both methods are applied to the computation of a low-density, hypersonic flow about a winged single-stage-to-orbit reusable launch vehicle concept at conditions corresponding to an altitude of 120 km. Both methods are shown to give comparable results for both surface and flowfield quantities as well as for the overall aerodynamic behavior. For the conditions simulated, the flowfield about the vehicle is very rarefied but the DSMC simulations show significant departure from free-molecular predictions for the surface friction and heat transfer as well as certain aerodynamic quantities.
This report provides details on the activities and accomplishments of Phase 1 of the Sunshine State Solar Grid Initiative (SUNGRIN) Project for the period beginning 4/28/2010 and ending 12/31/2011. SUNGRIN is a five-phase high-penetration solar PV project within the Systems Integration (SI) area of the Solar Energy Technologies (SETP) Program, under the SunShot Initiative. SUNGRIN is focused on understanding and enabling high-penetration grid-connected solar PV through simulation assisted studies of actual Florida utility high-penetration distribution circuits as well as substations and, to a limited extent, the bulk power system. Each phase builds and expands upon the efforts of the previous phase, leading to a comprehensive examination and understanding of high-penetration solar PV issues, from the solar resource to the conversion and integration technologies to the electric power system, with Florida and it’s utility partners providing the broad range of conditions and system integration scenarios necessary to develop useful insight and solutions. This phase, Phase 1, was funded with American Recovery and Reinvestment Act (ARRA) funds. This version of the final report is organized to align with statement of project objectives (SOPO) critical milestones.
Structural health monitoring (SHM) has the capacity to reduce failure by detecting damage during service life, by periodic, automated monitoring. Guided Wave (GW) Ultrasound is a common SHM approach for aerospace structures. Modelling the physics of GW SHM systems provides a route for understanding system dependencies, capabilities and limitations as damage evolves during service life. Such a toolset can strengthen the understanding of the connection between GW SHM results and the true material state. The most useful modelling tools are those that provide versatile solutions with respect to the simulated component geometry and computational grid connectivity. This work details a versatile application programming interface (API) for the elastodynamic finite integration technique for modelling GW SHM of metals. The custom code implementation, EFIT-CompCell, allows for the modelling of diverse geometries by automatically balancing the message passing interface parallelization layout. The user provides the basic parameters of the simulation and the software automatically performs an initial balancing based on anticipated computational loads, and establishes the CPU communication patterns for any geometry. This work describes the programming philosophy and code structure used to create EFIT-CompCell and compares its performance and capacity to simulation tools that are more specialized for specific architectures. Results are presented for a simulation of GW SHM of an aluminum fuselage section being tested by the FAA. The simulation consists of 733M voxels which took approximately 70 hours to complete 25000 time steps using 40 Intel Xeon E5-4650v2 Ivy Bridge processor cores.
New particle formation (NPF), nucleation of condensable vapors to the solid or liquid phase, is a significant source of atmospheric aerosol particle number concentrations. With sufficient growth, these nucleated particles may be a significant source of cloud condensation nuclei (CCN), thus altering cloud albedo, structure, and lifetimes, and insolation reaching the Earth's surface. Herein we present one of the first numerical experiments to quantify the impact of NPF on cloud radiative properties that is conducted at a convection permitting resolution and that explicitly simulates cloud droplet number concentrations. Consistent with observations, these simulations suggest that in spring over the Midwestern U.S.A., NPF occurs frequently and on regional scales. However, the simulations suggest that NPF is not associated with enhancement of regional cloud albedos as would be expected from an increase of CCN. These simulations indicate that NPF reduces ambient sulfuric acid concentrations sufficiently to inhibit growth of preexisting particles to CCN sizes. This reduction in CCN-sized particles reduces cloud albedo, resulting in a domain average positive top of atmosphere cloud radiative forcing of 10 W m-2 and up to ~ 50 W m-2 in individual grid cells relative to a simulation in which NPF is excluded.
This paper presents the results of Reynolds-averaged Navier-Stokes (RANS) simulations conducted by the NASA flow solver, mixed-element USM3D (USM3D-ME), for the 5th AIAA High-Lift Prediction Workshop. As part of the Fixed-Grid RANS Technology Focus Group (TFG), these simulations were performed to assess the accuracy and efficiency of the USM3D-ME solutions in predicting high-lift flows. The High-Lift Common Research Model (CRM-HL) served as the primary geometry. Several CRM-HL configurations were used for three case studies: a verification study (Case 1), a configuration buildup study (Case 2), and a Reynolds-number variation study (Case 3). Overall, USM3D-ME RANS results aligned with the solutions selected by the Fixed-Grid RANS TFG and available wind tunnel data. Simulations for Case 1 and Configuration 2.1 achieved machine-zero residual convergence, with aerodynamic coefficients converging to steady-state values. However, Configurations 2.2-2.4 and Case 3 encountered iterative- and grid-convergence challenges, particularly at high angles of attack. Compared with the experimental data available for Configurations 2.2-2.4, close agreement was demonstrated at low angles of attack. However, for angles of attack approaching the maximum lift conditions, the predicted lift coefficient and pitching moment deviated from experimental values. The drag-coefficient predictions were in relatively good agreement, however, slight overpredictions were observed at the highest angle of attack corresponding to the maximum-lift condition. Although iterative convergence for Configurations 2.2-2.4 at high angles of attack remains a persistent challenge, averaging aerodynamic coefficients over the last 5000 iterations yielded satisfactory agreement with the available wind tunnel experimental data. During the workshop, the lack of iterative convergence was attributed to the vortex structures emanating from the slat brackets. To investigate this issue further, post-workshop simulations were conducted on Configuration 2.2. In one study, RANS simulations were performed on a simplified geometry with the slat brackets removed. The second study focused on performing unsteady RANS (URANS) simulations on the original Configuration 2.2 geometry. Preliminary results from both studies are presented and compared with wind tunnel data for Configuration 2.2. Consistent with the findings of other participants in the Fixed-Grid RANS TFG, this study emphasizes the necessity for further exploration and advancement in RANS technology for predicting high-lift flows.
This paper presents the results of Reynolds-averaged Navier-Stokes (RANS) simulations conducted by NASA’s flow solver, mixed-element USM3D (USM3D-ME), for the 5th AIAA High-Lift Prediction Workshop. As part of the Fixed-Grid RANS Technology Focus Group (TFG), these simulations were performed to assess the accuracy and efficiency of the USM3D-ME solutions in predicting high-lift flows. The High-Lift Common Research Model (CRM-HL) served as the primary geometry. Several CRM-HL configurations were used for three case studies: a verification study (Case 1), a configuration buildup study (Case 2), and a Reynolds-number variation study (Case 3). Overall, USM3D-ME RANS results aligned with the solutions selected by the Fixed-Grid RANS TFG and available wind tunnel data Simulations for Cases 1 and Configuration 2.1 achieved machine-zero residual convergence, with aerodynamic coefficients converging to steady-state values. However, Configurations 2.2-2.4 and Case 3 encountered iterative- and grid-convergence challenges, particularly at high angles of attack. Compared with the experimental data available for Configurations 2.2-2.4, close agreement was demonstrated at low angles of attack. However, for angles of attack approaching the maximum lift conditions, the predicted lift coefficient and pitching moment deviated from experimental values. The drag-coefficient predictions were in a relatively good agreement, however, slight overpredictions were observed at the highest angle of attack corresponding to the maximum-lift condition. Although iterative convergence for Configurations 2.2-2.4 at high angles of attack remains a persistent challenge, averaging aerodynamic coefficients over the last 5000 iterations yielded satisfactory agreement with the available wind tunnel experimental data. During the workshop, the lack of iterative convergence was attributed to the vortex structures emanating from the slat brackets. To investigate this issue further, post-workshop simulations were conducted on Configuration 2.2. In one study, RANS simulations were performed on a simplified geometry with the slat brackets removed. The second study focused on performing URANS simulations on the original Configuration 2.2 geometry. Preliminary results from both studies are presented and compared with wind tunnel data for Configuration 2.2. Consistent with the findings of other participants in the Fixed-Grid RANS TFG, this study emphasizes the necessity for further exploration and advancement in RANS technology for predicting high-lift flows.
This project developed a publicly available, high-fidelity dataset about the interactions among humans, homes, and heat pumps supporting grid interactive efficient buildings to balance demand on the grid with comfort for occupants. Laboratory measurements and simulations of the hardware capture the second-scale electric power dynamics of heat pumps providing grid services like load shifting and load shedding. Field measurements, behavior tracking, and qualitative surveys of people in their homes over multiple years—including experimentally adjusting the heating and cooling system to provide grid services—to capture the reciprocal effect of human behavior on grid services, and grid services on human comfort. Taken together, these data capture the complete Hardware and Human in the loop system for residential heat pumps, reducing large uncertainties in simulation for design, and models for control of heat pumps, and grid-interactive buildings.
Very large eddy simulation (VLES) of the nonreacting turbulent flow in a single-element lean direct injection (LDI) combustor has been successfully performed via the approach known as the partially resolved numerical simulation (PRNS/VLES) using a nonlinear subscale model. The grid is the same as the one used in a previous RANS simulation, which was considered as too coarse for a traditional LES simulation. In this study, we first carry out a steady RANS simulation to provide the initial flow field for the subsequent PRNS/VLES simulation. We have also carried out an unsteady RANS (URANS) simulation for the purpose of comparing its results with that of the PRNS/VLES simulation. In addition, these calculated results are compared with the experimental data. The present effort has demonstrated that the PRNS/VLES approach, while using a RANS type of grid, is able to reveal the dynamically important, unsteady large-scale turbulent structures occurring in the flow field of a single-element LDI combustor. The interactions of these coherent structures play a critical role in the dispersion of the fuel, hence, the mixing between the fuel and the oxidizer in a combustor.
Type-5 wind turbines are unique in their use of a permanent magnet synchronous generator, as well as their use of a hydraulic torque converter. This architecture presents an opportunity to provide steady and grid-ready energy without the need for a power converter. With infrastructure continuity and reliability being an important topic amongst renewable energies, researchers have been prompted to further investigate the benefits of type-5 turbines’ unique electromechanical configuration on stable electricity generation. Researchers involved in the WindSG project, SG standing for synchronous generator, are aiming to model a type-5 turbine using Real Time Digital Simulation (RTDS) to evaluate its efficacy in the grid. RSCAD, the software run on the RTDS, comes pre-loaded with electrical and electromechanical components to help simulate electrical generation and grid conditions. However, within this repertoire there is a lack of a component to represent a gearbox with high-fidelity. Within RSCAD’s case studies, the gearbox is often represented simply by a gear ratio value. This presented the task of developing a high-fidelity gearbox model in RSCAD for use in the larger RTDS type-5 wind turbine model. This poster describes a method of developing a lumped parameter mathematical model to represent a planetary-parallel-parallel gearbox in RSCAD for use in RTDS.
The large size of multiscale, distribution and transmission, power grids hinders fast systemwide estimation and real-time control and optimization of operations. This paper studies graph reduction methods of power grids that are favorable for fast simulations and follow-up applications. While the classical Kron reduction has been successful in reduced order modeling of power grids with traditional, hierarchical design, the selection of reference nodes for the reduced model in a multiscale, distribution and transmission, network becomes ambiguous. In this work we extend the use of the iterative Kron reduction by utilizing the electric grid's graph topology for the selection of reference nodes, consistent with the design features of multiscale networks. Additionally, we propose further reductions by aggregation of coherent subnetworks of triangular meshes, based on the graph topology and network characteristics, in order to preserve currents and build another power-flow equivalent network. Our reductions are achieved through the use of iterative aggregation of subgraphs that include general tree structures, lines, and triangles. Important features of our reduction algorithms include that (i) the reductions are either equivalent to the Kron reduction or otherwise produce a power-flow equivalent network; (ii) due to the mentioned power-flow equivalence, the reduced network can model the dynamic of the swing equations for a lossless, inductive, steady state network; (iii) the algorithms efficiently utilize hash tables to store the sequential reduction steps. The third feature allows for easy reintroduction of detailed models into the reduced, conceptual network and makes the final reduced order model backward compatible with a sequence of intermediate, partially reduced networks with varying resolution---the ordered sequence of iterative reductions corresponds to a sequence of reduced order models. The performance of our graph reduction algorithms and features of the reduced grids are discussed on a real-word transmission and distribution grid. We produce visualizations of the reduced models through open source libraries and release our reduction algorithms with example code and toy data.
A calculation of periodic homogeneous isotropic turbulence is used to simulate the experimental decay of grid turbulence. The calculation is found to match the experiment in a number of important aspects and the computed flow field is then treated as a realization of a physical turbulent flow. From this flow, a calculation is conducted of the large eddy field and the various averages of the subgrid-scale turbulence that occur in the large eddy simulation equations. These quantities are compared with the predictions of the models that are usually applied in large eddy simulation. The results show that the terms which involve the large-scale field are accurately modeled but the subgrid-scale Reynolds stresses are only moderately well modeled. It is also possible to use the method to predict the constants of the models without reference to experiment. Attempts to find improved models have not met with success.
One of the key objectives of the Applied Research Branch in the Numerical Aerodynamic Simulation (NAS) Systems Division at NASA Ames Research Center is the accelerated introduction of highly parallel machines into a fully operational environment. In this report we summarize some of the experiences with the parallel testbed machines at the NAS Applied Research Branch. We discuss the performance results obtained from the implementation of two computational fluid dynamics (CFD) applications, an unstructured grid solver and a particle simulation, on the Connection Machine CM-2 and the Intel iPSC/860.
Type-5 wind turbines are unique in their use of a permanent magnet synchronous generator, as well as their use of a hydraulic torque converter. This architecture presents an opportunity to provide steady and grid-ready energy without the need for a power converter. With infrastructure continuity and reliability being an important topic amongst renewable energies, researchers have been prompted to further investigate the benefits of type-5 turbines’ unique electromechanical configuration on stable electricity generation. Researchers involved in the WindSG project, SG standing for synchronous generator, are aiming to model a type-5 turbine using Real Time Digital Simulation (RTDS) to evaluate its efficacy in the grid. RSCAD, the software run on the RTDS, comes pre-loaded with electrical and electromechanical components to help simulate electrical generation and grid conditions. However, within this repertoire there is a lack of a component to represent a gearbox with high-fidelity. Within RSCAD’s case studies, the gearbox is often represented simply by a gear ratio value. This presented the task of developing a high-fidelity gearbox model in RSCAD for use in the larger RTDS type-5 wind turbine model. This presentation describes a method of developing a lumped parameter mathematical model to represent a planetary-parallel-parallel gearbox in RSCAD for use in RTDS.
We propose a highly scalable demonstration of a portable asynchronous many-task programming model and runtime system applied to a grid-based adaptive mesh refinement hydrodynamic simulation of a double white dwarf merger with 14 levels of refinement that spans 17 orders of magnitude in astrophysical densities. The code uses the portable C++ parallel programming model that is embodied in the HPX library and being incorporated into the ISO C++ standard. The model reflects a significant shift from existing bulk synchronous parallel programming models under consideration for exascale systems. Through the use of the Futurization technique, seemingly sequential code is transformed into wait-free asynchronous tasks. We demonstrate the potential of our model by showing results from strong scaling runs on National Energy Research Scientific Computing Center’s Cori system (658,784 Intel Knight’s Landing cores) that achieve a parallel efficiency of 96.8% using billions of asynchronous tasks.
This paper reports results from the numerical implementation and testing of the compressible large eddy-simulation (LES). Relevant quantities from 32-cubed coarse grid LES solutions are compared with results generated from direct numerical simulations (DNS) of three-dimensional compressible turbulence that have been run both with sufficient resolution, at 96 cubed. The 32 cubed LES results overall agree well with their 96 cubed DNS counterparts. Moreover, the new DNS results confirm several recent conclusions about compressible turbulence that have been based primarily on two-dimensional simulations.