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This viewgraph presentation provides information on software development tools to facilitate the use of CFD (Computational Fluid Dynamics) codes. The specific CFD codes FDNS and CORSAIR are profiled, and uses for software development tools with these codes during pre-processing, interim-processing, and post-processing are explained.
It is very important to accurately predict the gas pressure, gas and solid temperature, as well as the amount of O-ring erosion inside the space shuttle Reusable Solid Rocket Motor (RSRM) joints in the event of a leak path. The scenarios considered are typically hot combustion gas rapid pressurization events of small volumes through narrow and restricted flow paths. The ideal method for this prediction is a transient three-dimensional computational fluid dynamics (CFD) simulation with a computational domain including both combustion gas and surrounding solid regions. However, this has not yet been demonstrated to be economical for this application due to the enormous amount of CPU time and memory resulting from the relatively long fill time as well as the large pressure and temperature rising rate. Consequently, all CFD applications in RSRM joints so far are steady-state simulations with solid regions being excluded from the computational domain by assuming either a constant wall temperature or no heat transfer between the hot combustion gas and cool solid walls.
This work couples a computational fluid dynamics (CFD) code and rotorcraft computational structural dynamics (CSD) code to calculate helicopter rotor airloads across a range of flight conditions. An iterative loose (weak) coupling methodology is used to couple the CFD and CSD codes on a per revolution, periodic basis. The CFD uses a high fidelity, Navier-Stokes, overset grid methodology with first principles-based wake capturing. Modifications are made to the CFD code for aeroelastic analysis. For a UH-60A Blackhawk helicopter, four challenging level flight conditions are computed: 1) low speed (u = 0.15) with blade-vortex interaction, 2) high speed (u = 0.37) with advancing blade negative lift, 3) high thrust with dynamic stall (u = 0.24), and 4) hover. Results are compared with UH-60A Airloads Program fight test data. Most importantly, for all cases the loose coupling methodology is shown to be stable, convergent, and robust with full coupling of normal force, pitching moment, and chord force. In comparison with flight test data, normal force and pitching moment magnitudes are in good agreement. For the high speed and dynamic stall cases a phase lag in comparison with the data is seen, nonetheless, the shapes of the curves are very good. Overall, the results are noteworthy improvement over lifting line aerodynamics used in rotorcraft comprehensive codes.
Experimental data were obtained to help validate analytical and computational fluid dynamics (CFD) codes used to compute unsteady cascade aerodynamics in a supersonicaxial- flow regime. Results from two analytical codes and one CFD code were compared with experimental data. One analytical code did not account for airfoil thickness or camber; another, using piston theory (piston code), accounted for thickness and camber upstream of the first shockwave/airfoil impingement locations. The Euler CFD code accounted fully for airfoil shape.
This paper presents a high-fidelity multidisciplinary analysis for the NASA lift+cruise vertical takeoff and landing urban air mobility concept aircraft. The reported simulations couple comprehensive rotorcraft aeromechanics and high-fidelity computational fluid dynamics (CFD). Aerodynamic solutions are computed on dynamic, deforming, unstructured, overset grid systems by an unsteady CFD solver, FUN3D, developed at the NASA Langley Research Center. An integrated overset-grid assembler, Yoga, is used for communications between component grids. Two turbulence models are compared for loose-coupling simulations in hover and low-speed forward flight conditions. One model is the negative variant of the one-equation Spalart-Allmaras model (SA-neg), and the other model is the SA-neg-R model adding a simple rotation correction term to the SA-neg model. It demonstrated that the rotation correction in the SA-neg-R turbulence model significantly improves resolution of secondary vortices and wake interactions for rotorcraft simulations.
This paper presents a high-fidelity multidisciplinary analysis for the NASA Lift+Cruise vertical takeoff and landing urban air mobility concept aircraft. The reported simulations couple comprehensive rotorcraft aeromechanics and high-fidelity computational fluid dynamics (CFD). Aerodynamic solutions are computed on dynamic, deforming, unstructured, overset grid systems by an unsteady CFD solver, FUN3D, developed at the NASA Langley Research Center. An integrated overset-grid assembler, Yoga, is used for communications between component grids. Two turbulence models are compared for loose-coupling simulations in hover and low-speed forward flight conditions. One model is the negative variant of the one-equation Spalart-Allmaras model (SA-neg), and the other model is the SA-neg-R model adding a simple rotation correction term to the SA-neg model. It demonstrated that the rotation correction in the SA-neg-R turbulence model significantly improves resolution of secondary vortices and wake interactions for rotorcraft simulations.
Dynamic line rating (DLR) is a technology that allows the ampacity of an electrical conductor to be calculated using real-time or forecasted weather conditions. Historically, the ampacity of a conductor has been determined using a static line rating method which assumes conservative weather assumptions. Therefore, not only can DLR give a more accurate measurement of the true ampacity of a conductor, but it can also increase its ampacity during weather conditions with greater thermal mitigations. The two primary cooling factors in the ampacity calculations are wind speed and direction. In complex terrain, wind speed and direction can have large variations over short distances. Therefore, accurately identifying the limiting span of a transmission line requires high spatial resolution of the wind along its path. One solution is to install dense weather stations along their path, though this can become costly over long distances. Therefore, researchers have investigated the use of Computation Fluid Dynamic (CFD) simulations to accurately compute the wind field along the path of a transmission line and use these results to identify the limiting section of the conductor. This work presents a case study that evaluates the coupling of CFD simulations and forecasted weather simulations using the High-Resolution Rapid Refresh (HRRR) model points over a 2-year span within a region in south eastern Idaho. The primary goal of the work is the evaluation of the number of HRRR model points used, i.e., weather stations, along the path of the line and the accuracy of the resulting DLR ampacity. This was done using 4, 10, 17, 26, and 35 HRRR model points along two transmission line paths. The results indicate that as the number of model points are increased, the DLR ampacity of the lines decrease, yet converge as more points are added and demonstrate little change with additional HRRR points. It is expected that these results can help transmission line operators identify the number of weather stations that must be installed when coupled with CFD simulations and DLR ampacity to ensure accurate ratings and safe operations.
Coupled Computational-Fluid-Dynamics (CFD) and Discrete-Element-Method (DEM) models provide an accurate description of multiphase physical systems where a solid granular particle phase exists in an underlying gaseous continuous medium. The time integration of the granular phase in these simulations is typically handled using an explicit scheme with a constant time-step among all particles that is invariant in time to resolve inter-particle collisions. A locally third-order accurate adaptive time integration technique for particles that employs an embedded locally second-order scheme for error determination is presented in this work. The particle time-step size is dynamically adapted based on solution error, thus leading to significant savings in computational time. The efficacy of our scheme is quantified using four test cases of varying complexity (binary collision, homogeneous cooling system, fluidized bed and hopper discharge). The adaptive time-stepping method exhibits improved performance (~ 2–3 times in most of the cases studied) compared to three commonly used non-adaptive time-step methods (first-order Euler-explicit, second-order Adams-Bashforth and third-order Runge-Kutta schemes), while maintaining the same level of accuracy and parallel scalability.
This paper provides an overview of the SPHERES-Slosh Experiment (SSE) aboard the International Space Station (ISS) and presents on-orbit results with data analysis. In order to predict the location of the liquid propellant during all times of a spacecraft mission, engineers and mission analysts utilize Computational Fluid Dynamics (CFD). These state-of-the-art computer programs numerically solve the fluid flow equations to predict the location of the fluid at any point in time during different spacecraft maneuvers. The models and equations used by these programs have been extensively validated on the ground, but long duration data has never been acquired in a microgravity environment. The SSE aboard the ISS is designed to acquire this type of data, used by engineers on earth to validate and improve the CFD prediction models, improving the design of the next generation of space vehicles as well as the safety of current missions. The experiment makes use of two Synchronized Position Hold, Engage, Reorient Experimental Satellites (SPHERES) connected by a frame. In the center of the frame there is a plastic, pill shaped tank that is partially filled with green-colored water. A pair of high resolution cameras records the movement of the liquid inside the tank as the experiment maneuvers within the Japanese Experimental Module test volume. Inertial measurement units record the accelerations and rotations of the tank, making the combination of stereo imaging and inertial data the inputs for CFD model validation.
This paper provides an overview of the SPHERES-Slosh Experiment (SSE) aboard the International Space Station (ISS) and presents on-orbit results with data analysis. In order to predict the location of the liquid propellant during all times of a spacecraft mission, engineers and mission analysts utilize Computational Fluid Dynamics (CFD). These state-of-the-art computer programs numerically solve the fluid flow equations to predict the location of the fluid at any point in time during different spacecraft maneuvers. The models and equations used by these programs have been extensively validated on the ground, but long duration data has never been acquired in a microgravity environment. The SSE aboard the ISS is designed to acquire this type of data, used by engineers on earth to validate and improve the CFD prediction models, improving the design of the next generation of space vehicles as well as the safety of current missions. The experiment makes use of two Synchronized Position Hold, Engage, Reorient Experimental Satellites (SPHERES) connected by a frame. In the center of the frame there is a plastic, pill shaped tank that is partially filled with green-colored water. A pair of high resolution cameras records the movement of the liquid inside the tank as the experiment maneuvers within the Japanese Experimental Module test volume. Inertial measurement units record the accelerations and rotations of the tank, making the combination of stereo imaging and inertial data the inputs for CFD model validation.
This paper provides an overview of the SPHERES-Slosh Experiment (SSE) aboard the International Space Station (ISS) and presents on-orbit results with data analysis. In order to predict the location of the liquid propellant during all times of a spacecraft mission, engineers and mission analysts utilize Computational Fluid Dynamics (CFD). These state-of-the-art computer programs numerically solve the fluid flow equations to predict the location of the fluid at any point in time during different spacecraft maneuvers. The models and equations used by these programs have been extensively validated on the ground, but long duration data has never been acquired in a microgravity environment. The SSE aboard the ISS is designed to acquire this type of data, used by engineers on earth to validate and improve the CFD prediction models, improving the design of the next generation of space vehicles as well as the safety of current missions. The experiment makes use of two Synchronized Position Hold, Engage, Reorient Experimental Satellites (SPHERES) connected by a frame. In the center of the frame there is a plastic, pill shaped tank that is partially filled with green-colored water. A pair of high resolution cameras records the movement of the liquid inside the tank as the experiment maneuvers within the Japanese Experimental Module test volume. Inertial measurement units record the accelerations and rotations of the tank, making the combination of stereo imaging and inertial data the inputs for CFD model validation.
Computational Fluid Dynamics (CFD) methods are presently applied to the design and analysis of scramjet propulsion systems for missiles and aircraft operating at speeds in excess of Mach 5, in forms ranging from simple inviscid codes for parametric studies of inlet geometries to Navier-Stokes codes incorporating chemistry models which address complex scramjet combustion phenomena. Attention is given to the development history of CFD for the hypersonic regime, as well as to scramjet flowfield modeling in inlets, combustors and nozzles, and prospective development trends.
Time-accurate computational fluid dynamics (CFD) algorithms are among the basic requirements as an engineering or research tool for realistic simulations of transient combustion phenomena, such as combustion instability, transient start-up, etc., inside the rocket engine combustion chamber. A time-accurate pressure based method is employed in the FDNS code for combustion model development. This is in connection with other program development activities such as spray combustion model development and efficient finite-rate chemistry solution method implementation. In the present study, a second-order time-accurate time-marching scheme is employed. For better spatial resolutions near discontinuities (e.g., shocks, contact discontinuities), a 3rd-order accurate TVD scheme for modeling the convection terms is implemented in the FDNS code. Necessary modification to the predictor/multi-corrector solution algorithm in order to maintain time-accurate wave propagation is also investigated. Benchmark 1-D and multidimensional test cases, which include the classical shock tube wave propagation problems, resonant pipe test case, unsteady flow development of a blast tube test case, and H2/O2 rocket engine chamber combustion start-up transient simulation, etc., are investigated to validate and demonstrate the accuracy and robustness of the present numerical scheme and solution algorithm.
The purpose here is to assess the state of the art in the areas of numerical analysis that are particularly relevant to computational fluid dynamics (CFD), to identify promising new developments in various areas of numerical analysis that will impact CFD, and to establish a long-term perspective focusing on opportunities and needs. Overviews are given of discretization schemes, computational fluid dynamics, algorithmic trends in CFD for aerospace flow field calculations, simulation of compressible viscous flow, and massively parallel computation. Also discussed are accerelation methods, spectral and high-order methods, multi-resolution and subcell resolution schemes, and inherently multidimensional schemes.
This dataset contains aerodynamic quantities - including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) - for 8,996 airfoil shapes, computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes were designed using the separable shape tensor parameterization that encodes two-dimensional shapes as elements of the Grassmann manifold. This data-driven approach learns two independent spaces of parameter from a collection of sample airfoils. The first captures large-scale, linear perturbations, and the second defines small-scale, higher-order perturbations. For this data, we used the G2Aero database of over 19,000 airfoil shapes to learn a parameter space that captured a wide array of shape characteristics. We fixed the linear deformations to be the mean over the database and sampled new shapes over a four-dimensional parameter space of higher-order perturbation. This sampling approaches allows for isolated analysis of non-linear airfoil shape deformations while holding other aspects (e.g., airfoil thickness) approximately constant. The aerodynamic quantities for the generated airfoil were obtained using the HAM2D code, which is a finite-volume Reynolds-averaged Navier-Stokes (RANS) flow solver. We employ a fifth-order WENO scheme for spatial reconstruction with Roe's flux difference scheme for inviscid flux and second-order central differencing for viscous flux. A preconditioned GMRES method is applied for implicit integration. The Spalart-Allmaras 1-eq turbulence model is used for the turbulence closure, and the Medida-Baeder 2-eq transition model is applied to account for the effects of laminar turbulent transition. The airfoil grid is generated with a total of 400 points on the airfoil surface, the initial wall-normal spacing of y+ = 1, and an outer boundary located at 300 chord lengths away from the wall. The CFD simulations are performed at a freestream Mach number of 0.1, Reynolds number of 9M, and at two angles of attack, 4 deg. and 12 deg. The simulations were performed using the Bridges-2 system at the Pittsburgh Supercomputing Center in February 2023 as part of the INTEGRATE project funded by the Advanced Research Projects Agency - Energy in the U.S. Department of Energy. The data was collected, reformatted, and preprocessed for this OEDI submission in July 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub Repository resource under explore_airfoil_9k_data.ipynb.
Topics covered include the computational fluid dynamics (CFD) task force philosophy, a road map for CFD code validation, computer code validation requirements for forebodies and inlets, the criteria for choosing recommended experiments, an all-body hypersonic experiment, and centerline heat transfer. Information is given in viewgraph form.
To design a more realistic low-boom supersonic demonstrator concept, theoretical engines were replaced with F-100 type engines. The original nacelle for the theoretical engine is replaced with a larger nacelle that is assumed adequate to house the F-100 engine. The process to redesign the configuration is then described and the rationales for design changes are given in some detail. Computational fluid dynamics (CFD) analysis was used to compute the equivalent area (A(sub e)) of the configuration during the redesign process. The goal of redesigning the configuration to match the CFD Ae of the configuration to a low-boom target was accomplished. The ground signature for CFD A(sub e) of the redesigned configuration has similar low-boom characteristics as that of the original low-boom configuration with theoretical engines.
The time integration of the granular phase in coupled computational fluid dynamics (CFD) – discrete element method (DEM) simulations presents a unique computational challenge brought about by the large variations in particle collisional time scales. Particles in the dilute regions of the computational domain can be advanced with large time steps while dense regions require much smaller time increments. However, the time step size in most solvers is globally set as the limit for accuracy and stability imposed by the collisions and is typically orders of magnitude less than that required away from collisions. This work addresses this precise issue and provides a strategy to avoid the use of a global conservative small time step size for the entire set of particles.A novel time stepping algorithm for CFD-DEM solvers using a partitioning approach using orthogonal recursive bisection (ORB) that allows for variable time steps among particles is described and its computational performance is compared against baseline explicit methods, typically used in several CFD-DEM solvers. ORB has advantages of being relatively quick and easy to update incrementally and has the required heuristic behavior (i.e., it will split the region in half with a cluster on each side) when groups of particles are well separated (clustered). The algorithm presented in this work uses a local time stepping approach to resolve collisional time scales for subsets of particles that are present at the leaves of the ORB, thereby resulting in substantial reduction of computational cost. The parallel implementation of this method where a ``knapsack” algorithm is used in tandem with ORB for effective load-balancing is also presented, where a best possible partitioning is obtained based on number of particles and local time-stepping costs. The algorithm is tested against benchmark problems with varying particle distributions that include fluidized bed and riser flow scenarios. Preliminary results indicate that the approach is 2-3X faster than traditional explicit methods for problems that involve both dense and dilute regions, while maintaining the same level of accuracy.