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The application of Galerkin/least-squares methodology to computational fluid dynamics is reviewed. Applications to advective-diffusive systems of equations and incompressible and compressible Euler and Navier-Stokes equations are described. Space-time finite-element methodology for time-dependent problems is emphasized and the status and role of so-called 'discontinuity-capturing operators' is reviewed.
Distributed concurrent visualization and computation in computational fluid dynamics (CFD) is not a new concept. Specialized applications such as Realtime Interactive Particle-tracer (RIP) and vendor specific tools like Distributed Graphics Language (DGL) have been in use for some time. This paper describes a current project underway at NASA Lewis Research Center to provide the CFD researcher with an easy method for incorporating distributed processing concepts into program development. Details on the FORTRAN capable interface to a set of network and visualization functions are presented along with some results from initial CFD case studies that employ these techniques.
Viewgraphs on computational fluid dynamics (CFD) for nuclear thermal propulsion are presented. Topics covered include: hydrogen mass fraction as a function of chamber temperature; specific enthalpy of hydrogen and mole fraction of hydrogen as a function of chamber pressure; and specific impulse as a function of chamber pressure. Wall configurations of several nozzles are shown.
The essential elements of a computational fluid dynamics analysis of the HL-20/personnel launch system aerothermal environment at hypersonic speeds including surface definition, grid generation, solution techniques, and visual representation of results are presented. Examples of solution technique validation through comparison with data from ground-based facilities are presented, along with results from computations at flight conditions. Computations at flight points indicate that real-gas effects have little or no effect on vehicle aerodynamics and, at these conditions, results from approximate techniques for determining surface heating are comparable with those obtained from Navier-Stokes solutions.
A combined geometric approach for computational fluid dynamics is presented for the analysis of unsteady flow about mechanisms in which its components are in moderate relative motion. For a CFD analysis, the total dynamics problem involves the dynamics of the aspects of geometry modeling, grid generation, and flow modeling. The interrelationships between these three aspects allow for a more natural formulation of the problem and the sharing of information which can be advantageous to the computation of the dynamics. The approach is applied to planar geometries with the use of an efficient multi-block, structured grid generation method to compute unsteady, two-dimensional and axisymmetric flow. The applications presented include the computation of the unsteady, inviscid flow about a hinged-flap with flap deflections and a high-speed inlet with centerbody motion as part of the unstart / restart operation.
Computational fluid dynamic analyses of the Navier-Stokes equations coupled with solid-phase pyrolysis, gas-phase combustion, turbulence and radiation are performed to study hybrid rocket combustor flowfields. The computational study is closely co-ordinated with a companion experimental program using a planar slab burner configuration with HTPB as fuel and gaseous oxygen. Computational predictions agree reasonably well with measurement data of fuel regression rates and surface temperatures. Additionally, most of the parametric trends predicted by the model are in general agreement with experimental trends. The computational model is applied to extend the results from the lab-scale to a full-scale axisymmetric configuration. The numerical predictions indicate that the full-scale configuration burns at a slower rate than the lab-scale combustor under identical specific flow rate conditions. The results demonstrate that detailed CFD analyses can play a useful role in the design of hybrid combustors.
A system and method for generating fluid flow parameter data for use in aerodynamic heating analysis. Computational fluid dynamics data is generated for a number of points in an area on a surface to be analyzed. Sub-areas corresponding to areas of the surface for which an aerodynamic heating analysis is to be performed are identified. A computer system automatically determines a sub-set of the number of points corresponding to each of the number of sub-areas and determines a value for each of the number of sub-areas using the data for the sub-set of points corresponding to each of the number of sub-areas. The value is determined as an average of the data for the sub-set of points corresponding to each of the number of sub-areas. The resulting parameter values then may be used to perform an aerodynamic heating analysis.
A system and method for generating fluid flow parameter data for use in aerodynamic heating analysis. Computational fluid dynamics data is generated for a number of points in an area on a surface to be analyzed. Sub-areas corresponding to areas of the surface for which an aerodynamic heating analysis is to be performed are identified. A computer system automatically determines a sub-set of the number of points corresponding to each of the number of sub-areas and determines a value for each of the number of sub-areas using the data for the sub-set of points corresponding to each of the number of sub-areas. The value is determined as an average of the data for the sub-set of points corresponding to each of the number of sub-areas. The resulting parameter values then may be used to perform an aerodynamic heating analysis.
Most tank slosh test programs are not conducted with flight hardware in a flight-like environment due to cost and schedule constraints. Instead, subscale tanks are typically tested on the ground. If the “real”, flight liquid in the tank is a cryogenic propellant, sometimes a cryogen is used during testing, but more often a simulant liquid is used. Fluid dynamic similarity analysis, or “scaling analysis” as it is sometimes called, for slosh examines nondimensional numbers to determine which fluid dynamic regime(s) a tank is operating in. If the relevant nondimensional numbers of a scale tank test are similar enough to the real tank’s nondimensional numbers, then it is likely that the scale test data will be similar to what would be obtained with the real tank. This type of analysis is useful for guiding experiment design, test liquid selection, and for understanding the physical relevance of prior test data to a specific application. The authors have performed scaling analyses for many slosh test programs conducted in ground, parabolic flight, suborbital, and in-orbit environments. Basics of how to perform the analysis, along with select examples from ground and microgravity environments, are presented. Suggestions for various assumptions and compromises to make are discussed. Limitations and challenges are also discussed.
Three-dimensional, time-resolved blood flow measurement (4D-flow) is a powerful research and clinical tool, but improved resolution and scan times are needed. Therefore, this study aims to (1) present a postprocessing framework for optimization-driven simulation-based flow imaging, called 4D-flow High-resolution Imaging with a priori Knowledge Incorporating the Navier-Stokes equations and the discontinuous Galerkin method (4D-flow HIKING), (2) investigate the framework in synthetic tests, (3) perform phantom validation using laser particle imaging velocimetry, and (4) demonstrate the use of the framework in vivo. An optimizing computational fluid dynamics solver including adjoint-based optimization was developed to fit computational fluid dynamics solutions to 4D-flow data. Synthetic tests were performed in 2D, and phantom validation was performed with pulsatile flow. Reference velocity data were acquired using particle imaging velocimetry, and 4D-flow data were acquired at 1.5 T. In vivo testing was performed on intracranial arteries in a healthy volunteer at 7 T, with 2D flow as the reference. Results Synthetic tests showed low error (0.4%-0.7%). Phantom validation showed improved agreement with laser particle imaging velocimetry compared with input 4D-flow in the horizontal (mean -0.05 vs -1.11 cm/s, P < .001; SD 1.86 vs 4.26 cm/s, P < .001) and vertical directions (mean 0.05 vs -0.04 cm/s, P = .29; SD 1.36 vs 3.95 cm/s, P < .001). In vivo data show a reduction in flow rate error from 14% to 3.5%. Phantom and in vivo results from 4D-flow HIKING show promise for future applications with higher resolution, shorter scan times, and accurate quantification of physiological parameters.
In order to establish the credibility of CFD results utilized in aerospace plane design, the following topics are discussed: CFD validation in relation to 'measureable' fluid dynamics (MFD) validation, credibility requirements, responsibility for credibility, and a guide for establishing credibility. What is of paramount concern for fluid dynamic design is not CFD code validation but qualification of CFD unknowns so that their magnitude is greatly reduced and that these uncertainties are employed for designing with margin. The designers must be trained to properly use CFD if they are to produce good designs. In approximately 70 percent of the flight envelopes of SSTO aerospace planes with supersonic combustion, CFD will be necessary to determine dynamics performance and specifications.
A raised-floor plenum is often used to distribute cooling airflow in data centers. Traditional Computational Fluid Dynamics (CFD) can accurately model airflow distribution in plenums, but it is expensive (computationally and financially) and is, therefore, often not accessible to the data center designer or operator. This paper presents an alternative CFD methodology based on Fast Fluid Dynamics (FFD), which is faster, more parallelizable, and simpler to program. The improvement in computational speed afforded by FFD is particularly important for multiple-iteration optimization, transient simulations, or applications for which near-real-time performance is required. Here, the potential speed improvements of FFD have been widely documented; however, it has been generally accepted that this benefit is accompanied by a modest loss of accuracy relative to traditional CFD. We show here that this is not necessarily true. Plenum airflow predictions by our FFD implementation, which utilizes a first-order upwind rather than Semi-Lagrangian advection scheme of previous research, are extremely close to those predicted by traditional CFD - provided the same turbulence model and computational grid are used consistently.
Some of the hardware and software tools and techniques in use at NASA's numerical aerodynamic simulation facility for the analysis of computational fluid dynamics are described. The visualization process can be illustrated by video tapes and stereo pictures. Although these visualization tools have dramatically improved the ability to conduct research in fluid dynamics, a comparison of the current environment for analysis with an 'ideal' environment illustrates that there are still major improvements that should be made. The most time-consuming task in future analyses of the increasingly complex computer simulations will be the extraction and clear display of the key features. In addition, the interface between the workstation and the scientist should be improved significantly. Current research on techniques for creating these improvements is described.
We describe a numerical method for simulating stochastic fluid dynamics near a critical point in the Ising universality class. This theory is known as model H, and is expected to govern the nonequilibrium dynamics of quantum chromodynamics (QCD) near a possible critical endpoint of the phase transition between a hadron liquid and the quark-gluon plasma. The numerical algorithm is based on a Metropolis scheme, and automatically ensures that the distribution function of the hydrodynamic variables in equilibrium is independent of the transport coefficients and only governed by the microscopic free energy. We verify dynamic scaling near the critical point of a two and three-dimensional fluid and extract the associated critical exponent z. Here, we find z≃3 in three dimensions, and z≃2 for a two-dimensional fluid. In a finite system, we observe a crossover between the mean field value z=4 and the true critical exponent z≃3 (z≃2 in d=2). This crossover is governed by the values of the correlation length and the renormalized shear viscosity.
The development of aerodynamic theory is traced from the days of Aristotle to the present, with the next stage in computational fluid dynamics dependent on superspeed computers for flow calculations. Additional attention is given to the history of numerical methods inherent in writing computer codes applicable to viscous and inviscid analyses for complex configurations. The advent of the superconducting Josephson junction is noted to place configurational demands on computer design to avoid limitations imposed by the speed of light, and a Japanese projection of a computer capable of several hundred billion operations/sec is mentioned. The NASA Numerical Aerodynamic Simulator is described, showing capabilities of a billion operations/sec with a memory of 240 million words using existing technology. Near-term advances in fluid dynamics are discussed.
An Oxygen Transport Membrane (OTM) combined reforming technology for producing syngas and hydrogen integrates the advantages of multiple processes—steam methane reforming (SMR), autothermal reforming (ATR), an air separation unit (ASU)—into a single integrated technology. The OTM consists of a primary reforming tube, in which desulfurized natural gas is partially reformed by steam at high pressure in the presence of a metal catalyst. This process is followed in series by a ceramic OTM with a secondary reformer, in which residual methane reforms and O 2 - ions react with a portion of the CO and H 2 fuel to provide the heat to support both primary and secondary reforming. Although the OTM combined reformer technology for syngas and H 2 production has been substantially developed in the last decade, several challenges that affect the overall production efficiency and reliability are yet to be fully understood, addressed, and resolved. Therefore, developing Computational Fluid Dynamics (CFD) models that incorporate fluid dynamics, mass transport, kinetics, heat transport, and structural mechanics is critical to understanding and minimizing the probability of tube failures during the startup and operation. In this report, an exhaustive literature review was performed to survey the current state of technology for producing syngas and H 2 using either conventional or renewable energy sources. The feedstocks reviewed include natural gas and coal for the conventional technologies, whereas biomass, solar, wind, and nuclear energy for the renewable technologies. The existing industry-grade COMSOL multiphysics models of OTM were upgraded for the latest software release. In addition, they were improved to help achieve grid and solver independence and were successfully ported on the ORNL high-performance computing clusters to speed up their run times. A 42% reduction in the simulation run time was achieved. A new higher-fidelity CFD model of an OTM tube was developed in the StarCCM+ simulation platform. This new model was designed to simulate various physics using first principles, e.g., turbulent flow, heat transfer, and chemical reactions while avoiding unnecessary simplifications. The resulting predictions were qualitatively assessed and provided useful insights into the multiphysics complexity of an OTM tube.
Packed columns are commonly used in post-combustion processes to capture CO 2 emissions by providing enhanced contact area between a CO 2 -laden gas and CO 2 -absorbing solvent. To study and optimize solvent-based post-combustion carbon capture systems (CCSs), computational fluid dynamics (CFD) can be used to model the liquid–gas countercurrent flow hydrodynamics in these columns and derive key determinants of CO 2 -capture efficiency. However, the large design space of these systems hinders the application of CFD for design optimization due to its high computational cost. In contrast, data-driven modeling approaches can produce fast surrogates to study large-scale physics problems. We build our surrogates using MeshGraphNets (MGN), a graph neural network framework that efficiently learns and produces mesh-based simulations. We apply MGN to a random packed column modeled with over 160K graph nodes and a design space consisting of three key input parameters: solvent surface tension, inlet velocity, and contact angle. Our models can adapt to a wide range of these parameters and accurately predict the complex interactions within the system at rates over 1700 times faster than CFD, affirming its practicality in downstream design optimization tasks. This underscores the robustness and versatility of MGN in modeling complex fluid dynamics for large-scale CCS analyses.
Report reviews recent progress in computational fluid dynamics (CFD). Addresses state of art in terms of methods, examples of solutions, and computer technology. Provides examples of CFD solutions of aerospace and fluid-physics problems to illustrate recent progress. Aerospace solutions include rotor/stator velocity vectors from three-dimensional Navier-Stokes code for turbomachinery, pressure distributions from simulation of aeroelasticity of wing surface-pressure contours on four-bladed helicopter rotor in forward flight, and particle traces about several aerospace vehicles. Computer technology covers supercomputers, scientific work stations, local supercomputing networks, and remote access to supercomputers.