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At least 397 records · Page 22

Controls/CFD Interdisciplinary Research Software Generates Low-Order Linear Models for Control Design From Steady-State CFD Results

The NASA Lewis Research Center is developing analytical methods and software tools to create a bridge between the controls and computational fluid dynamics (CFD) disciplines. Traditionally, control design engineers have used coarse nonlinear simulations to generate information for the design of new propulsion system controls. However, such traditional methods are not adequate for modeling the propulsion systems of complex, high-speed vehicles like the High Speed Civil Transport. To properly model the relevant flow physics of high-speed propulsion systems, one must use simulations based on CFD methods. Such CFD simulations have become useful tools for engineers that are designing propulsion system components. The analysis techniques and software being developed as part of this effort are an attempt to evolve CFD into a useful tool for control design as well. One major aspect of this research is the generation of linear models from steady-state CFD results. CFD simulations, often used during the design of high-speed inlets, yield high resolution operating point data. Under a NASA grant, the University of Akron has developed analytical techniques and software tools that use these data to generate linear models for control design. The resulting linear models have the same number of states as the original CFD simulation, so they are still very large and computationally cumbersome. Model reduction techniques have been successfully applied to reduce these large linear models by several orders of magnitude without significantly changing the dynamic response. The result is an accurate, easy to use, low-order linear model that takes less time to generate than those generated by traditional means. The development of methods for generating low-order linear models from steady-state CFD is most complete at the one-dimensional level, where software is available to generate models with different kinds of input and output variables. One-dimensional methods have been extended somewhat so that linear models can also be generated from two- and three-dimensional steady-state results. Standard techniques are adequate for reducing the order of one-dimensional CFD-based linear models. However, reduction of linear models based on two- and three-dimensional CFD results is complicated by very sparse, ill-conditioned matrices. Some novel approaches are being investigated to solve this problem.

Melcher, Kevin J.↗

Integration of Engine, Plume, and CFD Analyses in Conceptual Design of Low-Boom Supersonic Aircraft

This paper documents an integration of engine, plume, and computational fluid dynamics (CFD) analyses in the conceptual design of low-boom supersonic aircraft, using a variable fidelity approach. In particular, the Numerical Propulsion Simulation System (NPSS) is used for propulsion system cycle analysis and nacelle outer mold line definition, and a low-fidelity plume model is developed for plume shape prediction based on NPSS engine data and nacelle geometry. This model provides a capability for the conceptual design of low-boom supersonic aircraft that accounts for plume effects. Then a newly developed process for automated CFD analysis is presented for CFD-based plume and boom analyses of the conceptual geometry. Five test cases are used to demonstrate the integrated engine, plume, and CFD analysis process based on a variable fidelity approach, as well as the feasibility of the automated CFD plume and boom analysis capability.

Li, Wu↗

Comparison of Space Launch System Aerodynamic Surface Pressure Measurements from Experimental Testing and CFD

A comparison of surface pressure coefficient measurements obtained using pressure-sensitive paint (PSP) measurements with predictions from the computational fluid dynamics (CFD) code FUN3D is presented for the NASA SLS Block 1B crew vehicle. Overall, the flow features over the SLS configuration were captured by both the PSP data and CFD data at freestream Mach numbers (M(sub ∞)) of 0.8 and 1.3. Overall, the flow features over the SLS are captured by the PSP data but the intensities of large pressure gradients are less intense than what was predicted by the CFD data. Several examples of this observation are given including the flow interaction at the booster nose cone edge, core body, and forward booster attachment hardware at M(sub ∞) = 0.8.

FUN3D↗

Integration of CFD and Wind-Tunnel Testing at NASA

The debate over when wind-tunnel testing will be replaced by Computational Fluid Dynamics (CFD) comes and goes. More recently, however, the debate has subsided with a more collaborative spirit between practitioners of these two disciplines. Combining these complementary disciplines has led to significant improvements in both as well as better understanding of aero- and fluid dynamics. Also, as CFD codes become more accurate, the need for comparisons with experimental data has increased. New measurement techniques, pressure-sensitive paint and off-body velocity measurements for example, have provided detailed, high-quality data for the comparisons. In-tunnel CFD simulations are also providing more direct comparisons between predicted and measured flows. Given this newenvironment, a concerted effort is now underway to facilitate in-tunnel CFD for the 12 major wind tunnels operated by NASA.The Aerosciences Evaluation and Test Capabilities Portfolio (AETC) manages the major aerodynamic ground-testing facilities within NASA. This group is responsible for the operation, maintenance, and improvement of the wind-tunnel facilities and their capabilities. AETC has recently added a project to integrate CFD and wind-tunnel testing to better support customers of the NASA wind tunnels and to better understand the flow in the wind tunnels themselves. Being able to perform CFD simulations of wind-tunnel models in the wind tunnel environment providesthe cleanest way to assess the accuracy of the simulations relative to test data. AETC plans to provide accurate geometry and guidance to wind-tunnel customers who request it, to facilitate in-tunnel simulations. How this effort got started will be presented along with the status and plans for the project.

CFD↗

The impact of CFD on development test facilities - A National Research Council projection

The results of a National Research Council study on the effect that advances in computational fluid dynamics (CFD) will have on conventional aeronautical ground testing are reported. Current CFD capabilities include the depiction of linearized inviscid flows and a boundary layer, initial use of Euler coordinates using supercomputers to automatically generate a grid, research and development on Reynolds-averaged Navier-Stokes (N-S) equations, and preliminary research on solutions to the full N-S equations. Improvements in the range of CFD usage is dependent on the development of more powerful supercomputers, exceeding even the projected abilities of the NASA Numerical Aerodynamic Simulator (1 BFLOP/sec). Full representation of the Re-averaged N-S equations will require over one million grid points, a computing level predicted to be available in 15 yr. Present capabilities allow identification of data anomalies, confirmation of data accuracy, and adequateness of model design in wind tunnel trials. Account can be taken of the wall effects and the Re in any flight regime during simulation. CFD can actually be more accurate than instrumented tests, since all points in a flow can be modeled with CFD, while they cannot all be monitored with instrumentation in a wind tunnel.

Korkegi, R. H.↗

A CFD study of complex missile and store configurations in relative motion

An investigation was conducted from May 16, 1990 to August 31, 1994 on the development of computational fluid dynamics (CFD) methodologies for complex missiles and the store separation problem. These flowfields involved multiple-component configurations, where at least one of the objects was engaged in relative motion. The two most important issues that had to be addressed were: (1) the unsteadiness of the flowfields (time-accurate and efficient CFD algorithms for the unsteady equations), and (2) the generation of grid systems which would permit multiple and moving bodies in the computational domain (dynamic domain decomposition). The study produced two competing and promising methodologies, and their proof-of-concept cases, which have been reported in the open literature: (1) Unsteady solutions on dynamic, overlapped grids, which may also be perceived as moving, locally-structured grids, and (2) Unsteady solutions on dynamic, unstructured grids.

Baysal, Oktay↗

CFD Model of Water Droplet Transport for ISS Hygiene Activity

The goal of the study is to assess the impacts of free water propagation in the Waste and Hygiene Compartment (WHC). Free water can be generated inside the WHC in small quantities due to crew hygiene activity. To mitigate potential impact of free water in Node 3 cabin the WHC doorway is enclosed by a waterproof bump-out, Kabin, with openings at the top and bottom. At the overhead side of the rack, there is a screen that prevents large drops of water from exiting. However, as the avionics fan in the WHC causes airflow toward the deck side of the rack, small quantities of free water may exit at the bottom of the Kabin. A Computational Fluid Dynamics (CFD) analysis of Node 3 cabin airflow made possible to identify the paths of water transport. The Node 3 airflow was computed for several ventilation scenarios. To simulate the droplet transport the Lagrangian discrete phase approach was used. Various initial droplet distributions were considered in the study. The droplet diameter was varied in the range of 2-20 mm. The results of the computations showed that most of the drops fall to the rack surface not far from the WHC curtain. The probability of the droplet transport to the adjacent rack surface with electronic equipment was predicted.

Son, Chang H.↗

Comparison Between DSMC and CFD for Hypersonic Planetary Entry Simulations

Hypersonic planetary entry flows span a wide range of Knudsen numbers between rarefied and continuum flows. While computational fluid dynamics (CFD) techniques cannot provide an accurate solution for flows in the rarefied regime, the direct simulation Monte Carlo (DSMC) method is capable of providing accurate solutions for flows in both in the rarefied and continuum regimes but becomes prohibitively expensive as the Knudsen number decreases. For the purpose of thermal protection systems (TPS) design and post-flight reconstruction, various selected points along an entry trajectory are often solved using hypersonic solvers. The quantities of interest that are obtained from that exercise are generally surface quantities, such as pressure, heat flux and enthalpy. Then, material response solvers are used to either design the heat shield to an optimal thickness based on a choice of material, or to provide in-depth heating profiles through the material at various select locations, and compare with flight instrumentation such as the ones that flew on NASA’s two most recent Mars missions, MSL and Mars2020. While most of the heating is generally experienced during the continuum part of the entry, the heating within the rarefied regime is significant for some atmospheres, and hence the flow solutions need to be computed using the DSMC method. Ensuring consistency between hypersonic CFD and the DSMC is crucial so that reliable surface quantities can be passed to material response solvers. Studies were performed to compare the two methods at various select locations, for both non-reacting argon flows as well reacting CO2/N2 flows. Preliminary conclusions show that, for non-reacting flows, the agreement between the two methods for surface heating is excellent (within expected uncertainties) for a freestream Knudsen number of 0.0006, and gets progressively worse as the Knudsen number increases to 0.06. Continuum breakdown analyses were performed and showed that, in general, the Gradient Length Local Knudsen number (KnGLL) from Boyd [1] and associated criteria (KnGLL > 0.05) can be accurately used to predict zones of breakdown in the flow, and associated errors for surface quantities. Furthermore, when studying reacting flow, our studies showed that while flow quantities are highly dependent on relaxation parameters and chemistry rates, it is possible to obtain a good agreement for surface heating, as long as the continuum breakdown in minimal (see Fig. 1). Finally, we studied the impact of the grid refinement on the surface quantities in DSMC.

DSMC↗

Comparison Between DSMC and CFD for Hypersonic Planetary Entry Simulations

Hypersonic planetary entry flows span a wide range of Knudsen numbers between rarefied and continuum flows. While computational fluid dynamics (CFD) techniques cannot provide an accurate solution for flows in the rarefied regime, the direct simulation Monte Carlo (DSMC) method is capable of providing accurate solutions for flows in both in the rarefied and continuum regimes but becomes prohibitively expensive as the Knudsen number decreases. For the purpose of thermal protection systems (TPS) design and post-flight reconstruction, various selected points along an entry trajectory are often solved using hypersonic solvers. The quantities of interest that are obtained from that exercise are generally surface quantities, such as pressure, heat flux and enthalpy. Then, material response solvers are used to either design the heat shield to an optimal thickness based on a choice of material, or to provide in-depth heating profiles through the material at various select locations, and compare with flight instrumentation such as the ones that flew on NASA’s two most recent Mars missions, MSL and Mars2020. While most of the heating is generally experienced during the continuum part of the entry, the heating within the rarefied regime is significant for some atmospheres, and hence the flow solutions need to be computed using the DSMC method. Ensuring consistency between hypersonic CFD and the DSMC is crucial so that reliable surface quantities can be passed to material response solvers. Studies were performed to compare the two methods at various select locations, for both non-reacting argon flows as well reacting CO2/N2 flows. Preliminary conclusions show that, for non-reacting flows, the agreement between the two methods for surface heating is excellent (within expected uncertainties) for a freestream Knudsen number of 0.0006, and gets progressively worse as the Knudsen number increases to 0.06. Continuum breakdown analyses were performed and showed that, in general, the Gradient Length Local Knudsen number (KnGLL) from Boyd and associated criterion (KnGLL > 0.05) seems conservative in predicting zones of breakdown in the flow, and associated errors for surface quantities. Updated criteria of KnGLL = 2.0 and 0.5 appear to be more appropriate for surface and flow quantities, respectively. Furthermore, when studying reacting flows, our studies showed that while flow quantities are highly dependent on relaxation parameters and chemistry rates, it is possible to obtain a good agreement for surface heating, as long as the continuum breakdown is minimal.

DSMC↗

Validation of the Hypersolve CFD Solver for Entry Descent and Landing Applications

The functional equivalence of the HyperSolve unstructured edge-based, finite-volume computational fluid dynamics code to the Langley Aerothermodynamic Upwind Relaxation Algorithm multiblock structured grid code is documented for applications of interest to the Entry, Descent, and Landing community. A suite of cases using a range of thermochemical gas models on relevant vehicle configurations were analyzed with both codes and the results compared. A tolerance of ±4% difference in surface pressure and surface heat flux from a benchmark LAURA solution was used as the criterion for functional equivalence, and comparisons of flowfield quantities are also included to verify that the thermochemical nonequilibrium capabilities in HyperSolve match those of the LAURA code. The functional equivalence of the HyperSolve unstructured edge-based finite-volume computational fluid dynamics (CFD) code to the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) multiblock structured grid code is documented for applications of interest to the Entry, Descent, and Landing (EDL) community. A suite of cases using a range of thermochemical gas models on EDL-relevant vehicle configurations were analyzed with both codes and the results compared. A tolerance of ±4% difference in surface pressure and surface heat flux from a benchmark LAURA solution was used as the criterion for functional equivalence, and comparisons of flow field quantities are also included to verify that the thermochemical nonequilibrium capabilities in HyperSolve match those of the LAURA code. In general, HyperSolve predictions for surface pressure and surface heat flux are in close agreement with those predicted by LAURA.

hypersolve↗

Validation of the HyperSolve CFD Solver for Entry Descent and Landing Applications

The functional equivalence of the HyperSolve unstructured edge-based, finite-volume computational fluid dynamics code to the Langley Aerothermodynamic Upwind Relaxation Algorithm multiblock structured grid code is documented for applications of interest to the Entry, Descent, and Landing community. A suite of cases using a range of thermochemical gas models on relevant vehicle configurations were analyzed with both codes and the results compared. A tolerance of ±4% difference in surface pressure and surface heat flux from a benchmark LAURA solution was used as the criterion for functional equivalence, and comparisons of flowfield quantities are also included to verify that the thermochemical nonequilibrium capabilities in HyperSolve match those of the LAURA code. The functional equivalence of the HyperSolve unstructured edge-based finite-volume computational fluid dynamics (CFD) code to the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) multiblock structured grid code is documented for applications of interest to the Entry, Descent, and Landing (EDL) community. A suite of cases using a range of thermochemical gas models on EDL-relevant vehicle configurations were analyzed with both codes and the results compared. A tolerance of ±4% difference in surface pressure and surface heat flux from a benchmark LAURA solution was used as the criterion for functional equivalence, and comparisons of flow field quantities are also included to verify that the thermochemical nonequilibrium capabilities in HyperSolve match those of the LAURA code. In general, HyperSolve predictions for surface pressure and surface heat flux are in close agreement with those predicted by LAURA.

hypersolve↗

Low-cost Quantification of Fluid Flow Parameter Sensitivity using Reduced-order Modeling

Uncertainty quantification of computational fluid dynamics (CFD) simulations is a complicated procedure which still relies in many cases on engineering judgment and factors of safety. This is in part because the computational cost of measuring the simulation's sensitivity to all meaningful parameters (e.g., body surface roughness) and hyperparameters (e.g., subiteration convergence criterion) is intractable for even a single simulation. Reduced-order modeling dramatically lowers this computational cost of simulating fluid flows, but usually only where similar data is already available. In this work, fluid reduced-order models are utilized to quantify a flow's sensitivity to certain physical parameters for the purposes of improved uncertainty quantification. Characteristic observability and sensitivity are both explored. The resulting sensitivity quantifications enable more informed CFD frameworks and more rigorous uncertainty bounds on the resulting data.

uncertainty quantification↗

Low-cost Quantification of Fluid Flow Parameter Sensitivity using Reduced-order Modeling

Uncertainty quantification of computational fluid dynamics (CFD) simulations is a complicated procedure which still relies in many cases on engineering judgment and factors of safety. This is in part because the computational cost of measuring the simulation's sensitivity to all meaningful parameters (e.g., body surface roughness) and hyperparameters (e.g., subiteration convergence criterion) is intractable for even a single simulation. Reduced-order modeling dramatically lowers this computational cost of simulating fluid flows, but usually only where similar data is already available. In this work, fluid reduced-order models are utilized to quantify a flow's sensitivity to certain physical parameters for the purposes of improved uncertainty quantification. Characteristic observability and sensitivity are both explored. The resulting sensitivity quantifications enable more informed CFD frameworks and more rigorous uncertainty bounds on the resulting data.

uncertainty quantification↗

Computational Challenges of Viscous Incompressible Flows

Over the past thirty years, numerical methods and simulation tools for incompressible flows have been advanced as a subset of the computational fluid dynamics (CFD) discipline. Although incompressible flows are encountered in many areas of engineering, simulation of compressible flow has been the major driver for developing computational algorithms and tools. This is probably due to the rather stringent requirements for predicting aerodynamic performance characteristics of flight vehicles, while flow devices involving low-speed or incompressible flow could be reasonably well designed without resorting to accurate numerical simulations. As flow devices are required to be more sophisticated and highly efficient CFD took become increasingly important in fluid engineering for incompressible and low-speed flow. This paper reviews some of the successes made possible by advances in computational technologies during the same period, and discusses some of the current challenges faced in computing incompressible flows.

Kwak, Dochan↗

An improved three-dimensional aerodynamics model for helicopter airloads prediction

The importance of unsteady aerodynamic effects due to rotor blade motion is demonstrated for a helicopter in high-speed forward flight. These unsteady effects are modeled as surface boundary conditions to a three-dimensional, unsteady Computational Fluid Dynamics (CFD) code called the Full-Potential Rotor Code (FPR). These boundary conditions cause significant changes in the computed lift and pitching moment at the front and rear of the rotor disk. Airloads from the modified FPR code are then iteratively coupled with the helicopter comprehensive code, CAMRAD/JA. Computed airloads show good agreement with flight-test data when lift values from the FPR code are used in the coupled calculation. However, the computed airloads from CAMRAD/JA along also show good agreement with the experimental data. Thus for this case one cannot demonstrate a significant improvement in computed airloads with the hybrid coupled scheme. The addition of the pitching moment values from the FPR code into the CAMRAD/JA calculation slows down the overall iterative convergence and does not yield any improvement in the final results.

Strawn, Roger C.↗

Visual analysis of fluid dynamics at NASA's numerical aerodynamic simulation facility

A study aimed at describing and illustrating visualization tools used in Computational Fluid Dynamics (CFD) and indicating how these tools are likely to change by showing a projected resolution of the human computer interface is presented. The following are outlined using a graphically based test format: the revolution of human computer environments for CFD research; comparison of current environments; current environments with the ideal; predictions for the future CFD environments; what can be done to accelerate the improvements. The following comments are given: when acquiring visualization tools, potential rapid changes must be considered; environmental changes over the next ten years due to human computer interface cannot be fathomed; data flow packages such as AVS, apE, Explorer and Data Explorer are easy to learn and use for small problems, excellent for prototyping, but not so efficient for large problems; the approximation techniques used in visualization software must be appropriate for the data; it has become more cost effective to move jobs that fit on workstations and run only memory intensive jobs on the supercomputer; use of three dimensional skills will be maximized when the three dimensional environment is built in from the start.

Watson, Velvin R.↗

NTR plume modeling

Viewgraphs on nuclear thermal propulsion are presented. Topics covered include computational fluid dynamics (CFD) for plume analysis; molecular fluid dynamics; molecular CFD characteristics; direct-simulation Monte-Carlo (DSMC) method; integration of DSMC and Navier-Stokes computations; and density profiles.

Byers, D.↗

Computational flow predictions for hypersonic drag devices

The effectiveness of two types of hypersonic decelerators is examined: mechanically deployable flares and inflatable ballutes. Computational fluid dynamics (CFD) is used to predict the flowfield around a solid rocket motor (SRM) with a deployed decelerator. The computations are performed with an ideal gas solver using an effective specific heat ratio of 1.15. The results from the ideal gas solver are compared to computational results from a thermochemical nonequilibrium solver. The surface pressure coefficient, the drag, and the extend of the compression corner separation zone predicted by the ideal gas solver compare well with those predicted by the nonequilibrium solver. The ideal gas solver is computationally inexpensive and is shown to be well suited for preliminary design studies. The computed solutions are used to determine the size and shape of the decelerator that are required to achieve a drag coefficient of 5. Heat transfer rates to the SRM and the decelerators are predicted to estimate the amount of thermal protection required.

Tokarcik, Susan A.↗