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All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Comparison of CFD Predictions with Shuttle Global Flight Thermal Imagery and Discrete Surface Measurements

Surface temperature measurements from the STS-119 boundary-layer transition experiment on the space shuttle orbiter Discovery provide a rare opportunity to assess turbulent CFD models at hypersonic flight conditions. This flight data was acquired by on-board thermocouples and by infrared images taken off-board by the Hypersonic Thermodynamic Infrared Measurements (HYTHIRM) team, and is suitable for hypersonic CFD turbulence assessment between Mach 6 and 14. The primary assessment is for the Baldwin-Lomax and Cebeci-Smith algebraic turbulence models in the DPLR and LAURA CFD codes, respectively. A secondary assessment is made of the Shear-Stress Transport (SST) two-equation turbulence model in the DPLR code. Based upon surface temperature comparisons at eleven thermocouple locations, the algebraic-model turbulent CFD results average 4% lower than the measurements for Mach numbers less than 11. For Mach numbers greater than 11, the algebraic-model turbulent CFD results average 5% higher than the three available thermocouple measurements. Surface temperature predictions from the two SST cases were consistently 3 4% higher than the algebraic-model results. The thermocouple temperatures exhibit a change in trend with Mach number at about Mach 11; this trend is not reflected in the CFD results. Because the temperature trends from the turbulent CFD simulations and the flight data diverge above Mach 11, extrapolation of the turbulent CFD accuracy to higher Mach numbers is not recommended.

Wood, William A.↗
NASA NTRS2011

Assessment of CFD-based Response Surface Model for Ares I Supersonic Ascent Aerodynamics

The Ascent Force and Moment Aerodynamic (AFMA) Databases (DBs) for the Ares I Crew Launch Vehicle (CLV) were typically based on wind tunnel (WT) data, with increments provided by computational fluid dynamics (CFD) simulations for aspects of the vehicle that could not be tested in the WT tests. During the Design Analysis Cycle 3 analysis for the outer mold line (OML) geometry designated A106, a major tunnel mishap delayed the WT test for supersonic Mach numbers (M) greater than 1.6 in the Unitary Plan Wind Tunnel at NASA Langley Research Center, and the test delay pushed the final delivery of the A106 AFMA DB back by several months. The aero team developed an interim database based entirely on the already completed CFD simulations to mitigate the impact of the delay. This CFD-based database used a response surface methodology based on radial basis functions to predict the aerodynamic coefficients for M > 1.6 based on only the CFD data from both WT and flight Reynolds number conditions. The aero team used extensive knowledge of the previous AFMA DB for the A103 OML to guide the development of the CFD-based A106 AFMA DB. This report details the development of the CFD-based A106 Supersonic AFMA DB, constructs a prediction of the database uncertainty using data available at the time of development, and assesses the overall quality of the CFD-based DB both qualitatively and quantitatively. This assessment confirms that a reasonable aerodynamic database can be constructed for launch vehicles at supersonic conditions using only CFD data if sufficient knowledge of the physics and expected behavior is available. This report also demonstrates the applicability of non-parametric response surface modeling using radial basis functions for development of aerodynamic databases that exhibit both linear and non-linear behavior throughout a large data space.

Hanke, Jeremy L.↗
NASA NTRSDate not supplied

Free-Flight CFD Simulations and Dynamic StabilityAnalysis of the Orion Crew Module

Dynamic stability analysis of the Multi-Purpose Crew Vehicle (MPCV) is performed us-ing the US3D flow solver and a plugin library to solve rigid-body dynamics, Free-Flight CFD(FF-CFD). Previous efforts investigated the free-flight behavior of higher speed, open-backaeroshell shapes. Three primary experimental sources are used to evaluate the predictivecapability of the FF-CFD solver in the low supersonic range (Mach≈1). First, the ballisticrange results obtained at the HFFAF facility at NASA Ames is used to verify the six degree-of-freedom (6-DoF) dynamic capability of the FF-CFD solver. Next, FF-CFD simulationsare preformed using restricted motion and the resultant trajectories are post-processed toobtain pitch damping coefficient as a function of angle-of-attack. The comparison of thepitch damping results obtained with one degree-of-freedom (1-DoF) FF-CFD compare wellwith experimental fits derived from ballistic range data. Finally, the atmospheric flight ca-pability of FF-CFD is compared to data from the Ascent Abort-2 (AA-2) flight experiment.Two simulations were performed using forced and forced-free flight to investigate surfacepressure predictive capability and free-flight aerodynamic performance through a varyingatmosphere at low speed (Mach 0.6-0.2). Surface pressure predicted with FF-CFD agreeswell with experimental trends, with slight over-prediction near the end of the trajectory.The total angle-of-attack for the free-flight portion agrees well with experimental data.

FFCFD↗
NASA NTRSDate not supplied

Progress on Inverse Estimation Technique of Non-Linear Pitch Damping Coefficient Curves Using Free-Flight CFD Generated Trajectories

Characterization of entry vehicle pitch damping coefficient curves is crucial to ensure appropriate re-entry and overall mission success. The pitch damping coefficient (C_(m_q )+C_(m_α ̇ )) is used to encapsulate the oscillatory growth or decay of a body during a trajectory. The inverse estimation technique utilizes an existing Free-Flight CFD (FF-CFD) dataset and wraps a reconstruction algorithm in an optimizer. The reconstruction integrates the planar equations of motion derived by Schoenenberger, Queen [1] using Python’s scipy.integrate.solve_ivp. The optimizer’s objective function is the normalized 𝐿2 residual of the angle of attack peaks between the reconstructed trajectory and the original data produced with FF-CFD. Inclusion of the peak times in this residual calculation allows for simultaneous optimization of the pitch moment coefficient, C_(m_α ). This residual equation is shown below in Eq. 1. The optimizer scipy.optimize.minimize was used with the gradient-based Powell method for the analysis presented, however the differential evolution method was investigated as means of comparison, and was found to produce marginally lower residual values with prohibitively longer run times. Further, the pitch damping curve is found by fitting a cubic interpolation function to a set of (α, (C_(m_q )+C_(m_α ̇ ))) control points, where the α points are held constant and the (C_(m_q )+C_(m_α ̇ )) values are the optimized parameters. The pitch moment curve uses a linear interpolation between the minimum and maximum α in the dataset. FF-CFD generated trajectories using the Dragonfly capsule geometry with the Genesis ballistic range model parameters were simulated and used for this analysis. These FF-CFD trajectories simulate planar motion, as restricted by the reconstructing the equations of motion, of three different cases: 1-DoF (free-to-pitch), 2-DoF (free-to-pitch and heave), and 3-DoF (free-to-pitch, heave, and decelerate). Pitch damping coefficient curves generated using this inverse estimation curve technique with FF-CFD 1-DoF Dragonfly data are found in Fig. 1. Preliminary results reconstructing ballistic range shots using these FF-CFD derived predictions of the pitch damping curve (Fig. 1) are shown in Fig. 2. It should be noted that the ballistic range shot used a Genesis model whereas the FF-CFD data used a Dragonfly geometry, however these geometries are similar.

entry↗
NASA NTRSDate not supplied

CFD Predictions of Boiling Regime Transitions during Line Chilldown validated against a 1G LN2 Experiment

Introduction Before filling a propellant tank on the ground or in Space, the transfer line between the donor and receiver tanks must be cooled down preferably by sacrificing a minimum amount of the cryogenic fluid. The cryogenic line chill-down process involves a transition between different flow boiling regimes, namely, film boiling, transition film boiling, and nucleate boiling which are complex and may be quite gravity-dependent. Capturing these boiling phenomena and predicting the transition between them in a CFD framework is new and challenging both for 1g and microgravity applications. Materials & Methods The present work addresses this challenge by employing a two-phase Eulerian approach in the context of a homogeneous fluid mixture together with the Lee phase change model to capture the film boiling regime of the chill-down process using ANSYS Fluent®. The nucleate boiling regime is predicted by incorporating an in-house developed sub-grid model that accounts for bubble nucleation, bubble growth, bubble departure diameter, and their shedding frequency. The sub-grid model is encoded and implemented into Fluent via a user-defined function for the wall-fluid heat flux calculations. The mathematical formulation and numerical implementation of the CFD model are described in detail. The coupled CFD-Subgrid model is validated against published experimental data for liquid nitrogen chill-down of a heated stainless-steel pipe in 1g. Results Numerical simulation results show good agreements between the CFD predictions of the wall temperature evolution, rewetting temperature, and transition between film and nucleate boiling, with the experimental measurements published by Darr et al [2] for several different LN2 flowrates in the vertical pipe orientation. The CFD predictions for the wall temperature distribution indicate a rapid quenching of the wall at two upstream and downstream temperature sensing locations as compared to the experimental measurement. The only tuning parameter in the CFD model is the Lee mass transfer coefficient. The CFD Model predicts the Liedenfrost rewetting temperature in close agreement with the experiment. This marks a transition between stable and transitionary flow boiling regimes. The CFD-predicted boiling curve for the downstream sensor location is also compared against its experimental counterpart and indicates that the model is able to predict all the key temperature and heat flux parameters during the transitions from stable to transitionary film boiling to nucleate boiling in close agreement with the experiment. A sequence of predicted volume fraction, and temperature contours depicting these transitions will be presented.

Evaporation Condensation↗
NASA NTRS1996

Observations Regarding Use of Advanced CFD Analysis, Sensitivity Analysis, and Design Codes in MDO

Observations regarding the use of advanced computational fluid dynamics (CFD) analysis, sensitivity analysis (SA), and design codes in gradient-based multidisciplinary design optimization (MDO) reflect our perception of the interactions required of CFD and our experience in recent aerodynamic design optimization studies using CFD. Sample results from these latter studies are summarized for conventional optimization (analysis - SA codes) and simultaneous analysis and design optimization (design code) using both Euler and Navier-Stokes flow approximations. The amount of computational resources required for aerodynamic design using CFD via analysis - SA codes is greater than that required for design codes. Thus, an MDO formulation that utilizes the more efficient design codes where possible is desired. However, in the aerovehicle MDO problem, the various disciplines that are involved have different design points in the flight envelope; therefore, CFD analysis - SA codes are required at the aerodynamic 'off design' points. The suggested MDO formulation is a hybrid multilevel optimization procedure that consists of both multipoint CFD analysis - SA codes and multipoint CFD design codes that perform suboptimizations.

Newman, Perry A.↗
NASA NTRS2003

Using CFD as Rocket Injector Design Tool: Recent Progress at Marshall Space Flight Center

The choice of tools used for injector design is in a transitional phase between exclusive reliance on the empirically based correlations and extensive use of computational fluid dynamics (CFD). The Next Generation Launch Technology (NGLT) Program goals emphasizing lower costs and increased reliability have produced a need to enable CFD as an injector design tool in a shorter time frame. This is the primary objective of the Staged Combustor Injector Technology Task currently under way at Marshall Space Flight Center (MSFC). The documentation of this effort begins with a very brief status of current injector design tools. MSFC's vision for use of CFD as a tool for combustion devices design is stated and discussed with emphasis on the injector. The concept of the Simulation Readiness Level (SRL), comprised of solution fidelity, robustness and accuracy, is introduced and discussed. This quantitative measurement is used to establish the gap between the current state of demonstrated capability and that necessary for regular use in the design process. MSFC's view of the validation process is presented and issues associated with obtaining the necessary data are noted and discussed. Three current experimental efforts aimed at generating validation data are presented. The importance of uncertainty analysis to understand the data quality is also demonstrated. First, a brief status of current injector design tools is provided as context for the current effort. Next, the MSFC vision for using CFD as an injector design tool is stated. A generic CFD-based injector design methodology is also outlined and briefly discussed. Three areas where MSFC is using injector CFD analyses for program support will be discussed. These include the Integrated Powerhead Development (IPD) engine which uses hydrogen and oxygen propellants in a full flow staged combustion (FFSC) cycle and the TR-107 and the RS84 engine both of which use RP-1 and oxygen in an ORSC cycle. Finally, an attempt is made to objectively summarize what progress has been made at MSFC in enabling CFD as an injector design tool.

Tucker, Kevin↗
NASA NTRS2004

A Best Practices System to Enhance CFD Use in Stability and Control Applications

Successful use of CFD to provide aerodynamics for stability and control (S&C) applications will require that the traditional time and costs associated with CFD be reduced and that the errors and uncertainties currently associated with CFD be better understood. CFD will be required to work under a wide range of flow conditions and provide fast and reliable aerodynamics if it is to contribute to this next generation of S&C analyses. CFD solutions have errors and uncertainties due to poorly converged solutions, solution anomalies caused by grids, turbulence models, and parameter selection, and other manifold reasons. In addition to the above problems, there will be a requirement for communications between the CFD expert and the S&C expert and possibly experts from other related disciplines. The CFD expert may not understand the technical problems associated with S&C, and it is almost certain the converse is true.

Morrison, Joseph H.↗
NASA NTRS2011

CFD-CAA Coupled Calculations of a Tandem Cylinder Configuration to Assess Facility Installation Effects

This paper presents a numerical assessment of acoustic installation effects in the tandem cylinder (TC) experiments conducted in the NASA Langley Quiet Flow Facility (QFF), an open-jet, anechoic wind tunnel. Calculations that couple the Computational Fluid Dynamics (CFD) and Computational Aeroacoustics (CAA) of the TC configuration within the QFF are conducted using the CFD simulation results previously obtained at NASA LaRC. The coupled simulations enable the assessment of installation effects associated with several specific features in the QFF facility that may have impacted the measured acoustic signature during the experiment. The CFD-CAA coupling is based on CFD data along a suitably chosen surface, and employs a technique that was recently improved to account for installed configurations involving acoustic backscatter into the CFD domain. First, a CFD-CAA calculation is conducted for an isolated TC configuration to assess the coupling approach, as well as to generate a reference solution for subsequent assessments of QFF installation effects. Direct comparisons between the CFD-CAA calculations associated with the various installed configurations allow the assessment of the effects of each component (nozzle, collector, etc.) or feature (confined vs. free jet flow, etc.) characterizing the NASA LaRC QFF facility.

Redonnet, Stephane↗
NASA NTRS2016

Unstructured Grid Adaptation: Status, Potential Impacts, and Recommended Investments Toward CFD Vision 2030

Unstructured grid adaptation is a powerful tool to control discretization error for Computational Fluid Dynamics (CFD). It has enabled key increases in the accuracy, automation, and capacity of some fluid simulation applications. Slotnick et al. provides a number of case studies in the CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences to illustrate the current state of CFD capability and capacity. The authors forecast the potential impact of emerging High Performance Computing (HPC) environments forecast in the year 2030 and identify that mesh generation and adaptivity continue to be significant bottlenecks in the CFD work flow. These bottlenecks may persist because very little government investment has been targeted in these areas. To motivate investment, the impacts of improved grid adaptation technologies are identified. The CFD Vision 2030 Study roadmap and anticipated capabilities in complementary disciplines are quoted to provide context for the progress made in grid adaptation in the past fifteen years, current status, and a forecast for the next fifteen years with recommended investments. These investments are specific to mesh adaptation and impact other aspects of the CFD process. Finally, a strategy is identified to diffuse grid adaptation technology into production CFD work flows.

Park, Michael A.↗
NASA NTRSDate not supplied

Dynamic Stability Analysis Using Free-Flight CFD

Blunt body probes are the primary design for atmospheric entry. The blunted capsule shape, while desirable for the decreased forebody heating, typically experiences dynamic instability at low supersonic and transonic flight. At moderate to low supersonic conditions, the unsteady wake begins to adversely interact with the vehicle in free-flight resulting in attitude oscillations which can grow in time and result in tumbling. Understanding vehicle dynamics is thus important when considering vehicle entry design and guidance navigation and control (GN&C) considerations. Historically, dynamic stability has been carried out exclusively using experimental techniques. The wide range of experimental approaches provide reasonable coverage in Mach and dynamic pressure space for a given trajectory, however achieving flight similitude is often difficult or impossible. Advancements in Computational Fluid Dynamics (CFD) techniques allow for dynamic motion of the vehicle surface during the simulation with either forced/prescribed motion or free motion in response to fluid forces. Several examples of CFD software with the ability to simulate fluid dynamics and vehicle motion are available in literature. The Free-Flight CFD (FF-CFD) capability developed by NASA Ames within the US3D flow solver has shown extensive validation and verification (V&V) efforts from moderate to low supersonic flow across a range of vehicle architectures. The solver is able to simulate full rotational and translation motion resulting in full 6 degrees-of-freedom (DoF) motion. The validation and verification efforts the solver's ability to predict the motion of a ballistic range model as compared to experimental results. Similar to other computational capabilities in literature, FF-CFD relied on heritage data reduction methodologies and processes for reducing dynamic data into aerodynamic coefficients intended for use in design and trajectory codes. These heritage approaches, initially developed with the assumptions (and restrictions) of ground test facilities, resulted in the significant culling of the full 6-DoF dynamic data set to discrete values which are then fit using an aerodynamic model. Recent development of simulation and data reduction methodologies has resulted in an improved approach to FF-CFD simulations of vehicle dynamics which leverage the control of dynamic constraints within a simulation set-up. The presentation of this work will cover the constrained dynamic simulation approach for deriving dynamic coefficients for a Genesis capsule. The methodology will be outlined and a discussion of implications in motion restriction will be discussed. Finally, reconstructed vehicle trajectories using FF-CFD derived aerodynamic coefficients will be presented.

Joseph M Brock↗
NASA NTRS2012

Computational Fluid Dynamics (CFD) Analysis Of Optical Payload For Lasercomm Science (OPALS) sealed enclosure module

Computational Fluid Dynamics (CFD) using the commercial CFD package CFDesign has been performed at NASA Jet Propulsion Laboratory (JPL) California Institute of Technology (Caltech) in support of the Phaeton Early Career Hire Program's Optical Payload for Lasercomm Science (OPALS) mission. The OPALS project is one which involves an International Space Station payload that will be using forced convection cooling in a hermetically sealed enclosure at 1 atm of air to cool "off-the-shelf" vendor electronics. The CFD analysis was used to characterize the thermal and fluid flow environment within a complicated labyrinth of electronics boards, fans, instrumentation, harnessing, ductwork and heat exchanger fins. The paradigm of iteratively using CAD/CAE tools and CFD was followed in order to determine the optimum flow geometry and heat sink configuration to yield operational convective film coefficients and temperature survivability limits for the electronics payload. Results from this current CFD analysis and correlation of the CFD model against thermal test data will be presented. Lessons learned and coupled thermal / flow modeling strategies will be shared in this paper.

Computational Fluid Dynamics (CFD)↗
NASA NTRSDate not supplied

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↗
NASA NTRS1994

Merging Intelligent Systems Technologies with CFD Analysis Strategies: Prototype Development at NASA Ames

A collaborative team of researchers from fields of Computational Fluid Dynamics (CFD), fluid physics, computer architectures, and computer science and knowledge engineering have begun work on a prototype system that addresses several of industry's concerns in using NASA-developed CFD codes as part of the design cycle. A major problem exists in the application of CFD technologies within the aeronautics design cycle due primarily to misunderstandings in the ranges of applicability of the various solver codes or turbulence models. Features that arise during the CFD solution process need to be discriminated and recognized as actual flow features with physical support in the geometry and flow conditions of the problem being solved, or as numerical or non-physical errors arising from mis-application of solver code and its parameters, gridding strategies, or discretization. interpolations. The fundamental concept is to develop an intelligent computational system that can accept the engineer's definition of the problem and construct an optimal CFD solution. To do this requires capturing both the knowledge of how to apply the various CFD tools and how to adapt the application of those tools to flow structures as they evolve during the flow simulation. Embedded within this adaptive system approach is the additional desire to automatically identify and quantify the quality of resolution of the pertinent flow structures, be they genuine or error-induced, and then to adjust the solution strategy accordingly. This paper discusses the status of that prototyping effort.

Thompson, David E.↗
NASA NTRS2004

Study of CFD Variation on Transport Configurations from the Second Drag-Prediction Workshop

This paper describes and analyzes a series of nearly 90 CFD test cases performed as a contribution to the second Drag Prediction Workshop, held in association with the AIAA in June 2003. Two configurations are included: DLR-F6 wing-body and wing-body-nacelle-pylon. The ability of CFD to predict the drag, lift, and pitching moment from experiment-including the "delta" arising from the addition of the nacelle and pylon-is assessed. In general, at a fixed angle of attack CFD overpredicts lift, but predicts the delta C (sub L) reasonably well. At low lift levels (C (sub L) less than 0.3)), delta C (sub D) is 20-30 drag counts (30-45%) high. At the target lift coefficient of C(sub L) = 0.5, delta C (sub D) is overpredicted by between 11-16 counts. However, the primary contribution of this paper is mot so much the assessment of CFD against experiment, but rather a detailed assessment and analysis of CFD variation. The series of test cases are designed to determine the sensitivity/variability of CFD to a variety of factors, including grid, turbulence model, transition code, and viscous model. Using medium-level grids (6-11 million points) at the target lift coefficient, the maximum variation in drag due to different grids is 5-11 drag counts, due to code is 5-10 counts, due to turbulence model is 7-15 counts, due to transition is 10-11 counts, and due to viscous model is 4-5 counts. Other specific variations are described in the paper.

Christopher L Rumsey↗
NASA NTRS2004

Summary of the 2004 CFD Validation Workshop on Synthetic Jets and Turbulent Separation Control

A CFD validation workshop for synthetic jets and turbulent separation control (CFDVAL2004) was held in Williamsburg, Virginia in March 2004. Three cases were investigated: synthetic jet into quiescent air, synthetic jet into a turbulent boundary layer crossflow, and flow over a hump model with no-flow-control, steady suction, and oscillatory control. This paper is a summary of the CFD results from the workshop. Although some detailed results are shown, mostly a broad viewpoint is taken, and the CFD state-of-the-art for predicting these types of flows is evaluated from a general point of view. Overall, for synthetic jets, CFD can only qualitatively predict the flow physics, but there is some uncertainty regarding how to best model the unsteady boundary conditions from the experiment consistently. As a result. there is wide variation among CFD results. For the hump flow, CFD as a whole is capable of predicting many of the particulars of this flow provided that tunnel blockage is accounted for, but the length of the separated region compared to experimental results is consistently overpredicted.

Rumsey, C. L.↗
NASA NTRS2005

Using CFD as a Rocket Injector Design Tool: Recent Progress at Marshall Space Flight Center

New programs are forcing American propulsion system designers into unfamiliar territory. For instance, industry s answer to the cost and reliability goals set out by the Next Generation Launch Technology Program are engine concepts based on the Oxygen- Rich Staged Combustion Cycle. Historical injector design tools are not well suited for this new task. The empirical correlations do not apply directly to the injector concepts associated with the ORSC cycle. These legacy tools focus primarily on performance with environment evaluation a secondary objective. Additionally, the environmental capability of these tools is usually one-dimensional while the actual environments are at least two- and often three-dimensional. CFD has the potential to calculate performance and multi-dimensional environments but its use in the injector design process has been retarded by long solution turnaround times and insufficient demonstrated accuracy. This paper has documented the parallel paths of program support and technology development currently employed at Marshall Space Flight Center in an effort to move CFD to the forefront of injector design. MSFC has established a long-term goal for use of CFD for combustion devices design. The work on injector design is the heart of that vision and the Combustion Devices CFD Simulation Capability Roadmap that focuses the vision. The SRL concept, combining solution fidelity, robustness and accuracy, has been established as a quantitative gauge of current and desired capability. Three examples of current injector analysis for program support have been presented and discussed. These examples are used to establish the current capability at MSFC for these problems. Shortcomings identified from this experience are being used as inputs to the Roadmap process. The SRL evaluation identified lack of demonstrated solution accuracy as a major issue. Accordingly, the MSFC view of code validation and current MSFC-funded validation efforts were discussed in some detail. The objectives of each effort were noted. Issues relative to code validation for injector design were discussed in some detail. The requirement for CFD support during the design of the experiment was noted and discussed in terms of instrumentation placement and experimental rig uncertainty. In conclusion, MSFC has made significant progress in the last two years in advancing CFD toward the goal of application to injector design. A parallel effort focused on program support and technology development via the SCIT Task have enabled the progress.

Tucker, Kevin↗
NASA NTRS2006

Summary of the 2004 CFD Validation Workshop on Synthetic Jets and Turbulent Separation Control

A computational fluid dynamics (CFD) validation workshop for synthetic jets and turbulent separation control (CFDVAL2004) was held in Williamsburg, Virginia in March 2004. Three cases were investigated: synthetic jet into quiescent air, synthetic jet into a turbulent boundary layer crossflow, and flow over a hump model with no-flow-control, steady suction, and oscillatory control. This paper is a summary of the CFD results from the workshop. Although some detailed results are shown, mostly a broad viewpoint is taken, and the CFD state-of-the-art for predicting these types of flows is evaluated from a general point of view. Overall, for synthetic jets, CFD can only qualitatively predict the flow physics, but there is some uncertainty regarding how to best model the unsteady boundary conditions from the experiment consistently. As a result, there is wide variation among CFD results. For the hump flow, CFD as a whole is capable of predicting many of the particulars of this flow provided that tunnel blockage is accounted for, but the length of the separated region compared to experimental results is consistently overpredicted.

Rumsey, C. L.↗