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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Dynamic CFD simulations of the SIAD ballistic test model were performed using US3D flow solver. Motivation for performing these simulations is for the purpose of validation and verification of the US3D flow solver as a viable computational tool for predicting dynamic coefficients.
The development of optical non-intrusive measurement techniques that can make global surface measurements in aero flow fields with increased temporal and spatial resolution is of major interest to the aeronautical research community. The ability to globally measure quantities such as velocity, temperature, density and pressure can provide better insight into the complex flow characteristics associated with the aero vehicle and aero propulsion concepts being investigated by NASA. In addition, these measurements are needed to validate Computational Fluid Dynamic (CFD) codes that are being developed to model aero phenomena and predict system performance. This presentation will give an overview of the advanced optical techniques that are being developed at the NASA Glenn Research Center (GRC) for the measurement of flow field and surface parameters in the GRC aeronautical test facilities.
In preparation for comparisons with data obtained from the recently concluded experiments in the National Transonic Facility at the NASA Langley Research Center on the new common research model with natural laminar flow (CRM-NLF), an assessment of the current transition modeling capability in the NASA OVERFLOW 2.2o code has been carried out. A combination of the available experimental data and linear stability analysis is used to evaluate the accuracy and robustness of these models for selected swept-wing type configurations, with significant crossflow. An additional goal for this work involves providing a comparative assessment of the relevant transition models in the context of a single flow solver and identifying model limitations as well as the potential for future improvements that would help strengthen the physical basis of such transition models. Included in this investigation is an assessment of the sensitivities of the underlying transition models to grid resolution (wall-normal, as well as streamwise and spanwise) and the values of extra input parameters such as the level of surface roughness and freestream turbulence variables. The flow configurations targeted in this assessment include the NASA NLF(2)-0415 swept-wing configuration, the sickle-shaped wing introduced by the Technical University of Braunschweig, and the wing-body configuration of the CRM model from the fourth and fifth AIAA CFD Drag Prediction Workshops.
CFD methods are employing semi-empirical models used in analysis of hypersonic airbreathing engine flow paths. RANS (or Favre averaged) codes have models for turbulent stresses, mass and energy transport; turbulence chemistry interactions. LES methods have models for subgrid scale turbulence. Models depend upon experimental data for validation. Information on mean flow and statistics of the turbulent fluctuation in flow properties is useful. Data requirements: simple well defined supersonic combustion flows with well-known boundary conditions, time and spatially resolved, good instrument precision, and converged statistics. Approach: dual-pump CARS and planar laser-induced fluorescence imaging of OH radical (PLIF).
A hypersonic particle phase solver based on a continuum model is implemented in the NASA HyperSolve CFD code and used to predict particle phase conditions in a dusty Mars entry scenario. Black-body radiative emission from high temperature dust particles is predicted for a Mars relevant entry problem, and the emission integrated to an entry vehicle using a ray tracing approach to estimate surface heat flux. The surface heating due to this mechanism is found to be small relative to convective and radiation from the gas phase emission. Additionally, the effect of atmospheric haze particulates vaporizing in the Titan atmosphere is studied. The increase in carbon availability due to the composition of the haze particles is found to increase the gas radiative heating to the vehicle by up to 3% on the forebody of a representative Titan entry vehicle with approximately 0.15% haze in the freestream by mass.
As part of a larger effort to demonstrate a simulation-based capability for the evaluation and optimization of helical coil steam generators, the performance of a helical coil steam generator tube is being considered using a Eulerian two-fluid multiphase flow capability implemented within the commercial computational fluid dynamics (CFD) code STAR-CCM+. The objective of these evaluations is to characterize boiling and the resultant two-phase flow structures within the helical coil heat exchanger tube so that structural analyses can more accurately account for vibration sources and damping. These studies have shown that CFD predictions using the two-fluid model are consistent with published measurements of pressure drop and heat transfer characteristics. The sensitivity of model predictions to both flow conditions and modeling parameters associated with bubble dynamics closure models has been investigated.
This paper describes several approaches to back pressuring an inlet/isolator model at Mach 4.0 and the differences in unstart predictions using common RANS simulation methods. The CFD codes OVERFLOW and CREATE-AV Kestrel were used for this work. Verification and validation was conducted on a relevant shock-wave-boundary-layer-interaction case with both solvers. Using aftmounted back pressure flaps did not produce a stable pre-combustion shock train. An unstart comparison between CFD codes OVERFLOW and CREATE-AV Kestrel as well as common 2-equation turbulence models was conducted with numerical back pressure. Unstart predictions using a novel louver back pressure mechanism was done with OVERFLOW. There is notable differences in shock train travel and predicted unstart limit due to turbulence modeling, temporal resolution, and use of the 2D simplification.
The homogeneous relaxation model (HRM) is one of the most widely used models to describe the liquid–gas phase transition in multiphase flows due to the occurrence of cavitation. However, in its original formulation, the HRM does not account for the presence of ambient gas species, which generally limits its applicability to the injector's internal flow where ambient gases are negligible. In this work, a mixing-driven vaporization (MDV) model was developed to extend the capability of the HRM in handling the mixing effect in the regions external to the nozzle, where vapor–liquid equilibrium for multi-species mixtures of fuel and ambient gas is considered. Herein, to assess the model performance, simulations of the Engine Combustion Network's Spray G injector were performed with the HRM and the MDV model under both flash-boiling and evaporating conditions. It was found that the MDV model led to a better match against x-ray measurements of fuel density in the near-nozzle region. In contrast to the HRM, the MDV model was able to reproduce the vaporization process in the mixing zone at the edge of the fuel jet, which aligns with the expected physics. This resulted in substantial differences in the prediction of other flow characteristics such as mixture temperature and pressure. Furthermore, this work demonstrates that evaporation timescales have a considerable effect on the MDV model's predictions, as shown by a parametric study in which a time factor was introduced to mimic the effect of different timescales due to different phase change mechanisms.
The fluid dynamics of a high-speed jet are governed by the instability waves that form in the free-shear boundary layer of the jet. Jet excitation manipulates the growth and saturation of particular instability waves to control the unsteady flow structures that characterize the energy cascade in the jet.The results may include jet noise mitigation or a reduction in the infrared signature of the jet. The Localized Arc Filament Plasma Actuators (LAFPA) have demonstrated the ability to excite a high-speed jets in laboratory experiments. Extending and optimizing this excitation technology, however, is a complex process that will require many tests and trials. Computational simulations can play an important role in understanding and optimizing this actuator technology for real-world applications. Previous research has focused on developing a suitable actuator model and coupling it with the appropriate computational fluid dynamics (CFD) methods using two-dimensional spatial flow approximations. This work is now extended to three-dimensions (3-D) in space. The actuator model is adapted to a series of discrete actuators and a 3-D LES simulation of an excited jet is run. The results are used to study the fluid dynamics near the actuator and in the jet plume.
The process of computational fluid dynamics (CFD) validation is described from two perspectives, numerical error validation and physical model validation. Errors associated with time and space discretization, grid refinement, numerical dissipation, and level of solution convergence, are all possible sources of numerical error. The second aspect of CFD code validation is associated with the governing equations and the physical models, e.g., chemistry and turbulence models. This type of validation requires comparisons with carefully conducted experiments and is the primary aspect of the validation process discussed in this paper. Examples of validation are shown for selected Reynolds-averaged Navier-Stokes codes for conditions from transonic through hypersonic. Since code applications are becoming more complex, it no longer suffices to use data from surface or integral quantities alone to provide the required validation. Flow field surveys and experimental boundary condition measurements are emerging as critical data that must be obtained for CFD code validation. Progress in the overall level of validation is shown to be improving. However, future challenges remain, some of which are enumerated.
Separation of light weight molecules, such as nitrogen, argon, and oxygen, from heavier compounds can have significant impacts on energy capture, environmental monitoring, or isotopic applications. Large-scale gas separation techniques, like gas centrifugation and membrane mitigation, can be problematic as they impart tremendous energy and induce high mechanical stress onto the instrumentation. Microsieves, also known as micronozzles or microfunnels, are developed to create physical barriers to separate specific isotopes and gases. Separation is achieved using a converging and diverging micronozzle to impose supersonic gas flow around a curved wall, and it has been used for the separation of heavy actinide isotopes in low weight gas as well as separation of low weight gas compositions of nitrogen and argon back in 1900s. However, systematic reviews of this unique technology are lacking. The application of the Laval style nozzle, which has a converging/diverging entrance fundamental to the micronozzle, is included in this review due to its importance in industrial applications in uranium (U) isotope refinement. Using advanced computational fluid dynamic (CFD) simulations, the extent of gas separation can be modelled. Herein, we first examine the literature and survey recent advances on fabrication techniques for creating curved micronozzles, methods and separation principles used to design devices. Furthermore, we then follow with highlights of CFD simulations applied to evaluate the separation effects using microsieves. Finally, identification of the gap and recommendation for future development and applications are suggested for using intrinsic molecular features and fluidic dynamics in formulating separation strategies.
An approximately 6-percent scale model of the NASA Second-Generation Large Civil Tiltrotor (LCTR2) Aircraft was tested in the U.S. Army 7- by 10-Foot Wind Tunnel at NASA Ames Research Center January 4 to April 19, 2012, and September 18 to November 1, 2013. The full model was tested, along with modified versions in order to determine the effects of the wing tip extensions and nacelles; the wing was also tested separately in the various configurations. In both cases, the wing and nacelles used were adopted from the U.S. Army High Efficiency Tilt Rotor (HETR) aircraft, in order to limit the cost of the experiment. The full airframe was tested in high-speed cruise and low-speed hover flight conditions, while the wing was tested only in cruise conditions, with Reynolds numbers ranging from 0 to 1.4 million. In all cases, the external scale system of the wind tunnel was used to collect data. Both models were mounted to the scale using two support struts attached underneath the wing; the full airframe model also used a third strut attached at the tail. The collected data provides insight into the performance of the preliminary design of the LCTR2 and will be used for computational fluid dynamics (CFD) validation and the development of flight dynamics simulation models.
The Bigelow Expandable Activity Module (BEAM) was a collaboration between NASA and Bigelow Aerospace to develop an expandable habitat technology that could be used for future space exploration missions such as the Artemis program. On April 26, 2016, the BEAM was launched and berthed to the International Space Station (ISS) on the aft port of Node 3. After the originally planned two-year mission life, BEAM was approved for use as a stowage module for a 109-cargotransfer bag equivalent (CTBE) to alleviate stowage limitations onboard the ISS. The present work builds on the previous 2017 model validation to flight data that demonstrated that BEAM could generally accommodate cargo stowage without adversely affecting BEAM thermal control, primarily for condensation management. Once the stowage was configured in early 2019, model validation efforts resumed. The thermal model revisions included the CTBE stowage and updated CFD-derived heat transfer coefficients for various intra-module ventilation (IMV) flow rates. The coefficients were provided by the Crew and Thermal Systems Division (EC) at NASA JSC and Jacobs Technology. The model is now revalidated and able to predict minimum temperatures with good agreement to flight temperatures (within 1 °C) for both historic and recurring minimum values. Additionally, the model is partially validated for reduced flow rates. With this model, the team was able to provide new flight rule recommendations for condensation and IMV operations management.
The distance from a grid point to the closest wall surface, wall distance, is a funda- mental quantity in turbulence modeling. Efficiency of wall-distance calculations has become more critical as the size of computational grids has significantly increased in recent years. This paper reports on an initial implementation of a new search-based wall-distance method that is suitable for general unstructured computational fluid dynamics (CFD) grids and tailored for requirements specific for turbulence modeling. The method represents a two-step approach to calculate the wall distance. In the first step, the wall distance is approximated for each grid point as the minimum distance from this point to a vertex of a triangular face at the wall. The point-to-vertex distance calculation is relatively inexpensive but may lead to a significant error in the wall-distance ap- proximation, especially for grid points near the wall. In the second step, for grid points located within a predefined distance ( threshold ) from the wall, the wall distance is computed as the minimum distance to wall faces. As a result, the wall distance is exact for all grid points within the threshold. This two-step approach reduces the computational cost yet achieves high and controllable accuracy in the evaluation of the wall distance. Algorithmic enhancements are presented to improve efficiency of wall-distance computations. Comprehensive assessment of the new method is reported for large-scale unstructured CFD grids generated for the Fifth AIAA CFD High-Lift Prediction Workshop. The performance of the new wall-distance method compares favorably with performance of two established methods implemented in high-performance CFD codes.
Combining linear stability calculations with computational fluid dynamics (CFD) simulations has great potential for the automated modeling of high-speed flows, especially when adequate information about the configuration and the disturbance environment is available. However, a significant impediment to the applicability of this technique is the lack of an efficient method to calculate the crucial amplification ratio corresponding to the onset of transition in hypersonic flows. This ratio, also known as the "transition N-factor," is dependent upon the freestream disturbance environment as well as the surface properties of the test article. In response to the need for an engineering solution to predict the transition N-factor within conventional hypersonic wind tunnels, this paper presents a data-driven correlation that expands the existing correlations from straight circular cones with a narrow range of half angles to a broader array of axisymmetric configurations. Furthermore, when tested against a chosen dataset that was not used in its calibration, the suggested correlation shows good predictive accuracy with an RMS error of only 6.9%. Although similar accuracy may also be achieved via existing correlations based on similar datasets, predictions based on the proposed correlation have the advantage of not requiring an extensive amount of configuration-specific data. Practical applications often have access to the input parameters needed for this correlation, such as the freestream disturbance intensity, Mach number, and body-based slenderness Reynolds number. Additionally, this correlation outperforms the traditional assumption of a constant N-factor, particularly for configurations with blunted nose geometries. The development of this correlation is grounded in an extensive dataset encompassing conical models with body half-angles varying between 5 degrees and 16 degrees, Mach numbers ranging from 5 to 14, and nosetip-based Reynolds numbers approaching the transition reversal limit for blunt-nosed cones.
A combined Monte Carlo-computational fluid dynamic (CFD) algorithm was developed recently at Lewis Research Center (LeRC) for turbulent reacting flows. In this algorithm, conventional CFD schemes are employed to obtain the velocity field and other velocity related turbulent quantities, and a Monte Carlo scheme is used to solve the evolution equation for the probability density function (pdf) of species mass fraction and temperature. In combustion computations, the predictions of chemical reaction rates (the source terms in the species conservation equation) are poor if conventional turbulence modles are used. The main difficulty lies in the fact that the reaction rate is highly nonlinear, and the use of averaged temperature produces excessively large errors. Moment closure models for the source terms have attained only limited success. The probability density function (pdf) method seems to be the only alternative at the present time that uses local instantaneous values of the temperature, density, etc., in predicting chemical reaction rates, and thus may be the only viable approach for more accurate turbulent combustion calculations. Assumed pdf's are useful in simple problems; however, for more general combustion problems, the solution of an evolution equation for the pdf is necessary.
1 A Breakthrough in Rotorcraft Prediction Accuracy Using Detached Eddy Simulation; 2 Adjoint-Based Design for Complex Aerospace Configurations; 3 Simulating Hypersonic Turbulent Combustion for Future Aircraft; 4 From a Roar to a Whisper: Making Modern Aircraft Quieter; 5 Modeling of Extended Formation Flight on High-Performance Computers; 6 Supersonic Retropropulsion for Mars Entry; 7 Validating Water Spray Simulation Models for the SLS Launch Environment; 8 Simulating Moving Valves for Space Launch System Liquid Engines; 9 Innovative Simulations for Modeling the SLS Solid Rocket Booster Ignition; 10 Solid Rocket Booster Ignition Overpressure Simulations for the Space Launch System; 11 CFD Simulations to Support the Next Generation of Launch Pads; 12 Modeling and Simulation Support for NASA's Next-Generation Space Launch System; 13 Simulating Planetary Entry Environments for Space Exploration Vehicles; 14 NASA Center for Climate Simulation Highlights; 15 Ultrascale Climate Data Visualization and Analysis; 16 NASA Climate Simulations and Observations for the IPCC and Beyond; 17 Next-Generation Climate Data Services: MERRA Analytics; 18 Recent Advances in High-Resolution Global Atmospheric Modeling; 19 Causes and Consequences of Turbulence in the Earths Protective Shield; 20 NASA Earth Exchange (NEX): A Collaborative Supercomputing Platform; 21 Powering Deep Space Missions: Thermoelectric Properties of Complex Materials; 22 Meeting NASA's High-End Computing Goals Through Innovation; 23 Continuous Enhancements to the Pleiades Supercomputer for Maximum Uptime; 24 Live Demonstrations of 100-Gbps File Transfers Across LANs and WANs; 25 Untangling the Computing Landscape for Climate Simulations; 26 Simulating Galaxies and the Universe; 27 The Mysterious Origin of Stellar Masses; 28 Hot-Plasma Geysers on the Sun; 29 Turbulent Life of Kepler Stars; 30 Modeling Weather on the Sun; 31 Weather on Mars: The Meteorology of Gale Crater; 32 Enhancing Performance of NASAs High-End Computing Applications; 33 Designing Curiosity's Perfect Landing on Mars; 34 The Search Continues: Kepler's Quest for Habitable Earth-Sized Planets.
Combining linear stability calculations with computational fluid dynamics (CFD) simulations has great potential for the automated modeling of high-speed flows, especially when adequate information about the configuration and the disturbance environment is available. However, a significant impediment to the applicability of this technique is the lack of an efficient method to calculate the crucial amplification ratio corresponding to the onset of transition in hypersonic flows. This ratio, also known as the "transition N-factor," is dependent upon the freestream disturbance environment as well as the surface properties of the test article. In response to the need for an engineering solution to predict the transition N-factor within conventional hypersonic wind tunnels, this paper presents a data-driven correlation that expands the existing correlations from straight circular cones with a narrow range of half angles to a broader array of axisymmetric configurations. Furthermore, when tested against a chosen dataset that was not used in its calibration, the suggested correlation shows good predictive accuracy with an RMS error of only 6.9%. Although similar accuracy may also be achieved via existing correlations based on similar datasets, predictions based on the proposed correlation have the advantage of not requiring an extensive amount of configuration-specific data. Practical applications often have access to the input parameters needed for this correlation, such as the freestream disturbance intensity, Mach number, and body-based slenderness Reynolds number. Additionally, this correlation outperforms the traditional assumption of a constant N-factor, particularly for configurations with blunted nose geometries. The development of this correlation is grounded in an extensive dataset encompassing conical models with body half-angles varying between 5 degrees and 16 degrees, Mach numbers ranging from 5 to 14, and nosetip-based Reynolds numbers approaching the transition reversal limit for blunt-nosed cones.