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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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At least 361 records · Page 20

Sketch-to-Solution: A Case Study in RCS Aerodynamic Interaction

Thanks to recent advances in the fields of anisotropic grid adaptation, error estimation, and geometry modeling, a sketch-to-solution work flow is now possible for viscous computational fluid dynamic (CFD) simulations. With this workflow, a CFD application engineer provides geometry, boundary conditions, and flow parameters; and the sketch-to-solution process yields a CFD simulation through automatic, error-based, grid adaptation. To explore the benefits of this nascent capability, a conventional manual grid generation work flow is compared to this new automatic grid generation work flow for a given engineering question: What are the aerodynamic interactions caused by the reaction control system (RCS) on an entry vehicle? This case study indicates that while the automatic grid generation sketch-to- solution process is not yet mature, it is preferred over a manual grid generation work flow because it greatly reduces manual labor, eliminates many opportunities for human error, and provides grid sensitivity information.

Bill Kleb↗

Nitric Oxide Laser-Induced Fluorescence Rotational Thermometry in a Hypersonic Non-Equilibrium Flow

Spatially-resolved nitric oxide (NO) planar laser-induced fluorescence (PLIF) rotational thermometry was performed on a Mach 5 non-equilibrium flow around a blunt-body specimen in the Hypersonic Materials Environmental Test System (HyMETS) arc-heat wind tunnel at the NASA Langley Research Center. Transitions within the (0,0) band in the A(exp⁡ 2)∑(sup⁡ +) - X(exp⁡ 2)Π system of NO were excited with a 10 Hz pulsed ultra-violet laser. A multi-line fitting algorithm was applied to the PLIF spectra and transitions were filtered based on an iterative method that maximizes thermometry accuracy. NO PLIF thermometry results are compared to non-equilibrium computational fluid dynamics (CFD) simulations reported in the literature. Differences between the experiment and CFD are quantified for the free-stream, post-shock, shear-layer, and expansion-fan regions of the flow. Potential sources of error, applicable to both the CFD and experiment, are discussed.

Connor C McDougall↗

A Simple Model for Rotating Detonation Rocket Engine Sizing and Performance Estimates

A Rotating Detonation Rocket Engine (RDRE) model is described which characterizes the device as an essentially infinite number of circumferentially arranged, sequentially firing pulse detonation engine (PDE) tubes. The PDE tubes are in turn treated as lumped-parameter chambers, each of which executes a dynamic (i.e. time dependent) Atkinson cycle with an allowance for a finite Mach number during the refill portion of the cycle. The formulation results in several free parameters which are used to essentially tune the model such that it closely matches higher fidelity computational fluid dynamic RDRE simulations in terms of performance, flow rates, etc. The simplicity of the model allows for straightforward combination with component models (e.g. turbopumps, cooling jackets, etc.) as well as implementation within larger vehicle simulations. Such capability allows for realistic mission analyses and benefits studies which will help to determine the best application for the RDRE concept.

detonation↗

A Simple Model for Rotating Detonation Rocket Engine Sizing and Performance Estimates

A Rotating Detonation Rocket Engine (RDRE) model is described which characterizes the device as an essentially infinite number of circumferentially arranged, sequentially firing pulse detonation engine (PDE) tubes. The PDE tubes are in turn treated as lumped-parameter chambers, each of which executes a dynamic (i.e. time dependent) Atkinson cycle with an allowance for a finite Mach number during the refill portion of the cycle. The formulation results in several free parameters which are used to essentially tune the model such that it closely matches higher fidelity computational fluid dynamic RDRE simulations in terms of performance, flow rates, etc. The simplicity of the model allows for straightforward combination with component models (e.g. turbopumps, cooling jackets, etc.) as well as implementation within larger vehicle simulations. Such capability allows for realistic mission analyses and benefits studies which will help to determine the best application for the RDRE concept.

detonation↗

Multiscale Mesh Adaptation for Transonic Aeroelastic Flutter Problems

This work applies multiscale mesh adaptation with refine to reduce spatial discretization error of aeroelastic computational fluid dynamics (CFD) simulations. Benchmark flutter models, such as the pitch and plunge NACA64A-010 airfoil and the benchmark supercritical wing, are studied with both a linearized frequency-domain solver and time-marching CFD coupled to a modal structural solver in FUN3D. The undeformed NASA Common Research Model (CRM), an aeroelastic jig shape variant of the CRM, is also studied with the linearized frequency-domain approach. For these cases, the adaptation process converges to comparable flutter predictions to hand-generated meshes but with smaller node counts. However the additional disciplines of the linearized frequency-domain analysis, the mesh deformation, and the unsteady finite-volume solver create robustness challenges that need to be addressed before it can be applied as a fully automated process for complex transonic aeroelastic problems. In particular, negative volumes are observed to be an issue for FUN3D’s linear elasticity mesh deformation solver when moving the adapted meshes.

Aeroelasticity↗

Cross-Validation of Computational and Experimental Distributed Surface Pressures on the Space Launch System

This paper presents a new workflow for comparing experimental pressure-sensitive paint (PSP) data to computational fluid dynamic (CFD) simulations by way of mapping data from corresponding grids utilizing interpolation methods. In addition to generating quantitative and qualitative point-to-point comparisons between PSP and CFD data, this workflow extracts sectional loading data from both grids and generates lineload comparison charts for corresponding PSP and CFD runs. Experimental PSP data presented in this paper were taken from a 2016 NASA Ames Research Center Unitary Plan Wind Tunnel 11- by 11-Foot Transonic WindTunnel Facility test of the NASA Space Launch System. CFD simulation data for comparison purposes were generated using the FUN3D code. Overall, interpolation onto PSP grids versus CFD grids yields comparable surface pressure fields. However, lineload comparisons are easier to make on the CFD grid-mapped data due to the grid topology and the current capabilities of the lineload analysis tools at NASA Langley Research Center. This workflow is written using contemporary software (Python, Tecplot, PyTecplot), is compatible with existing tools at NASA Langley, and is developed to be adaptable depending on the situation.

SLS↗

Computational Assessment of Inlet Backflow Effects on Rotating Detonation Engine Performance and Operability

The performance impact of flow reversal at the inlet of an airbreathing rotating detonation engine (RDE) is investigated using 2 and 3-dimensional computational fluid dynamic (CFD) simulations. Flow reversal, or backflow, occurs in RDE inlets in the high-pressure region directly behind the rotating detonation front. This is also where most of the engine thrust or pressure gain is produced. The amount of backflow relative to throughflow depends on the inlet design. For the present work, a simple annular ‘slit’ design is used. The simulations are idealized in several ways, including that fuel and air are premixed, but prevented from reacting when within the inlet region. The results indicate that even with idealizations, the impact of inlet backflow on pressure gain can be substantial. The simulations also reveal an intriguing instability that develops in certain configurations. The mass flow rate into the RDE begins to oscillate at a regular frequency that is substantially less than the detonation rotational frequency. This is accompanied by oscillations in the detonation height. The oscillation amplitude grows over time until the detonation ultimately fails. Both the performance and instability results emphasize the need for carefully designed RDE inlets that provide low loss when flow is in the forward direction, but high resistance when the flow is reversed. Development of such high-diodicity inlets is critical to achieving pressure gain in airbreathing RDE’s.

Detonation↗

Wall-Modeled Large-Eddy Simulations for High-Lift Configurations using FUN3D

Wall-modeled large-eddy simulation (WMLES) capability has recently been implemented into FUN3D, an unstructured, node-centered, finite-volume solver developed at the NASA Langley Research Center. In this paper, WMLES is assessed for two configurations that are representative for high-lift applications. The first configuration is a nominal two-dimensional multielement airfoil that has been extensively studied in the literature. WMLES solutions are computed for four angles of attack and compared with previously reported solutions. Good agreement of integrated forces, surface pressures, and boundary-layer velocity profiles is shown with available experimental data especially at lower angles of attack. WMLES solutions are also computed for the NASA High-Lift Common Research Model over a large range of angles of attack. Forces, pitching moments, and pressure distributions are favorably compared with the experimental data up to the maximum lift, including the angle of attack where the maximum lift is obtained experimentally. Eddy visualization techniques of q-criterion and density-gradient magnitude illustrate the resolved content.

High-Lift flows↗

Computational Assessment of Inlet Backflow Effects on Rotating Detonation Engine Performance and Operability

The performance impact of flow reversal at the inlet of an airbreathing rotating detonation engine (RDE) is investigated using 2 and 3-dimensional computational fluid dynamic (CFD) simulations. Flow reversal, or backflow, occurs in RDE inlets in the high-pressure region directly behind the rotating detonation front. This is also where most of the engine thrust or pressure gain is produced. The amount of backflow relative to throughflow depends on the inlet design. For the present work, a simple annular ‘slit’ design is used. The simulations are idealized in several ways, including that fuel and air are premixed, but prevented from reacting when within the inlet region. The results indicate that even with idealizations, the impact of inlet backflow on pressure gain can be substantial. The simulations also reveal an intriguing instability that develops in certain configurations. The mass flow rate into the RDE begins to oscillate at a regular frequency that is substantially less than the detonation rotational frequency. This is accompanied by oscillations in the detonation height. The oscillation amplitude grows over time until the detonation ultimately fails. Both the performance and instability results emphasize the need for carefully designed RDE inlets that provide low loss when flow is in the forward direction, but high resistance when the flow is reversed. Development of such high-diodicity inlets is critical to achieving pressure gain in airbreathing RDE’s.

detonation↗

High-Fidelity Aerodynamic Analysis and Optimization of the SUSAN Electrofan Concept

The Subsonic Single Aft Engine (SUSAN) Electrofan is a new single-aisle regional jet class transport aircraft being studied by NASA, which benefits from reduced fuel consumption through a reduction in the number of hydrocarbon fuel-burning engines from two to one. This is achieved through a hybrid-electric system architecture, where a series of generators are used to extract power from a fuel-consuming tail cone thruster to drive electric propulsors mounted on the wings. To support the development of these propulsion systems, which involve high levels of propulsion-airframe integration, this paper presents high-fidelity analyses through computational fluid dynamics (CFD) simulations provided by the Launch Ascent and Vehicle Aerodynamics (LAVA) framework, which also includes capabilities for modeling the effect of active propulsors. A trade space exploration is performed to investigate the advantages of several wing mounted distributed electric propulsion system configurations, including over-wing, under-wing, and trailing-edge arrangements. For the aft fuselage propulsor, focus is on the sizing of the inlet, core, and bypass ducts. High-fidelity aerodynamic shape optimization is also used to help minimize the inlet distortion intensity experienced by the aft propulsor fan through a reshaping of the fuselage.

CAS↗

MEDLI2: MISP Inferred Aerothermal Environment and Flow Transition Assessment

The Mars Entry, Descent, and Landing Instrumentation 2 (MEDLI2) sensor suite on the Mars2020 mission contained multiple sensors on the aeroshell to measure the aerothermal environment during entry into the Martian atmosphere. These sensors performed superbly and successfully returned forebody and aftbody heating measurements. Analysis of MEDLI2 data indicated flow transitioning from a laminar to turbulent state on the heatshield. No evidence of flow transition was observed on the backshell. Two methods were used to estimate flow transition times on the heatshield: (1) temperature gradient of near-surface thermocouple data and (2) heat flux gradient from an inverse reconstruction approach using thermocouple data and material response modeling. Both methods produced similar transition times with an estimated accuracy of ±1 s. To assess various transition criteria, transition parameters were evaluated at each sensor location using flow field solutions from computational fluid dynamics (CFD) simulations. The idea was to use conservative values inferred from MEDLI2 data as transition criteria for other Mars missions. To test this hypothesis, MEDLI data from the Mars Science Laboratory (MSL) mission was used to compare predicted vs. actual flow transition times. The comparisons suggest smooth wall transition criteria are not well-suited in modeling the rapid progression of a turbulent transition front. Transition criteria containing a roughness element parameter agreed better with the flight data. In summary, critical transition values derived from MEDLI2 data may be used as a starting point in constructing a flow transition model for future Mars missions.

Chun Y Tang↗

Modeling of Particle Transport and Impact in Transient, Multiphase Oxidizer-Rich Environments Using Computational Fluid Dynamics and Lagrangian Particle Tracking

Particle impacts from foreign object debris (FOD) in an oxidizer-rich environment have been shown to be a credible and significant risk for ignition and failure of components and vehicles. The risk of particle ignition is dependent on many factors, including particle impact velocity/energy and fluid composition (i.e. fluid phase, species presence, and state). Prediction of particle transport and particle impacts in relevant environments, including transient, multiphase flows, is important for assessing the risk and avoiding repeated expensive system level tests. The capability to model both the fluid dynamics and particle transport in complex three-dimensional geometries and multiphase environments has been developed at Marshall Space Flight Center (MSFC) in the propulsion fluid dynamic branch (ER42) by utilizing computational fluid dynamics (CFD) simulations and Lagrangian particle tracking. Using CFD tools, including density-based Loci/CHEM with a cavitation model and pressure-based Loci/STREAM with a volume of fluids model, MSFC/ER42 has provided particle impact predictions to multiple projects for oxidizer compatibility assessments. Simulations of transient, multiphase environments such as liquid slugs flowing through tubing and cavitating flow in valves have been completed alongside one-way coupled Lagrangian particle tracking to predict particle impacts.

M.V. Fischels↗

Enhancements to Linear Stability-Based, CFD-integrated Transition Prediction for High-Speed Flows

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.

CFD↗

Experimental and Computational Investigation of Valve Motion in a Resonant Pulse Combustor

The motion of a passive reed-type valve and a poppet-style valve operating in a small scale, liquid-fueled pulse combustor is investigated experimentally. Valve position and combustion chamber pressure are simultaneously measured using an in-house fabricated optical position probe. The reed valve configuration is found to operate in a self-aspirated mode, generating significant pressure gain. The poppet valve configuration cannot operate without forced air, and does not generate pressure gain. Both type valves are tested in combustors of multiple lengths. Close examination of the respective valve motions indicate that the reed valve is highly non-linear, with unique attributes that appear essential for self-aspiration. Dynamic models for the motion of each valve are implemented in a computational fluid dynamic (CFD) simulation of the pulse combustor in order to assess if this unique valve motion is critical to successful operation. The results show that it is. The implications of these results are discussed. The need for active actuation with feedback control, rather than passive valve actuation is highlighted as a critical technology for practical resonant pulse combustors.

Combustion↗

Surface Instability of Liquid Propellants in Microgravity During Pulsed Settling Operations

Pulsing reaction control system (RCS) thrusters, vent valves, or other propulsion devices can preserve propellant resources in space, but this operation also effectively introduces a vibration to the vehicle. When the vibration is perpendicular to the liquid propellant surface, Faraday waves may be generated at the liquid-vapor interface. These Faraday instabilities can perturb or break up the liquid surface of cryogenic tanks, leading to inefficiencies in thermal management or even ullage collapse. Drawing from theory and experiments, an engineering model defining the allowable design regions for pulsed settling in microgravity was assembled and verified with computational fluid dynamics (CFD) simulations. A traditional settling metric, the Bond number, was also overlaid in the model to indicate which duty cycles were insufficient to overcome surface tension and aggregate propellant. Mission planners and engineers can consult the tool to rapidly evaluate the stability of a liquid-vapor interface given the pulse frequency and the excitation acceleration. Expressions developed for Faraday waves induced by a sinusoidal forcing input at standard gravity were found to provide excellent predictive capabilities for pulsed, or rectangular, waveforms in the absence of a consistent gravitational acceleration. This study extends the usage of these equations to an alternative forcing function and microgravity environments for the purpose of estimating natural frequencies, surface mode shapes, surface wave amplitudes, and the onset of droplet ejection. CFD simulations with the Loci/STREAM-VoF (Volume of Fluid) solver were initially validated against experimental results in standard gravity. Discrete points on the design map were then investigated with CFD and confirmed that the engineering model reliably indicates surface stability and most Faraday wave characteristics without requiring higher-fidelity tools. The engineering model is highly extensible and can be adapted for various propellant fill fractions, fluid properties, and tank sizes.

Faraday Waves↗

Deep Neural Network Based Convergence Classification for Computational Fluid Dynamics

A supervised deep learning approach is coupled with heuristic convergence criteria to construct a classification model for detecting the completion (convergence) of computational fluid dynamics (CFD) simulations. Heuristic convergence criteria alone are not always sufficient and more complex decisions are often left to a human analyst. The proposed approach leverages heuristic convergence criteria as well as two deep neural network (DNN) models, one binary and one multi-class, to improve the efficiency and consistency of convergence classification across a wide range of flight regimes. The DNN models presented are each trained on a subset of ascent aerodynamic CFD simulations for NASA’s Space Launch System and were produced using NASA’s unstructured Navier-Stokes solver FUN3D. Individual solutions are analyzed intermittently and are classified as sufficiently converged, further iterations required, or switch from steady Reynolds Averaged Navier-Stokes (RANS) to unsteady RANS CFD based on the iterative histories of four aerodynamic coefficients. The implemented classification model is shown to produce solutions that closely correlate to solutions produced by a human analyst. This work lays groundwork for expanding the capabilities of DNNs for automating and improving more of the CFD process.

SLS↗

Enhancements to Linear Stability-Based, CFD-integrated Transition Prediction for High-Speed Flows

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.

CFD↗