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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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The PDT project will investigate the use of retro propulsion during the supersonic phase of atmospheric entry for Mars missions. The project technical approach involves a combination of procurement and evaluation of commercially provided flight data, development of candidate vehicle configurations, and engineering calibration of computational fluid dynamics models to the available flight data.
This paper presents a CFD (computational fluid dynamics) model for simulating the self-pressurization of a large scale liquid hydrogen storage tank. In this model, the kinetics-based Schrage equation is used to account for the evaporative and condensing interfacial mass flows. Laminar and turbulent approaches to modeling natural convection in the tank and heat and mass transfer at the interface are compared. The flow, temperature, and interfacial mass fluxes predicted by these two approaches during tank self-pressurization are compared against each other. The ullage pressure and vapor temperature evolutions are also compared against experimental data obtained from the MHTB (Multipuprpose Hydrogen Test Bed) self-pressurization experiment. A CFD model for cooling cryogenic storage tanks by spraying cold liquid in the ullage is also presented. The Euler- Lagrange approach is utilized for tracking the spray droplets and for modeling interaction between the droplets and the continuous phase (ullage). The spray model is coupled with the VOF (volume of fluid) model by performing particle tracking in the ullage, removing particles from the ullage when they reach the interface, and then adding their contributions to the liquid. Droplet ullage heat and mass transfer are modeled. The flow, temperature, and interfacial mass flux predicted by the model are presented. The ullage pressure is compared with experimental data obtained from the MHTB spray bar mixing experiment. The results of the models with only droplet/ullage heat transfer and with heat and mass transfer between the droplets and ullage are compared.
Thermodynamic and computational fluid dynamics modeling has been conducted to examine the feasibility of adapting the NASA-Glenn erosion burner rigs for use in studies of corrosion of environmental barrier coatings by the deposition of molten CMAS. The effect of burner temperature, Mach number, particle preheat, duct heating, particle size, and particle phase (crystalline vs. glass) were analyzed. Detailed strategies for achieving complete melting of CMAS particles were developed, thereby greatly improving the probability of future successful experimental outcomes.
This paper reports on temperature and humidity measurements from a series of ice-crystal icing tunnel experiments conducted in June 2018 at the Propulsion Systems Laboratory at the NASA Glenn Research Center. The tests were fundamental in nature and were aimed at investigating the icing processes on a two-dimensional NACA0012 airfoil subjected to artificially generated icing clouds. Prior to the tests on the airfoil, a suite of instruments, including total temperature and humidity probes, were used to characterize the thermodynamic flow and icing cloud conditions of the facility. Two different total temperature probes were used in these tests which included a custom designed rearward facing probe and a commercial self-heating total temperature probe. The rearward facing probe, the main total temperature probe, was designed to reduce and mitigate the contaminating effects of icing and ingestion of ice crystals and water droplets at the probe's inlet. The probe also serves as an air-sample inlet for a light absorption based humidity measurement. The paper includes a section which discusses total temperature and humidity measurement considerations, and another section which provides an analysis of the main probe's performance characteristics. A computational fluid dynamic model of the flow around the probe was also conducted to gain insight into the trajectory of the flow entering the probe inlet. The experiments included a series of tests in which the relative humidity of the facility flow was swept through with increasingly larger values. The data showed that the rearward facing probe can reasonably capture the flow's total temperature and humidity under mild to moderate icing conditions but produces anomalous results under more intense icing conditions. The experimental data was also compared to an in-house developed thermodynamic model which takes into account the interaction of the main flow with the icing cloud. Comparison to the thermodynamic model showed that the rearward facing probe measured the predicted trends.
This paper presents an uncertainty analysis of the stagnation-point calibration probe surface predictions for conditions that span the performance envelope of the Hypersonic Materials Environmental Test System facility located at NASA Langley Research Center. A second-order stochastic expansion was constructed over 47 uncertain parameters to evaluate the sensitivities, identify the most significant uncertain variables, and quantify the uncertainty in the stagnation-point heat flux and pressure predictions of the calibration probe for a low- and high-enthalpy test condition. A sensitivity analysis showed that measurement bias uncertainty is the most significant contributor to the stagnation-point pressure and heat flux variance for the low-enthalpy condition. For the high-enthalpy condition, a paradigm shift in sensitivities revealed the computational fluid dynamics model input uncertainty as the main contributor. A comparison between the prediction and measurement of the stagnation-point conditions under uncertainty showed that there was evidence of statistical disagreement. A validation metric was proposed and applied to the prediction uncertainty to account for the statistical disagreement when compared to the possible stagnation-point heat flux and pressure measurements.
A variably premixed rotating detonation engine using gaseous hydrogen and air reactants is introduced to enable investigation of key cycle processes while varying the homogeneity of the reactant inlet conditions. Two chamber configurations are investigated, the first with reactants filling the entire span of a straight annular channel and the second with a slightly larger channel and a backward-facing step. The first configuration permits both premixed and non-premixed fuel injection, enabling mixing quality modulation. The second configuration is operated only at fully premixed conditions. Operating modes and detonation wave speeds are characterized using exhaust-plume imaging, while the chamber heat release field is captured by transverse imaging through a transparent outer body. Tests using the first configuration were characterized by unstable counterpropagating modes with low detonation wave speeds regardless of the state of premixing, while the second configuration rendered single-wave behavior with wave speeds up to 86% of the Chapman–Jouguet velocity. Comparisons with a simple computational fluid dynamics model of the second configuration indicate that reactant preheating significantly influences the detonation wave topology, highlighting the potential utility of the test platform for isolating key physics associated with the effects of reactant premixing, preheating, and chamber geometry on rotating detonation engine operation.
Spacecraft fires pose a threat to the success of future Lunar, Martian, and deep space exploration missions. As NASA plans to return humans to the Moon in the next decade, novel mission requirements will present new fire safety challenges. For example, materials that are fire resistant on Earth are expected to burn under planned habitat conditions (elevated oxygen concentrations and reduced cabin pressure) and partial gravity (0.16g). Optimal smoke detector placement will depend on a combination of buoyant plume velocities, induced by partial gravity, and Environmental Control and Life Support Systems (ECLSS) parameters, including particle filtration rates, supply and return placement within the cabin, and forced air velocities. These ECLSS parameters must also address the need for rapid Lunar dust removal, as Lunar dust exposure poses a risk to crew health and hardware functionality. Here, we present progress toward a computational fluid dynamics model to evaluate smoke transport in a Lunar habitat. Recent work has demonstrated that if air supplies are placed on ceilings and returns on the floor, a buoyant smoke layer at the ceiling may disperse over the order of minutes even under low forced flow conditions. We expand upon these results to examine the influence of different supply and return configurations on smoke plume development. Additionally, we also address differences in the transport of smoke particles and Lunar dust by varying particle parameters like size, density, and shape factor. Finally, we discuss ongoing and future experimental efforts to measure smoke particle properties and transport under partial gravity, elevated oxygen, and reduced pressure conditions.
The aeroelastic stability of a tail cone thruster fan was analyzed for three structural modes and various nodal diameter patterns. Computational fluid dynamics modeling with blade vibrations was used in the analyses performed at design (peak-efficiency) and two near-stall conditions at the design rotational speed. Aerodynamic damping was used to assess flutter since this integrally bladed rotor design will have minimal structural damping. Aerodynamic damping was found to be low at the design condition. For the first mode, aerodynamic damping was seen to decrease towards stall, vanishing for a zero nodal diameter pattern. Further decrease in mass flow led to negative aerodynamic damping (flutter) for the first and second nodal diameters in the near stall condition. The flowfield at this lowest mass flow rate exhibited some additional unsteadiness at higher frequency. The sensitivity of results to time step and amplitudes of vibration was examined and found to be very satisfactory. The largest uncertainty in the results comes from the observed sensitivity of the aerodynamic damping to details of the variation of grid deformations in the blade passage mesh from the blade passage to the boundaries. For the parametric variations analyzed, the calculated aerodynamic damping is lower if the grid deformations near the blade surface are higher. Further work is needed to understand the cause of this sensitivity and find possible solutions to reduce the effects on flutter predictions.
This paper focuses on the development and validation of a combustion model for Computational Fluid Dynamics (CFD) modeling of a Rotating Detonation Engines (RDE).
For many important classes of Mod-Sim problems, even quantum computing will not enable accurate predictions/computation vis-à-vis the real world due to boundary/initial condition shortfalls in terms of both range of parameters and requisite amplitudes/coverage. The Mod-Sim community needs to consider going forward the knowability of initial and boundary conditions.
Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This proposal describes an approach to validate the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft. The research described here is absolutely cutting edge. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional"validation by test only'' mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions. Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computationaf Fluid Dynamics can be used to veritY these requirements; however, the model must be validated by test data. The proposed research project includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT and OPEN FOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid . . . Dynamics model using the methodology found in "Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations". This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions. The method accounts for all uncertainty terms from both numerical and input variables. Objective three is to compile a table of uncertainty parameters that could be used to estimate the error in a Computational Fluid Dynamics model of the Environmental Control System /spacecraft system. Previous studies have looked at the uncertainty in a Computational Fluid Dynamics model for a single output variable at a single point, for example the re-attachment length of a backward facing step. To date, the author is the only person to look at the uncertainty in the entire computational domain. For the flow regime being analyzed (turbulent, threedimensional, incompressible), the error at a single point can propagate into the solution both via flow physics and numerical methods. Calculating the uncertainty in using Computational Fluid Dynamics to accurately predict airflow speeds around encapsulated spacecraft in is imperative to the success of future missions.
This work describes the development of a transported Livengood–Wu (L–W) integral model for computational fluid dynamics (CFD) simulation to predict autoignition and engine knock tendency. The currently employed L–W integral model considers both single-stage and two-stage ignition processes, thus can be generally applied to different fuels such as paraffin, olefin, aromatics, and alcohol. The model implementation is first validated in simulations of homogeneous charge compression ignition (HCCI) combustion for three different fuels, showing good accuracy in prediction of autoignition timing for fuels with either single-stage or two-stage ignition characteristics. Then, the L–W integral model is coupled with G-equation model to indicate end-gas autoignition and knock tendency in CFD simulations of a direct-injection spark-ignition engine. This modeling approach is about 10 times more efficient than the ones that based on detailed chemistry calculation and pressure oscillation analysis. Two fuels with same Research Octane Number (RON) but different octane sensitivity are studied, namely, Co-Optima alkylate and Co-Optima E30. Feed-forward neural network model in conjunction with multivariable minimization technique is used to generate fuel surrogates with targets of matched RON, octane sensitivity, and ethanol content. The CFD model is validated against experimental data in terms of pressure traces and heat release rate for both fuels under a wide range of operating conditions. The knock tendency—indicated by the fuel energy contained in the autoignited region—of the two fuels at different load conditions correlates well with the experimental results and the fuel octane sensitivity, implying the current knock modeling approach can capture the octane sensitivity effect and can be applied to further investigation on composition of octane sensitivity.
Golden Eagle (Aquila chrysaetos) habitats may overlap with wind energy development in some regions of the US. Eagles, and similar soaring bird species, are therefore at risk of collision with wind turbines when flying through wind farms. Recently developed behavioral modeling approaches can predict the presence of eagles near turbines within the rotor-swept layer but require reliable prediction of atmospheric flowfield conditions. In particular, the vertical component of the wind speed dictates a soaring bird's ability to maintain or gain altitude, since they rely on updrafts to subsidize their flight. In this work, we investigate the atmospheric conditions around a wind farm in complex terrain and compare methods for atmospheric characterization. We use computational fluid dynamics (specifically, large-eddy simulations, or LES) to simulate the atmospheric boundary layer over a region encompassing multiple wind farms with high temporal and spatial resolution (seconds and 10's of meters, respectively). We compare traditional non-simulation-based methods of determining the orographic updraft potential based on wind direction, terrain slope and aspect, with the flowfields from LES that include both orographic updrafts alone and combined thermal and orographic updrafts. Preliminary analysis suggests that although the model captures the horizontal pattern of vertical updrafts, their magnitude can be improved with information about the surface heat flux, which is usually correlated with time of the day. Within our study region, we found that the low-fidelity model may over- or underestimate updraft potential by up to 400% at 80 m AGL, depending on local orographic features. This can result in an inaccurate representation of eagle presence and, consequently, risk. Another important finding is that flowfield time-averaging can hide important details about the flight environment, including how thermally generated flow structures within the atmospheric boundary layer (e.g., convective rolls and/or cells) may be important drivers of eagle flight.
Multiphysics and analytical calculations were conducted for a heat exchanger with passive, natural circulation flow. A glycol/water working fluid convects the heat to a dimpled heat exchanger shell, which subsequently transfers the heat to the soil, which acts as the ultimate heat sink. Because the system is fully-passive, it is not subject to the expenses, maintenance, and mechanical breakdowns associated with moving parts. Density, heat capacity, and thermal conductivity material properties were measured for various soil samples, and subsequently included as input for the soil heat conduction model. The soil model was coupled to a computational fluid dynamics (CFD) heat exchanger model that included the dynamic Smagorinsky large eddy simulation and k- omega turbulence models. The analysis showed that the fluid dynamics and heat transfer models worked properly, albeit at a slow pace. Nevertheless, the coupled CFD/heat conduction simulation ran long enough to determine a key parameter—the amount of heat conducted from the heat exchanger to the ground. This unique performance value, along with experimental data, was used as input for stand-alone, fast-running CFD models, as well as boundaries to obtain solutions to partial differential equations for soil heat conduction.
This paper presents the implementation of gust modeling capability in the CFD code FUN3D. The gust capability is verified by computing the response of an airfoil to a sharp edged gust. This result is compared with the theoretical result. The present simulations will be compared with other CFD gust simulations. This paper also serves as a users manual for FUN3D gust analyses using a variety of gust profiles. Finally, the development of an Auto-Regressive Moving-Average (ARMA) reduced order gust model using a gust with a Gaussian profile in the FUN3D code is presented. ARMA simulated results of a sequence of one-minus-cosine gusts is shown to compare well with the same gust profile computed with FUN3D. Proper Orthogonal Decomposition (POD) is combined with the ARMA modeling technique to predict the time varying pressure coefficient increment distribution due to a novel gust profile. The aeroelastic response of a pitch/plunge airfoil to a gust environment is computed with a reduced order model, and compared with a direct simulation of the system in the FUN3D code. The two results are found to agree very well.
The Building and Fire Research Laboratory (BFRL) was given the opportunity to make measurements during fire calibration tests of the heat detection system in an aircraft hangar with a nominal 30.4 (100 ft) ceiling height near Dallas, TX. Fire gas temperatures resulting from an approximately 8250 kW isopropyl alcohol pool fire were measured above the fire and along the ceiling. The results of the experiments were then compared to predictions from the computer fire models DETACT-QS, FPETOOL, and LAVENT. In section A of the analysis conducted, DETACT-QS AND FPETOOL significantly underpredicted the gas temperature. LAVENT at the position below the ceiling corresponding to maximum temperature and velocity provided better agreement with the data. For large spaces, hot gas transport time and an improved fire plume dynamics model should be incorporated into the computer fire model activation routines. A computational fluid dynamics (CFD) model, HARWELL FLOW3D, was then used to model the hot gas movement in the space. Reasonable agreement was found between the temperatures predicted from the CFD calculations and the temperatures measured in the aircraft hangar. In section B, an existing NASA high bay space was modeled using the CFD model. The NASA space was a clean room, 27.4 m (90 ft) high with forced horizontal laminar flow. The purpose of this analysis is to determine how the existing fire detection devices would respond to various size fires in the space. The analysis was conducted for 32 MW, 400 kW, and 40 kW fires.
Recent studies estimate that emissions from oil and gas production facilities contribute between 20 and 50% of the total methane ( CH 4 ) emitted in the US; therefore, quantifying and reducing these emissions are crucial for achieving climate goals. Methane quantification depends on both measuring methane concentrations and converting them to emissions through a modeling framework. Currently, simple atmospheric dispersion models are primarily used to quantify emissions and concentrations, but these estimates are highly uncertain when quantifying emissions from complex aerodynamic sources, such as oil and gas facilities. This investigation used a CFD modeling approach, which can account for aerodynamic complexity but has hitherto not been used to model methane concentrations downwind of a methane release of a known rate, and compared it against in situ measurements. High-time-resolution (1 Hz) methane concentration and meteorological data were measured during experiments conducted at the METEC on 21 March and 11 July 2024. The METEC site configuration, measured wind data, and controlled emission rates were used as input for the CONVERGE CFD model to model downwind CH 4 concentration. The modeling was carried out between 20 and 70 m, from two different points of release in two separate controlled-release experiments, one from a separator and another from a wellhead. In these experiments, we found that the CFD model could predict the CH 4 concentrations downwind of the release to a good degree. The model was evaluated on multiple metrics to assess its performance in estimating methane concentrations at typical fence line distances (∼30 m). These results help us to understand external flows and the ability of CFD models to predict downwind concentrations in aerodynamically complex environments.
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