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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Assessment of HAB Particulate Tracing in EMU Helmet in Support of Eva 80

After water was reported in the EMU helmet during ISS US EVA-80, mitigation strategies were created to attempt to arrest the motion of any droplets that enter the helmet for future Extravehicular Activities (EVAs). This included adding absorbent materials into the interior of the helmet. But before a mitigation strategy can be implemented, it must first be proven to be safe. Towards this aim, a computational fluid dynamics (CFD) analysis was done tracing the paths of particulates potentially generated by the absorbent material. The objective was to characterize the risk these particulates pose for inspiration and eye irritation by tracking what percentage of particulates contact the suit-wearer’s face, eyes, or mouth. The model consisted of a human mannikin head and torso inside the EMU suit and helmet. The software used was ANSYS Fluent, with discrete phase modeling enabled to generate and track the particulates within the ventilation flow of the helmet.

Abigail Rose Baukus↗
NASA NTRSDate not supplied

Assessment of HAB Particulate Tracing in EMU Helmet in Support of Eva 80

After water was reported in the EMU helmet during ISS US EVA-80, mitigation strategies were created to attempt to arrest the motion of any droplets that enter the helmet for future Extravehicular Activities (EVAs). This included adding absorbent materials into the interior of the helmet. But before a mitigation strategy can be implemented, it must first be proven to be safe. Towards this aim, a computational fluid dynamics (CFD) analysis was done tracing the paths of particulates potentially generated by the absorbent material. The objective was to characterize the risk these particulates pose for inspiration and eye irritation by tracking what percentage of particulates contact the suit-wearer’s face, eyes, or mouth. The model consisted of a human mannikin head and torso inside the EMU suit and helmet. The software used was ANSYS Fluent, with discrete phase modeling enabled to generate and track the particulates within the ventilation flow of the helmet.

Abigail Baukus↗
NASA NTRSDate not supplied

Assessment of HAB Particulate Tracing in EMU Helmet in Support of Eva 80

After water was reported in the EMU helmet during ISS US EVA-80, mitigation strategies were created to attempt to arrest the motion of any droplets that enter the helmet for future Extravehicular Activities (EVAs). This included adding absorbent materials into the interior of the helmet. But before a mitigation strategy can be implemented, it must first be proven to be safe. Towards this aim, a computational fluid dynamics (CFD) analysis was done tracing the paths of particulates potentially generated by the absorbent material. The objective was to characterize the risk these particulates pose for inspiration and eye irritation by tracking what percentage of particulates contact the suit-wearer’s face, eyes, or mouth. The model consisted of a human mannikin head and torso inside the EMU suit and helmet. The software used was ANSYS Fluent, with discrete phase modeling enabled to generate and track the particulates within the ventilation flow of the helmet.

Abigail Baukus↗
NASA NTRS2015

An Internal Thermal Environment Model of an Aluminized Solid Rocket Motor with Experimental Validation

Due to the severity of the internal solid rocket motor (SRM) environment, very few direct measurements of that environment exist; therefore, the appearance of such data provides a unique opportunity to assess current thermal/fluid modeling capabilities. As part of a previous study of SRM internal insulation performance, the internal thermal environment of a laboratory-scale SRM featuring aluminized propellant was characterized with two types of custom heat-flux calorimeters: one that measured the total heat flux to a graphite slab within the SRM chamber and another that measured the thermal radiation flux. Therefore, in the current study, a thermal/fluid model of this lab-scale SRM was constructed using ANSYS Fluent to predict not only the flow field structure within the SRM and the convective heat transfer to the interior walls, but also the resulting dispersion of alumina droplets and the radiative heat transfer to the interior walls. The dispersion of alumina droplets within the SRM chamber was determined by employing the Lagrangian discrete phase model that was fully coupled to the Eulerian gas-phase flow. The P1-approximation was engaged to model the radiative heat transfer through the SRM chamber where the radiative contributions of the gas phase were ignored and the aggregate radiative properties of the alumina dispersion were computed from the radiative properties of its individual constituent droplets, which were sourced from literature. The convective and radiative heat fluxes computed from the thermal/fluid model were then compared with those measured in the lab-scale SRM test firings and the modeling approach evaluated.

Martin, Heath T.↗
NASA NTRSDate not supplied

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

This paper evaluates simulation predictions against experimental test data of icing clouds that were produced during 2018 ice crystal icing physics tests conducted at the NASA Propulsion Systems Laboratory icing wind tunnel. Aero-thermal and cloud parameters are set and known upstream at the tunnel inlet and spray system, but change as the cloud and air thermodynamically interact as the flowing masses reach the tunnel test section. Utilizing the ANSYS Fluent Discrete Phase Model function, 3D computational fluid dynamics (CFD) simulations were performed, capturing the thermodynamic interactions between the test parameters, and providing predictions of the aero thermal and cloud conditions at the tunnel test section. Simulation predictions were compared with test data that were measured at the tunnel exit plane. Evaluations focused on the cloud concentration (total water content), humidity content, and air temperature. CFD simulation predictions showed areas of agreement and disagreement. Simulations showed that cloud concentration profiles at the test section are strongly related to the initial spray nozzle pattern used at the tunnel inlet. Experimental data suggest that greater dispersion of the cloud occurred as the simulated cloud predicted areas of high and low cloud concentration compared to test data profiles. Simulations, however, captured the magnitude and location of the change in humidity content and the change in air temperature due to the presence of the cloud reasonably well, when compared to test data. This result would suggest that while the ANSYS simulation did not fully predict the spreading of the cloud as measured during experiment, it did capture evaporation and the molecular movements of air and vapor relatively well.

CFD↗
NASA NTRSDate not supplied

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

This paper evaluates simulation predictions against experimental test data of icing clouds that were produced during 2018 ice crystal icing physics tests conducted at the NASA Propulsion Systems Laboratory icing wind tunnel. Aero-thermal and cloud parameters are set and known upstream at the tunnel inlet and spray system, but change as the cloud and air thermodynamically interact as the flowing masses reach the tunnel test section. Utilizing the ANSYS Fluent Discrete Phase Model function, 3D computational fluid dynamics (CFD) simulations were performed, capturing the thermodynamic interactions between the test parameters, and providing predictions of the aero thermal and cloud conditions at the tunnel test section. Simulation predictions were compared with test data that were measured at the tunnel exit plane. Evaluations focused on the cloud concentration (total water content), humidity content, and air temperature. CFD simulation predictions showed areas of agreement and disagreement. Simulations showed that cloud concentration profiles at the test section are strongly related to the initial spray nozzle pattern used at the tunnel inlet. Experimental data suggest that greater dispersion of the cloud occurred as the simulated cloud predicted areas of high and low cloud concentration compared to test data profiles. Simulations, however, captured the magnitude and location of the change in humidity content and the change in air temperature due to the presence of the cloud reasonably well, when compared to test data. This result would suggest that while the ANSYS simulation did not fully predict the spreading of the cloud as measured during experiment, it did capture evaporation and the molecular movements of air and vapor relatively well.

CFD↗
NASA NTRS1987

Discrete element weld model, phase 2

A numerical method was developed for analyzing the tungsten inert gas (TIG) welding process. The phenomena being modeled include melting under the arc and the flow in the melt under the action of buoyancy, surface tension, and electromagnetic forces. The latter entails the calculation of the electric potential and the computation of electric current and magnetic field therefrom. Melting may occur at a single temperature or over a temperature range, and the electrical and thermal conductivities can be a function of temperature. Results of sample calculations are presented and discussed at length. A major research contribution has been the development of numerical methodology for the calculation of phase change problems in a fixed grid framework. The model has been implemented on CHAM's general purpose computer code PHOENICS. The inputs to the computer model include: geometric parameters, material properties, and weld process parameters.

Prakash, C.↗
NASA NTRS1972

On higher order discrete phase-locked loops.

An exact mathematical model is developed for a discrete loop of a general order particularly suitable for digital computation. The deterministic response of the loop to the phase step and the frequency step is investigated. The design of the digital filter for the second-order loop is considered. Use is made of the incremental phase plane to study the phase error behavior of the loop. The model of the noisy loop is derived and the optimization of the loop filter for minimum mean-square error is considered.

Gill, G. S.↗
NASA NTRS1988

A numerical simulation of the full two-dimensional electrothermal de-icer pad

The ability to predict the time-temperature history of electrothermal de-icer pads is important in the subsequent design of improved and more efficient versions. These de-icer pads are installed near the surface of aircraft components, for the specific purpose of removing accreted ice. The proposed numerical model can incorporate the full 2-D geometry through a section of a region (i.e., section of an airfoil), that current 1-D numerical codes are unable to do. Thus, the effects of irregular layers, curvature, etc., can now be accounted for in the thermal transients. Each layer in the actual geometry is mapped via a body-fitted coordinate transformation into uniform, rectangular computational grids. The relevant heat transfer equations are transformed and discretized. To model the phase change that might occur in any accreted ice, in an enthalpy formulation the phase change equations are likewise transformed and discretized. The code developed was tested against numerous classical numerical solutions, as well as against experimental de-icing data on a UH1H rotor blade obtained from the NASA Lewis Research Center. The excellent comparisons obtained show that this code can be a useful tool in predicting the performance of current de-icer models, as well as in the designing of future models.

Masiulaniec, Konstanty C.↗
NASA NTRS2002

Influence of Turbulence on the Restraint of Liquid Jets by Surface Tension in Microgravity Investigated

Microgravity poses many challenges to the designer of spacecraft tanks. Chief among these are the lack of phase separation and the need to supply vapor-free liquid or liquidfree vapor to the spacecraft processes that require fluid. One of the principal problems of phase separation is the creation of liquid jets. A jet can be created by liquid filling, settling of the fluid to one end of the tank, or even closing a valve to stop the liquid flow. Anyone who has seen a fountain knows that jets occur in normal gravity also. However, in normal gravity, the gravity controls and restricts the jet flow. In microgravity, with gravity largely absent, surface tension forces must contain jets. To model this phenomenon, a numerical method that tracks the fluid motion and the surface tension forces is required. Jacqmin has developed a phase model that converts the discrete surface tension force into a barrier function that peaks at the free surface and decays rapidly away. Previous attempts at this formulation were criticized for smearing the interface. This can be overcome by sharpening the phase function, double gridding the fluid function, and using a higher order solution for the fluid function. The solution of this equation can be rewritten as two coupled Poisson equations that also include the velocity. After the code was implemented in axisymmetric form and verified by several test cases at the NASA Glenn Research Center, the drop tower runs of Aydelott were modeled. Work last year with a laminar model was found to overpredict Aydelott's results, except at the lowest Reynolds number conditions of 400. This year, a simple turbulence model was implemented by adding a turbulent viscosity based on the mixing-length hypothesis and empirical measurements of previous works. Predictions made after this change was implemented have been much closer to experimentally observed flow patterns and geyser heights. Two model runs is shown. The first, without any turbulence correction, breaks through the free surface and strikes the far end of the tank. In the second, the turbulence spreads the jet momentum over more of the free surface, enabling the surface tension forces to turn the jet back into the bulk liquid. The model geyser height with the second model is 1.1 cm. This is quite close to the 1.5-cm geyser height measured by Aydelott.

Chato, David J.↗
NASA NTRS2004

Contact Angle Influence on Geysering Jets in Microgravity Investigated

Microgravity poses many challenges to the designer of spacecraft tanks. Chief among these are the lack of phase separation and the need to supply vapor-free liquid or liquid-free vapor to the spacecraft processes that require fluid. One of the principal problems of phase separation is the creation of liquid jets. A jet can be created by liquid filling, settling of the fluid to one end of the tank, or even closing a valve to stop the liquid flow. Anyone who has seen a fountain knows that jets occur in normal gravity also. However, in normal gravity, the gravity controls and restricts the jet flow. In microgravity, with gravity largely absent, surface tension forces must be used to contain jets. To model this phenomenon, a numerical method that tracks the fluid motion and the surface tension forces is required. Jacqmin has developed a phase model that converts the discrete surface tension force into a barrier function that peaks at the free surface and decays rapidly away. Previous attempts at this formulation were criticized for smearing the interface. This can be overcome by sharpening the phase function, double gridding the fluid function, and using a higher-order solution for the fluid function. The solution of this equation can be rewritten as two coupled Poisson equations that also include the velocity.

Chato, David J.↗
NASA NTRS2021

Analysis of Nonlinear Shrinkage for the Bound Metal Deposition Manufacturing using Multi-scale Approach

We consider problem of nonlinear shrinkage of the metal part during bound metal deposition manufacturing on the ground and in zero-G. To analyze this problem we developed multi-scale physics-based approach that spans atomistic dynamics at the scale of nanoseconds and the full part shrinkage at the time scale of hours. Using this approach we estimated the key parameters of the problem including grain boundary width, coefficient of surface diffusion, initial redistribution of particles during debinding stage, micro-structure evolution from round particles to densely packed grains and corresponding change of the total and chemical free energy, and sintering stress. The introduced method was used to predict shrinkage at the level of two particles, filament cross-section, sub-model, and the whole green, brown, and metal parts. To further improve accuracy and reliability of the shrinkage predictions we propose concept of intelligent additive manufacturing of metal powders in space that combines the strengths of both physics-based and data-driven methods of analysis of AM.

bound metal deposition↗
NASA NTRSDate not supplied

Modeling Self-Pressurization and Spray Bar Pressure Control of a Cryogenic Storage Tank in Normal Gravity

This paper presents Computational Fluid Dynamics (CFD) models for simulating self-pressurization and spray bar cooling processes in a large-scale liquid hydrogen storage tank under normal gravity. The self-pressurization model utilizes the kinetics-based Schrage equation with the Volume-Of-Fluid (VOF) model to account for the evaporative and condensing interfacial mass fluxes. It uses a laminar approach to model natural convection and compares the pressures and temperatures predicted by the CFD model with experimental data from the Multipurpose Hydrogen Test Bed (MHTB) self-pressurization experiment. Additionally, the predicted interfacial mass flux is presented. A CFD model for simulating pressure control using a spray bar is also presented. An Eulerian-Lagrangian approach models the interactions between the discrete droplets and the continuous ullage phase. The spray model is coupled with the VOF model by tracking particles in the ullage, removing particles from the ullage when they reach the interface, and then adding their contributions to the liquid. The T-sat model is used to calculate the droplet-ullage heat and mass transfer. In this model, droplets warm up to the saturation temperature corresponding to the ullage vapor pressure thereafter evaporating while remaining at the saturation temperature. The tank pressure, vapor, and liquid temperature evolutions are validated against data from the MHTB spray bar mixing experiment.

Self-Pressurization↗
NASA NTRSDate not supplied

Modeling Self-Pressurization and Spray Bar Pressure Control of A Cryogenic Storage Tank in Normal Gravity

This paper presents computational fluid dynamics (CFD) models for simulating self-pressurization and spray-bar pressure control processes in a large-scale liquid hydrogen storage tank under normal gravity conditions. For self-pressurization, the model employs the kinetics-based Schrage equation alongside the volume-of-fluid (VOF) method to account for interfacial mass transfer. The CFD predictions of pressure and temperature are compared with experimental data from the Multipurpose Hydrogen Test Bed (MHTB) experiment, and the predicted interfacial mass transfer rates are also presented. A CFD model simulating pressure control using a spray bar has also been developed. An Eulerian-Lagrangian approach models the interactions between discrete droplets and the continuous ullage (vapor) phase. The spray model is coupled with the VOF method by tracking droplets in the ullage and removing them when they reach the liquid interface. The T-sat model calculates droplet-ullage heat and mass transfer, where droplets warm up to the saturation temperature corresponding to the ullage vapor pressure before evaporating while remaining at the saturation temperature. The evolution of tank pressure, vapor temperature, and liquid temperature predicted by the CFD model is validated against data from the MHTB spray-bar mixing experiment. Overall, the CFD models agree with experimental data, demonstrating their capability to simulate self-pressurization and pressure control processes in large-scale cryogenic storage tanks. These models can be valuable tools for designing and optimizing cryogenic fluid management systems in future applications.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

Modeling Self-Pressurization and Spray Bar Pressure Control of A Cryogenic Storage Tank in Normal Gravity

This paper presents computational fluid dynamics (CFD) models for simulating self-pressurization and spray-bar pressure control processes in a large-scale liquid hydrogen storage tank under normal gravity conditions. For self-pressurization, the model employs the kinetics-based Schrage equation alongside the volume-of-fluid (VOF) method to account for interfacial mass transfer. The CFD predictions of pressure and temperature are compared with experimental data from the Multipurpose Hydrogen Test Bed (MHTB) experiment, and the predicted interfacial mass transfer rates are also presented. A CFD model simulating pressure control using a spray bar has also been developed. An Eulerian-Lagrangian approach models the interactions between discrete droplets and the continuous ullage (vapor) phase. The spray model is coupled with the VOF method by tracking droplets in the ullage and removing them when they reach the liquid interface. The T-sat model calculates droplet-ullage heat and mass transfer, wherein droplets warm up to the saturation temperature corresponding to the ullage vapor pressure before evaporating while remaining at the saturation temperature. The evolution of tank pressure, vapor temperature, and liquid temperature predicted by the CFD model is validated against data from the MHTB spray-bar mixing experiment. Overall, the CFD models agree with experimental data, demonstrating their capability to simulate self-pressurization and pressure control processes in large-scale cryogenic storage tanks. These models can be valuable tools for designing and optimizing cryogenic fluid management systems in future applications.

Self-Pressurization↗
NASA NTRS1986

Modeling and equalization of nonlinear bandlimited satellite channels

The problem of modeling and equalization of a nonlinear satellite channel is considered. The channel is assumed to be bandlimited and exhibits both amplitude and phase nonlinearities. A discrete time satellite link is modeled under both uplink and downlink white Gaussian noise. Under conditions of practical interest, a simple and computationally efficient design technique for the minimum mean square error linear equalizer is presented. The bit error probability and some numerical results for a binary phase shift keyed (BPSK) system demonstrate that the proposed equalization technique outperforms standard linear receiver structures.

Konstantinides, K.↗
NASA NTRS1986

Two-phase flow

An experimental program to characterize the spray from candidate nozzles for icing-cloud simulation is discussed. One canidate nozzle, which is currently used for icing research, has been characterized for flow and drop size. The median-volume diameter (MVD) from this air-assist nozzle is compared with correlations in the literature. The new experimental spray facility is discussed, and the drop-size instruments are discussed in detail. Since there is no absolute standard for drop-size measurements and there are other limitations, such as drop -size range and velocity range, several instruments are used and results are compared. A two-phase model was developed at Pennsylvania State University. The model uses the k-epsilon model of turbulence in the continous phase. Three methods for treating the discrete phase are used: (1) a locally homogeneous flow (LHF) model, (2) a deterministic separated flow (DSF) model, and (3) a stochastic separated flow (SSF) model. In the LHF model both phases have the same velocity and temperature at each point. The DSF model provides interphase transport but ignores the effects of turbulent fluctuations. In the SSF model the drops interact with turbulent eddies whose properties are determined by the k-epsilon turbulence model. The two-phase flow model has been extended to include the effects of evaporation and combustion.

Tacina, Robert R.↗