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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 91 records · Page 5
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NASA NTRS2010

Constraints on Mercury's Na Exosphere: Combined MESSENGER and Ground-Based Data

We have used observations of sodium emission obtained with the McMath-Pierce solar telescope and MESSENGER's Mercury Atmospheric and Surface Composition Spectrometer (MASCS) to constrain models of Mercury's sodium exosphere, The distribution of sodium in Mercury's exosphere during the period January 12-15. 2008. was mapped using the McMath-Pierce solar telescope with the 5" X 5" image slicer to observe the D-line emission. On January 14, 2008, the Ultraviolet and Visible Spectrometer (UVVS) channel on MASCS sampled the sodium in Mercury's anti-sunward tail region. We find that the bound exosphere has an equivalent temperature of 900-1200 K, and that this temperature can be achieved if the sodium is ejected either by photon-stimulated desorption (PSD) with a 1200 K Maxwellian velocity distribution, or by thermal accommodation of a hotter source. We were not able to discriminate between the two assumed velocity distributions of the ejected particles for the PSD. but the velocity distributions require different values of the thermal accommodation coefficient and result in different upper limits on impact vaporization, We were able to place a strong constraint on the impact vaporization rate that results in the release of neutral Na atoms with an upper limit of 2.1 x 10(exp 6) sq cm/s, The variability of the week-long ground-based observations can be explained by variations in the sources, including both PSD and ion-enhanced PSD, as well as possible temporal enhancements in meteoroid vaporization. Knowledge of both dayside and anti-sunward tail morphologies and radiances are necessary to correctly deduce the exospheric source rates, processes, velocity distribution, and surface interaction.

Mouawad, Nelly↗
NASA NTRS2012

Mercury's Na Exosphere from MESSENGER Data

MESSENGER entered orbit about Mercury on March 18, 2011. Since then, the Ultraviolet and Visible Spectrometer (UWS) channel of MESSENGER's Mercury Atmospheric and Surface Composition Spectrometer (MASCS) has been observing Mercury's exosphere nearly continuously. Daily measurements of Na brightness were fitted with non-uniform exospheric models. With Monte Carlo sampling we traced the trajectories of a representative number of test particles, generally one million per run per source process, until photoionization, escape from the gravitational well, or permanent sticking at the surface removed the atom from the simulation. Atoms were assumed to partially thermally accommodate on each encounter with the surface with accommodation coefficient 0.25. Runs for different assumed source processes are run separately, scaled and co-added. Once these model results were saved onto a 3D grid, we ran lines of sight from the MESSENGER spacecraft :0 infinity using the SPICE kernels and we computed brightness integrals. Note that only particles that contribute to the measurement can be constrained with our method. Atoms and molecules produced on the nightside must escape the shadow in order to scatter light if the excitation process is resonant-light scattering, as assumed here. The aggregate distribution of Na atoms fits a 1200 K gas, with a PSD distribution, along with a hotter component. Our models constrain the hot component, assumed to be impact vaporization, to be emitted with a 2500 K Maxwellian. Most orbits show a dawnside enhancement in the hot component broadly spread over the leading hemisphere. However, on some dates there is no dawn/dusk asymmetry. The portion of the hot/cold source appears to be highly variable.

Killen, Rosemary M.↗
NASA NTRS2015

Numerical Investigation of Microgravity Tank Pressure Rise Due to Boiling

The ability to control self-pressurization in cryogenic storage tanks is essential for NASAs long-term space exploration missions. Predictions of the tank pressure rise in Space are needed in order to inform the microgravity design and optimization process. Due to the fact that natural convection is very weak in microgravity, heat leaks into the tank can create superheated regions in the liquid. The superheated regions can instigate microgravity boiling, giving rise to pressure spikes during self-pressurization. In this work, a CFD model is developed to predict the magnitude and duration of the microgravity pressure spikes. The model uses the Schrage equation to calculate the mass transfer, with a different accommodation coefficient for evaporation at the interface, condensation at the interface, and boiling in the bulk liquid. The implicit VOF model was used to account for the moving interface, with bounded second order time discretization. Validation of the models predictions was carried out using microgravity data from the Tank Pressure Control Experiment, which flew aboard the Space Shuttle Mission STS-52. Although this experiment was meant to study pressurization and pressure control, it underwent boiling during several tests. The pressure rise predicted by the CFD model compared well with the experimental data. The ZBOT microgravity experiment is scheduled to fly on February 2016 aboard the ISS. The CFD model was also used to perform simulations for setting parametric limits for the Zero-Boil-Off Tank (ZBOT) Experiments Test Matrix in an attempt to avoid boiling in the majority of the test runs that are aimed to study pressure increase rates during self-pressurization. *Supported in part by NASA ISS Physical Sciences Research Program, NASA HQ, USA

pressure rise↗
NASA NTRS2017

Pressurization of a Flightweight, Liquid Hydrogen Tank: Evaporation & Condensation at a Liquid/Vapor Interface

This paper presents an analysis and simulation of evaporation and condensation at a motionless liquid/vapor interface. A 1-D model equation, emphasizing heat and mass transfer at the interface, is solved in two ways, and incorporated into a subgrid interface model within a CFD simulation. Simulation predictions are compared with experimental data from the CPST Engineering Design Unit tank, a cryogenic fluid management test tank in 1-g. The numerical challenge here is the physics of the liquid/vapor interface; pressurizing the ullage heats it by several degrees, and sets up an interfacial temperature gradient that transfers heat to the liquid phase-the rate limiting step of condensation is heat conducted through the liquid and vapor. This physics occurs in thin thermal layers O(1 mm) on either side of the interface which is resolved by the subgrid interface model. An accommodation coefficient of 1.0 is used in the simulations which is consistent with theory and measurements. This model is predictive of evaporation/condensation rates, that is, there is no parameter tuning.

Stewart, Mark E. M.↗
NASA NTRSDate not supplied

Interfacial thermodynamics of cryogenic fluids: The effect on non-condensable gas on fluid storage

Propellant tanks that contain cryogenic fluids (CFs) in low gravity conditions are usually pressurized with non-condensable (NC) gases for fast extraction. Unfortunately, the presence of NC gases causes CFs to exhibit higher boil-offs compared to pure CF systems. For optimal utilization of the cryogenic fuels, these higher boil-off rates must be minimized. Our goal is to quantify the effects NC gases have on the evaporation and condensation dynamics of CFs to develop strategies that mitigate the higher boil-offs. The hypothesis is that the NC gas accumulates around the CF’s liquid vapor interface in the Knudsen layer, creating a kinetic barrier for both evaporation and condensation. Testing this hypothesis with experimental methods is difficult due to the transient nature of the Knudsen layer, which is only a few nanometers thick. Furthermore, experimental capabilities are limited in low gravity conditions and extremely expensive. Accordingly, we approach this problem from a theoretical perspective. In this study, we employ molecular dynamics (MD) simulations to probe the interfacial mechanisms that affect CF’s evaporation and condensation at varying concentrations of NC gases. Specifically, we use nitrogen (N2) and oxygen (O2) as our CFs and neon (Ne) as our NC gas. Using MD simulations, we show that Ne accumulates at N2 liquid vapor interface across a wide range of Ne concentrations, thereby impeding mass transport of N2. Our simulations allow for direct computation of the molar flux as well as the mass accommodation coefficient (MAC) which can then be used as input parameters to continuum fluid dynamics (CFD) models for optimal storage tank design.

Michael Robert DeLyser↗
NASA NTRSDate not supplied

Modeling Autogenous Pressurization and Draining of a Cryogenic Storage Tank in Normal Gravity

A two-phase CFD model for autogenous pressurization and draining of a cryogenic storage tank is presented using both the Sharp Interface and Volume-Of-Fluid (VOF) approaches for capturing the front and the associated interfacial heat, mass and momentum transfer between the liquid and vapor regions. Both models are validated against data provided by the Cryogenic Propellant Storage and Transfer (CPST) Engineering Development Unit (EDU) experiment. The results of the autogenous pressurization are presented first, focusing on the phase change and turbulence effects on the tank pressure and temperature predictions. Both the Sharp Interface (SI-CFD) and VOF (VOF-CFD) multiphase models predict tank pressure during pressurization within 3% of the measured values. The sensitivity of key physical and numerical parameters of the problem are tested using the Sharp Interface model. Effects of the accommodation coefficient (AC), and the computational grid structure are studied. The second part of this paper is devoted to validating the SI-VOF model, with an enhanced capability of moving the liquid-vapor interface, against the draining segment of the EDU experiment. The VOF-CFD model was also used to simulate tank draining and its results were compared with the results of the Sharp Interface model with the moving interface. Both models predict tank pressure during draining within 3.5% of the measured values. Pressure decrease rate is underpredicted by both models during the first 100 seconds of draining but matches the experimental rate for the rest of the simulation.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

Modeling Autogenous Pressurization and Draining of a Cryogenic Storage Tank in Normal Gravity

A two-phase CFD model for autogenous pressurization and draining of a cryogenic storage tank is presented using both the Sharp Interface and Volume-Of-Fluid (VOF) approaches for capturing the front and the associated interfacial heat, mass and momentum transfer between the liquid and vapor regions. Both models are validated against data provided by the Cryogenic Propellant Storage and Transfer (CPST) Engineering Development Unit (EDU) experiment1. The results of the autogenous pressurization are presented first, focusing on the phase change and turbulence effects on the tank pressure and temperature predictions. Both the Sharp Interface (SI-CFD) and VOF (VOF-CFD) multiphase models predict tank pressure during pressurization within 3% of the measured values. The sensitivity of key physical and numerical parameters of the problem are tested using the Sharp Interface model. Effects of the accommodation coefficient (AC), and the computational grid structure are studied. The second part of this paper is devoted to validating the SI-VOF model, with an enhanced capability of moving the liquid-vapor interface, against the draining segment of the EDU experiment. The VOF-CFD model was also used to simulate tank draining and its results were compared with the results of the Sharp Interface model with the moving interface. Both models predict tank pressure during draining within 3.5% of the measured values. Pressure decrease rate is underpredicted by both models during the first 100 seconds of draining but matches the experimental rate for the rest of the simulation.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

CFD Model Development of a Cryogenic Storage Tank Self-Pressurization in Normal Gravity and Validation against SHIIVER Experiment

Two-phase flow and heat transfer simulations with interfacial phase change of the Structural Heat Intercept, Insulation, and Vibration Evaluation Rig (SHIIVER) self-pressurization experiment were conducted using storage tank CFD model in the framework of the ANSYS Fluent CFD code. The simulations were performed for the 70% fill level case with MLI on domes and no vapor cooling. All the phase change calculations in these simulations were generated by in-house Schrage-based evaporation-condensation model. The calculations were performed using both the Volume of Fluid (VOF) and Sharp Interface multiphase 2D axisymmetric models. A number of parametric and sensitivity studies were performed to check the various aspects of the CFD model. These studies helped to understand the effects of varying several parameters on the tank pressure and temperature during self-pressurization. Turbulence modeling; turbulence damping at the interface; and using constant vs. temperature dependent fluid properties were shown to have the most profound influence on predicted tank pressures and temperatures. Current study indicates that including phase change at the interface into the computational model is crucial for accurate prediction of the tank self-pressurization process. The effect of accommodation coefficient was also studied. Tank pressure values predicted by the VOF, and Sharp Interface models are within 4% of the experimental ones.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

CFD Model Development of a Cryogenic Storage Tank Self-Pressurization in Normal Gravity and Validation against SHIIVER Experiment

Two-Phase flow and heat transfer simulations with interfacial phase change of the Structural Heat Intercept, Insulation, and Vibration Evaluation Rig (SHIIVER) self-pressurization experiment were conducted using storage tank CFD model in the framework of the ANSYS Fluent CFD code. The simulations were performed for the 70% fill level case with MLI on domes and no vapor cooling. All the phase change calculations in these simulations were generated by in-house Schrage-based evaporation-condensation model. The calculations were performed using both the VOF and Sharp Interface multiphase 2Daxisymmetric models. A number of parametric and sensitivity studies were performed to check the various aspects of the CFD model. These studies helped to understand the effects of varying several parameters on the tank pressure and temperature during self-pressurization. These parameters include: the effect of turbulence modeling and turbulence damping at the interface; the effect of constant vs. temperature dependent fluid properties; the effect of accommodation coefficient; the effect of modeling phase change at the interface and the effect of the fill level.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

Validation of a Two-Phase CFD Model for Predicting Tank Self-Pressurization in the Ground-Based K-Site Experiment

A two-phase CFD model for self-pressurization of a cryogenic storage tank partially filled with liquid hydrogen is presented using the Volume-Of-Fluid approach for modeling two-phase flow, as well as interfacial heat, mass and momentum transfer between the liquid and the vapor regions. The CFD model is validated against self-pressurization experiment performed using the K-site flightweight hydrogen storage tank at NASA Glenn Research Center1. Laminar and turbulent simulations are performed together with conjugated heat transfer analysis. Effects of turbulence, the value of accommodation coefficient used for predicting phase change rates, as well as tank wall geometry are presented and discussed. Predicted tank pressures, fluid and wall temperatures are compared with the experimental data at 49% fill level and two different heat loads for validating this CFD model.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

Validation of a Two-Phase CFD Model for Predicting Tank Self-Pressurization in the Ground-Based K-Site Experiment

A two-phase CFD model for self-pressurization of a cryogenic storage tank partially filled with liquid hydrogen is presented using the Volume-Of-Fluid approach for modeling two-phase flow, as well as interfacial heat, mass and momentum transfer between the liquid and vapor regions. The CFD model is validated against self-pressurization experiment performed using the K-site flightweight hydrogen storage tank at NASA Glenn Research Center 1 . Laminar and turbulent simulations are performed together with conjugate heat transfer analysis. Effects of turbulence, the value of accommodation coefficient used for predicting phase change rates, as well as tank wall geometry are presented and discussed. Predicted tank pressures, fluid and wall temperatures are compared with the experimental data at 49% fill level and two different heat loads for validating this CFD model.

Computational Fluid Dynamics↗
NASA NTRS1989

Performance optimization for rotors in hover and axial flight

Performance optimization for rotors in hover and axial flight is a topic of continuing importance to rotorcraft designers. The aim of this Phase 1 effort has been to demonstrate that a linear optimization algorithm could be coupled to an existing influence coefficient hover performance code. This code, dubbed EHPIC (Evaluation of Hover Performance using Influence Coefficients), uses a quasi-linear wake relaxation to solve for the rotor performance. The coupling was accomplished by expanding of the matrix of linearized influence coefficients in EHPIC to accommodate design variables and deriving new coefficients for linearized equations governing perturbations in power and thrust. These coefficients formed the input to a linear optimization analysis, which used the flow tangency conditions on the blade and in the wake to impose equality constraints on the expanded system of equations; user-specified inequality contraints were also employed to bound the changes in the design. It was found that this locally linearized analysis could be invoked to predict a design change that would produce a reduction in the power required by the rotor at constant thrust. Thus, an efficient search for improved versions of the baseline design can be carried out while retaining the accuracy inherent in a free wake/lifting surface performance analysis.

Quackenbush, T. R.↗
NASA NTRS1989

Optimization of rotor performance in hover and axial flight using a free wake analysis

Performance optimization for rotors in hover and axial flight is a topic of continuing importance to rotorcraft designers. The aim of this effort was to demonstrate that a numerical performance optimization algorithm could be coupled to an existing free wake hover code. This code, dubbed EHPIC (Evaluation of Hover Performacne using Influence Coefficients), uses a quasi-linear wake relaxation to solve for the rotor performance. The coupling was accomplished by expanding of the matrix of linearized influence coefficients in EHPIC to accommodate design variables and by deriving new coefficients for linearized equations governing perturbations in power and thrust. These coefficients formed the input to a linear optimization analysis, which used the flow tangency conditions on the blade and in the wake to impose equality constraints on the expanded system of equations; user-specified inequality constraints were also employed to bound the changes in the design. It was found that this locally linearized analysis could be invoked to predict a design change that would produce a reduction in the power required by the rotor at constant thrust. Thus, an efficient search for improved versions of the baseline design can be carried out while retaining the accuracy inherent in a free wake/lifting surface performance analysis. A variety of sample problems were undertaken to demonstrate the success of this approach in reducing the power required at a specified thrust for several representative rotor configurations in hover and axial flight.

Quackenbush, T. R.↗