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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 271 records · Page 15

Effect of Residual Noncondensables on Pressurization and Pressure Control of a Zero-Boil-Off Tank in Microgravity

The Zero-Boil-Off Tank (ZBOT) Experiment is a small-scale experiment that uses a transparent ventless Dewar and a transparent simulant phase-change fluid to study sealed tank pressurization and pressure control with applications to on-surface and in-orbit storage of propellant cryogens. The experiment will be carried out under microgravity conditions aboard the International Space Station in the 2014 timeframe. This paper presents preliminary results from ZBOT's ground-based research that focuses on the effects of residual noncondensable gases in the ullage on both pressurization and pressure reduction trends in the sealed Dewar. Tank pressurization is accomplished through heating of the test cell wall in the wetted and un-wetted regions simultaneously or separately. Pressure control is established through mixing and destratification of the bulk liquid using a temperature controlled forced jet flow with different degrees of liquid jet subcooling. A Two-Dimensional axisymmetric two-phase CFD model for tank pressurization and pressure control is also presented. Numerical prediction of the model are compared to experimental 1g results to both validate the model and also indicate the effect of the noncondensable gas on evolution of pressure and temperature distributions in the ullage during pressurization and pressure control. Microgravity simulations case studies are also performed using the validated model to underscore and delineate the profound effect of the noncondensables on condensation rates and interfacial temperature distributions with serious implications for tank pressure control in reduced gravity.

Marangoni and Natural Convection↗

Simscape Modeling of a Custom Closed-Volume Tank

The library for Mathworks Simscape does not currently contain a model for a closed volume fluid tank where the ullage pressure is variable. In order to model a closed-volume variable ullage pressure tank, it was necessary to consider at least two separate cases: a vertical cylinder, and a sphere. Using library components, it was possible to construct a rough model for the cylindrical tank. It was not possible to construct a model for a spherical tank, using library components, due to the variable area. It was decided that, for these cases, it would be preferable to create a custom library component to represent each case, using the Simscape language. Once completed, the components were added to models, where filling and draining the tanks could be simulated. When the models were performing as expected, it was necessary to generate code from the models and run them in Trick (a real-time simulation program). The data output from Trick was then compared to the output from Simscape and found to be within acceptable limits.

Simscape↗

Computational Fluid Dynamics Based Extraction of Heat Transfer Coefficient in Cryogenic Propellant Tanks

Current reduced-order thermal model for cryogenic propellant tanks is based on correlations built for flat plates collected in the 1950's. The use of these correlations suffers from: inaccurate geometry representation; inaccurate gravity orientation; ambiguous length scale; and lack of detailed validation. The work presented under this task uses the first-principles based Computational Fluid Dynamics (CFD) technique to compute heat transfer from tank wall to the cryogenic fluids, and extracts and correlates the equivalent heat transfer coefficient to support reduced-order thermal model. The CFD tool was first validated against available experimental data and commonly used correlations for natural convection along a vertically heated wall. Good agreements between the present prediction and experimental data have been found for flows in laminar as well turbulent regimes. The convective heat transfer between tank wall and cryogenic propellant, and that between tank wall and ullage gas were then simulated. The results showed that commonly used heat transfer correlations for either vertical or horizontal plate over predict heat transfer rate for the cryogenic tank, in some cases by as much as one order of magnitude. A characteristic length scale has been defined that can correlate all heat transfer coefficients for different fill levels into a single curve. This curve can be used for the reduced-order heat transfer model analysis.

Yang, H. Q.↗

CFD Extraction of Heat Transfer Coefficient in Cryogenic Propellant Tanks

Current reduced-order thermal model for cryogenic propellant tanks is based on correlations built for flat plates collected in the 1950's. The use of these correlations suffers from inaccurate geometry representation; inaccurate gravity orientation; ambiguous length scale; and lack of detailed validation. This study uses first-principles based CFD methodology to compute heat transfer from the tank wall to the cryogenic fluids and extracts and correlates the equivalent heat transfer coefficient to support reduced-order thermal model. The CFD tool was first validated against available experimental data and commonly used correlations for natural convection along a vertically heated wall. Good agreements between the present prediction and experimental data have been found for flows in laminar as well turbulent regimes. The convective heat transfer between the tank wall and cryogenic propellant, and that between the tank wall and ullage gas were then simulated. The results showed that the commonly used heat transfer correlations for either vertical or horizontal plate over-predict heat transfer rate for the cryogenic tank, in some cases by as much as one order of magnitude. A characteristic length scale has been defined that can correlate all heat transfer coefficients for different fill levels into a single curve. This curve can be used for the reduced-order heat transfer model analysis.

Yang, H. Q.↗

CFD Modeling of the Multipurpose Hydrogen Test Bed (MHTB) Self-Pressurization and Spray Bar Mixing Experiments in Normal Gravity: Effect of the Accommodation Coefficient on the Tank Pressure

A CFD model for simulating the self-pressurization of a large scale liquid hydrogen storage tank is utilized in this paper to model the MHTB self-pressurization experiment. The kinetics-based Schrage equation is used to account for the evaporative and condensi ng interfacial mass flows in this model. The effect of the accommodation coefficient for calculating the interfacial mass transfer rate on the tank pressure during tank selfpressurization is studied. The values of the accommodation coefficient which were considered in this study vary from 1.0e-3 to 1.0e-1 for the explicit VOF model and from 1.0e-4 to 1.0e-3 for the implicit VOF model. The ullage pressure evolutions are compared against experimental data. A CFD model for controlling pressure in cryogenic storage tanks by spraying cold liquid into the ullage is also presented. The Euler-Lagrange approach is utilized for tracking the spray droplets and for modeling the interaction between the droplets and the continuous phase (ullage). The spray model is coupled with the VOF 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, as well as droplets trajectories, size distribution and temperatures predicted by the model are presented. The ul lage pressure and vapor temperature evolutions are compared with experimental data obtained from the MHTB spray bar mixing experiment. The effect of the accommodation coefficient for calculating the interfacial and droplet mass transfer rates on the tank pressure during mixing of the vapor using spray is studied. The values used for the accommodation coefficient at the interface vary from 1.0e-5 to 1.0e-2. The droplet accommodation coefficient values vary from 2.0e-6 to 1.0e-4.

cryogenic fluid storage↗

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↗

Validation of High-Resolution CFD Method for Slosh Damping Extraction of Baffled Tanks

Determination of slosh damping is a very challenging task as there is no analytical solution. The damping physics involve the vorticity dissipation which requires the full solution of the nonlinear Navier-Stokes equations. As a result, previous investigations and knowledge were mainly carried out by extensive experimental studies. A Volume-Of-Fluid (VOF) based CFD program developed at NASA MSFC was applied to extract slosh damping in a baffled tank from the first principle. First, experimental data using water with subscale smooth wall tank were used as the baseline validation. CFD simulation was demonstrated to be capable of accurately predicting natural frequency and very low damping value from the smooth wall tank at different fill levels. The damping due to a ring baffle at different liquid fill levels from barrel section and into the upper dome was then investigated to understand the slosh damping physics due to the presence of a ring baffle. Based on this study, the Root-Mean-Square error of our CFD simulation in estimating slosh damping was less than 4.8%, and the maximum error was less than 8.5%. Scalability of subscale baffled tank test using water was investigated using the validated CFD tool, and it was found that unlike the smooth wall case, slosh damping with baffle is almost independent of the working fluid and it is reasonable to apply water test data to the full scale LOX tank when the damping from baffle is dominant. On the other hand, for the smooth wall, the damping value must be scaled according to the Reynolds number. Comparison of experimental data, CFD, with the classical and modified Miles equations for upper dome was made, and the limitations of these semi-empirical equations were identified.

Yang, H. Q.↗

Experimental Thermal Performance Testing of Cryogenic Tank Systems and Materials

A comparative study was conducted to collect and analyze thermal conductivity data on a wide variety of low density materials, as well as thermal performance data on a number of vacuum-jacketed cryogenic tank systems. Although a vast number of these types of materials and cryogenic tank systems exist, the thermal conductivity of insulation materials and the thermal performance of cryogenic tank systems is often difficult to compare because many industrial methods and experimental conditions are available and utilized. The availability of a new thermal conductivity measurement device, the Macroflash Cup Cryostat, which is applicable for assessing a variety of materials, is accessible at NASA's Cryogenic Test Laboratory (CTL) at the Kennedy Space Center (KSC). The convenience of this device has resulted in the ability to rapidly measure the thermal conductivity properties of these materials by using a flat-plate liquid nitrogen (LN2) boiloff technique that employs a guarded heat flow test methodology in order to determine the effective thermal conductivity (ke) of a test specimen. As the thermal conductivities are measured at cryogenic temperatures, materials suitable for both future space missions and cryogenic tank systems can be identified and experimentally analyzed. Also recognizable are materials which may help increase energy efficiency by limiting the thermal losses encountered under various environmental conditions. The overall focus of this work consisted of two parts. One part, was to produce and analyze thermal conductivity data on a wide variety of materials with suitable properties conducive to those needed to aid in the production of a calibration curve for the "low end" of the Macroflash instrument. (Low end meaning materials with a thermal conductivity rating below 100 milliwatts per meter-Kelvin). The second part was to collect and analyze heat transfer data for a variety of small vacuum-jacketed vessels (cryogenic tank systems) in order to compare the thermal performance between them.

Myers, Wesley C.↗

Validation of a CFD Model Predicting the Effect of High Level Lateral Acceleration Sloshing on the Heat Transfer and Pressure Drop in a Small-Scale Tank in Normal Gravity

A two-phase CFD model is developed to study the effects of sloshing with high level lateral acceleration on the heat transfer and pressure drop in a small scale tank. Computational results are compared to the data provided by a non-isothermal sloshing experiment without phase change conducted by T. Himeno et al. at the University of Tokyo and JAXA in 2011. The results of the current model are, also, compared to CFD predictions reported by Himeno et al. A step change in lateral acceleration was applied in the experiment. Different levels of lateral acceleration amplitude, varying between 0G and 0.5G, were considered. CFD results for interface movement and tank pressure are presented and compared in this paper to the experimental data for the case in which the value of lateral acceleration was set to 0.5G. The effects of initial and boundary conditions and turbulence modeling approach on the tank pressure change during sloshing are discussed in detail. The effect of conjugate heat transfer in the tank wall is also studied to show its important role in determining the tank pressure evolution. The results of the Reynolds Averaged Navier Stokes (RANS) models are compared to the results of the Large Eddy Simulation model (LES) to underscore the importance of correctly capturing the effects of turbulence for high fidelity predictions.

multiphase flow↗

Validation of A CFD Model Predicting the Effect of High Level Lateral Acceleration Sloshing on the Heat Transfer and Pressure Drop in A Small-Scale Tank in Normal Gravity

A two-phase CFD model is developed to study the effects of sloshing with high level lateral acceleration on the heat transfer and pressure drop in a small scale tank. Computational results are compared to the data provided by a non-isothermal sloshing experiment without phase change conducted by T. Himeno et al. at the University of Tokyo and JAXA in 2011 [1]. The results of the current model are, also, compared to CFD predictions reported by Himeno et al. [2]. A step change in lateral acceleration was applied in the experiment. Different levels of lateral acceleration amplitude, varying between 0G and 0.5G, were considered. CFD results for interface movement and tank pressure are presented and compared in this paper to the experimental data for the case in which the value of lateral acceleration was set to 0.5G. The effects of initial and boundary conditions and turbulence modeling approach on the tank pressure change during sloshing are discussed in detail. The effect of conjugate heat transfer in the tank wall is also studied to show its important role in determining the tank pressure evolution. The results of the Reynolds Averaged Navier Stokes (RANS) models are compared to the results of the Large Eddy Simulation model (LES) to underscore the importance of correctly capturing the effects of turbulence for high fidelity predictions.

multiphase flow↗

Multi-Node Modeling of Cryogenic Tank Pressurization System Using Generalized Fluid System Simulation Program

Cryogenic Tanks are pressurized by inert gas such as Helium or Nitrogen to maintain the required pressure of the propellant delivered to the turbo-pump of a liquid rocket engine. Thermo-fluid system simulation tools are used to analyze the pressurization process of a cryogenic tank. Most system level codes (GFSSP and ROCETS) use single node1 to represent ullage which is the gaseous space in the tank. Ullage space in a cryogenic tank is highly stratified because the entering inert gas is at ambient temperature whereas the liquid propellant is at a cryogenic temperature. A single node model does not account for the effect of temperature gradient in the ullage. High fidelity Navier-Stokes based CFD model of Tank Pressurization is not practical for running a long duration transient model with thousands and millions of nodes. A possible recourse is to construct a multi-node model with system level code that can account for ullage stratification.

Bandyopadhyay, Alak↗

Vapor Cooling of a Structural Skirt for a Large-Scale Hydrogen Tank

The demonstration of vapor cooling on a structural skirt was one of the main objectives of the Structural Heat Intercept, Insulation, and Vibration Evaluation Rig (SHIIVER) testing. SHIIVER consisted of a 4-meter diameter stainless steel tank with an aluminum forward skirt. The forward skirt was cooled by directing effluent vapor from the tank through two flow channels that each went 360 degrees around the interior of the skirt in a helical pattern. Flow rates, temperatures, and pressures in the system were measured allowing for the calculation of heat load removed via cooling stream and heat load reduction into the tank. Testing occurred at fill levels between 25% and 90% full using both liquid hydrogen and liquid nitrogen. Boil-off rate was varied independent of the skirt performance by adding multilayer insulation over the spray-on-foam insulation on the tank domes, while leaving the barrel insulated only with spray-on-foam. The results from the testing, which demonstrate vapor cooling reversed heat flow from the skirt into the tank and reduces total propellant heat load by as much as 19%, are analyzed and discussed.

Cryogenic Fluid Management↗

Numerical Prediction of Heat Transfer Coefficients during Xenon Tank Fill in Microgravity

NASA’s Gateway will serve as an orbital outpost to enable sustained human lunar exploration and facilitate access to destinations beyond the Moon. To maintain sustainable deep space missions, on-orbit propellant transfer and refueling must be realized. One of Gateway’s critical components, the Power and Propulsion Element (PPE), will use solar electric propulsion to perform attitude control maneuvers and orbit transfers. Xenon will be used as the propellant for the PPE and stored in a composite overwrapped pressure vessel (COPV). During the propellant refueling process, xenon will compress causing the fluid and tank walls to warm. There is concern that the bond between the tank liner and composite may degrade at elevated temperatures, along with the possibility of the tank exceeding design pressure. While on-orbit testing is being proposed, numerical models are being used to predict the thermal response and reduce risk during a refueling operation in microgravity where natural convection is diminished. Accurate numerical models may be used to inform decisions for follow-on testing, or design and operation of refueling architectures. Challenges of modeling xenon tank fill in microgravity include non-ideal gas behavior, operating near the fluid’s critical point, and lack of experimental flight data. This study presents a computational fluid dynamics (CFD) model with conjugate heat transfer that is used to predict averaged heat transfer coefficients during tank filling. At the anticipated injection flow rates, the CFD results showed that forced convection dominates in microgravity. Initial results from a multi-node Thermal Desktop model that assumed a purely conducting fluid (Nu=1) over-predicted the CFD fluid temperature and pressure, while a similar model allowing for natural convection under-predicted. The heat transfer coefficients predicted by CFD were implemented into the multi-node model, and the COPV thermal response from the two computational approaches were compared with good agreement.

Heat Transfer↗

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↗

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↗

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↗

CFD Modeling of Tank Pressurization and Axial Jet Mixing Experiments with and without Non-Condensable Gas in the Ullage

A two-phase CFD model for tank pressurization and following jet mixing of a cryogenic storage tank is presented using VOF approach for representing the phase boundary and the associated interfacial heat, mass and momentum transfer between the liquid and vapor regions. The CFD model was validated against pressurization and liquid jet mixing data for a 110-inch diameter tank provided by Bullard1. Cases with like-gas and non-condensable gas pressurization are studied. The results of the cases with like-gas pressurization and following mixing are presented first, focusing on the effects of turbulence at the vapor-liquid interface on the tank pressure and phase change rates predictions. The second part of this paper is devoted to testing and validating the CFD model against non-condensable gas pressurization and following mixing. Tank pressures predicted in both cases are compared with each other and with the experimental data.

Computational Fluid Dynamics↗

Validation of a Two-Phase CFD Model for Predicting Propellant Tank Pressurization and Pressure Collapse in The Ground-Based K-Site Hydrogen Slosh Experiment

A two-phase CFD model for tank pressurization and following sloshing in a cryogenic storage tank partially filled with liquid hydrogen is presented using the Volume-Of-Fluid approach for representing the phase boundary and the associated interfacial heat, mass and momentum transfer between the liquid and the vapor regions. The CFD model was validated against pressurization and sloshing data for a 62 cubic foot tank provided by Moran et al. Cases with different sloshing amplitudes and frequencies are studied. The results of modeling tank pressurization are presented first followed by the results of sloshing cases. Predicted tank pressures are compared with the experimental data.

Computational Fluid Dynamics↗