Results for “Mixing thermodynamics” — Page 10

NASA NTRS1983

Thermodynamic analysis of journal bearings operating under steady state loading in laminar regime

Thermohydrodynamic effects in journal bearings operating under steady load in laminar regime are investigated. An analytical model for the finite and infinitely long journal bearings is formulated. The model includes correction factors for the cavitation effects in the unloaded region of the bearing and the mixing of the recirculating oil and supply oil at the oil inlet. A finite difference computer program is developed to numerically solve the governing equations of the continuity, Reynolds, energy, Laplace heat conduction, and a viscosity-temperature relation simultaneously. The program includes a numerical technique for obtaining an isothermal shaft temperature. The numerical results of temperature distribution and the heat effects on the bearing load carrying capacity agree closely with those of experimental findings. Several different sets of simpler boundary conditions for the energy equation are studied.

Khonsari, M. M.↗

NASA NTRS1998

Some Comments on the Status of Shell Theory at the End of the 20th Century: Complaints and Correctives

This review is divided into complaints and correctives. Complaints are directed at: sloppy refereeing and editing; authors who fail to read or acknowledge what others have done; the mis-naming or mis-crediting of results; the misunderstanding and misuse of the Kirchhoff hypothesis; inflated claims of accuracy based on overly-simplified benchmark problems; the failure to appreciate the inherent errors in various shell models; the failure to appreciate that the physical response and mathematical structure of shell theory are fundamentally different from 3-dimensional elasticity; and the irrelevance of Cosserat-type theories. Correctives include a simple, straight-forward derivation of a general nonlinear dynamic shell theory with the following features: (1) the equations of motion and kinematics (and those of thermodynamics, if desired) are exact consequences of their 3-dimensional counterparts; (2) there are no asymptotic or series expansions through the thickness; (3) all approximations (including the Kirchhoff Hypothesis) occur in the constitutive relations; (4) in static problems, there is a mixed form of the governing equations involving a mixed-energy density and exhibiting remnants of the well-known static-geometric duality of linear theory which is numerically robust because the limiting cases of nonlinear membrane theory and inextensional bending theory fall out naturally. (These latter two special cases are known to produce numerical nightmares unless treated with great care); and (5) all equations may be expressed in coordinate-free form (although, sometimes, a hybrid form is shown to be superior).

Simmonds, James G.↗

NASA NTRSDate not supplied

High-Resolution Global Ocean Simulation in the SWOT ERA: Introducing ECCO Llc4320v2

The Surface Water and Ocean Topography (SWOT) mission is opening up new opportunities to evaluate and drive improvement in km-scale global ocean and atmosphere-ocean models via its simultaneous swath observations of sea-surface height, wind speed, and significant wave height down to 2 km scales globally. Motivated by this, we have initiated a collaborative effort at NASA Ames to run a new global ocean-sea-ice simulation in MITgcm at a nominal 1/48-deg resolution of the year 2023 that enables direct comparisons with SWOT observations. New features relative to a prior simulation at a similar resolution of the year 2012 include much more realistic tidal forcing, thermodynamic coupling in ice-shelf cavities, high-frequency hourly atmospheric forcing, much improved river runoff, double the vertical resolution in the deep ocean (173 vs 90 levels), updated bathymetry including improvements in finescale bathymetry derived from SWOT, and updated vertical mixing scheme parameters that improve the equatorial Pacific circulation.

ECCO↗

NASA NTRS2012

Simulation of Oxygen Disintegration and Mixing With Hydrogen or Helium at Supercritical Pressure

The simulation of high-pressure turbulent flows, where the pressure, p, is larger than the critical value, p(sub c), for the species under consideration, is relevant to a wide array of propulsion systems, e.g. gas turbine, diesel, and liquid rocket engines. Most turbulence models, however, have been developed for atmospheric-p turbulent flows. The difference between atmospheric-p and supercritical-p turbulence is that, in the former situation, the coupling between dynamics and thermodynamics is moderate to negligible, but for the latter it is very significant, and can dominate the flow characteristics. The reason for this stems from the mathematical form of the equation of state (EOS), which is the perfect-gas EOS in the former case, and the real-gas EOS in the latter case. For flows at supercritical pressure, p, the large eddy simulation (LES) equations consist of the differential conservation equations coupled with a real-gas EOS. The equations use transport properties that depend on the thermodynamic variables. Compared to previous LES models, the differential equations contain not only the subgrid scale (SGS) fluxes, but also new SGS terms, each denoted as a correction. These additional terms, typically assumed null for atmospheric pressure flows, stem from filtering the differential governing equations, and represent differences between a filtered term and the same term computed as a function of the filtered flow field. In particular, the energy equation contains a heat-flux correction (q-correction) that is the difference between the filtered divergence of the heat flux and the divergence of the heat flux computed as a function of the filtered flow field. In a previous study, there was only partial success in modeling the q-correction term, but in this innovation, success has been achieved by using a different modeling approach. This analysis, based on a temporal mixing layer Direct Numerical Simulation database, shows that the focus in modeling the q-correction should be on reconstructing the primitive variable gradients rather than their coefficients, and proposes the approximate deconvolution model (ADM) as an effective means of flow field reconstruction for LES heat flux calculation. Further, results for a study conducted for temporal mixing layers initially containing oxygen in the lower stream, and hydrogen or helium in the upper stream, show that, for any LES, including SGS-flux models (constant-coefficient Gradient or Scale-Similarity models, dynamic-coefficient Smagorinsky/Yoshizawa or mixed Smagorinsky/Yoshizawa/Gradient models), the inclusion of the q-correction in the LES leads to the theoretical maximum reduction of the SGS heat-flux difference. The remaining error in modeling this new subgrid term is thus irreducible.

Bellan, Josette↗

NASA NTRS1990

A cloudiness transition in a marine boundary layer

In situ aircraft data and lidar data are used to analyze a transition in the boundary layer thermodynamic structure from a clear boundary layer through small cumulus and broken stratocumulus to a deck of solid stratocumulus. The data was collected in conjunction with a Landsat overpass on July 7, 1987 off the coast of southern California. A steady progression in mixing line stability is seen associated with the change in cloudiness. The (empirically based) stability threshold for the breakup of this stratocumulus is that the slope of the mixing line is 0.66 + or - 0.04 of the slope of the wet virtual adiabat. A simple linear parameterization is proposed for cloud fraction in terms of mixing line stability. Surface flux measurements are consistent with bulk aerodynamic estimates.

Boers, Reinout↗

NASA NTRS2004

Sliding Mode Control of a Thermal Mixing Process

In this paper we consider the robust control of a thermal mixer using multivariable Sliding Mode Control (SMC). The mixer consists of a mixing chamber, hot and cold fluid valves, and an exit valve. The commanded positions of the three valves are the available control inputs, while the controlled variables are total mass flow rate, chamber pressure and the density of the mixture inside the chamber. Unsteady thermodynamics and linear valve models are used in deriving a 5th order nonlinear system with three inputs and three outputs, An SMC controller is designed to achieve robust output tracking in the presence of unknown energy losses between the chamber and the environment. The usefulness of the technique is illustrated with a simulation.

Richter, Hanz↗

NASA NTRS1979

WETAIR: A computer code for calculating thermodynamic and transport properties of air-water mixtures

A computer program subroutine, WETAIR, was developed to calculate the thermodynamic and transport properties of air water mixtures. It determines the thermodynamic state from assigned values of temperature and density, pressure and density, temperature and pressure, pressure and entropy, or pressure and enthalpy. The WETAIR calculates the properties of dry air and water (steam) by interpolating to obtain values from property tables. Then it uses simple mixing laws to calculate the properties of air water mixtures. Properties of mixtures with water contents below 40 percent (by mass) can be calculated at temperatures from 273.2 to 1497 K and pressures to 450 MN/sq m. Dry air properties can be calculated at temperatures as low as 150 K. Water properties can be calculated at temperatures to 1747 K and pressures to 100 MN/sq m. The WETAIR is available in both SFTRAN and FORTRAN.

Fessler, T. E.↗

NASA NTRS2001

Processes Controlling Water Vapor in the Winter Arctic Tropopause Region

This work describes transport and thermodynamic processes that control water vapor near the tropopause during the SAGE Ozone Loss and Validation Experiment (SOLVE), held during the Arctic 1999-2000 winter season. Aircraft based water vapor, carbon monoxide, and ozone measurements are analyzed so as to establish how deeply tropospheric air mixes into the arctic lower-most stratosphere, and what the implications are for cloud formation and water vapor removal in this region of the atmosphere. There are three major findings. First, troposphere-to- stratosphere exchange extends into the arctic stratosphere to about 13 km. Penetration is to similar levels throughout the winter, however, because ozone increases idly in the early spring, tropospheric air mixes with the highest values of ozone in that season. The effect of this upward mixing is to elevate water vapor mixing ratios significantly above their prevailing stratospheric values of about 5 ppmv. Second, the potential for cloud formation in the stratosphere is highest during early spring, with about 20\% of the parcels which have ozone values of 300-350ppbv experiencing ice saturation in a given 10 day period. Third, during early Spring temperatures at the tropopause are cold enough so that 5-10\% of parcels experience relative humidities above 100\%, even if the water content is as low as 5 ppmv. The implication is that during, this period the arctic tropopause can play an important role in maintaining a very dry upper troposphere during early Spring.

Pfister, Leonhard↗

NASA NTRS2015

Use of Generalized Fluid System Simulation Program (GFSSP) for Teaching and Performing Senior Design Projects at the Educational Institutions

This paper describes the experience of the authors in using the Generalized Fluid System Simulation Program (GFSSP) in teaching Design of Thermal Systems class at University of Alabama in Huntsville. GFSSP is a finite volume based thermo-fluid system network analysis code, developed at NASA/Marshall Space Flight Center, and is extensively used in NASA, Department of Defense, and aerospace industries for propulsion system design, analysis, and performance evaluation. The educational version of GFSSP is freely available to all US higher education institutions. The main purpose of the paper is to illustrate the utilization of this user-friendly code for the thermal systems design and fluid engineering courses and to encourage the instructors to utilize the code for the class assignments as well as senior design projects. The need for a generalized computer program for thermofluid analysis in a flow network has been felt for a long time in aerospace industries. Designers of thermofluid systems often need to know pressures, temperatures, flow rates, concentrations, and heat transfer rates at different parts of a flow circuit for steady state or transient conditions. Such applications occur in propulsion systems for tank pressurization, internal flow analysis of rocket engine turbopumps, chilldown of cryogenic tanks and transfer lines, and many other applications of gas-liquid systems involving fluid transients and conjugate heat and mass transfer. Computer resource requirements to perform time-dependent, three-dimensional Navier-Stokes computational fluid dynamic (CFD) analysis of such systems are prohibitive and therefore are not practical. Available commercial codes are generally suitable for steady state, single-phase incompressible flow. Because of the proprietary nature of such codes, it is not possible to extend their capability to satisfy the above-mentioned needs. Therefore, the Generalized Fluid System Simulation Program (GFSSP1) has been developed at NASA Marshall Space Flight Center (MSFC) as a general fluid flow system solver capable of handling phase changes, compressibility, mixture thermodynamics and transient operations. It also includes the capability to model external body forces such as gravity and centrifugal effects in a complex flow network. The objectives of GFSSP development are: a) to develop a robust and efficient numerical algorithm to solve a system of equations describing a flow network containing phase changes, mixing, and rotation; and b) to implement the algorithm in a structured, easy-to-use computer program. The analysis of thermofluid dynamics in a complex network requires resolution of the system into fluid nodes and branches, and solid nodes and conductors as shown in Figure 1. Figure 1 shows a schematic and GFSSP flow circuit of a counter-flow heat exchanger. Hot nitrogen gas is flowing through a pipe, colder nitrogen is flowing counter to the hot stream in the annulus pipe and heat transfer occurs through metal tubes. The problem considered is to calculate flowrates and temperature distributions in both streams. GFSSP has a unique data structure, as shown in Figure 2, that allows constructing all possible arrangements of a flow network with no limit on the number of elements. The elements of a flow network are boundary nodes where pressure and temperature are specified, internal nodes where pressure and temperature are calculated, and branches where flowrates are calculated. For conjugate heat transfer problems, there are three additional elements: solid node, ambient node, and conductor. The solid and fluid nodes are connected with solid-fluid conductors. GFSSP solves the conservation equations of mass and energy, and equation of state in internal nodes to calculate pressure, temperature and resident mass. The momentum conservation equation is solved in branches to calculate flowrate. It also solves for energy conservation equations to calculate temperatures of solid nodes. The equations are coupled and nonlinear; therefore, they are solved by an iterative numerical scheme. GFSSP employs a unique numerical scheme known as simultaneous adjustment with successive substitution (SASS), which is a combination of Newton-Raphson and successive substitution methods. The mass and momentum conservation equations and the equation of state are solved by the Newton-Raphson method while the conservation of energy and species are solved by the successive substitution method. GFSSP is linked with two thermodynamic property programs, GASP2 and WASP3 and GASPAK4, that provide thermodynamic and thermophysical properties of selected fluids. Both programs cover a range of pressure and temperature that allows fluid properties to be evaluated for liquid, liquid-vapor (saturation), and vapor region. GASP and WASP provide properties of 12 fluids. GASPAK includes a library of 36 fluids. GFSSP has three major parts. The first part is the graphical user interface (GUI), visual thermofluid analyzer of systems and components (VTASC). VTASC allows users to create a flow circuit by a 'point and click' paradigm. It creates the GFSSP input file after the completion of the model building process. GFSSP's GUI provides the users a platform to build and run their models. It also allows post-processing of results. The network flow circuit is first built using three basic elements: boundary node, internal node, and branch.

Majumdar, A. K.↗

NASA NTRS2017

Computational and Experimental Characterization of the Mach 6 Facility Nozzle Flow for the Enhanced Injection and Mixing Project at NASA Langley Research Center

Computational fluid dynamics analyses and experimental data are presented for the Mach 6 facility nozzle used in the Arc-Heated Scramjet Test Facility for the Enhanced Injection and Mixing Project (EIMP). This project, conducted at the NASA Langley Research Center, aims to investigate supersonic combustion ramjet (scramjet) fuel injection and mixing physics relevant to flight Mach numbers greater than 8. The EIMP experiments use a two-dimensional Mach 6 facility nozzle to provide the high-speed air simulating the combustor entrance flow of a scramjet engine. Of interest are the physical extent and the thermodynamic properties of the core flow at the nozzle exit plane. The detailed characterization of this flow is obtained from three-dimensional, viscous, Reynolds-averaged simulations. Thermodynamic nonequilibrium effects are also investigated. The simulations are compared with the available experimental data, which includes wall static pressures as well as in-stream static pressure, pitot pressure and total temperature obtained via in-stream probes positioned just downstream of the nozzle exit plane.

Drozda, Tomasz G.↗

NASA NTRSDate not supplied

Modeling and Simulation of Tank Pressure Control using Zero-Boil Off Active Thermal Control for LOXSAT Technology Demonstration Mission

To-date, research and modeling of cryogenic fluid management technologies (CFM) for spaceflight has been limited to ground tests, short-duration zero-g simulations (e.g. drop towers), and small-scale experiments on-orbit. There has not been a large-scale flight demonstration of a flight-like system. As future NASA missions to take humans further from Earth will require large, in-space cryogenic propulsion vehicles, it is imperative to begin collecting flight data for these systems to accurately model and design future vehicles. To meet this goal, NASA awarded tipping point technology demonstration awards to Eta Space, Lockheed Martin, Space Exploration Technologies (SpaceX), and United Launch Alliance (ULA) to demonstrate on-orbit storage and transfer of cryogenic propellant. For its award, Eta Space is developing LOXSAT-1. It is a small satellite that will be launched on a Rocket Lab Electron rocket. The spacecraft consists of a Rocket Lab Photon spacecraft bus with a primary payload of a spherical liquid oxygen (LOX) storage tank with thermodynamic control systems. The primary objective of the mission is to demonstrate zero-boil-off storage of liquid oxygen. To accomplish this objective, the payload is equipped with an active thermal control system fluid loop that consists of propellant management device (PMD), positive-displacement pump, heat exchanger connected to a cryocooler, and a spray bar mixing injector. When the fluid loop is operating, fluid is drawn from the tank by the PMD and pumped through the heat exchanger, lowering the fluid temperature below the fluid temperature in the tank. This subcooled liquid is then injected back into the tank through the spray bar. The subcooled injected liquid has two effects. If it is sprayed into the ullage space, the injected liquid will form into jets or droplets and exchange heat with the ullage gas. This will cool and condense the gas, reducing the pressure in the tank. Additionally, the liquid that is not sprayed through the ullage, as well as any remaining liquid spray from the ullage, will rejoin the liquid mass of the tank, lowering the bulk temperature of the liquid. These combines effects provide for zero-boil off pressure control by lowering the tank pressure and the liquid saturation pressure simultaneously, ensuring the liquid stays subcooled. To model these complex mechanics and predict the performance of the active thermal control system, NASA is providing Eta Space with 3 parallel models of the tank. The approach of providing 3 different models allows for cross-checking and comparisons between the three to better understand how different modeling assumptions and selection semi-empirical factors affects the modeling result. Additionally, developing 3 models provides three different schemes for numerical simulation, providing confidence that results depict real physical phenomenon and not numerical quirks of the program. Within the tank thermodynamics, there are two primary areas of heat transfer we concern ourselves with: the heat transfer between the ullage space and the droplet spray, and between the ullage space and bulk liquid. For the droplet heat transfer, there are multiple sets of assumptions that can be made and correlations that can be used. Currently, two working models - the TankSIM model and Easy5 model – provide for an overview of the different approaches available. The TankSIM model and Easy5 model use two different models for droplet heating and evaporation that illustrate how the models use different types of mechanisms to arrive at the same answer. For the TankSIM model, droplets are treated as spheres of constant radius. Heat is transferred from the ullage to the droplet and warms the droplet until it reaches saturation, then the droplet begins evaporating and reducing its radius and mass. To calculate the heat transfer coefficient between the droplet and ullage, the Ranz-Marshall correlation is used. To determine the number of droplets in the ullage, a resident mass approach is used. This approach averages the number of droplets such that residuals at the start-up and shut-off of the spray bar cancel out. This same approach is used in the Easy5 model. The GFSSP model implements a linked list to track individual droplet “nodes” within the model. For the Easy5 model, the droplet is assumed to have an interface at a temperature equal to the saturation temperature corresponding to the pressure of the gas phase. The heat transfer from the gas to the interface and the interface to the droplet bulk is then calculated, and the net mass transfer between the droplet and interface is determined by performing an energy balance across the interface. For the gas side of the interface, the Ranz-Marshall correlation is used. For the liquid side of the interface, a variety of correlations were tried, including Kronig and Brink (1950) and effective conductivity models. As a result of these assumptions, the Easy5 model currently predicts faster depressurization, as at saturated vapor conditions, the heat transfer coeffect on the liquid side for the Easy5 model is greater than the heat transfer coefficient predicted by Ranz-Marshall used in the TankSIM code. This greater heat flux translates into faster condensation of the saturated ullage gas. At the bulk liquid to ullage interface, the models are in much closer agreement. Both models model the ullage as a sphere centered within the bulk liquid in the tank, and both use the energy-jumping boundary condition to model heat and mass transfer across the interface. There are slight differences in how the interface temperature is calculated, however. The Easy5 model assumes the temperature of the interface is equal to the saturation temperature associated with the pressure of the gas phase. The TankSIM model calculates this temperature with Alabovskii’s equation, which provides a correction factor for interface temperatures. Analysis tasks are focused on determining rates of depressurization within the tank during active cooling operation. To maintain net positive suction head at the pump inlet, the tank pressure cannot fall faster than the saturation pressure associated with the temperature of the bulk liquid. Additionally, there is interest in analyzing the performance of the loop at different pump speeds and cryocooler input powers. Adjusting the flowrate affects both the performance of the heat exchanger between the cryocooler and pumped liquid, and the heat transfer between the droplet spray and the ullage. Ideally, a pump speed and cryocooler power can be selected that will allow the tank to operate in zero-boil-off mode with a very narrow range of storage pressure.

Cameron J. Hines↗

NASA NTRSDate not supplied

Modeling and Simulation of Tank Pressure Control using Zero-Boil Off Active Thermal Control for LOXSAT Technology Demonstration Mission

To-date, research and modeling of cryogenic fluid management technologies (CFM) for spaceflight has been limited to ground tests, short-duration zero-g simulations (e.g. drop towers), and small-scale experiments on-orbit. There has not been a large-scale flight demonstration of a flight-like system. As future NASA missions to take humans further from Earth will require large, in-space cryogenic propulsion vehicles, it is imperative to begin collecting flight data for these systems to accurately model and design future vehicles. To meet this goal, NASA awarded tipping point technology demonstration awards to Eta Space, Lockheed Martin, Space Exploration Technologies (SpaceX), and United Launch Alliance (ULA) to demonstrate on-orbit storage and transfer of cryogenic propellant. For its award, Eta Space is developing LOXSAT-1. It is a small satellite that will be launched on a Rocket Lab Electron rocket. The spacecraft consists of a Rocket Lab Photon spacecraft bus with a primary payload of a spherical liquid oxygen (LOX) storage tank with thermodynamic control systems. The primary objective of the mission is to demonstrate zero-boil-off storage of liquid oxygen. To accomplish this objective, the payload is equipped with an active thermal control system fluid loop that consists of propellant management device (PMD), positive-displacement pump, heat exchanger connected to a cryocooler, and a spray bar mixing injector. When the fluid loop is operating, fluid is drawn from the tank by the PMD and pumped through the heat exchanger, lowering the fluid temperature below the fluid temperature in the tank. This subcooled liquid is then injected back into the tank through the spray bar. The subcooled injected liquid has two effects. If it is sprayed into the ullage space, the injected liquid will form into jets or droplets and exchange heat with the ullage gas. This will cool and condense the gas, reducing the pressure in the tank. Additionally, the liquid that is not sprayed through the ullage, as well as any remaining liquid spray from the ullage, will rejoin the liquid mass of the tank, lowering the bulk temperature of the liquid. These combines effects provide for zero-boil off pressure control by lowering the tank pressure and the liquid saturation pressure simultaneously, ensuring the liquid stays subcooled. To model these complex mechanics and predict the performance of the active thermal control system, NASA is providing Eta Space with 3 parallel models of the tank. The approach of providing 3 different models allows for cross-checking and comparisons between the three to better understand how different modeling assumptions and selection semi-empirical factors affects the modeling result. Additionally, developing 3 models provides three different schemes for numerical simulation, providing confidence that results depict real physical phenomenon and not numerical quirks of the program. Within the tank thermodynamics, there are two primary areas of heat transfer we concern ourselves with: the heat transfer between the ullage space and the droplet spray, and between the ullage space and bulk liquid. For the droplet heat transfer, there are multiple sets of assumptions that can be made and correlations that can be used. Currently, two working models - the TankSIM model and Easy5 model – provide for an overview of the different approaches available. The TankSIM model and Easy5 model use two different models for droplet heating and evaporation that illustrate how the models use different types of mechanisms to arrive at the same answer. For the TankSIM model, droplets are treated as spheres of constant radius. Heat is transferred from the ullage to the droplet and warms the droplet until it reaches saturation, then the droplet begins evaporating and reducing its radius and mass. To calculate the heat transfer coefficient between the droplet and ullage, the Ranz-Marshall correlation is used. To determine the number of droplets in the ullage, a resident mass approach is used. This approach averages the number of droplets such that residuals at the start-up and shut-off of the spray bar cancel out. This same approach is used in the Easy5 model. The GFSSP model implements a linked list to track individual droplet “nodes” within the model. For the Easy5 model, the droplet is assumed to have an interface at a temperature equal to the saturation temperature corresponding to the pressure of the gas phase. The heat transfer from the gas to the interface and the interface to the droplet bulk is then calculated, and the net mass transfer between the droplet and interface is determined by performing an energy balance across the interface. For the gas side of the interface, the Ranz-Marshall correlation is used. For the liquid side of the interface, a variety of correlations were tried, including Kronig and Brink (1950) and effective conductivity models. As a result of these assumptions, the Easy5 model currently predicts faster depressurization, as at saturated vapor conditions, the heat transfer coeffect on the liquid side for the Easy5 model is greater than the heat transfer coefficient predicted by Ranz-Marshall used in the TankSIM code. This greater heat flux translates into faster condensation of the saturated ullage gas. At the bulk liquid to ullage interface, the models are in much closer agreement. Both models model the ullage as a sphere centered within the bulk liquid in the tank, and both use the energy-jumping boundary condition to model heat and mass transfer across the interface. There are slight differences in how the interface temperature is calculated, however. The Easy5 model assumes the temperature of the interface is equal to the saturation temperature associated with the pressure of the gas phase. The TankSIM model calculates this temperature with Alabovskii’s equation, which provides a correction factor for interface temperatures. Analysis tasks are focused on determining rates of depressurization within the tank during active cooling operation. To maintain net positive suction head at the pump inlet, the tank pressure cannot fall faster than the saturation pressure associated with the temperature of the bulk liquid. Additionally, there is interest in analyzing the performance of the loop at different pump speeds and cryocooler input powers. Adjusting the flowrate affects both the performance of the heat exchanger between the cryocooler and pumped liquid, and the heat transfer between the droplet spray and the ullage. Ideally, a pump speed and cryocooler power can be selected that will allow the tank to operate in zero-boil-off mode with a very narrow range of storage pressure.

zero boil-off↗

NASA NTRSDate not supplied

Modeling and Simulation of Tank Pressure Control using Zero-Boil Off Active Thermal Control for LOXSAT Technology Demonstration Mission

To-date, research and modeling of cryogenic fluid management technologies (CFM) for spaceflight has been limited to ground tests, short-duration zero-g simulations (e.g. drop towers), and small-scale experiments on-orbit. There has not been a large-scale flight demonstration of a flight-like system. As future NASA missions to take humans further from Earth will require large, in-space cryogenic propulsion vehicles, it is imperative to begin collecting flight data for these systems to accurately model and design future vehicles. To meet this goal, NASA awarded tipping point technology demonstration awards to Eta Space, Lockheed Martin, Space Exploration Technologies (SpaceX), and United Launch Alliance (ULA) to demonstrate on-orbit storage and transfer of cryogenic propellant. For its award, Eta Space is developing LOXSAT-1. It is a small satellite that will be launched on a Rocket Lab Electron rocket. The spacecraft consists of a Rocket Lab Photon spacecraft bus with a primary payload of a spherical liquid oxygen (LOX) storage tank with thermodynamic control systems. The primary objective of the mission is to demonstrate zero-boil-off storage of liquid oxygen. To accomplish this objective, the payload is equipped with an active thermal control system fluid loop that consists of propellant management device (PMD), positive-displacement pump, heat exchanger connected to a cryocooler, and a spray bar mixing injector. When the fluid loop is operating, fluid is drawn from the tank by the PMD and pumped through the heat exchanger, lowering the fluid temperature below the fluid temperature in the tank. This subcooled liquid is then injected back into the tank through the spray bar. The subcooled injected liquid has two effects. If it is sprayed into the ullage space, the injected liquid will form into jets or droplets and exchange heat with the ullage gas. This will cool and condense the gas, reducing the pressure in the tank. Additionally, the liquid that is not sprayed through the ullage, as well as any remaining liquid spray from the ullage, will rejoin the liquid mass of the tank, lowering the bulk temperature of the liquid. These combines effects provide for zero-boil off pressure control by lowering the tank pressure and the liquid saturation pressure simultaneously, ensuring the liquid stays subcooled. To model these complex mechanics and predict the performance of the active thermal control system, NASA is providing Eta Space with 3 parallel models of the tank. The approach of providing 3 different models allows for cross-checking and comparisons between the three to better understand how different modeling assumptions and selection semi-empirical factors affects the modeling result. Additionally, developing 3 models provides three different schemes for numerical simulation, providing confidence that results depict real physical phenomenon and not numerical quirks of the program. Within the tank thermodynamics, there are two primary areas of heat transfer we concern ourselves with: the heat transfer between the ullage space and the droplet spray, and between the ullage space and bulk liquid. For the droplet heat transfer, there are multiple sets of assumptions that can be made and correlations that can be used. Currently, two working models - the TankSIM model and Easy5 model – provide for an overview of the different approaches available. The TankSIM model and Easy5 model use two different models for droplet heating and evaporation that illustrate how the models use different types of mechanisms to arrive at the same answer. For the TankSIM model, droplets are treated as spheres of constant radius. Heat is transferred from the ullage to the droplet and warms the droplet until it reaches saturation, then the droplet begins evaporating and reducing its radius and mass. To calculate the heat transfer coefficient between the droplet and ullage, the Ranz-Marshall correlation is used. To determine the number of droplets in the ullage, a resident mass approach is used. This approach averages the number of droplets such that residuals at the start-up and shut-off of the spray bar cancel out. This same approach is used in the Easy5 model. The GFSSP model implements a linked list to track individual droplet “nodes” within the model. For the Easy5 model, the droplet is assumed to have an interface at a temperature equal to the saturation temperature corresponding to the pressure of the gas phase. The heat transfer from the gas to the interface and the interface to the droplet bulk is then calculated, and the net mass transfer between the droplet and interface is determined by performing an energy balance across the interface. For the gas side of the interface, the Ranz-Marshall correlation is used. For the liquid side of the interface, a variety of correlations were tried, including Kronig and Brink (1950) and effective conductivity models. As a result of these assumptions, the Easy5 model currently predicts faster depressurization, as at saturated vapor conditions, the heat transfer coeffect on the liquid side for the Easy5 model is greater than the heat transfer coefficient predicted by Ranz-Marshall used in the TankSIM code. This greater heat flux translates into faster condensation of the saturated ullage gas. At the bulk liquid to ullage interface, the models are in much closer agreement. Both models model the ullage as a sphere centered within the bulk liquid in the tank, and both use the energy-jumping boundary condition to model heat and mass transfer across the interface. There are slight differences in how the interface temperature is calculated, however. The Easy5 model assumes the temperature of the interface is equal to the saturation temperature associated with the pressure of the gas phase. The TankSIM model calculates this temperature with Alabovskii’s equation, which provides a correction factor for interface temperatures. Analysis tasks are focused on determining rates of depressurization within the tank during active cooling operation. To maintain net positive suction head at the pump inlet, the tank pressure cannot fall faster than the saturation pressure associated with the temperature of the bulk liquid. Additionally, there is interest in analyzing the performance of the loop at different pump speeds and cryocooler input powers. Adjusting the flowrate affects both the performance of the heat exchanger between the cryocooler and pumped liquid, and the heat transfer between the droplet spray and the ullage. Ideally, a pump speed and cryocooler power can be selected that will allow the tank to operate in zero-boil-off mode with a very narrow range of storage pressure.

zero boil-off↗

NASA NTRSDate not supplied

Modeling and Simulation of Tank Pressure Control using Zero-Boiloff Active Thermal Control for LOXSAT Technology Demonstration Mission

To-date, research and modeling of cryogenic fluid management technologies (CFM) for spaceflight has been limited to ground tests, short-duration zero-g simulations (e.g. drop towers), and small-scale experiments on-orbit. There has not been a large-scale flight demonstration of a flight-like system. As future NASA missions to take humans further from Earth will require large, in-space cryogenic propulsion vehicles, it is imperative to begin collecting flight data for these systems to accurately model and design future vehicles. To meet this goal, NASA awarded tipping point technology demonstration awards to Eta Space, Lockheed Martin, Space Exploration Technologies (SpaceX), and United Launch Alliance (ULA) to demonstrate on-orbit storage and transfer of cryogenic propellant. For its award, Eta Space is developing LOXSAT-1. It is a small satellite that will be launched on a Rocket Lab Electron rocket. The spacecraft consists of a Rocket Lab Photon spacecraft bus with a primary payload of a spherical liquid oxygen (LOX) storage tank with thermodynamic control systems. The primary objective of the mission is to demonstrate zero-boil-off storage of liquid oxygen. To accomplish this objective, the payload is equipped with an active thermal control system fluid loop that consists of propellant management device (PMD), positive-displacement pump, heat exchanger connected to a cryocooler, and a spray bar mixing injector. When the fluid loop is operating, fluid is drawn from the tank by the PMD and pumped through the heat exchanger, lowering the fluid temperature below the fluid temperature in the tank. This subcooled liquid is then injected back into the tank through the spray bar. The subcooled injected liquid has two effects. If it is sprayed into the ullage space, the injected liquid will form into jets or droplets and exchange heat with the ullage gas. This will cool and condense the gas, reducing the pressure in the tank. Additionally, the liquid that is not sprayed through the ullage, as well as any remaining liquid spray from the ullage, will rejoin the liquid mass of the tank, lowering the bulk temperature of the liquid. These combines effects provide for zero-boil off pressure control by lowering the tank pressure and the liquid saturation pressure simultaneously, ensuring the liquid stays subcooled. To model these complex mechanics and predict the performance of the active thermal control system, NASA is providing Eta Space with 3 parallel models of the tank. The approach of providing 3 different models allows for cross-checking and comparisons between the three to better understand how different modeling assumptions and selection semi-empirical factors affects the modeling result. Additionally, developing 3 models provides three different schemes for numerical simulation, providing confidence that results depict real physical phenomenon and not numerical quirks of the program. Within the tank thermodynamics, there are two primary areas of heat transfer we concern ourselves with: the heat transfer between the ullage space and the droplet spray, and between the ullage space and bulk liquid. For the droplet heat transfer, there are multiple sets of assumptions that can be made and correlations that can be used. Currently, two working models - the TankSIM model and Easy5 model – provide for an overview of the different approaches available. The TankSIM model and Easy5 model use two different models for droplet heating and evaporation that illustrate how the models use different types of mechanisms to arrive at the same answer. For the TankSIM model, droplets are treated as spheres of constant radius. Heat is transferred from the ullage to the droplet and warms the droplet until it reaches saturation, then the droplet begins evaporating and reducing its radius and mass. To calculate the heat transfer coefficient between the droplet and ullage, the Ranz-Marshall correlation is used. To determine the number of droplets in the ullage, a resident mass approach is used. This approach averages the number of droplets such that residuals at the start-up and shut-off of the spray bar cancel out. This same approach is used in the Easy5 model. The GFSSP model implements a linked list to track individual droplet “nodes” within the model. For the Easy5 model, the droplet is assumed to have an interface at a temperature equal to the saturation temperature corresponding to the pressure of the gas phase. The heat transfer from the gas to the interface and the interface to the droplet bulk is then calculated, and the net mass transfer between the droplet and interface is determined by performing an energy balance across the interface. For the gas side of the interface, the Ranz-Marshall correlation is used. For the liquid side of the interface, a variety of correlations were tried, including Kronig and Brink (1950) and effective conductivity models. As a result of these assumptions, the Easy5 model currently predicts faster depressurization, as at saturated vapor conditions, the heat transfer coeffect on the liquid side for the Easy5 model is greater than the heat transfer coefficient predicted by Ranz-Marshall used in the TankSIM code. This greater heat flux translates into faster condensation of the saturated ullage gas. At the bulk liquid to ullage interface, the models are in much closer agreement. Both models model the ullage as a sphere centered within the bulk liquid in the tank, and both use the energy-jumping boundary condition to model heat and mass transfer across the interface. There are slight differences in how the interface temperature is calculated, however. The Easy5 model assumes the temperature of the interface is equal to the saturation temperature associated with the pressure of the gas phase. The TankSIM model calculates this temperature with Alabovskii’s equation, which provides a correction factor for interface temperatures. Analysis tasks are focused on determining rates of depressurization within the tank during active cooling operation. To maintain net positive suction head at the pump inlet, the tank pressure cannot fall faster than the saturation pressure associated with the temperature of the bulk liquid. Additionally, there is interest in analyzing the performance of the loop at different pump speeds and cryocooler input powers. Adjusting the flowrate affects both the performance of the heat exchanger between the cryocooler and pumped liquid, and the heat transfer between the droplet spray and the ullage. Ideally, a pump speed and cryocooler power can be selected that will allow the tank to operate in zero-boil-off mode with a very narrow range of storage pressure.

zero boil-off↗

NASA NTRS2002

Processes Controlling Water Vapor in the Winter Arctic Tropopause Region

This work describes transport and thermodynamic processes that control water vapor near the tropopause during the SAGE III-Ozone Loss and Validation Experiment (SOLVE), held during the Arctic 1999/2000 winter season. Aircraft-based water vapor, carbon monoxide, and ozone measurements were analyzed so as to establish how deeply tropospheric air mixes into the Arctic lowermost stratosphere and what the implications are for cloud formation and water vapor removal in this region of the atmosphere. There are three major findings. First, troposphere-to-stratosphere exchange extends into the Arctic stratosphere to about 13 km. Penetration is to similar levels throughout the winter, however, because ozone increases with altitude most rapidly in the early spring, tropospheric air mixes with the highest values of ozone in that season. The effect of this upward mixing is to elevate water vapor mixing ratios significantly above their prevailing stratospheric values of above 5ppmv. Second, the potential for cloud formation in the stratosphere is highest during early spring, with about 20% of the parcels which have ozone values of 300-350 ppbv experiencing ice saturation in a given 10 day period. Third, during early spring, temperatures at the troposphere are cold enough so that 5-10% of parcels experience relative humidities above 100%, even if the water content is as low as 5 ppmv. The implication is that during this period, dynamical processes near the Arctic tropopause can dehydrate air and keep the Arctic tropopause region very dry during early spring.

Pfister, Leonhard↗

NASA NTRS1994

Budget analysis of FIFE 1987 sonde data

Mean thermodynamic profiles are presented for the daytime convective boundary layer evolution for three groups of sunny days in late June and early July, August, and October using data from the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) 1987 Kansas experiment. Budget models for the mixed layer evolution and the boundary layer rise are used to estimate the boundary layer top entrainment parameter. A value of A(sub R) = 0.44 +/- 0.21 is found for the mean ratio of the inversion level virtual heat flux to the surface virtual heat flux.

Betts, Alan K.↗

NASA NTRS2003

Real-Time Optical Monitoring and Simulations of Gas Phase Kinetics in InN Vapor Phase Epitaxy at High Pressure

Understanding the kinetics of nucleation and coalescence of heteroepitaxial thin films is a crucial step in controlling a chemical vapor deposition process, since it defines the perfection of the heteroepitaxial film both in terms of extended defect formation and chemical integrity of the interface. The initial nucleation process also defines the film quality during the later stages of film growth. The growth of emerging new materials heterostructures such as InN or In-rich Ga(x)In(1-x)N require deposition methods operating at higher vapor densities due to the high thermal decomposition pressure in these materials. High nitrogen pressure has been demonstrated to suppress thermal decomposition of InN, but has not been applied yet in chemical vapor deposition or etching experiments. Because of the difficulty with maintaining stochiometry at elevated temperature, current knowledge regarding thermodynamic data for InN, e.g., its melting point, temperature-dependent heat capacity, heat and entropy of formation are known with far less accuracy than for InP, InAs and InSb. Also, no information exists regarding the partial pressures of nitrogen and phosphorus along the liquidus surfaces of mixed-anion alloys of InN, of which the InN(x)P(1-x) system is the most interesting option. A miscibility gap is expected for InN(x)P(1-x) pseudobinary solidus compositions, but its extent is not established at this point by experimental studies under near equilibrium conditions. The extension of chemical vapor deposition to elevated pressure is also necessary for retaining stoichiometric single phase surface composition for materials that are characterized by large thermal decomposition pressures at optimum processing temperatures.

Dietz, Nikolaus↗

NASA NTRSDate not supplied

Exploring the Continuum of Stratiform and Cumulus Cloudiness: Observational Insights Related to Marine Boundary Layer Clouds

Low-level marine clouds take on a wide range of morphological states owing to external forcing and internal feedbacks. Rarely are shallow marine clouds adequately described by a single simplified framework but instead exhibit features that partially conform to several states that could be considered “limiting”. Perhaps the most apparent dichotomy is whether to consider shallow clouds as existing within a surface-driven mixed layer or as convective “plume” elements positioned on top. Do the rules that govern the limiting cases transition smoothly through the hybrid scenarios found in nature, or are there particular regions of attraction or repulsion?We have identified 3 ”axes” along which to investigate how the energetics, thermodynamics and cloud macro structure relate to the intermediate spaces between idealizations.

Ewan Crosbie↗