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At least 235 records · Page 13

Knowledge-based control of an adaptive interface

The analysis, development strategy, and preliminary design for an intelligent, adaptive interface is reported. The design philosophy couples knowledge-based system technology with standard human factors approaches to interface development for computer workstations. An expert system has been designed to drive the interface for application software. The intelligent interface will be linked to application packages, one at a time, that are planned for multiple-application workstations aboard Space Station Freedom. Current requirements call for most Space Station activities to be conducted at the workstation consoles. One set of activities will consist of standard data management services (DMS). DMS software includes text processing, spreadsheets, data base management, etc. Text processing was selected for the first intelligent interface prototype because text-processing software can be developed initially as fully functional but limited with a small set of commands. The program's complexity then can be increased incrementally. The intelligent interface includes the operator's behavior and three types of instructions to the underlying application software are included in the rule base. A conventional expert-system inference engine searches the data base for antecedents to rules and sends the consequents of fired rules as commands to the underlying software. Plans for putting the expert system on top of a second application, a database management system, will be carried out following behavioral research on the first application. The intelligent interface design is suitable for use with ground-based workstations now common in government, industrial, and educational organizations.

Lachman, Roy↗

Initial Testing of the Stainless Steel NaK-Cooled Circuit (SNaKC)

An actively pumped alkali metal flow circuit, designed and fabricated at the NASA Marshall Space Flight Center, is currently undergoing testing in the Early Flight Fission Test Facility (EFF-TF). Sodium potassium (NaK) was selected as the primary coolant. Basic circuit components include: simulated reactor core, NaK to gas heat exchanger, electromagnetic liquid metal pump, liquid metal flowmeter, load/drain reservoir, expansion reservoir, test section, and instrumentation. Operation of the circuit is based around the 37-pin partial-array core (pin and flow path dimensions are the same as those in a full core), designed to operate at 33 kWt. This presentation addresses the construction, fill and initial testing of the Stainless Steel NaK-Cooled Circuit (SNaKC).

Garber, Anne↗

Comparing Tropopause-Penetrating Convection Identifications Derived from NEXRAD and GOES over the Contiguous United States

Overshooting cloud tops (OTs) are a result of powerful updrafts that rapidly transport air from the troposphere to the lower stratosphere. Aside from the well-known relationships between strong updrafts and severe weather, the boundaries of updrafts, including the OT, are turbulent, which leads to irreversible mixing of air between the stratosphere and troposphere, altering the composition of both layers. In order to better understand the impact of OTs, knowing precisely when and where they occur is vital. Within the last decade remote-sensing observations from satellites and radars have been used to identify OTs, but the results thus far have not been entirely consistent due to challenges with accurately identifying OTs with these sensor datasets. This study compares OTs identified using NEXRAD reflectivity data from the GridRad dataset with an approach that uses GOES infrared (IR) data. The GridRad method estimates the altitude of echo tops directly from the radar pointing geometry, merging a combination of radars that enables products every 5 mins, with 2 km spatial and 1 km vertical grid spacing. The GOES satellite method uses spatial patterns in tropopause-relative IR brightness temperature to derive an OT likelihood. The study region covers a large part of the contiguous United States during selected active convection dates in 2017 and includes data from GOES-13/16. A large sample of OTs observed by NEXRAD and GOES-13/16 satellites are analyzed to better understand NEXRAD and IR observations of OTs, quantify agreement between the OT detection methods, and demonstrate how the 4x increase in spatial resolution from GOES-13 to GOES-16 impacts OT algorithm detection performance. The results show that for nearly time-matched scenes, with many severe storms, GOES-13 and -16 detection accuracy is quite comparable; however, some missed detections are attributed to poorer GOES-13 image resolution. It was found that GOES-13 OT regions are ~2 K warmer than GOES-16 on average, but such differences exceed 5 K for the most intense OT regions. It is found that false GOES IR-based detections are unavoidable, given that cold cloud pixels significantly colder than the tropopause from nearby or recently decayed OTs can persist within anvils for 15 minutes or more.

John W. Cooney↗

Decision Space Modeling: Trade Space Ontology

As the National Aeronautics and Space Administration (NASA) works to develop a crewed Moon to Mars Architecture, it is dealing with a large decision space consisting of the overlay of human exploration architectures for both the Moon and for Mars. Efforts are underway to enable reasoning, analysis, and deliberation on this decision space. A critical first step is to develop a model of the decision space, which will then allow for various methods and techniques to be applied in support of the larger architecture decision-making process. The Trade Space Ontology consists of a set of terminologies and relations (an ontology) and a MagicDraw resource that enables documentation of decisions and alternatives. It also provides a means by which decisions and alternatives can be traced to other Systems Engineering artifacts. For documenting alternatives, the Trade Space Ontology adapts the Morphological Matrix methodology to The Systems Modeling Language (SysML) through a profile; custom diagrams are also implemented to simplify the profile's use. With the profile and custom diagrams, system architects can specify options for architecture attributes, as well as compatibility between them, in a compact visual format. While the approach shares similarities to a trade tree, the emphasis at this stage is less on enumerating specific combinations of options and instead on specifying the options and their compatibility. Enumeration of alternatives is performed by an external analysis that operates on an output file from a model constructed using the Trade Space Ontology. For decisions, the Trade Space Ontology provides a way to model generic precedence relationships as well as documenting inputs and outputs. These may include what alternatives, criteria, and rationale are understood to be relevant for each decision. Importantly, the decision-making side of the Trade Space Ontology is defined at a more general level, such that it can be adapted to the specific terms in use by projects and programs at NASA. However, this adaptability also means that less capability is provided ``out-of-the-box'' from installation. Currently the resource includes plugin functionality to enumerate paths through generic precedence relationships between decisions and to export these paths to a spreadsheet. Custom dependency stereotypes are included in the profile to indicate the cross-cutting relationships between the trade space and the architecture decisions, providing a means to map which parts of the trade space enumerate alternatives for a decision, and to identify how the output of a decision may modify the trade space through pruning or down-selection. While the motivating use case for this resource is in human exploration architectures, the broad applicability of the Morphological Matrix methodology indicates that the Trade Space Ontology should also be useful for other activities and tasks at the agency.

Trade Tree↗

Cryogenic Selective Surface - How Cold Can We Go?

Selective surfaces have wavelength dependent emissivitya bsorption. These surfaces can be designed to reflect solar radiation, while maximizing infrared emittance, yielding a cooling effect even in sunlight. On earth cooling to -50 C below ambient has been achieved, but in space, outside of the atmosphere, theory using ideal materials has predicted a maximum cooling to 40 K! If this result holds up for real world materials and conditions, then superconducting systems and cryogenic storage can be achieved in space without active cooling. Such a result would enable long term cryogenic storage in deep space and the use of large scale superconducting systems for such applications as galactic cosmic radiation (GCR) shielding and large scale energy storage.

Emmissivity↗

Wideband Disturbance Accomodation in Precision Flexible Space Structures

Numerous spacecraft missions currently being formulated exhibit several basic and sharply conflicting features: selected components (e.g., an optical train) of inherently flexible structures are to maintain precision pointing performance in a wideband disturbance environment. Within the overall process of synthesizing an active controller to deal with this difficult problem, the aspects of reduced-order modelling and of actuator and sensor selection are crucial to the successful implementation of any controller feedback strategy. The principal focus in this paper is on the influence of actuator and sensor selection upon the effectiveness of a specified controller strategy for wideband disturbance accommodation. A genetic optical support structure is used for a number of design examples. Active transducer selections are made systematically based upon their direct contributuion to optical pointing error. Controller designs incorporating the various transducer selections exhibit stability in the presence of unmodeled modes over a frequency range substantially beyond the bandwidth of the disturbance.

Hegg, D. R.↗

NASA's NextSTEP Advanced Electric Propulsion Activities

Developing propulsion technology systems in the 50-to 300-kW per thruster range to meet the needs of a variety of long duration, deep-space mission applications beyond capabilities being developed for 40-kW SEP Tech Demo Mission. Three proposals were selected to develop and demonstrate NextSTEP advanced electric propulsion (EP) subsystems. The primary goal is during the third year, to demonstrate 100-hour of continuous, steady-state operation of propulsion subsystem at 100-kW in a relevant TRL 5 environment.

Moore, Christopher L.↗

Mars Sample Return (MSR) Sample Receiving Facility (SRF) Assessment Study (MSAS)

NASA, in partnership with the European Space Agency (ESA), is seeking to return Martian geological and atmospheric samples to Earth for scientific study in the early 2030s. Due to the possibility that the samples could contain extraterrestrial life, Mars Sample Return (MSR) is classified as a Category V: Restricted Earth Return mission by the NASA Planetary Protection Office. As a result of this classification, a MSR Sample Receiving Facility (SRF) must not only provide a pristine environment to ensure samples are protected from terrestrial contamination for scientific investigations, it must also provide high-containment (biosafety level 4 [BSL-4]-equivalence) to isolate the samples from Earth’s biosphere until the samples are deemed safe for release and/or sterilized. The nominal utilization period for a SRF is anticipated to be 2-5 years and is intended to enable curation activities, biohazard assessment, select early science activities, and the rapid release of samples to the scientific community. However, to account for possible delays in schedule or the identification of extant life, this anticipated period of time must be flexible to accommodate schedule extensions and contingency plans. Due to requirements for high-level biological containment and cleanliness, a traditional receiving/curation facility cannot be utilized for MSR. Therefore, beginning in 2022, NASA Johnson Space Center is performing a MSR SRF Assessment Study (MSAS) to investigate the most optimal facility modality for a MSR SRF, as well as start to define programmatic early estimate of costs and schedules before the initial design phase begins. NASA is partnering with industry contractors (architectural and engineering firms with BSL-4 and cleanroom technology experience, as well as other contracted infrastructure and construction specialists) along with selected experts from NASA, ESA, existing U.S. BSL-4 facilities, and other U.S. government agencies, to carry out the assessment study. The MSAS should also aid in the future refinement of the science requirements (e.g., contamination control, equipment accommodations) before site-specific design would commence. As part of the MSAS, NASA is planning to assess an array of possibilities for a MSR SRF. One of the main considerations is the facility modality and whether an existing BSL-4 facility can be utilized (for some or all functions); or, if new constructure would be required, would a traditional fixed facility or a modular facility the best choice. MSAS will also investigate the ability of the modalities to accommodate two different facility capability endmembers: 1) a minimal facility focusing on biohazard assessment and curation tasks with a small footprint, and 2) an enhanced facility with additional capabilities to enable expedited processing and the completion of time-sensitive and (some) sterilization-sensitive science. The assessment is intended to generate information that will inform the selection of facility modalities for high-level conceptual design development. While the assessment study will focus on SRF requirements for accommodating curation, science, and sample safety assessment infrastructure, it will also consider an array of other factors, such as ease of access for international users, decommissioning, repurposing, future sale or lease following MSR’s use of the facility, and uncontained preparatory laboratory spaces. Upon completion of the study, the preferred modality and refined requirements would be utilized for site-specific design but will not be finalized until NASA’s completion of the National Environmental Policy Act (NEPA) process.

A.D. Harrington↗

An overview of the Space Station Technology/Advanced Development Program

The Advanced Technology Plan of the Fiscal Year (FY) 1986 is designed to focus on the most promising technology options applicable to the Space Station (SS), selected from the list of tasks identified by the FY 1984 Technology Program as the most critical technologies to be developed for the initial SS Initial Operating Capability. Most of the current activities are in the stages of manufacture and life tests of specific SS subsystems. Special attention is given to major technologies, which include power systems (PSs) (with emphasis on a Solar Dynamic PS concept); the thermal control system (with the focus on the 'thermal bus' concept); the environmental control and life support system; and the data management system; all are illustrated schematically. Other tasks, including dynamics, communications, extravehicular activities, mechanics, propulsion, and fluid, as well as the tasks of cost, maintainability, automation and robotics, and productivity are discussed.

Carlisle, R. F.↗

Apparatus for Controlling Low Power Voltages in Space Based Processing Systems

A low power voltage control circuit for use in space missions includes a switching device coupled between an input voltage and an output voltage. The switching device includes a control input coupled to an enable signal, wherein the control input is configured to selectively turn the output voltage on or off based at least in part on the enable signal. A current monitoring circuit is coupled to the output voltage and configured to produce a trip signal, wherein the trip signal is active when a load current flowing through the switching device is determined to exceed a predetermined threshold and is inactive otherwise. The power voltage control circuit is constructed of space qualified components.

Petrick, David J.↗

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↗

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↗

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↗

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↗

Space Science and the International Traffic in Arms Regulations: Summary of a Workshop

The United States seeks to protect its security and foreign-policy interests, in part, by actively controlling the export of goods, technologies, and services that are or may be useful for military development in other nations. "Export" is defined not simply as the sending abroad of hardware but also as the communication of related technology and know-how to foreigners in the United States and overseas. The U.S. government mechanism for controlling dual-use items--items in commerce that have potential military use is the Export Administration Regulations (EAR) administered by the Department of Commerce; items defined in law as defense articles fall under the jurisdiction of the Department of State and the International Traffic in Arms Regulations (ITAR). Because of the potential military implications of the export of defense articles, the ITAR regime imposes much greater burdens (on both the applicant and the government) than does the EAR regime during the process of applying for, and implementing the provisions of, licenses and technical-assistance agreements. Until the early 1990s export control activity related to all space satellites (commercial and scientific) was handled under ITAR. Between 1992 and 1996 the George H.W. Bush and the Clinton administrations transferred jurisdiction over the licensing of civilian communications satellites to the Commerce Department under EAR. In 1999, however, in response to broad concerns about Chinese attempts to acquire U.S. high technology, the U.S. House of Representatives convened the Select Committee on U.S. National Security and Military/Commercial Concerns with the People s Republic of China, also known as the Cox Committee. One of the many consequences of the Cox Committee's report was Congress's mandate that jurisdiction over export and licensing of satellites and related equipment and services, irrespective of military utility, be transferred from the Department of Commerce to the State Department and that such equipment and services be covered as defense articles under ITAR. Scientific satellites were explicitly included despite their use for decades in peaceful internationally conducted cooperative scientific research. It is widely recognized that the shift in regulatory regime from EAR to ITAR has had major deleterious effects on international scientific research activities that depend on satellites, spaceflight hardware, and other items that are now controlled by ITAR. Furthermore, contravening U.S. interests in attracting foreign students to U.S. universities, the capture of space technology by ITAR has caused serious problems in the teaching of university space science and engineering classes, virtually all of which include non-U.S. students. This report is a summary of a September 2007 workshop in which participants from the space research communities and the export-control administration and policy communities came together to discuss problems, effects, and potential solutions regarding the application of ITAR to space science. The principal themes and ideas that emerged from the discussions are summarized.

Finarelli, Margaret G.↗

Development of flight experiment work performance and workstation interface requirements, part 1. Technical report and appendices A through G

A skill requirement definition method was applied to the problem of determining, at an early stage in system/mission definition, the skills required of on-orbit crew personnel whose activities will be related to the conduct or support of earth-orbital research. The experiment data base was selected from proposed experiments in NASA's earth orbital research and application investigation program as related to space shuttle missions, specifically those being considered for Sortie Lab. Concepts for two integrated workstation consoles for Sortie Lab experiment operations were developed, one each for earth observations and materials sciences payloads, utilizing a common supporting subsystems core console. A comprehensive data base of crew functions, operating environments, task dependencies, task-skills and occupational skills applicable to a representative cross section of earth orbital research experiments is presented. All data has been coded alphanumerically to permit efficient, low cost exercise and application of the data through automatic data processing in the future.

Hatterick, R. G.↗

Space station

The need for a space station, its cost, its use, and completion are examined. The Space Station Task Force was established by NASA Administrators to answer questions and to provide focus and direction for Space Station planning activities. The task force provides Congress and the Administration with sufficient information to make decisions on whether the United States should proceed with a Space Station as the next major national initiative in space. Current thinking on selected issues, planning guidelines, unique considerations and organization are presented.

Forestieri, A. F.↗

Space shuttle phase B study plan

Phase B emphasis was directed toward development of data which would facilitate selection of the booster concept, and main propulsion system for the orbiter. A shuttle system is also defined which will form the baseline for Phase C program activities.

Hello, B.↗