Results for “ground loop” — Page 52

NASA NTRS1987

Rotational modulation and flares on RS CVn and BY Dra stars. VI - Physical parameters of the chromospheres/transition regions of V 711 Tau (HR 1099), II Peg and AR Lac during October 1981

Ground-based optical and IUE satellite-ultraviolet observations of three RS CVn stars are combined with density sensitive line ratios and differential emission measure curves to describe the physical conditions in their outer atmospheres. Solar-like densities are found to be representative of average conditions on two of the stars, V 711 Tau and AR Lac. The total radiative losses from these two stars are estimated and found to be larger than the sun by at least two orders of magnitude. Consideration of the volume emitting in two of the principal transition region lines suggests a possible relation between the disk 'filling factor' for these two lines and the dynamo-related Rossby number. Only one hemisphere of the star II Peg, the one showing least evidence of starspots, is similar. On the opposite hemisphere the presence of a discrete emitting region is deduced which is almost coincident in phase with the passage of the dominant optical spot group across the visible disk. The dimensions of this region, and an illustrative interpretation in terms of a large emitting magnetic loop, are discussed. It is compared to large active region loops on the sun.

Byrne, P. B.↗

DOE OSTI2020

Iron(III)–Oxo Cluster Chemistry with Dimethylarsinate Ligands: Structures, Magnetic Properties, and Computational Studies

A program has been initiated to develop Fe III /oxo cluster chemistry with the ‘pseudo-carboxylate’ ligand dimethylarsinate (Me 2 AsO 2 - ) for comparison with the well investigated Fe III /oxo/carboxylate cluster area. The synthesis and characterization of three polynuclear Fe III complexes are reported, [Fe 12 O 4 (O 2 C t Bu) 8 (O 2 AsMe 2 ) 17 (H 2 O) 3 ]Cl 3 (1), Na 2 [Fe 12 Na 2 O 4 (O 2 AsMe 2 ) 20 (NO 3 ) 6 (Me 2 AsO 2 H) 2 (H 2 O) 4 ](NO 3 ) 6 (2) and [Fe 3 (O 2 AsMe 2 ) 6 (Me 2 AsO 2 H) 2 (hqn) 2 ](NO 3 ) (3), where hqn is 8-hydroxyquinoline. The Fe 12 core of 1 is a type never previously encountered in Fe III carboxylate chemistry, consisting of two Fe 6 units each of which comprises two {Fe 3 (μ 3 -O 2- )} units bridged by three Me 2 AsO 2 - groups and linked into an Fe 12 loop structure by two anti-anti η 1 :η 1 :μ Me 2 AsO 2 - groups, a bridging mode extremely rare with carboxylates. 2 also consists of two Fe 6 units, differing in their ligation from those in 1, and this time linked together into a linear structure by a central {Na 2 (NO 3 ) 2 } bridging unit. 3 is a linear Fe 3 complex with no monoatomic bridges between Fe III ions, a very rare situation in Fe III chemistry with any ligands, and unprecedented in Fe carboxylate chemistry. The distinct differences observed in arsinate vs carboxylate ligation modes are rationalized largely based on the greater basicity of the former vs the latter. Variable-temperature dc and ac magnetic susceptibility data reveal all Fe 2 pairwise interactions to be antiferromagnetic. For 1 and 2, the different J ij couplings were estimated by use of a magnetostructural correlation for high nuclearity Fe III -oxo clusters and by density functional theory calculations using broken symmetry methods, allowing identification of their relative spin vector alignments and thus rationalization of their S = 0 ground states. The J ij values were then used as input values to give excellent fits of the experimental χM T vs T data. For 3, the fits of the experimental χM T vs T data to the Van Vleck equation or with PHI gave a very weak J 12 = -0.8(1) cm -1 (H = –2JŠ i ·Š j convention) between adjacent Fe III ions, and an S = 5/2 ground state. Furthermore, these initial Fe III arsinate complexes also provide structural parameters that help validate literature assignments of arsinate binding modes to iron oxide/hydroxide minerals as part of environmental concerns of using arsenic-containing herbicides in agriculture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2001

Radiometry Measurements of Mars at 1064 nm Using the Mars Orbiter Laser Altimeter

Measurements by the Mars Orbiter Laser Altimeter (MOLA) on board the Mars Global Surveyor (MGS) may be used to provides a radiometric measurement of Mars in addition to the topographic measurement. We will describe the principle of operation, a mathematical model, and the receiver calibration in this presentation. MOLA was designed primarily to measure Mars topography, surface roughness end the bidirectional reflectance to the laser beam. To achieve the highest sensitivity the receiver detection threshold is dynamically adjusted to be as low as possible while keeping a predetermined false alarm rate. The average false alarm rate 29 monitored in real time on board MOLA via a noise counter, whose output is fed to the threshold control loop. The false alarm rate at a given threshold is a function of the detector output noise which is the sum of the photo detector, shot noise due to the background light seen by the detector and the dark noise. A mathematical model has been developed that can be used to numerically solve for the optical background power given the MOLA threshold setting and the average noise count. The radiance of Mars can then be determined by dividing the optical power by the solid angle subtended by the MOLA receiver, the receiver optical band-width, end the Mars surface area within the receiver field of view. The phase angle which is the sun-Mars-MOLA angle is available from the MGS database. MOLA also measures simultaneously the bidirectional reflectance of Mars vie its 106-lum loser beam at nadir with nearly zero phase angle. The optical bandwidth of the MOLA receiver is 2um full width at half maximum (FWHM) and centered at 106-lum. The receiver field of view is 0.95mrad FWHM. The nominated spacecraft altitude is 100km and the ground track speed is about 3km/s. Under normal operation, the noise counter are read and the threshold levels are updated at 1Hz. The receiver sensitivity is limited by the detector dark noise to about 0.1nW, which corresponds to less than 2% the maximum radiance during daytime from the brightest area on Mars. The results from the mathematical model agree well with the prelaunch measurements at several calibrated optical power levels. The radiance of sunlit Mars estimated with this technique correlates well with the measurement from the MGS. Thermal Emission Spectrometer (TES) and the Hubble Space Telescope at similar wavelength.

Sun, Xiao-Li↗

NASA NTRS2018

Human Automation Teaming: Lessons Learned and Future Directions

Full autonomy seems to be the goal for system developers in almost every area of the economy. However, as we move from automated systems to autonomous systems, designers have needed to insert humans to oversee automation that has traditionally been brittle or incomplete. This creates its own problems as the operator is usually out of the loop when the automation hands over problems that it cannot handle. To better handle these situations, it has been proposed that we develop human automation teams that have shared goals and objectives to support task performance. This paper will describe an initial model of Human Automation Teaming (HAT) which has three elements: transparency, bi-directional communications, and human-directed execution. Transparency in our model is a method for giving insight into the reasoning behind automated recommendations and actions, bi-directional communication allows the operator to communicate directly with the automation, and finally the automation defers execution to the human. The model was implemented through a number of features on an electronic flight bag (EFB) which are described in the paper. The EFB was installed in a mid-fidelity flight simulator and used by 12 airline pilots to support diversion decisions during off-nominal flight scenarios. Pilots reported that working with the HAT automation made diversion decisions easier and reduced their workload. They also reported that the information provided about diversion airports was similar to what they would receive from ground dispatch, thus making coordination with dispatch easier and less time consuming. These HAT features engender more trust in the automation when appropriate, and less when not, allowing improved supervision of automated functions by flight crews.

Human-Autonomy Teaming↗

DOE OSTI2026

Multi‐Model Ensembles in Ecosystem Modeling: Challenges and Best Practices for Decision‐Making

Ecosystem models are increasingly central to the decision-making for environmental policy, conservation planning, and climate-related investments. Yet, the growing reliance on Multi-Model Ensembles (MMEs) of ecosystem models by practitioners and policymakers, sometimes under tight timelines and imperfect information, has frequently outpaced the scientific rigor required to ensure ensemble reliability. Here, MMEs refer to approaches that combine targeted predictions from multiple models with the expectation of improving robustness and quantifying predictive uncertainty. Poorly designed MMEs may create a false sense of confidence and lead to suboptimal policy and market decisions. This perspective argues that robust decision-making-relevant MMEs must be grounded on two pillars: (1) rigorous Model Intercomparison Projects (MIPs), which identify inter-model agreement and disagreement, characterize model uncertainties, and evaluate robustness with observationally based benchmarks—MIPs' diagnostic evaluation is so critical that it must be needed to drive MME's decision in model selection and weighting, especially when only a limited number of models available; and (2) co-design by both stakeholders and scientists to ensure that scenarios, metrics and uncertainty requirements provide decision-relevant information. Building upon the past success and lessons from the existing MIPs-MMEs efforts (e.g., climate/Earth system/crop), we derived the theoretical basis for MMEs, addressed their specific challenges in ecosystem modeling, and highlighted proper consideration of model numbers and diversity, risk of model inter-dependence, effective calibration of model parameters, possible overdue of some ecosystem model development, critical roles of open benchmark data across a wide range of conditions, and suggested use of Artificial Intelligence to support MIPs-MMEs. We highlighted the under-recognized opportunity for MIPs and MMEs to drive scientific progress and innovation through identifying better performing models, systematic benchmarking, feedback loops, and targeted model improvement. By following actionable best practice guidelines, MMEs can evolve from ad hoc aggregation of models into a trusted backbone of environmental policy and decision-making.

ecosystem modeling↗

DOE OSTI2023

Semi-Automatic Geographic Information System Framework for Creating Photo-Realistic Digital Twin Cities to Support Autonomous Driving Research

Digital twin cities are frequently used in vehicle and traffic simulations to render realistic on-road driving scenarios under various traffic and environmental conditions. These digital twins provide a high-fidelity replica of the physical world (e.g., buildings, roads, infrastructures, traffic) to create three-dimensional (3D) virtual-physical environments to support various emerging vehicle and transportation technologies such as connected and automated vehicles. These virtual environments provide a cost-effective digital proving ground to evaluate, validate, and test emerging technologies that include control algorithms, localization, perception, and sensors. Replicating a real-world traffic scenario in a digital twin using a traditional 3D modeling approach is a time-consuming and labor-intensive effort. Here this paper presents a semi-automated spatial framework to construct realistic 3D digital twin cities to support autonomous driving research using readily available geographic information system (GIS) data and 3D prefabricated (prefab) models. We start with a comprehensive review of geospatial data sources of essential digital entities required in a 3D digital twin city and present an integrated GIS-3D modeling pipeline using customized QGIS/GDAL and Blender scripting in Python. The pipeline outputs are realistic 3D digital twin cities compatible with common vehicle simulation software, such as CARLA and IPG CarMaker. The paper closes with a showcase to demonstrate the quality and usability of a digital twin city created to replicate the Shallowford Road corridor in Chattanooga in both Unity and Unreal engine-based virtual environment. The generated digital twin city can be applied to a hardware-in-the-loop simulation environment with an actual testing vehicle to facilitate autonomous driving research.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Abstract for CRADA among NETL, Mälardalen University, University College Cork (acting through its Tyndall National Institute), and Micro Electricity Generation Association

GeoCoHorT aims to accelerate the transition to 4 th generation district heating and cooling (4GDHC) in Europe and globally, by assessing, optimizing, and demonstrating the integration of shallow geothermal heat extraction with other renewable sources and smart buildings. The target geo-source is ground water from River Shannon (Limerick, Ireland), which will provide both an efficiency and noise-reduction benefit to the micro-district and a method of combatting climate-change-warming of the Shannon Estuary. The heat from this low-temperature source will be recycled and supplied to a smart district located in Limerick, Ireland, through heat pumps powered by renewable electricity and by means of a suitable DH network design. The mandate is to find solutions that work for entire communities in a fair and sustainable manner, with the involvement of the communities themselves to highlight their needs. The project brings together four partners from Ireland, Sweden, and the U.S.A. with strong multi-disciplinary competencies. The Tyndall Institute at University of Cork (UCC) and Mälardalen University (MDU) will design and optimize the 4GDH micro-district system, and the Micro Electricity Generation Association (MEGA) will work with the community to build a sense of ownership of the Climate Challenge and ensure close community involvement. The National Energy Technology Laboratory of the U.S. Department of Energy (NETL) will design the prospective geo-fluid loop to optimize heat-extraction effectiveness with ecological safety and assess the environmental benefits of the proposed solutions. Industrial advisors (Eskilstuna Strängnäs Energi och Miljö (ESEM) and Mimer in Sweden, and Smart MPOWER in Ireland) will steer the technology development to meet the needs of public utilities and consumers. Current infrastructure in the smart district in Limerick (demonstration site of an EU Lighthouse project) will be exploited and modified with support of MEGA, UCC, and MPOWER to integrate micro-DH from low-temperature heat sources, such as the river heat, and to allow increasing penetration of prosumers in the grid. Additional case studies will be developed with the help of industrial advisors to extend the results to other regions (e.g., Sweden and USA) and provide valuable insights for the development of 4GDH worldwide.

15 GEOTHERMAL ENERGY↗

NASA NTRS1993

Dwarf novae

Dwarf novae are defined on grounds of their semi-regular brightness variations of some two to five magnitudes on time scales of typically 10 to 100 days. Historically several different classification schemes have been used. Today, dwarf novae are divided into three sub-classes: the U Geminorum stars, the SU Ursae Majoris stars, and the Z Camelopardalis stars. Outbursts of dwarf novae occur at semi-periodic intervals of time, typically every 10 to 100 days; amplitudes range from typically 2 to 5 mag. Within certain limits values are characteristic for each object. Relations between the outburst amplitude, or the total energy released during outburst, and the recurrence time have been found, as well as relations between the orbital period and the outburst decay time, the absolute magnitude during outburst maximum, and the widths of long and short outbursts, respectively. Some dwarf novae are known to have suspended their normal outburst activity altogether for a while. They later resumed it without having undergone any observable changes. The optical colors of dwarf novae all are quite similar during outburst, considerably bluer than during the quiescent state. During the outburst cycle, characteristic loops in the two color diagram are performed. At a time resolution on the order of minutes, strictly periodic photometric changes due to orbital motion become visible in the light curves of dwarf novae. These are characteristic for each system. Remarkably little is known about orbital variations during the course of an outburst. On time-scales of minutes and seconds, further more or less periodic types of variability are seen in dwarf novae. Appreciable flux is emitted by dwarf novae at all wavelengths from the X-rays to the longest IR wavelengths, and in some cases even in the radio. Most dwarf novae exhibit strong emission line spectra in the optical and UV during quiescence, although some have only very weak emissions in the optical and/or weak absorptions at UV wavelengths.

Ladous, Constanze↗

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 NTRS2022

PAAV Concept Document

The Pathfinding for Airspace with Autonomous Vehicles (PAAV) Concept Document, version 1.0, lays out the key challenges and potential solutions for the use of uncrewed aircraft (UA) technology for future regional air cargo operations. The challenges and solutions described in this document were informed by communications with the UA industry community (e.g., RTCA, the Federal Aviation Administration, and regional air cargo business operators), as well as the PAAV team’s research activities during the last two years including four tabletop exercises, a human-in-the-loop simulation study, a numerical simulation study, a functional allocation study, and flight data analysis (Appendix A). This document first describes the expected operational context of PAAV (Section 2), such as the flight mission, baseline UAS components, nominal operations, m:N operations (i.e., "m" remote pilots per "N" aircraft), and off-nominal operations. This context sets the scope for the PAAV concept development work. PAAV concept development assumes that UA operations will be increasingly autonomous. Thus, near- and far-term assumptions are defined (Section 3). PAAV identified seven key challenges for UA operations (Section 4): - Flight route planning - Separation and flow management - Traffic pattern integration - Contingency management - Taxi, takeoff, and landing - m:N operations - Communications operations The following 13 potential solutions to these challenges are then described (Section 5): - Scalable communications architecture - Data link - Designated UAS corridors - Crew planning for m:N operations - Flight route optimization - Traffic load-level control - Trajectory solutions with data link - Automated hazard avoidance for m:N operations - Traffic pattern integration (TPI) tool - Standard lost command and control (C2) link (LC2L) procedures - Automated hazard avoidance under LC2L - Auto-taxi, auto-takeoff, and auto-land - Ground control station (GCS) user interface for m:N operations The document attempts to link each of these solutions to one or more of the challenge areas. Novel solutions involving numerous automation technologies are needed to mitigate traffic and airspace management challenges, especially for realizing m:N operations and ensuring safety under LC2L conditions. The purpose of this document is to help understand alternatives and tradeoffs among potential solutions and provide a foundation for a cohesive PAAV concept that will be described and refined in subsequent concept versions.

Unmanned aircraft, uncrewed aircraft, regional air↗

NASA NTRSDate not supplied

SERFE Water Quality Results

NASA has been developing a new spacesuit, called the Exploration Extravehicular Mobility Unit (xEMU) for over a decade. This spacesuit is underdevelopment to support missions to the International Space Station (ISS) and also to the Moon. Improvements in the life and robustness of the Portable Life Support System (PLSS) has been a major objective of these efforts. Water quality, and how that impacts the performance of the life support system hardware, are areas where improvements could greatly help to achieve these goals. The Suit Water Membrane Evaporator (SWME) was chosen as the technology to provide cooling to the xEMU and has undergone several iterations of development over this period. An ISS flight experiment centered around the SWME and other thermal loop technologies was developed and has been under test in an ISS EXpedite PRocessing of Experiments to the Space Station (EXPRESS) rack since November of 2020. In addition to the SWME, The SWME EXPRESS Rack Flight Experiment (SERFE) contains several technology demonstrations from the xEMU project and has been demonstrating their performance in micro-gravity and over an extended duration. This paper will summarize the results of the water quality analysis performed to date throughout the SERFE testing program. Special care was taken to select materials, process hardware, and control the quality of the feedwater used in SERFE testing so that it would be representative of a thermal control system that could be used on a spacesuit for a lunar mission. In addition, the testing schedule, including periods of quiescence in between tests, was also selected to simulate a real mission profile in ways that would be critical to water quality. Results include data and analysis on microbial activity, biocidal iodine, metals, organic carbon, and several other customary indicators of water quality in an operational system. Testing spans over a year and a half of wetted life of the SERFE Flight Unit and the SERFE Ground Unit.

Colin Campbell↗

NASA NTRS2011

Automated Air Traffic Control Operations with Weather and Time-Constraints: A First Look at (Simulated) Far-Term Control Room Operations

In this paper we discuss results from a recent high fidelity simulation of air traffic control operations with automated separation assurance in the presence of weather and time-constraints. We report findings from a human-in-the-loop study conducted in the Airspace Operations Laboratory (AOL) at the NASA Ames Research Center. During four afternoons in early 2010, fifteen active and recently retired air traffic controllers and supervisors controlled high levels of traffic in a highly automated environment during three-hour long scenarios, For each scenario, twelve air traffic controllers operated eight sector positions in two air traffic control areas and were supervised by three front line managers, Controllers worked one-hour shifts, were relieved by other controllers, took a 3D-minute break, and worked another one-hour shift. On average, twice today's traffic density was simulated with more than 2200 aircraft per traffic scenario. The scenarios were designed to create peaks and valleys in traffic density, growing and decaying convective weather areas, and expose controllers to heavy and light metering conditions. This design enabled an initial look at a broad spectrum of workload, challenge, boredom, and fatigue in an otherwise uncharted territory of future operations. In this paper we report human/system integration aspects, safety and efficiency results as well as airspace throughput, workload, and operational acceptability. We conclude that, with further refinements. air traffic control operations with ground-based automated separation assurance can be an effective and acceptable means to routinely provide very high traffic throughput in the en route airspace.

Prevot, Thomas↗

DOE OSTI2022

Generalized symmetries of the graviton

We find the set of generalized symmetries associated with the free graviton theory in four dimensions. These are generated by gauge invariant topological operators that violate Haag duality in ring-like regions. As expected from general QFT grounds, we find a set of “electric” and a dual set of “magnetic” topological operators and compute their algebra. To do so, we describe the theory using phase space gauge-invariant electric and magnetic dual variables constructed out of the curvature tensor. Electric and magnetic fields satisfy a set of constraints equivalent to the ones of a stress tensor of a 3d CFT. The constraints give place to a group $\mathbb{R}^{20}$ of topological operators that are charged under space-time symmetries. Finally, we discuss similarities and differences between linearized gravity and tensor gauge theories that have been introduced recently in the context of fractonic systems in condensed matter physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2021

UAS Integration in the NAS Flight Test 6: Full Mission Results

Recent standards development efforts for the integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS) such as those in RTCA Inc. Special Committee 228 (SC-228) have focused on relatively large UAS transitioning to and from Class A airspace. In an effort to expand the range of vehicle classes that can access the NAS, the NASA UAS Integration in the NAS project has investigated Low Size, Weight, and Power (Low SWaP) technologies that would allow smaller UAS to detect-and-avoid (DAA) traffic. Through batch and human in the loop (HITL) simulation studies, the UAS Integration in the NAS DAA subproject have identified candidate performance standards that would contribute to enabling extended Low SWaP, UAS operations under 10,000 feet. These candidate performance standards include minimum field of regard (FOR) values for Low SWaP air surveillance sensors as well as a DAA well-clear (DWC) definition which can be applied to non-cooperative traffic to reduce the required maneuver initiation range. To test the assumptions of the project’s simulation studies and validate the candidate performance standards, a live flight research event was executed at NASA Armstrong Flight Research Center. The UAS Integration in the NAS Project Flight Test 6 Full Mission sought to characterize UAS pilot responses to traffic conflicts using a representative Low SWAP DAA system in an operational NAS environment. To achieve this, live, virtual and constructive distributed environment (LVC-DE) elements were combined to simulate a sector of Oakland center airspace and induce encounters with a live, manned aircraft. A Navmar Applied Sciences Tigershark XP was used as the UAS ownship and was integrated into the test architecture to enable it to be controlled from a Vigilant Spirit Control Station (VSCS) research ground control station. Qualified UAS pilots were recruited to act as subject pilots under test (SPUT) to control the Tigershark XP in a simulated mission while coordinating with a participating air traffic controller in simulated airspace. The intruder speed, intruder equipage and encounter geometry were varied between six scripted encounters per SPUT. Various metrics were collected including pilot reaction time from the onset of DAA alert, ATC coordination rate, probability and severity of losses of DAA well clear, and subjective ratings of system acceptability. The implications of these results on the development of standards for Low SWAP DAA systems will be discussed.

UAV↗

NASA NTRS1997

A Cognitive System Model for Human/Automation Dynamics in Airspace Management

NASA has initiated a significant thrust of research and development focused on providing the flight crew and air traffic managers automation aids to increase capacity in en route and terminal area operations through the use of flexible, more fuel-efficient routing, while improving the level of safety in commercial carrier operations. In that system development, definition of cognitive requirements for integrated multi-operator dynamic aiding systems is fundamental. In order to support that cognitive function definition, we have extended the Man Machine Integrated Design and Analysis System (MIDAS) to include representation of multiple cognitive agents (both human operators and intelligent aiding systems) operating aircraft, airline operations centers and air traffic control centers in the evolving airspace. The demands of this application require representation of many intelligent agents sharing world-models, and coordinating action/intention with cooperative scheduling of goals and actions in a potentially unpredictable world of operations. The MIDAS operator models have undergone significant development in order to understand the requirements for operator aiding and the impact of that aiding in the complex nondeterminate system of national airspace operations. The operator model's structure has been modified to include attention functions, action priority, and situation assessment. The cognitive function model has been expanded to include working memory operations including retrieval from long-term store, interference, visual-motor and verbal articulatory loop functions, and time-based losses. The operator's activity structures have been developed to include prioritization and interruption of multiple parallel activities among multiple operators, to provide for anticipation (knowledge of the intention and action of remote operators), and to respond to failures of the system and other operators in the system in situation-specific paradigms. The model's internal representation has been be modified so that multiple, autonomous sets of equipment will function in a scenario as the single equipment sets do now. In order to support the analysis requirements with multiple items of equipment, it is necessary for equipment to access the state of other equipment objects at initialization time (a radar object may need to access the position and speed of aircraft in its area, for example), and as a function of perception and sensor system interaction. The model has been improved to include multiple world-states as a function of equipment am operator interaction. The model has been used -1o predict the impact of warning and alert zones in aircraft operation, and, more critic-ally, the interaction of flight-deck based warning mechanisms and air traffic controller action in response to ground-based conflict prediction and alerting systems. In this operation, two operating systems provide alerting to two autonomous, but linked sets of operators, whose view of the system and whose dynamics in response are radically different. System stability and operator action was predicted using the MIDAS model.

Corker, Kevin M.↗