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879 records · Page 49

Predictability of the Minimum Sea Ice Extent from Late Winter Fram Strait Ice Export: Model vs Observations

Late winter coastal divergence along the Eurasian coastline (referred to as the ice factory) – or the Fram Strait ice export, a proxy for coastal divergence in the ice factory – is a skillful predictor of the minimum sea ice extent (Williams et al., 2016; Brunette et al., 2018; Sesternikov and, 1979). Coastal divergence leads to the formation of coastal polynya where new ice grows but to a thickness that is not large enough to survive the following summer melt. This signal is then amplified by the ice albedo feedback and leads to more open water at the end of the summer melt season. In this thesis project, we will identify if this source of predictive skill in the seasonal forecast of the minimum sea ice extent is present in General Circulation Models, more precisely in the CESM2-LE, GISS-E2.1-G, GFDL FLOR-LE, CNRM-CM6-1 and the CanESM5. Since even small biases in the large-scale atmospheric circulation simulated by a model can short circuit this coupling between dominant modes of atmospheric variability (NAO and AO), coastal divergence along the Eurasian coastline, Fram Strait ice export and therefore seasonal forecasting skill of the model, failure to reproduce this coupling observed in the real Arctic will be used to identify biases in GCM. Preliminary results show that subtle changes in the large-scale atmospheric circulation leads to opposite statistical relationship between Fram Strait ice area export, coastal divergence along the Eurasian coastline, and seasonal predictability of the minimum sea ice extent both in the CESM2-LE and the GISS-E2.1-G models. Differences are linked with the partitioning between recirculation within the Beaufort Gyre, ice exported through Fram Strait and ridging north of the Canadian Arctic Archipelago.

Sea ice↗

Time-Resolved OH-PLIF Assessment of Deflagrations Levels in a CH4-O2 Rotating Detonation Rocket Combustor

The parasitic loss incurred by deflagrative pre-burning is considered to be one of the key challenges to the effective implementation of rotating detonation engine (RDE) systems. Thus far, there have been relatively limited high fidelity, spatio-temporally resolved measurements of the pre-burning process as a function of the reactant conditions and composition within an RDE. In this work, simultaneous high-repetition-rate broadband OH* chemiluminescence and OH planar laser-induced fluorescence (PLIF) imaging are employed to investigate deflagrative burning dynamics in a fully optically accessible CH4-O2 RDE as compared to a H2-air systems under the same conditions. A custom-built optical parametric oscillator (OPO) is coupled with a high-repetition-rate burst-mode laser to generate the 284 nm source for the excitation of the Q1(9) transition of the OH radical. Significant deflagrative burning is observed throughout the chamber as a consequence of the oxygen-rich environment. Trailing wave systems that consume unburned reactants in the region immediately following the primary detonation wave are observed. The formation of a product gas recirculation zone that entrains and combusts incoming reactants is observed, and quantitative analysis is performed to gain valuable insight into deflagration characteristics. At an oxidizer mass flux of Gox ≈ 350kg/m2/s, it is found that the levels of pre-wave burning in CH4-O2 are a factor of ∼2-3 times higher than in H2-air in the region directly ahead of the detonation wave at a global equivalence ratio Φ ≈ 1.0. This study highlights the key roles of ignition delay and turbulent mixing of the combustion product and reactant fields on the levels of pre-burning and establishes a methodology for further investigation, such as for the effects of various RDE inlet configurations.

Propulsion↗

Analysis of Launch Vehicle Liftoff Debris: Historical Perspective from Space Shuttle and Application to Artemis I

Human exploration-class launch vehicles are inherently prone to debris due to the extreme environments generated during pre-launch operations, liftoff, and flight. The use of cryogenic propellants often requires thermal protection system (TPS) coatings, typically foam, to maintain the propellant conditions in the tank and prevent an accumulation ice on the external surface of the vehicle. Some ice growth is to be expected at umbilical interfaces, vents, flanges, or brackets where it is difficult to apply TPS. This ice may come loose at any time due to wind on the launch pad, structural vibration and acoustics after rocket ignition, or aerodynamic forces during flight. This phenomena is especially apparent on vehicles with no TPS, such as the Saturn V rockets used in the Apollo Program, see Figure 1. During propellant tanking, the thermal contraction of the underlying substrate may generate cracks in the TPS (Figure 1). Chunks of TPS can release due to the expansion of ingested gas from cryopumping or from aerodynamic forces if the crack creates an offset surface. Most foams will also have a certain amount of “popcorning” where small pieces of foam will pop off during flight because of the differential between the static surface pressure and the pressure of the gas trapped in the foam cell structure. There are a number of other coating or closeout materials that may be shed from the vehicle and become debris. During pre-launch operations and liftoff, the vehicle may also be exposed to debris originating from the launch pad or ground support equipment. This debris is separate from foreign object debris, or FOD, which is not intended to be present and is strictly controlled through operations and maintenance procedures. In this case, debris is generated from hardware and materials that are necessary for launch and are subject to the intense vibration, acoustics, and direct plume impingement of the launch environment. Examples include ice from umbilicals, tape and tie wraps that protect cables, and rust or corrosion from the launch platform. While NASA has historically been aware of debris as a potential issue that could cause a failure resulting in loss of mission, loss of vehicle, or loss of crew, the likelihood and severity of that risk was not always well understood or given sufficient weight in program and flight decisions. After the Space Shuttle Columbia accident (STS-107), the investigation found that foam TPS debris shed from the external tank was the proximate cause of the damage to the orbiter wing. Six previous observations of debris released from the foam ramp that covered the bipod connecting the forward end of the orbiter to the external tank resulted in minor changes or were determined to be accepted flight risks. Two occurrences of bipod ramp foam loss were not identified until the STS-107 investigation. Despite the damage inflicted by these debris strikes, the Shuttle Program Requirements Control Board deemed the vehicle safe to fly. During the Return to Flight effort following the Columbia disaster, NASA Engineering developed a process for the assessment of debris transport, impact, and damage tolerance to support independent assessments of risk by NASA Safety and Mission Assurance (S&MA). Under this system, each element (vehicle or ground system) defines a catalog of all expected debris based on launch history, component testing, or analysis. Debris transport analysis (DTA) is conducted using the debris catalog characteristics and potential flow transport mechanisms (e.g., vehicle aerodynamics, gravity, wind, plume-driven). The predicted debris impact locations and velocities are provided to the hardware owners, who use available test data and analysis to determine whether each component can withstand the impacts. In cases where the element hardware may be severely damaged or fail, the options are to mitigate the debris source through some change in design or operation, or to work with S&MA to try to characterize the probability of the impact and damage for program risk acceptance. Because of the differences in debris characteristics and transport, the DTA has been divided between the Liftoff and Ascent regimes. The development and application of Liftoff DTA methodology from the Shuttle Program to the current Artemis Program is the subject of this paper. Liftoff DTA covers the time from the start of pre-launch operations at the launch pad, up until the vehicle clears the launch tower and there is no longer any interaction with ground systems. Debris transport during this period is broadly classified as either gravity, wind, and plume-entrained (GWPE) or plume driven (PD). GWPE debris is generally lower speed, travelling in a forward-to-aft direction. PD transport includes flow features from the rocket ignition transient, as well as plume impingement and recirculation that occur as the vehicle lifts off the launch platform. In these cases, the debris typically moves in an aft-to-forward direction at higher speeds. The applicable transport mechanisms must be considered for each piece of debris depending on the material, and release location and time. For example, rust or metallic debris from the tower could fall (GWPE) and impact the vehicle before landing on the launch platform deck where it could be also be transported by plume impingement (PD). However, falling ice (GWPE) from an umbilical is unlikely to survive impact with the vehicle or launch platform and be available for PD transport. Modeling of debris transport is accomplished using a set of DTA tools which simulate debris trajectories subject to a reference frame acceleration (i.e., gravity) and aerodynamic drag. Where the trajectory encounters a solid surface, the debris is allowed to rebound with a specified coefficient of restitution. The drag is calculated by interpolating the fluid state at each point in the debris trajectory from high-fidelity computational fluid dynamics (CFD) simulations of the launch vehicle and pad. The CFD data may either be static (steady state or time averaged), typically for GWPE transport, or dynamic (time-accurate) for PD flow features like the ignition transient. Examples of the CFD flow field solutions for the Space Launch System (SLS) rocket and launch pad are shown in Figure 2. Typical SLS debris trajectory predictions from DTA are illustrated in Figure 3. The final version of this paper will include a more detailed examination of the Liftoff DTA process developed during the Shuttle Program, and how it has been augmented and applied to the SLS rocket under the Artemis Program. Comparisons with debris observations from the Artemis I launch will demonstrate validation of the tools and methodology.

Debris↗

Plasma Produced Gaseous Species for Food, Seed, and Equipment Sanitization

Researchers at KSC have shown that plasma produced gaseous species have shown greater than 5.89 log reduction of inoculated coupons and sanitization (greater than 3 log reduction) of produce and 3D printed materials, though with more variable results. The results were obtained using a recirculating plasma system, with 1 L of air, 1 mL of H 2 O, and less than 500 W of power being the only consumable commodities. The work is versatile and enabling for future missions since the air and the produced gases can be reused or recycled on board the spacecraft.

Kenneth Engeling↗

Investigating Commercial Off-The-Shelf (COTS) Glovebox and Support Components Compared to Custom Curatorial Laboratories

There is a need envisioned to investigate the application of commercial off-the-shelf (COTS) systems as tools that could be used within commercial preliminary curation as the expected space economy is supported and begins to take flight. NASA is involved with supporting and developing the space economy [1] and therefore it’s feasible that at some point, a commercial space company would bring back materials and either store initially, or permanently, within COTS equipment as a stand-in for custom curation laboratories. While utilizing opportunities to explore this capability at NASA-Johnson Space Center (JSC) during the establishment of other laboratories [2] it was realized that cleanliness and/or other properties could be evaluated for these COTS systems during their installation in advanced research facilities that are not ISO-class rated clean rooms. Several aspects of a COTS-Curation system were explored including various gloves for curation manipulation within a negative pressure glovebox (Fig.1), Balazs organic and inorganic contaminant levels testing prior to glovebox ever being used, mode swapping comparison of recirculation vs. single pass, constant monitoring of oxygen (O2) and moisture (H2O) levels in various conditions, etc. To acquire inorganic and organic compound loads inside the glovebox, Balazs wafer testing and gas sampling were implemented. These are standardized analytical tests provided by Balazs™ NanoAnalysis, a division of Air Liquide USA. Deployment of 8-inch silicon wafer witness plates for 24-hours in an undisturbed environment capture the organic compound load and inorganic trace metal contents which can be obtained by Vapor Phase Decomposition Inductively Coupled Plasma Mass Spectrometry (VPD ICP-MS). Balazs gas sample analysis was also performed for better measurements of volatile organic compounds (VOC) in glovebox air analyzed by Thermal Desorption Gas Chromatography Mass Spectrometry (TD GC-MS). These analytical testings were carried out in a controlled ultra high pure (UHP) gaseous nitrogen (N2)-purged environment where oxygen and moisture contents were continuously monitored at certain temperature and pressure. The preliminary outcomes of these testings are promising. The COTS systems appear to maintain the steady-state controlled environment for days, if not weeks, with uninterrupted gaseous N2-supply which was operated from a standard medium pressure LN2 250L 230L dewar, exchanged as needed. The outgassing load can be maintained by selecting the glove materials that have the least outgassing and particle shedding performances. Further experiments will be considered to validate the preliminary findings. While this project is exploratory, it is not intended as an endorsement by NASA Curation for approved materials or usage for advanced curatorial activities. NASA does not endorse nor promote any one particular product or company. References: [1] McCubbin F. M. et al. (2019) Space Science Reviews 215:A48. [2] Lewis, E.K. et. al (2024) LPSC LV, Abstract #2457.

Curation↗

Trace Contaminant Control Test Bed for Evaluation of TCC Prototypes with Vacuum Regenerable and Non-Regenerable Sorbents

A new Space Suit Exploration Portable Life Support System (xPLSS) is being designed, built, integrated, and tested into the Extra-Vehicular Mobility Unit (xEMU). The Trace Contaminant Control (TCC) system is a component in the oxygen ventilation loop of xPLSS that removes contaminants generated by the crewmembers’ metabolic processes. The primary trace contaminants that must be removed include ammonia (NH3), carbon monoxide (CO), formaldehyde (CH2O), and methyl mercaptan (CH3SH). The current state-of-the-art TCC sorbent is non-regenerable activated carbon. As a non-regenerable sorbent, its use negatively impacts the logistics for future missions. Thus, an ideal solution can be a vacuum-regenerable sorbent integrated with the xPLSS CO2/H2O removal system. To test new designs and sorbents, XploSafe has constructed a recirculating test bed that mimics the environment within the xPLSS by providing concentrations of the trace contaminant analytes generated at the operating temperature, humidity, pressure, and flow rates of the xPLSS. This system can perform regeneration or desorption by exposing the sorbent to a pressure swing from 4.3 psia to <1 torr over approximately 2 minutes. Using this test system, XploSafe evaluated various TCC prototypes constructed using rapid prototyping techniques and identified a process that allows vacuum regenerative TCC designs to be quickly examined for flow, pressure drop, and performance. By using toluene as a segregate for volatile organics, this test system was evaluated using both vacuum regenerable and non-regenerable sorbents to demonstrate the operational effectiveness of these sorbents in maintaining the concentrations of the trace contaminant analytes below the 7-day Spacecraft Maximum Allowable Concentrations.

Nicholas Materer↗

High Ice Water Content in Tropical Mesoscale Convective Systems (A Conceptual Model)

The phenomenon of high ice water content (HIWC) occurs in mesoscale convective systems (MCSs) when a large number of small ice particles with typical sizes of a few hundred micrometers, concentrations of the order of 10 2 –10 3 L −1 , and IWC exceeding 1 g m −3 are present at high altitudes. HIWC regions in MCSs may extend vertically up to 10 km above the melting layer and horizontally up to hundreds of kilometers, filling large volumes of the convective systems. HIWC has great geophysical significance due to its effect on precipitation formation, the hydrological cycle, and the radiative properties of MCSs. It is also recognized as a hazard for commercial aviation operations since it can result in engine power loss and in the malfunctioning of aircraft data probes. This study summarizes observational and numerical simulation efforts leading to the development of a conceptual model for the production of HIWC in tropical MCSs based on the data collected during the HAIC–HIWC campaign. It is hypothesized that secondary ice production (SIP) in the vicinity of the melting layer plays a key role in the formation and sustainability of HIWC. In situ observations suggest that the major SIP mechanism in the vicinity of the melting layer is related to the fragmentation of freezing drops (FFDs). Both in situ data and numerical simulations suggest that the recirculation of drops through the melting layer led to the amplification of SIP. The proposed conceptual model and simulation results motivate further efforts to extend reproducible laboratory measurements.

high ice water content↗

Wake Velocimetry of a Sphere-Cone Model in a Mach 10 Air Freestream using FLEET

Velocity measurements in the wake behind a sphere-cone-shaped vehicle wind tunnel model in a Mach 10 hypersonic air flow using femtosecond laser electronic excitation tagging (FLEET) are reported in this work. The FLEET measurements were performed at 1 kHz using a femtosecond laser centered at 800 nm and an ultrahigh-speed intensified camera system. The results reported here are for a single freestream condition corresponding to approximately Re ∞ /L = 3.6∙10 6 m -1 . The performance of the velocimetry instrument was evaluated in the quiescent test section at conditions relevant to the wake measurements. For velocity measurements in the wake, the FLEET measurement volume was translated to several radial locations from the model centerline in the vertical direction and at a streamwise location corresponding to approximately 12 mm from the payload. Reverse flow with mean velocities ranging from -12 m/s to -48 m/s were observed in the recirculating region of the wake, whereas hypersonic velocities in the range of 1079 m/s to 1183 m/s were observed in the free shear layer. A velocity uncertainty methodology is also outlined and applied for the reported measurements. The velocity data reported in this work is expected to play a significant role in the validation of computational codes modeling the hard-to-predict separated hypersonic wake.

FLEET↗

Wake Velocimetry of a Sphere-Cone Model in a Mach 10 Air Freestream using FLEET

Velocity measurements in the wake behind a sphere-cone-shaped vehicle wind tunnel model in a Mach 10 hypersonic air flow using femtosecond laser electronic excitation tagging (FLEET) are reported in this work. The FLEET measurements were performed at 1 kHz using a femtosecond laser centered at 800 nm and an ultrahigh-speed intensified camera system. The results reported here are for a single freestream condition corresponding to approximately Re ∞ /L = 3.6∙10 6 m -1 . The performance of the velocimetry instrument was evaluated in the quiescent test section at conditions relevant to the wake measurements. For velocity measurements in the wake, the FLEET measurement volume was translated to several radial locations from the model centerline in the vertical direction and at a streamwise location corresponding to approximately 12 mm from the payload. Reverse flow with mean velocities ranging from -12 m/s to -48 m/s were observed in the recirculating region of the wake, whereas hypersonic velocities in the range of 1079 m/s to 1183 m/s were observed in the free shear layer. A velocity uncertainty methodology is also outlined and applied for the reported measurements. The velocity data reported in this work is expected to play a significant role in the validation of computational codes modeling the hard-to-predict separated hypersonic wake.

FLEET↗

Evaluation of Long-Term Storage Stability and Operational Efficiency of Rapid Cycle Amine Adsorbents

With the recent incorporation of Mars Extravehicular Activity (EVA) into the 2025 NASA roadmap, Rapid Cycle Amine (RCA) technology advancement within the Exploration Extravehicular Mobility Unit (xEMU) applies to both the upcoming Lunar Artemis missions and future human exploration of Mars. The incorporation of commercial spacesuit vendors to service NASA’s crewed-space programs since 2021 has increased the demand for regenerable, RCA-based carbon dioxide (CO2) and humidity control adsorbents. The regenerable RCA subunit is the most advanced, long-term solution for CO2 removal and humidity control, enabling both lunar and Martian EVAs. The adsorbent selected for use within the RCA unit must exhibit sufficient storage stability and operational efficiency for prolonged missions. As XploSafe worked to simultaneously develop both a recirculating sub-atmospheric test rig and adsorbents for the RCA system within the xEMU, several novel adsorbents were evaluated for long-term storage stability in support of future extended-duration missions. The chosen materials were periodically evaluated by nuclear magnetic resonance (NMR) spectroscopy, thermal desorption-coupled with gas chromatography/mass spectrometry (TD-GC/MS), and CO2 adsorption to assess long-term storage efficacy across various environmental storage conditions. NMR spectroscopy was utilized by extracting the active CO2 adsorbing chemical from the solid support with deuterated solvent and comparing the spectra over time for degradation and change. The solid adsorbents were also analyzed via TD-GC/MS to reveal any potential off-gassing chemicals over time. Additionally, XploSafe’s breakthrough test rig was utilized to dose the solid adsorbents with a 585 BTU/h metabolic rate flow-equivalent CO2 stream and monitored for 0–99% CO2 breakthrough. The performance metrics from the breakthrough analysis were compared over the storage study duration for CO2 removal and humidity control. Xplo-SA9T was evaluated for 24 months, whereas two additional adsorbent variants, MMPA-Sorbent and LPEI-Sorbent, were each evaluated for 12 months.

John R Tidwell↗

Artemis I Space Launch System Base Heat Shield Thermal Protection System Performance

The Space Launch System (SLS) Core Stage base heat shield experienced the highest external heating environments on the entire launch vehicle during Artemis I ascent flight. This result was consistent with design predictions. The base heat shield experiences P50 cork combustion dynamics at low altitudes, plume-induced recirculation at moderate altitudes and then in-space base flow physics out to Main Engine Cut-Off (MECO). The base heat shield thermal protection system (TPS) is composed of a P50 cork ablator which is bonded to a substrate. The heat shield protects the gimbal actuation system, RS-25 turbomachinery systems and other aft section sensitive components during ascent. This paper estimates the base heat shield TPS performance from Artemis I using flight data from the NASA Langley Research Center’s Scientifically Calibrated In-Flight Imagery (SCIFLI) Airborne Multispectral Imager (SAMI), development flight instrumentation (DFI) and other TPS recession flight measurements. Predictions from computational and ground test-derived engineering ablation models and observations are also applied. Since no base heat shield substrate thermocouple data were obtained for Artemis I, an estimate of the TPS performance data is derived here. This data assesses thermal margin of the SLS Core Stage base heat shield and best informs the Artemis II Crewed mission to the moon.

aerothermodynamics↗

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↗