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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

SINDA/FLUINT and Thermal Desktop Multi-Node Settled and Unsettled Propellant Tank Modeling of Zero Boil Off Test

Cryogenic propellant storage tank self-pressurization involves complex physical phenomena which are usually analytically modelled via complex multidimensional CFD codes. Unfortunately these codes, even when modelling axisymmetric domains, may takes weeks or longer to obtain transient pressure and temperature information for relatively short periods of time (several seconds to several hours). Propellant tank storage end-to-end mission simulations can last a duration of days to weeks to months. Multi-node modelling of propellant tanks is a viable alternative to traditional CFD modelling and presents the advantage of greatly reduced run times on the order of hours and days compared to the weeks or longer for CFD codes. A multi-node model represents the fluid within the storage tank, as well as the storage tank itself, as a fluid-thermal network. This type of setup is not necessarily geometrically based. This can be accomplished using a commercial generalized fluid-thermal network code, such as SINDA/FLUINT (SF). The advantage of using a fluid-thermal network code like SF lies in its extensive ability to model the external environment of the storage tank through the graphical user interface, Thermal Desktop (TD). The total heat load into the tank may be a function of heaters and a complex radiative environment as well. Thermal Desktop may be used to address the detailed radiative environment of the tank as well as building a geometrically accurate depiction of the storage tank itself.

Sakowski, Barbara↗
NASA NTRS2023

Thermal Desktop Modeling of the 2016 CRYOTE-2 Tank Chill and Fill Tests

The storing and transfer of cryogenic propellants is an enabling technology for NASA as it moves to expand future missions into low Earth orbit (LEO) and beyond. The transfer of cryogenic propellants is of particular interest because it has never been successfully demonstrated in microgravity. Several ground tests have been conducted in past decades examining various tank chilldown and fill methods. Creating accurate models using these historical datasets is a vital step toward developing appropriate modeling tools to form pre-test predictions for eventual flight and ground tests of various novel injector concepts. The goal of this work was to create a working model in Thermal Desktop using data from the CRYOTE-2 experiments whose purpose was to demonstrate the chill and fill process in a spherical receiver tank parametrically examining the effect of injection method, receiver tank initial wall temperature and initial state, supply pressure, and mass flow rate on the NVF process. These tests were conducting using liquid nitrogen with different injectors with different injection patterns. The focus of the current work is on one particular spray nozzle. The pressure rise inside the tank, the fill level, and the change in the outside wall temperature were all tracked and compared with test data. The Thermal Desktop model was able to accurately predict each of these metrics for this nozzle within 11.0%, 22.0%, and 7.0%, respectively.

Cryogenic Tank Chilldown↗
NASA NTRSDate not supplied

Using Thermal Desktop to Model Effects of Plume Heating on MLI

Gateway draws on experience from International Space Station (ISS) and geostationary satellites for many aspects of design, including Multilayer Insulation (MLI) material selection. MLI is used on external thermal surfaces and can be exposed to high plume heating on modular spacecraft with visiting vehicles such as Gateway. Due to Gateway’s smaller size and closer proximity of sensitive hardware to plumes from visiting vehicles, the expected and contingency plume heating loads are higher than those of ISS. Because of MLI’s low mass and thermal conductivity between layers, high plume heating loads can potentially heat MLI past its thermal limits. Usually when modeling MLI, it is a single node of insulation with a given effective emissivity. This method is not adequate for modeling with plume heating because you cannot accurately measure the MLI temperature, or the temperature of each individual layer. Modeling MLI is complicated because there are several layers and the conduction between each layer is undefined. It is further complicated by the variety of material options for MLI and their respective weights, optics, transmissivity, and temperature limits. This paper shows an attempt at modeling different MLI blankets exposed to solar and plume heating loads using Thermal Desktop. Several sensitivity studies were run including examining distance between layers, varying conductivity between layers, effects of different MLI materials, and plume heating loads and durations.

MLI↗
NASA NTRSDate not supplied

Using Thermal Desktop to Model the Effects of Plume Heating on MLI

Gateway draws on experience from International Space Station (ISS) and geostationary satellites for many aspects of design, including Multilayer Insulation (MLI) material selection. MLI is used on many external surfaces, some of which can be exposed to high plume heating from visiting vehicle during docking and undocking. Due to Gateway’s smaller size and closer proximity of sensitive hardware to plumes from visiting vehicles, the expected and contingency plume heating loads are higher than those experienced by the ISS. Because of MLI’s low mass and thermal conductivity between layers, high plume heating loads can potentially heat MLI past its thermal limits. MLI is typically modeled as a single node of insulation with a given effective emissivity. This method is not adequate for modeling plume heating impacts because the temperature of each individual layer cannot be determined. Modeling MLI is complicated because there are several layers and the conduction between each layer is undefined. It is further complicated by the variety of material options for MLI and their respective mass, optics, transmissivity, and temperature limits. This paper shows modeling of a MLI blanket exposed to solar and plume heating loads using Thermal Desktop. Several sensitivity studies were run including examining distance between layers, varying effective emissivity, effects of different MLI materials, and plume heating loads and durations.

MLI↗
NASA NTRSDate not supplied

Using Thermal Desktop to Model the Effects of Plume Heating on MLI

Gateway draws on experience from International Space Station (ISS) and geostationary satellites for many aspects of design, including Multilayer Insulation (MLI) material selection. MLI is used on many external surfaces, some of which can be exposed to high plume heating from visiting vehicle during docking and undocking. Due to Gateway’s smaller size and closer proximity of sensitive hardware to plumes from visiting vehicles, the expected and contingency plume heating loads are higher than those experienced by the ISS. Because of MLI’s low mass and thermal conductivity between layers, high plume heating loads can potentially heat MLI past its thermal limits. MLI is typically modeled as a single node of insulation with a given effective emissivity. This method is not adequate for modeling plume heating impacts because the temperature of each individual layer cannot be determined. Modeling MLI is complicated because there are several layers and the conduction between each layer is undefined. It is further complicated by the variety of material options for MLI and their respective mass, optics, transmissivity, and temperature limits. This paper shows modeling of a MLI blanket exposed to solar and plume heating loads using Thermal Desktop. Several sensitivity studies were run including examining distance between layers, varying effective emissivity, effects of different MLI materials, and plume heating loads and durations.

MLI↗
NASA NTRSDate not supplied

Thermal Vacuum Testing Strategy and Thermal Desktop Model Correlation for the Moon to Mars Planetary Autonomous Construction Technologies (MMPACT) Robotic Terrestrial Arm

This paper discusses the initial thermal vacuum testing of the MMPACT robotic terrestrial arm. The robotic arm is part of a construction system designed for the lunar south pole surface. The first thermal vacuum test was a risk mitigation test to ensure the arm could operate in vacuum, with all other data collection as secondary priorities. 44 thermocouples (TCs) were attached to the arm. Installation was done with additional care to account for both the extra wiring harness weight on the arm with the TC wires and increased focus on stabilizing the TC attachments to the moving components. Thermal steady state of <= 0.01°C/hour was reached for the hot set of testing conditions. This data was used to correlate the Thermal Desktop (TD) model to the test results within +/- 5°C.

Thermal analysis↗
NASA NTRSDate not supplied

Thermal Vacuum Testing Strategy and Thermal Desktop Model Correlation for the Moon to Mars Planetary Autonomous Construction Technologies (MMPACT) Robotic Terrestrial Arm

This paper discusses the initial thermal vacuum testing of the MMPACT robotic terrestrial arm. The robotic arm is part of a construction system designed for the lunar south pole surface. The first thermal vacuum test was a risk mitigation test to ensure the arm could operate in vacuum, with all other data collection as secondary priorities. 44 thermocouples (TCs) were attached to the arm. Installation was done with additional care to account for both the extra wiring harness weight on the arm with the TC wires and increased focus on stabilizing the TC attachments to the moving components. Thermal steady state of <= 0.01°C/hour was reached for the hot set of testing conditions. This data was used to correlate the Thermal Desktop (TD) model to the test results within +/- 5°C.

Thermal analysis↗
NASA NTRS2026

Predicting Operational Performance of xEMU Boot at Lunar South Pole Temperatures using Thermal Desktop ®

The spacesuit boots that will be used on Artemis lunar south pole surface missions will be exposed to extremely cold temperatures (down to ~50 K). To assess the performance of the government’s Exploration Extravehicular Mobility Unit (xEMU) lunar boot in these permanently shadowed regions, testing was performed at the Jet Propulsion Lab (JPL) in the Cryogenic Ice Transfer, Acquisition Development, and Excavation Laboratory (CITADEL) thermal vacuum (TVAC) chamber. This paper documents the data analysis, thermal boot model correlation, and operational predictions conducted using data from the xEMU CITADEL TVAC test. Expected thermal conductances within the boot and between the boot and environment were calculated from test data, which was then used as an initial guess for conductances within a Thermal Desktop (TD) model. Correlation of the TD model using the internal SOLVER feature was performed across 10 different test points which varied external temperature, internal boot ventilation flowrate, and contact pressure. Operational performance at the lunar south pole was then predicted using results from the correlated model. While the predictions provide evidence for acceptable performance of the boots at the 100K environment test point, there is still substantial uncertainty in performance, especially at the 48K test point. This uncertainty is due in part to testing limitations such as contacting the foot to a hard metal plate rather than granular regolith, and model limitations such as the lack of a realistic foot model. These limitations and their impacts are addressed in detail in this paper. The results of this test series and model correlation underscore the importance of additional improved testing and modeling for characterizing the expected thermal resistance between the outside of the boot and the lunar surface.

Spacesuit↗
NASA NTRS2017

Correleation of the SAGE III on ISS Thermal Models in Thermal Desktop

The Stratospheric Aerosol and Gas Experiment III (SAGE III) instrument is the fifth in a series of instruments developed for monitoring aerosols and gaseous constituents in the stratosphere and troposphere. SAGE III was launched on February 19, 2017 and mounted to the International Space Station (ISS) to begin its three-year mission. A detailed thermal model of the SAGE III payload, which consists of multiple subsystems, has been developed in Thermal Desktop (TD). Correlation of the thermal model is important since the payload will be expected to survive a three-year mission on ISS under varying thermal environments. Three major thermal vacuum (TVAC) tests were completed during the development of the SAGE III Instrument Payload (IP); two subsystem-level tests and a payload-level test. Additionally, a characterization TVAC test was performed in order to verify performance of a system of heater plates that was designed to allow the IP to achieve the required temperatures during payload-level testing; model correlation was performed for this test configuration as well as those including the SAGE III flight hardware. This document presents the methods that were used to correlate the SAGE III models to TVAC at the subsystem and IP level, including the approach for modeling the parts of the payload in the thermal chamber, generating pre-test predictions, and making adjustments to the model to align predictions with temperatures observed during testing. Model correlation quality will be presented and discussed, and lessons learned during the correlation process will be shared.

Amundsen, Ruth M.↗
NASA NTRS2017

Mars Propellant Liquefaction Modeling in Thermal Desktop

NASAs current Mars architectures are assuming the production and storage of 23 tons of liquid oxygen on the surface of Mars over a duration of 500+ days. In order to do this in a mass efficient manner, an energy efficient refrigeration system will be required. Based on previous analysis NASA has decided to do all liquefaction in the propulsion vehicle storage tanks. In order to allow for transient Martian environmental effects, a propellant liquefaction and storage system for a Mars Ascent Vehicle (MAV) was modeled using Thermal Desktop. The model consisted of a propellant tank containing a broad area cooling loop heat exchanger integrated with a reverse turbo Brayton cryocooler. Cryocooler sizing and performance modeling was conducted using MAV diurnal heat loads and radiator rejection temperatures predicted from a previous thermal model of the MAV. A system was also sized and modeled using an alternative heat rejection system that relies on a forced convection heat exchanger. Cryocooler mass, input power, and heat rejection for both systems were estimated and compared against sizing based on non-transient sizing estimates.

Cryogenics↗
NASA NTRS2017

Mars Propellant Liquefaction and Storage Performance Modeling using Thermal Desktop with an Integrated Cryocooler Model

NASAs current Mars architectures are assuming the production and storage of 23 tons of liquid oxygen on the surface of Mars over a duration of 500+ days. In order to do this in a mass efficient manner, an energy efficient refrigeration system will be required. Based on previous analysis NASA has decided to do all liquefaction in the propulsion vehicle storage tanks. In order to allow for transient Martian environmental effects, a propellant liquefaction and storage system for a Mars Ascent Vehicle (MAV) was modeled using Thermal Desktop. The model consisted of a propellant tank containing a broad area cooling loop heat exchanger integrated with a reverse turbo Brayton cryocooler. Cryocooler sizing and performance modeling was conducted using MAV diurnal heat loads and radiator rejection temperatures predicted from a previous thermal model of the MAV. A system was also sized and modeled using an alternative heat rejection system that relies on a forced convection heat exchanger. Cryocooler mass, input power, and heat rejection for both systems were estimated and compared against sizing based on non-transient sizing estimates.

fluid modeling↗
NASA NTRS2023

Thermal Desktop Modeling of the RRM3 On-Orbit Cryogenic Methane Storage and Active Cooling Experiment

The storing of cryogenic propellants is an enabling technology for NASA as it moves to expand future missions into low Earth orbit (LEO) and beyond. The Robotic Refueling Mission–3 (RRM3) experiment launched in 2018 and was designed to demonstrate tank self-pressurization during storage and active cooling of liquid methane in microgravity. Creating accurate models using existing datasets from flight experiments such as RRM3 is a vital step toward developing appropriate modeling tools to form pre-test predictions for future flight systems. The goal of this work was to create a working model in Thermal Desktop of the RRM3 source Dewar during the microgravity self-pressurization experiment. The pressure rise, temperature distribution of the fluid inside the tank, and the wall temperatures were all tracked and compared with test data. Initial results show good agreement between each of these metrics and the experimental results. This work is ongoing and will yield further insights into the thermal behavior of cryogens in microgravity.

Tank self-pressurization↗
NASA NTRSDate not supplied

Validation of Thermodynamic Vent System Performance using Thermal Desktop

Cryogenic fluid management (CFM) for in-space propulsion systems is crucial to enabling future space missions. A means to control the pressure inside a propellant tank is necessary to prevent the venting of liquid propellant in microgravity environments. A thermodynamic vent system (TVS) is one way to regulate the pressure and temperature of the fluid inside a tank. A previous study created a simplified model of a TVS in a two-phase cryogenic heat exchanger. The TVS expands the working fluid across a Joule-Thomson (J-T) device and routes the cooled fluid through the heat exchanger to remove heat from the surrounding fluid. The model was able to predict the TVS heat extraction performance and was validated against experimental data using the same hardware. This study expands the model of the TVS into Thermal Desktop (TD) and recreates the results from both the original model and the experimental data. This new TD model has the potential to be used to predict TVS heat extraction performance in cryogenic propellant tanks for future space missions.

Cryogenic Fluid Management↗
NASA NTRS2002

How to Quickly Import CAD Geometry into Thermal Desktop

There are several groups at JPL (Jet Propulsion Laboratory) that are committed to concurrent design efforts, two are featured here. Center for Space Mission Architecture and Design (CSMAD) enables the practical application of advanced process technologies in JPL's mission architecture process. Team I functions as an incubator for projects that are in the Discovery, and even pre-Discovery proposal stages. JPL's concurrent design environment is to a large extent centered on the CAD (Computer Aided Design) file. During concurrent design sessions CAD geometry is ported to other more specialized engineering design packages.

Wright, Shonte↗