Results for “CAMPAIGN STORAGE”

NASA NTRS2018

Calendar Life Aging of Two Models of 18650 Lithium Ion Cells

This study will analyze calendar life aging performance of two 18650 lithium ion cell models deployed in human space flight applications. Test conditions of voltage and temperature were selected based on product application. The cell test campaign includes storage of a cell model produced in April 2007 and initial calendar life performance for a cell produced in December 2013. Mechanistic aging models will be considered. The results of this study are applicable to applications requiring extended low state of charge storage and low cycle life.

18650↗

NASA NTRSDate not supplied

Updates in Developing a Prototype Science Pipeline and Full-Volume, Global Hyperspectral Synthetic Data Sets for NASA’s Earth System Observatory’s Upcoming Surface, Biology and Geology Mission

The Surface Biology and Geology (SBG) mission recently passed mission confirmation review and has entered phase A – design and development. SBG will acquire high resolution solar-reflected spectroscopy and thermal infrared observations at a data rate of ~2.5 TB/day and generate products at ~40 TB/day. Given that the per-day volume is greater than NASA’s total extant airborne hyperspectral data collection, collecting, processing, disseminating, and exploiting the SBG data present new challenges. To meet these challenges, we have developed a prototype science pipeline and a full-volume global hyperspectral synthetic data set to help prepare for SBG’s flight (see poster GC42D-0730). Our science pipeline is based on the science processing technology developed for NASA’s Kepler and TESS planet-hunting missions. The pipeline infrastructure, Ziggy, provides a scalable architecture for robust, repeatable, and replicable science and application products that can be run on a range of systems from a laptop to the cloud or a supercomputer. Ziggy is compliant with NASA Procedural Requirement (NPR) 7150.2C, is at a technical readiness level (TRL) of 7 and has been released to github.com/nasa/ziggy. We integrated Ziggy with EO-1/Hyperion workflows to build a prototype pipeline and ingested the 17-year mission archive that provides globally sampled visible through shortwave infrared spectra that are representative of SBG data types and volumes. We fully implemented the first stage and processed the entire 55 TB Hyperion data set from the raw data (Level 0) to top-of-the-atmosphere radiance (Level 1R). We are currently evaluating the ISOFIT atmospheric correction module to convert the L1R data to surface reflectance (Level 2) before reprocessing the full data set to L2. Crosschecks are being performed with RadCalNet as well as with coincident observations by AVIRIS. We are also investigating modern methods for georectifying the Hyperion scenes. Finally, we describe an analysis of the cost to conduct forward processing and reprocessing campaigns for SBG on HECC with dedicated compute and storage resources using the resurrected Hyperion pipeline as a proxy for full-volume SBG data. The analysis demonstrates that SBG L0 data can be processed to L2 on HECC with full reprocessing campaigns every two years for ~$2.6M over a 7-year lifespan. Moreover, 69% of the system capacity would be available for other activities, possibly enabling future open-source science activities, including algorithm development, L3+ processing, .etc.

ESD↗

NASA NTRS2021

Scheduling and Operations of the ECOSTRESS Mission

This paper describes the development and use of an automated scheduling system for the National Aeronautics and Space Administration’s (NASA) ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission. Key to the success of the ECOSTRESS mission has been the use of automated scheduling in mission analysis pre-launch, and in successful operations where automated scheduling was deployed to address several operational challenges. ECOSTRESS uses an adaptation of the Compressed Large-scale Activity Scheduling and Planning (CLASP) system to automatically select science observations respecting area and point target priorities as well as visibility, illumination, onboard storage, and radiation constraints to satisfy high-level prioritized science campaigns. The ECOSTRESS scheduler was used pre-launch to predict the effectiveness of alternative formulations of science campaign definitions accounting for the impact of data volume, keepout, and orbit/illumination/visibility constraints to derive the initial operational science campaign definitions and priorities. The scheduler was then used after instrument checkout for operations. ECOSTRESS has faced multiple operational challenges relating to instrument firmware and hardware, and the scheduler has been updated several times to address these challenges. The instrument Mass Storage Units (MSUs) had operational issues, requiring the scheduler to plan for and schedule commands to handle intricacies of data management. After many months of operations, both MSUs on the instrument became non-functioning and the firmware of the instrument was updated to bypass the MSUs. A further update to the ECOSTRESS scheduler enabled the scheduler to operate in this new operations mode. The ECOSTRESS scheduler has also been updated to improve handling of along-track uncertainty inherent in International Space Station operations. The flexibility and ease of updating of the automated scheduler has been a significant contributor to successful operations of the ECOSTRESS mission.

Padams, Jordan↗

NASA NTRS2014

Interannual Variations in Aerosol Sources and Their Impact on Orographic Precipitation Over California's Central Sierra Nevada

Aerosols that serve as cloud condensation nuclei (CCN) and ice nuclei (IN) have the potential to profoundly influence precipitation processes. Furthermore, changes in orographic precipitation have broad implications for reservoir storage and flood risks. As part of the CalWater I field campaign (2009-2011), the impacts of aerosol sources on precipitation were investigated in the California Sierra Nevada. In 2009, the precipitation collected on the ground was influenced by both local biomass burning (up to 79% of the insoluble residues found in precipitation) and long-range transported dust and biological particles (up to 80% combined), while in 2010, by mostly local sources of biomass burning and pollution (30-79% combined), and in 2011 by mostly long-range transport from distant sources (up to 100% dust and biological). Although vast differences in the source of residues was observed from year-to-year, dust and biological residues were omnipresent (on average, 55% of the total residues combined) and were associated with storms consisting of deep convective cloud systems and larger quantities of precipitation initiated in the ice phase. Further, biological residues were dominant during storms with relatively warm cloud temperatures (up to -15 C), suggesting these particles were more efficient IN compared to mineral dust. On the other hand, lower percentages of residues from local biomass burning and pollution were observed (on average 31% and 9%, respectively), yet these residues potentially served as CCN at the base of shallow cloud systems when precipitation quantities were low. The direct connection of the source of aerosols within clouds and precipitation type and quantity can be used in models to better assess how local emissions versus long-range transported dust and biological aerosols play a role in impacting regional weather and climate, ultimately with the goal of more accurate predictive weather forecast models and water resource management.

Creamean, J. M.↗

NASA NTRS2006

Observed Scaling Behavior of Snow and Soil Moisture Signatures from the CLPX and NAFE Campaigns

Seasonal snow and soil moisture (SM) are important elements of the Earth's water cycle, acting as storage elements and by modulating water and energy exchanges between the land surface and the atmosphere and space. Accurate estimates of snow water equivalent (SWE) and SM also play an important role in weather and climate models over a range of scales. There are many advantages for the retrieval of snow parameters using passive microwave sensors. However, the current scale mismatch between many high-resolution applications and available satellite snow sensor footprints (approx.25km) presents challenges. There is also a scale mismatch for planned L-band soil moisture satellite measurements with their large (50-100 km) passive microwave footprints. Combined radiometer-radar schemes are being explored as possible aids, but this is still an area of ongoing research. Retrieval accuracies are limited in part by complex, and potentially nonlinear relationships between SWE or SM and microwave emission signatures. We will use airborne and satellite observations from two field campaigns to examine the scaling behavior of brightness temperatures and SWE and SM across scales from 100 meters to 10's of kilometers. The results will provide examples of the appropriate spatial sampling scales for new sensors, and guidance for downscaling schemes. The two campaigns are NASA's Cold Land Processes Experiment- 1 (CLPX- 1 : Colorado, 2002 & 2003), and the Australian National Airborne Field Experiment (NAFE, Nov, 2005). The analyses will also illustrate the roles and spatial scales of the underlying phenomena (e.g., vegetation, topography) that control subpixel heterogeneity.

Kim, Edward J.↗

NASA NTRSDate not supplied

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗

NASA NTRSDate not supplied

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗

NASA NTRS2022

Europa Clipper Payload Verification and Validation: Avionics-Instrument Interface Test Campaign

NASA's Europa Clipper mission will investigate Jupiter's icy moon Europa using a payload suite consisting of nine instruments to address a range of scientific objectives concerning Europa's habitability. As the project proceeds past its Critical Design Review, confidence is being built in the system's ability to achieve mission objectives through the implementation of a rigorous payload verification and validation (V&V) program. As part of this payload V&V program, instrument box-level testing was performed by the payload team to verify select instrument-avionics interface requirements. This testing was performed at JPL using the avionics testbed's Bulk Data Storage Emulator (BDSEM) with visiting instrument Test Models. This paper summarizes the Data Link test campaign involving roughly four days of functional testing per instrument, including planning, testing methods, types of issues found, and the requirement closure process. Detail is also provided on the development, deployment, and validation of a standardized analysis tool used in data reviews. This testing verified requirements related to commanding rates, loss of link, packet format, clock counters, loopback test capability, and SpaceWire jitter and skew margins. Additional risk reduction testing of basic commanding, counter behavior, science data collection and transfer, and interface swapping was also performed. Because the BDSEM venue was not originally designed to be a run for record venue, the process of characterizing venue fidelity and establishing suitability for requirement closure using data collected in this venue will also be addressed.In order to close requirements, an extensible tool was developed to post-process instrument command and telemetry data from their original binary to a human-readable format and give visibility to errors detected within the data, such as packets with Cyclic Redundancy Check errors. This tool, called payload-packet-parser, is a Python 3.9 command line tool built using a variety of open-source Python libraries. Payload-packet-parser was designed to support parsing command and telemetry packets for all Europa Clipper instruments and additional analysis tools were developed for verification of specific information interface requirements. This test campaign, including post-processing using a single parsing and verification toolset, allowed for early interface testing, alleviating testing burdens on instrument teams and buying down risk on the instrument-avionics interface by finding hardware and software issues and idiosyncrasies prior to integration with system test venues. Over twenty issues were discovered across the payload, resulting in software updates and instrument rework well in advance of any system impacts. This paper concludes with an assessment of benefits and costs of this type of testing and lessons learned.

Montanez, Leticia↗

NASA NTRS2015

Opportunities and Strategies for Testing and Infusion of ISRU in the Evolvable Mars Campaign

HE Evolvable Mars Campaign (EMC) is developing the plans and systems needed for a robust, evolutionary strategy to explore cis-lunar space, the Mars sphere of influence (including the moons of Mars), and the surface of Mars. Recently, the emphasis of NASA's plans has changed to focus on the prolonged pioneering of space, rather than focusing on a single crewed mission as the ultimate goal. A sustainable, pioneering vision of space would include in-situ resource utilization (ISRU) in multiple forms and at multiple destinations: atmospheric capture of Mars CO2 and/or volatiles for consumables and propellants, regolith for bulk and refined materials, and in-situ manufacturing at the Moon, Mars, and other bodies. These resources would enable a reduction in the logistical needs from Earth for future missions, thus preparing the way for a sustained presence on Mars. Although the EMC initially relies only on propellant production for the Mars ascent vehicle via ISRU, one of its primary objectives is to prospect at every EMC destination to understand the potential for ISRU; this will permit true pioneering to be enabled after the first crew arrives at Mars. Recent and ongoing analysis has considered the possible prospecting measurements that can be performed at the asteroid returned to cis-lunar space by the Asteroid Robotic Redirect Mission (ARRM), at the lunar surface, at Phobos and Deimos, and on the surface of Mars to identify available resources for future use. These opportunities will be available on missions currently in the Evolvable Mars Campaign construct, and will also facilitate the testing and demonstration of resource acquisition, processing, storage, and useage technologies that can play a role in later missions. This analysis has also led to the identification of several objectives that should be targeted during the missions building up to and including the initial crewed missions. These objectives are mapped to strategies for incorporating ISRU to support resource cycle closure and reduce mass requirements from Earth. This analysis has yielded engineering constraints, based on ISRU, that impact the evaluation of landing sites for missions to the surface of Mars. The terrain of a particular site must be sufficiently flat to permit ISRU systems, as well as ancillary systems such as power and propellant storage tanks, to be landed, moved into position, set up, and operated. Water must be accessible in a form that can be acquired via ISRU, in quantities that align with demands. The chosen method of acquiring and processing water should align with the available resources at a particular site, and that site must have sufficient quantities to meet the requirements (based on crew consumables and propellant demands). Lower altitude landing sites are preferred, as the increase in density can facilitate carbon dioxide acquisition from the atmosphere. Another preference is for sites with a greater ability to move regolith for civil engineering purposes; for example, this would be conducive to both bulk regolith uses (such as the manufacture of berms), and processed regolith uses (such as microwave sintering).

Evolvable Mars Campaign↗

NASA NTRS2018

Temperature Constraints on the Storage and Curation of Volatile-Rich Samples from the Lunar Poles

Final Document is attached. Introduction: NASA's Lunar Exploration Campaign includes Lunar sample return efforts beginning in the mid-2020's and human landed missions in the late 2020's-early 2030's. Volatile-rich samples from the Lunar poles will be high-priority targets due to their resource potential for human explorers and high science value. In order to precisely characterize the nature of these polar volatile materials upon return to Earth, they will need to be transported and curated under conditions that minimize their chemical and physical alteration. NASA Policy Directive (NPD) 7100.10F mandates the preservation of existing extraterrestrial samples with minimal alteration, extensive and quantitative documentation of alteration that is provided to investigators, and "the development of long-range plans" for samples yet to be acquired. This abstract summarizes new efforts by the Astromaterials Acquisition and Curation Office at JSC to assess the optimal

Mitchell, J. L.↗

NASA NTRS2016

Liquefaction and Storage of In-Situ Oxygen on the Surface of Mars

ISRU is currently base-lined for the production of oxygen on the Martian surface in the Evolvable Mars Campaign Over 50 of return vehicle mass is oxygen for propulsion. There are two key cryogenic fluid-thermal technologies that need to be investigated to enable these architectures. High lift refrigeration systems. Thermal Insulation systems, either lightweight vacuum jackets of soft vacuum insulation systems.

Liquefaction↗

NASA NTRS1995

Plasma properties and magnetic field structure of the solar corona, based on coordinated Max 1991 observations from SERTS, the VLA, and magnetographs

The purposes of this investigation are to use existing, calibrated, coaligned sets of coordinated multiwaveband observations of the Sun to determine the coronal magnetic field strength and structure, and interpret the collective observations in terms of a self-consistent model of the coronal plasma and magnetic field. This information is vital to understanding processes such as coronal heating, solar wind acceleration, pre-flare energy storage, and active region evolution. Understanding these processes is the central theme of Max '91, the NASA-supported series of solar observing campaigns under which the observations acquired for this work were obtained. The observations came from NASA/GSFC's Solar EUV Rocket Telescope and Spectrograph (SERTS), the Very Large Array (VLA), and magnetographs. The technique of calculating the coronal magnetic field is to establish the contributions to the microwave emission from the two main emission mechanisms: thermal bremsstrahlung and thermal gyroemission. This is done by using the EUV emission to determine values of the coronal plasma quantities needed to calculate the thermal bremsstrahlung contribution to the microwave emission. Once the microwave emission mechanism(s) are determined, the coronal magnetic field can be calculated. A comparison of the coronal magnetic field derived from the coordinated multiwaveband observations with extrapolations from photospheric magnetograms will provide insight into the nature of the coronal magnetic field.

Brosius, Jeffrey W.↗

NASA NTRS1992

The Fifth Calibration/Data Product Validation Panel Meeting

The minutes and associated documents prepared from presentations and meetings at the Fifth Calibration/Data Product Validation Panel meeting in Boulder, Colorado, April 8 - 10, 1992, are presented. Key issues include (1) statistical characterization of data sets: finding statistics that characterize key attributes of the data sets, and defining ways to characterize the comparisons among data sets; (2) selection of specific intercomparison exercises: selecting characteristic spatial and temporal regions for intercomparisons, and impact of validation exercises on the logistics of current and planned field campaigns and model runs; and (3) preparation of data sets for intercomparisons: characterization of assumptions, transportable data formats, labeling data files, content of data sets, and data storage and distribution (EOSDIS interface).

Source record↗

NASA NTRS1997

Simulation of Boreal Ecosystem Carbon and Water Budgets: Scaling from Local to Regional Extents

A coupled water and energy balance model is developed. This model can predict the partitioning of water and energy between major source, sink and storage elements within the Boreal-Ecosystem-Atmospheric Study (BOREAS) areas. The results of testing the model against data collected at BOREAS tower sites during Intensive Field Campaigns and remotely sensed data collected across the BOREAS region are presented.

Wood, Eric F.↗

NASA NTRS2002

An End-to-End Architecture for Science Goal Driven Observing

New observatories will have greater on-board storage capacity and on-board processing capabilities. The new bottleneck will be download capacity. The cost of downlink time and limitations of bandwidth will end the era where all exposure data is downloaded and all data processing is performed on the ground. In addition, observing campaigns involving inherently variable targets will need scheduling flexibility to focus observing time and data download on exposures that are scientifically interesting. The ability to quickly recognize and react to such events by re-prioritizing the observing schedule will be an essential characteristic for maximizing scientific returns. It will also be a step towards increasing spacecraft autonomy, a major goal of NASA's strategic plan. The science goal monitoring (SGM) system is a proof-of-concept effort to address these challenges. We are developing an interactive distributed system that will use on-board processing and storage combined with event-driven interfaces with ground-based processing and operations, to enable fast re-prioritization of observing schedules, and to minimize time spent on non-optimized observations. SGM is initially aimed towards time-tagged observing modes used frequently in spectroscopic studies of varying targets. In particular, the SGM is collaborating with the proposed MIDEX-class mission Kronos team. The variable targets that Kronos seeks to study make an adaptive system such as SGM particularly valuable for achieving mission goals. However, the architecture and interfaces will also be designed for easy adaptability to other observing platforms, including ground-based systems and to work with different scheduling and pipeline processing systems. This talk will focus on our strategy for developing SGM and the technical challenges that we have encountered. We will discuss the SGM architecture as it applies to the Kronos mission and explain how it is scalable to other missions.

Jones, Jeremy↗

NASA NTRSDate not supplied

ARCTRON: A Rapid Experimental Proving Ground for TPS Experiments and Arcjet Technology Development

Innovation in high-enthalpy facilities is fundamentally limited by the cost and risk of experimentation. New concepts for plasma control, diagnostics, facility components, and plasma-material interaction often require repeated iterations that are impractical to perform in production arcjets. As a result, promising ideas may remain unexplored or reach operational facilities only after significant development effort. ARCTRON is being developed as a rapid experimental proving ground where new ideas in plasma science, arcjet engineering, diagnostics, and material response can be conceived, tested, and quantitatively evaluated before transition to large-scale facilities. The platform combines radio-frequency (RF) and DC arc plasma generation, externally applied magnetic fields, configurable gas composition, reduced-pressure operation, laser heating, electrical biasing, and modular diagnostic access. These capabilities permit the plasma source, applied forcing, test article, and measurement configuration to be modified independently, allowing individual physical mechanisms to be isolated more readily than in a traditional test environment. One class of investigations addresses fundamental plasma-surface interaction physics. Conventional material tests often expose a specimen simultaneously to convective heating, reactive species, pressure, shear, radiation, and surface-current effects. The resulting material response may be measured accurately, while the contribution of each mechanism remains difficult to identify. ARCTRON is designed to vary these effects selectively. Plasma chemistry can be changed independently through configurable gas mixtures; magnetic fields and electrical biasing can modify charged-particle transport; laser heating can provide a non-plasma thermal input; and pressure, flow, and discharge mode can be varied over a broad operating space. This enables controlled tests of hypotheses involving surface catalycity, reactive-species transport, plasma-assisted oxidation, electromagnetic effects, shear, and the relative contributions of thermal and chemical loading. A second class of investigations enabled by this approach concerns the engineering of high-enthalpy facilities themselves. Arc-heated facilities are limited by electrode erosion, unstable arc attachment, localized heating, and damage to nozzles and other plasma-facing components. ARCTRON provides a lower-cost environment for testing concepts intended to mitigate these limitations. Candidate investigations include the use of applied magnetic fields to alter current paths and reduce plasma interaction with nozzle walls, ExB forcing to introduce controlled plasma rotation, magnetic or geometric approaches for distributing arc attachment, and alternative electrode or discharge configurations intended to reduce erosion and improve stability. Because the platform is reconfigurable, these concepts can be evaluated through repeated design--build--test cycles before they are considered for implementation in operational facilities. The platform also supports the development and validation of diagnostics that may be difficult to introduce initially into a large arcjet. Current and planned measurements include spatially resolved optical emission spectroscopy, electrostatic probes, fast imaging, pyrometry, calorimetry, laser-induced fluorescence, and absorption spectroscopy. These diagnostics are intended not merely to document a nominal operating condition, but to constrain the local plasma state and its relationship to component or material response. The modular facility geometry allows diagnostic concepts to be tested, calibrated, and compared under repeatable conditions before deployment in more demanding environments. ARCTRON is also supported by an integrated software suite. Automated control and data acquisition allow discharge parameters, gas composition, magnetic fields, diagnostic timing, and test configuration to be recorded as part of each experiment (STARDAC - Software for Testing, Analysis, Research Data, and Control). The Backend for Experiment Analysis, Storage, and Traceability (BEAST) is a database that provides the infrastructure needed to associate heterogeneous measurements with facility configuration, specimen identity, calibration state, geometry, and analysis provenance. This backend is particularly important for exploratory campaigns, in which many related configurations may be tested, and the value of an individual experiment depends on its connection to earlier and subsequent iterations. Complementary analysis capabilities, including computer-vision-based transient response measurements (arcjetCV), three-dimensional surface reconstruction (STARSCAN), and model-based Bayesian inference (SHIELD), and tomography data analysis (TOMATO, PuMA) can be incorporated when required by a specific hypothesis without becoming the focus of every campaign. The central objective of ARCTRON is therefore not to maximize heat flux or reproduce a complete flight environment. Its purpose is to reduce the cost and time required to ask consequential questions about plasma behavior, plasma-facing materials, diagnostics, and arcjet technology. By providing a controlled environment for rapid reconfiguration, mechanism isolation, quantitative measurement, and iterative engineering, ARCTRON can help mature concepts that would otherwise remain too speculative or too risky for evaluation in production facilities. The resulting knowledge can then guide the design of material models, focus test objectives in larger arcjets, reduce facility-development risk, and improve the physical basis of high-enthalpy ground testing. This work will present the ARCTRON architecture, operating modes, diagnostic suite, and digital experimental workflow. Initial experimental results from the first integrated operation of the facility will be presented, including flow characterization, power limitations, and deployment of the initial diagnostic suite. Ongoing development efforts aimed at catalycity characterization, magnetic plasma control, and advanced optical diagnostics will also be discussed, illustrating how the platform supports rapid iteration from concept to experiment.

experimental diagnostics↗

NASA NTRSDate not supplied

ARCTRON: A Rapid Experimental Proving Ground for TPS Experiments and Arcjet Technology Development

Innovation in high-enthalpy facilities is fundamentally limited by the cost and risk of experimentation. New concepts for plasma control, diagnostics, facility components, and plasma-material interaction often require repeated iterations that are impractical to perform in production arcjets. As a result, promising ideas may remain unexplored or reach operational facilities only after significant development effort. ARCTRON is being developed as a rapid experimental proving ground where new ideas in plasma science, arcjet engineering, diagnostics, and material response can be conceived, tested, and quantitatively evaluated before transition to large-scale facilities. The platform combines radio-frequency (RF) and DC arc plasma generation, externally applied magnetic fields, configurable gas composition, reduced-pressure operation, laser heating, electrical biasing, and modular diagnostic access. These capabilities permit the plasma source, applied forcing, test article, and measurement configuration to be modified independently, allowing individual physical mechanisms to be isolated more readily than in a traditional test environment. One class of investigations addresses fundamental plasma-surface interaction physics. Conventional material tests often expose a specimen simultaneously to convective heating, reactive species, pressure, shear, radiation, and surface-current effects. The resulting material response may be measured accurately, while the contribution of each mechanism remains difficult to identify. ARCTRON is designed to vary these effects selectively. Plasma chemistry can be changed independently through configurable gas mixtures; magnetic fields and electrical biasing can modify charged-particle transport; laser heating can provide a non-plasma thermal input; and pressure, flow, and discharge mode can be varied over a broad operating space. This enables controlled tests of hypotheses involving surface catalycity, reactive-species transport, plasma-assisted oxidation, electromagnetic effects, shear, and the relative contributions of thermal and chemical loading. A second class of investigations enabled by this approach concerns the engineering of high-enthalpy facilities themselves. Arc-heated facilities are limited by electrode erosion, unstable arc attachment, localized heating, and damage to nozzles and other plasma-facing components. ARCTRON provides a lower-cost environment for testing concepts intended to mitigate these limitations. Candidate investigations include the use of applied magnetic fields to alter current paths and reduce plasma interaction with nozzle walls, ExB forcing to introduce controlled plasma rotation, magnetic or geometric approaches for distributing arc attachment, and alternative electrode or discharge configurations intended to reduce erosion and improve stability. Because the platform is reconfigurable, these concepts can be evaluated through repeated design--build--test cycles before they are considered for implementation in operational facilities. The platform also supports the development and validation of diagnostics that may be difficult to introduce initially into a large arcjet. Current and planned measurements include spatially resolved optical emission spectroscopy, electrostatic probes, fast imaging, pyrometry, calorimetry, laser-induced fluorescence, and absorption spectroscopy. These diagnostics are intended not merely to document a nominal operating condition, but to constrain the local plasma state and its relationship to component or material response. The modular facility geometry allows diagnostic concepts to be tested, calibrated, and compared under repeatable conditions before deployment in more demanding environments. ARCTRON is also supported by an integrated software suite. Automated control and data acquisition allow discharge parameters, gas composition, magnetic fields, diagnostic timing, and test configuration to be recorded as part of each experiment (STARDAC - Software for Testing, Analysis, Research Data, and Control). The Backend for Experiment Analysis, Storage, and Traceability (BEAST) is a database that provides the infrastructure needed to associate heterogeneous measurements with facility configuration, specimen identity, calibration state, geometry, and analysis provenance. This backend is particularly important for exploratory campaigns, in which many related configurations may be tested, and the value of an individual experiment depends on its connection to earlier and subsequent iterations. Complementary analysis capabilities, including computer-vision-based transient response measurements (arcjetCV), three-dimensional surface reconstruction (STARSCAN), and model-based Bayesian inference (SHIELD), and tomography data analysis (TOMATO, PuMA) can be incorporated when required by a specific hypothesis without becoming the focus of every campaign. The central objective of ARCTRON is therefore not to maximize heat flux or reproduce a complete flight environment. Its purpose is to reduce the cost and time required to ask consequential questions about plasma behavior, plasma-facing materials, diagnostics, and arcjet technology. By providing a controlled environment for rapid reconfiguration, mechanism isolation, quantitative measurement, and iterative engineering, ARCTRON can help mature concepts that would otherwise remain too speculative or too risky for evaluation in production facilities. The resulting knowledge can then guide the design of material models, focus test objectives in larger arcjets, reduce facility-development risk, and improve the physical basis of high-enthalpy ground testing. This work will present the ARCTRON architecture, operating modes, diagnostic suite, and digital experimental workflow. Initial experimental results from the first integrated operation of the facility will be presented, including flow characterization, power limitations, and deployment of the initial diagnostic suite. Ongoing development efforts aimed at catalycity characterization, magnetic plasma control, and advanced optical diagnostics will also be discussed, illustrating how the platform supports rapid iteration from concept to experiment.

experimental diagnostics↗

NASA NTRS2018

Transient Modeling of Large Scale Integrated Refrigeration and Storage Systems

Recently, next generation techniques and designs were demonstrated using Integrated Refrigeration and Storage (IRAS) for large scale storage of liquid hydrogen at NASA Kennedy Space Center (KSC) in Florida. Zero boil-off, densification, and in-situ liquefaction of hydrogen were achieved at various fill levels inside a custom-built 125,000 liter, horizontal-cylindrical IRAS tank, validating the applicability of the concept for large scale cryo-fluid storage architectures. This paper will discuss a number of transient physics models developed to predict the bulk behavior of large IRAS systems, and the comparison of those models to data gathered during the KSC test campaign. In an attempt to extent their usefulness to future IRAS designs, these models were agnostic with respect to stored fluid, tank size and geometry. Behavior during densification testing was examined at three fill levels, and ultimately the depressurization and bulk temperature trends of the KSC tests were predicted with good accuracy.

Swanger, Adam M.↗