Results for “large-scale data analysis” — Page 37

NASA NTRS2015

Influences of Models on the Unsteady Pressure Characteristics of the NASA National Transonic Facility

Pressure fluctuations have been measured over the course of several tests in the National Transonic Facility to study unsteady phenomenon both with and without the influence of a model. Broadband spectral analysis will be used to characterize the length scales of the tunnel. Special attention will be given to the large-scale, low frequency data that influences the Mach number and force and moment variability. This paper will also discuss the significance of the vorticity and sound fields that can be related to the Common Research Model and will also highlight the comparisons to an empty tunnel configuration. The effectiveness of vortex generators placed at the interface of the test section and wind tunnel diffuser showed promise in reducing the empty tunnel unsteadiness, however, the vortex generators were ineffective in the presence of a model.

Jones, Gregory↗

NASA NTRS2015

Modeling and Analysis of Realistic Fire Scenarios in Spacecraft

An accidental fire inside a spacecraft is an unlikely, but very real emergency situation that can easily have dire consequences. While much has been learned over the past 25+ years of dedicated research on flame behavior in microgravity, a quantitative understanding of the initiation, spread, detection and extinguishment of a realistic fire aboard a spacecraft is lacking. Virtually all combustion experiments in microgravity have been small-scale, by necessity (hardware limitations in ground-based facilities and safety concerns in space-based facilities). Large-scale, realistic fire experiments are unlikely for the foreseeable future (unlike in terrestrial situations). Therefore, NASA will have to rely on scale modeling, extrapolation of small-scale experiments and detailed numerical modeling to provide the data necessary for vehicle and safety system design. This paper presents the results of parallel efforts to better model the initiation, spread, detection and extinguishment of fires aboard spacecraft. The first is a detailed numerical model using the freely available Fire Dynamics Simulator (FDS). FDS is a CFD code that numerically solves a large eddy simulation form of the Navier-Stokes equations. FDS provides a detailed treatment of the smoke and energy transport from a fire. The simulations provide a wealth of information, but are computationally intensive and not suitable for parametric studies where the detailed treatment of the mass and energy transport are unnecessary. The second path extends a model previously documented at ICES meetings that attempted to predict maximum survivable fires aboard space-craft. This one-dimensional model implies the heat and mass transfer as well as toxic species production from a fire. These simplifications result in a code that is faster and more suitable for parametric studies (having already been used to help in the hatch design of the Multi-Purpose Crew Vehicle, MPCV).

life support↗

NASA NTRS2015

Composite Cryotank Technologies and Development 2.4 and 5.5M out of Autoclave Tank Test Results

The Composite Cryotank Technologies and Demonstration (CCTD) project substantially matured composite, cryogenic propellant tank technology. The project involved the design, analysis, fabrication, and testing of large-scale (2.4-m-diameter precursor and 5.5-m-diameter) composite cryotanks. Design features included a one-piece wall design that minimized tank weight, a Y-joint that incorporated an engineered material to alleviate stress concentration under combined loading, and a fluted core cylindrical section that inherently allows for venting and purging. The tanks used out-of-autoclave (OoA) cured graphite/epoxy material and processes to enable large (up to 10-m-diameter) cryotank fabrication, and thin-ply prepreg to minimize hydrogen permeation through tank walls. Both tanks were fabricated at Boeing using automated fiber placement on breakdown tooling. A fluted core skirt that efficiently carried axial loads and enabled hydrogen purging was included on the 5.5-m-diameter tank. Ultrasonic inspection was performed, and a structural health monitoring system was installed to identify any impact damage during ground processing. The precursor and 5.5-m-diameter tanks were tested in custom test fixtures at the National Aeronautics and Space Administration Marshall Space Flight Center. The testing, which consisted of a sequence of pressure and thermal cycles using liquid hydrogen, was successfully concluded and obtained valuable structural, thermal, and permeation performance data. This technology can be applied to a variety of aircraft and spacecraft applications that would benefit from 30 to 40% weight savings and substantial cost savings compared to aluminum lithium tanks.

Jackson, Justin R.↗

NASA NTRS2012

Flowfield Analysis of a Small Entry Probe (SPRITE) Tested in an Arc Jet

A novel concept of small size (diameter less than 15 inches) entry probes named SPRITE (Small Probe Re-entry Investigation for TPS Engineering) has been developed at NASA Ames Research Center (ARC). These flight probes have on-board data acquisition systems that have also been developed in parallel at NASA ARC by Greg Swanson1. Flight probes of this size facilitate testing over a wide range of conditions in arc jets available at NASA ARC, thereby fulfilling a 'test what you fly' paradigm. As indicated by the acronym, these probes, with suitably tailored trajectories, are primarily meant to be robotic flight test beds for TPS materials, although the design is flexible enough to accommodate additional objectives of flight-testing other vehicle subsystems. A first step towards establishing the feasibility of the SPRITE concept is to arc-jet test fully instrumented models at flight scale. In a follow-on to the Large-Scale Article Tests (LSAT2) performed in the 60 MW Interaction Heating Facility (IHF) in late 2008/early 2009, a full-scale model of Deep Space-2 (DS23) made of red oak was tested in the 20 MW Aerodynamic Heating Facility (AHF). There were no issues with mass capture by the diffuser for blunt bodies of roughly 15 inches diameter tested in the 18-inch nozzle of the AHF. Building on this initial success, two identical test articles - SPRITE-T1-1 and SPRITE-T1-2 (T1 indicating the choice of back shell geometry) - were fabricated, and one of them, SPRITE-T1-1, was tested in the AHF recently. Both these test articles, 14 inches in diameter, have a 45deg sphere-cone (like DS2) made of PICA bonded on to a 1/8th inch thick aluminum shell using RTV. The aft portion of the test article is a conical frustum (15deg cone angle) with LI-2200 bonded on to the aluminum shell. Each model is fully instrumented with: (a) thermocouples imbedded in plugs in the heat shield, (b) thermocouples bonded to the aluminum substructure; the thermocouples are distributed over the entire shell, and (c) a few strain gages. Data from some of the thermocouples and gages are acquired by the on-board data acquisition system (DAS), while data from the others are routed to the facility-provided DAS, thereby enabling a cross check on the in situ measurement capability. as inputs to v2.6.1 of the in-house materials thermal response code, FIAT

atmospheric entry↗

NASA NTRS2015

Introducing GFWED: The Global Fire Weather Database

The Canadian Forest Fire Weather Index (FWI) System is the mostly widely used fire danger rating system in the world. We have developed a global database of daily FWI System calculations, beginning in 1980, called the Global Fire WEather Database (GFWED) gridded to a spatial resolution of 0.5 latitude by 2-3 longitude. Input weather data were obtained from the NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA), and two different estimates of daily precipitation from rain gauges over land. FWI System Drought Code calculations from the gridded data sets were compared to calculations from individual weather station data for a representative set of 48 stations in North, Central and South America, Europe, Russia,Southeast Asia and Australia. Agreement between gridded calculations and the station-based calculations tended to be most different at low latitudes for strictly MERRA based calculations. Strong biases could be seen in either direction: MERRA DC over the Mato Grosso in Brazil reached unrealistically high values exceeding DCD1500 during the dry season but was too low over Southeast Asia during the dry season. These biases are consistent with those previously identified in MERRAs precipitation, and they reinforce the need to consider alternative sources of precipitation data. GFWED can be used for analyzing historical relationships between fire weather and fire activity at continental and global scales, in identifying large-scale atmosphereocean controls on fire weather, and calibration of FWI-based fire prediction models.

bias↗

NASA NTRS2016

Identifying and Analyzing Uncertainty Structures in the TRMM Microwave Imager Precipitation Product over Tropical Ocean Basins

Despite continuous improvements in microwave sensors and retrieval algorithms, our understanding of precipitation uncertainty is quite limited, due primarily to inconsistent findings in studies that compare satellite estimates to in situ observations over different parts of the world. This study seeks to characterize the temporal and spatial properties of uncertainty in the Tropical Rainfall Measuring Mission Microwave Imager surface rainfall product over tropical ocean basins. Two uncertainty analysis frameworks are introduced to qualitatively evaluate the properties of uncertainty under a hierarchy of spatiotemporal data resolutions. The first framework (i.e. 'climate method') demonstrates that, apart from random errors and regionally dependent biases, a large component of the overall precipitation uncertainty is manifested in cyclical patterns that are closely related to large-scale atmospheric modes of variability. By estimating the magnitudes of major uncertainty sources independently, the climate method is able to explain 45-88% of the monthly uncertainty variability. The percentage is largely resolution dependent (with the lowest percentage explained associated with a 1 deg x 1 deg spatial/1 month temporal resolution, and highest associated with a 3 deg x 3 deg spatial/3 month temporal resolution). The second framework (i.e. 'weather method') explains regional mean precipitation uncertainty as a summation of uncertainties associated with individual precipitation systems. By further assuming that self-similar recurring precipitation systems yield qualitatively comparable precipitation uncertainties, the weather method can consistently resolve about 50 % of the daily uncertainty variability, with only limited dependence on the regions of interest.

Climate↗

NASA NTRS2017

Comparison of Aero-Propulsive Performance Predictions for Distributed Propulsion Configurations

NASA's X-57 "Maxwell" flight demonstrator incorporates distributed electric propulsion technologies in a design that will achieve a significant reduction in energy used in cruise flight. A substantial portion of these energy savings come from beneficial aerodynamic-propulsion interaction. Previous research has shown the benefits of particular instantiations of distributed propulsion, such as the use of wingtip-mounted cruise propellers and leading edge high-lift propellers. However, these benefits have not been reduced to a generalized design or analysis approach suitable for large-scale design exploration. This paper discusses the rapid, "design-order" toolchains developed to investigate the large, complex tradespace of candidate geometries for the X-57. Due to the lack of an appropriate, rigorous set of validation data, the results of these tools were compared to three different computational flow solvers for selected wing and propulsion geometries. The comparisons were conducted using a common input geometry, but otherwise different input grids and, when appropriate, different flow assumptions to bound the comparisons. The results of these studies showed that the X-57 distributed propulsion wing should be able to meet the as-designed performance in cruise flight, while also meeting or exceeding targets for high-lift generation in low-speed flight.

Borer, Nicholas K.↗

NASA NTRS2016

Temporal Gain Correction for X-Ray Calorimeter Spectrometers

Calorimetric X-ray detectors are very sensitive to their environment. The boundary conditions can have a profound effect on the gain including heat sink temperature, the local radiation temperature, bias, and the temperature of the readout electronics. Any variation in the boundary conditions can cause temporal variations in the gain of the detector and compromise both the energy scale and the resolving power of the spectrometer. Most production X-ray calorimeter spectrometers, both on the ground and in space, have some means of tracking the gain as a function of time, often using a calibration spectral line. For small gain changes, a linear stretch correction is often sufficient. However, the detectors are intrinsically non-linear and often the event analysis, i.e., shaping, optimal filters etc., add additional non-linearity. Thus for large gain variations or when the best possible precision is required, a linear stretch correction is not sufficient. Here, we discuss a new correction technique based on non-linear interpolation of the energy-scale functions. Using Astro-HSXS calibration data, we demonstrate that the correction can recover the X-ray energy to better than 1 part in 104 over the entire spectral band to above 12 keV even for large-scale gain variations. This method will be used to correct any temporal drift of the on-orbit per-pixel gain using on-board calibration sources for the SXS instrument on the Astro-H observatory.

X-ray detector X-ray spectrometer X-ray calorimete↗

NASA NTRS2016

Development of the Model of Galactic Interstellar Emission for Standard Point-Source Analysis of Fermi Large Area Telescope Data

Most of the celestial gamma rays detected by the Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope originate from the interstellar medium when energetic cosmic rays interact with interstellar nucleons and photons. Conventional point-source and extended-source studies rely on the modeling of this diffuse emission for accurate characterization. Here, we describe the development of the Galactic Interstellar Emission Model (GIEM),which is the standard adopted by the LAT Collaboration and is publicly available. This model is based on a linear combination of maps for interstellar gas column density in Galactocentric annuli and for the inverse-Compton emission produced in the Galaxy. In the GIEM, we also include large-scale structures like Loop I and the Fermi bubbles. The measured gas emissivity spectra confirm that the cosmic-ray proton density decreases with Galactocentric distance beyond 5 kpc from the Galactic Center. The measurements also suggest a softening of the proton spectrum with Galactocentric distance. We observe that the Fermi bubbles have boundaries with a shape similar to a catenary at latitudes below 20deg and we observe an enhanced emission toward their base extending in the north and south Galactic directions and located within approximately 4deg of the Galactic Center.

gamma rays: diffuse background â€“ gamma rays: gen↗

NASA NTRS2017

Field Exploration and Life Detection Sampling Through Planetary Analogue Sampling (FELDSPAR).

Exploration missions to Mars rely on rovers to perform analyses over small sampling areas; however, landing sites for these missions are selected based on large-scale, low-resolution remote data. The use of Earth analogue environments to estimate the multi-scale spatial distributions of key signatures of habitability can help ensure mission science goals are met. A main goal of FELDSPAR is to conduct field operations analogous to Mars sample return in its science, operations, and technology from landing site selection, to in-field sampling location selection, remote or stand-off analysis, in situ analysis, and home laboratory analysis. Lava fields and volcanic regions are relevant analogues to Martian landscapes due to desiccation, low nutrient availability, and temperature extremes. Operationally, many Icelandic lava fields are remote enough to require that field expeditions address several sampling constraints that are experienced in robotic exploration, including in situ and sample return missions. The Fimmvruhls lava field was formed by a basaltic effusive eruption associated with the 2010 Eyjafjallajkull eruption. Mlifellssandur is a recently deglaciated plain to the north of the Myrdalsjkull glacier. Holuhraun was formed by a 2014 fissure eruptions just north of the large Vatnajkull glacier. Dyngjusandur is an alluvial plain apparently kept barren by repeated mechanical weathering. Informed by our 2013 expedition, we collected samples in nested triangular grids every decade from the 10 cm scale to the 1 km scale (as permitted by the size of the site). Satellite imagery is available for older sites, and for Mlifellssandur, Holuhraun, and Dyngjusandur we obtained overhead imagery at 1 m to 200 m elevation. PanCam-style photographs were taken in the field by sampling personnel. In-field reflectance spectroscopy was also obtained with an ASD spectrometer in Dyngjusandur. All sites chosen were 'homogeneous' in apparent color, morphology, moisture, grain size, and reflectance spectra at all scales greater than 10 cm. Field lab assays were conducted to monitor microbial habitation, including ATP quantification, qPCR for fungal, bacterial, and archaeal DNA, and direct cell imaging using fluorescence microscopy. Home laboratory analyses include Raman spectroscopy and community sequencing. ATP appeared to be significantly more sensitive to small changes in sampling location than qPCR or fluorescence microscopy. Bacterial and archaeal DNA content were more consistent at the smaller scales, but similarly variable across more distant sites. Conversely, cell counts and fungal DNA content have significant local variation but appear relatively homogeneous over scales of 1 km. ATP, bacterial DNA, and archaeal DNA content were relatively well correlated at many spatial scales. While we have observed spatial variation at various scales and are beginning to observe how that variation fluctuates over time as biodiversity recovers after an eruption, we do not yet fully understand what parameters lead to the observed spatial variation. Home laboratory analyses will help us further understand the elemental and structural composition of the basaltic matrices, but further field analyses are vital for the understanding how temperature, moisture, incident radiation, and so forth influence the habitability of a microclimate.

Field↗

NASA NTRS2017

Coupled Data Assimilation for Integrated Earth System Analysis and Prediction: Goals, Challenges, and Recommendations

The purpose of this report is to identify fundamental issues for coupled data assimilation (CDA), such as gaps in science and limitations in forecasting systems, in order to provide guidance to the World Meteorological Organization (WMO) on how to facilitate more rapid progress internationally. Coupled Earth system modeling provides the opportunity to extend skillful atmospheric forecasts beyond the traditional two-week barrier by extracting skill from low-frequency state components such as the land, ocean, and sea ice. More generally, coupled models are needed to support seamless prediction systems that span timescales from weather, subseasonal to seasonal (S2S), multiyear, and decadal. Therefore, initialization methods are needed for coupled Earth system models, either applied to each individual component (called Weakly Coupled Data Assimilation - WCDA) or applied the coupled Earth system model as a whole (called Strongly Coupled Data Assimilation - SCDA). Using CDA, in which model forecasts and potentially the state estimation are performed jointly, each model domain benefits from observations in other domains either directly using error covariance information known at the time of the analysis (SCDA), or indirectly through flux interactions at the model boundaries (WCDA). Because the non-atmospheric domains are generally under-observed compared to the atmosphere, CDA provides a significant advantage over single-domain analyses. Next, we provide a synopsis of goals, challenges, and recommendations to advance CDA: Goals: (a) Extend predictive skill beyond the current capability of NWP (e.g. as demonstrated by improving forecast skill scores), (b) produce physically consistent initial conditions for coupled numerical prediction systems and reanalyses (including consistent fluxes at the domain interfaces), (c) make best use of existing observations by allowing observations from each domain to influence and improve the full earth system analysis, (d) develop a robust observation-based identification and understanding of mechanisms that determine the variability of weather and climate, (e) identify critical weaknesses in coupled models and the earth observing system, (f) generate full-field estimates of unobserved or sparsely observed variables, (g) improve the estimation of the external forcings causing changes to climate, (h) transition successes from idealized CDA experiments to real-world applications. Challenges: (a) Modeling at the interfaces between interacting components of coupled Earth system models may be inadequate for estimating uncertainty or error covariances between domains, (b) current data assimilation methods may be insufficient to simultaneously analyze domains containing multiple spatiotemporal scales of interest, (c) there is no standardization of observation data or their delivery systems across domains, (d) the size and complexity of many large-scale coupled Earth system models makes it is difficult to accurately represent uncertainty due to model parameters and coupling parameters, (e) model errors lead to local biases that can transfer between the different Earth system components and lead to coupled model biases and long-term model drift, (e) information propagation across model components with different spatiotemporal scales is extremely complicated, and must be improved in current coupled modeling frameworks, (h) there is insufficient knowledge on how to represent evolving errors in non-atmospheric model components (e.g. as sea ice, land and ocean) on the timescales of NWP.

CDA↗

NASA NTRS2018

Development and Initial Testing of the Tiltrotor Test Rig

The NASA Tiltrotor Test Rig (TTR) is a new, large-scale proprotor test system, developed jointly with the U.S. Army and Air Force, to develop a new, large-scale proprotor test system for the National Full-Scale Aerodynamics Complex (NFAC). The TTR is designed to test advanced proprotors up to 26 feet in diameter at speeds up to 300 knots, and even larger rotors at lower airspeeds. This combination of size and speed is unprecedented and is necessary for research into 21st-century tiltrotors and other advanced rotorcraft concepts. The TTR will provide critical data for validation of state-of-the-art design and analysis tools.

Proprotor↗

NASA NTRS2018

A Decade of MWC 758 Disk Images: Where are the Spiral-Arm-Driving Planets?

Large-scale spiral arms have been revealed in scattered light images of a few protoplanetary disks. Theoretical models suggest that such arms may be driven by and corotate with giant planets, which has called for remarkable observational efforts to look for them. By examining the rotation of the spiral arms for the MWC 758 system over a 10 year timescale, we are able to provide dynamical constraints on the locations of their perturbers. We present reprocessed Hubble Space Telescope (HST)/NICMOS F110W observations of the target in 2005, and the new Keck/NIRC2 L'-band observations in 2017. MWC 758's two well-known spiral arms are revealed in the NICMOS archive at the earliest observational epoch. With additional Very Large Telescope (VLT)/SPHERE data, our joint analysis leads to a pattern speed of 0.°6(sup +3.°3, sub -0.°6)/yr at 3σ for the two major spiral arms. If the two arms are induced by a perturber on a near-circular orbit, its best-fit orbit is at 89 au (0."59), with a 3σ lower limit of 30 au (0."20). This finding is consistent with the simulation prediction of the location of an arm-driving planet for the two major arms in the system.

MWC 758↗

NASA NTRS1994

Large-Scale Variations in Ozone from the First Two Years of UARS MLS Data

Two years of stratospheric measurements of ozone from the Upper Atmosphere Research Satellite Microwave Limb Sounder are examined in order to characterize large horizontal scale wave variations.

Fourier↗

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↗

DOE OSTI2025

MOOSE ProbML: Parallelizable Probabilistic Machine Learning and Uncertainty Quantification Capabilities

The Multiphysics Object Oriented Simulation Environment (MOOSE) is a widely used open- source finite element software for performing multiphysics multiscale simulations in a massively parallel fashion. Recently, the computational team at Idaho National Laboratory (INL) has implemented Probabilistic Machine Learning (ProbML) capabilities in MOOSE—in a parallelized fashion—and enable active learning with large-scale computational models for tasks such as surrogate model development, scale bridging, forward/inverse uncertainty quantification (UQ), Bayesian optimization, etc. This presentation summarizes these developments in MOOSE along with demonstrations on several real applications relevant to nuclear energy. At the fundamental level, samplers like Monte Carlo/Latin Hypercube, variance reduction, parallelized Markov Chain Monte Carlo (MCMC) support uncertainty propagation in both forward and inverse settings. These samplers can be integrated with the Gaussian processes (GP) suite in MOOSE, which offer several variants like scalar GPs, multi-output GPs, and deep GPs, to enable active learning. These GPs can be tuned using gradient-based optimization methods like Adam and its variants or gradient-free methods like the elliptical slice sampler (a variant of MCMC adept under Gaussian settings) for more complex covariance kernels or likelihoods whose gradient computations can be cumbersome. A variety of batch acquisition functions permit parallelized evaluation of the computational model and support different learning objectives with high efficiency like Bayesian inference, global surrogate development, optimization, etc. Furthermore, libtorch integration supports training, evaluation, and re-training of neural networks and other complex machine learning models in active learning settings. The impacts of these developments are shown on several real applications: (1) nuclear fuel inverse UQ and model inadequacy assessment using the Kennedy O’Hagan framework; (2) uncertainty aware surrogate modeling for additive manufacturing to predict field quantities; (3) nuclear reactor rare events analysis; and (4) complex fluid flow prediction using a global surrogate with quantified prediction uncertainty. Finally, the outlook of MOOSE ProbML is discussed for both outer-loop and inner-loop computations in the broad view to accelerate fuels and materials qualification, address gaps in knowledge and data, and assess new reactor/fuel systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Precision Kinematic Sunyaev--Zel'dovich Measurements Across Halo Mass and Redshift with DESI DR2 and ACT DR6: Part II. Bright Galaxy Survey and Emission-Line Galaxies

We present the first high-significance spectroscopic stacked kinetic Sunyaev-Zel'dovich (kSZ) measurements of circumgalactic gas profiles for both Bright Galaxy Survey (BGS) and Emission Line Galaxy (ELG) tracers, combining DESI Data Release 2 with ACT Data Release 6. Using reconstructed line-of-sight velocities from the DESI galaxies and high-resolution ACT temperature maps, we detect the kSZ signal at high significance, reaching signal-to-noise ratios of up to $\sim$9 for BGS and $\sim$7.5 for ELGs in optimal stellar-mass selections. Together with the LRG measurements presented in Paper I, these constitute the most significant kSZ detections from any spectroscopic survey to date. We perform the analysis in both real and harmonic space, obtaining consistent results. By splitting both tracers into stellar-mass bins, we study the scaling of the kSZ amplitude with galaxy properties. Combining the kSZ measurements with ACT Data Release 6 (DR6) CMB lensing maps enables a joint calibration of the galaxy-halo connection and the gas fractions of host halos. For the BGS galaxies, we observe low gas fractions around the virial radius relative to standard expectations, likely attributable to active galactic nuclei (AGN) activity. We find some evidence for higher-mass halos retaining a larger fraction of their baryons, consistent with more efficient feedback in lower-mass systems. For the ELG sample, dominated by blue, star-forming galaxies, we provide the first detection of the gas distribution in ELG host halos. The ELGs appear to exhibit relatively high gas fractions, which points to the possibility of weaker feedback (due to e.g. low AGN and supernova feedback activity) at their mass scale. Finally, we present generalized Navarro-Frenk-White (GNFW) fits to the harmonic-space measurements, providing a compact parametrization of gas profiles for forward modeling in large-scale structure analyses.

Hadzhiyska, B. [Cambridge U.; Cambridge U., Inst. ↗