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NASA NTRSDate not supplied

A Comparative Study of Contrail Frequency Indices and GOES-16 Contrail Data Set

Contrail formations have been shown to contribute to the greenhouse effect: they are practically transparent to incoming solar radiation and do little to reflect heat away from Earth but are highly effective at trapping heat within Earth’s atmosphere. To understand the impact contrails have on climate change, contrail frequency indices (CFIs) can be used as a method to quantify aircraft-induced persistent contrails. These indices are capable of tracking long-term contrail formation and identify regions of airspace with the highest contrail formation rates. In this aper, an algorithm is proposed which is capable of using NASA Sherlock and Global Forecast System (GFS) datasets and computing CFIs over large geographic regions and long temporal intervals using NASA Ames’ High-End Computing Capability (HECC) supercomputing system. CFIs are computed using nowcast weather data and previously flown flight tracks. This paper calculated the CFIs of all twenty Air Route Traffic Control Centers in the National Airspace System on October 28th, 2019 and compared the distribution of non-zero CFIs with observed contrail data collected from GOES-16 Satellite data in order to assess the accuracy of the CFI system as a contrail prediction model. It was ultimately determined that the computed CFIs were broadly distributed in the same way as the GOES-16 contrail data and that the individual CFIs computed at the latitude/longitude points at which GOES-16 contrail masks were available had high precision and recall (at 0.75 and 0.86 respectively). While these validation results bode well for the accuracy of the CFI method, the number of provided GOES-16 masks was quite small. Future work should aim to increase the size of the GOES-16 dataset in order to perform a more comprehensive comparison between these two datasets.

Contrails↗
NASA NTRSDate not supplied

A Comparative Study of Contrail Frequency Indices and GOES-16 Contrail Data Set

Contrail formations have been shown to contribute to the greenhouse effect: they are practically transparent to incoming solar radiation and do little to reflect heat away from Earth but are highly effective at trapping heat within Earth’s atmosphere. To understand the impact contrails have on climate change, contrail frequency indices (CFIs) can be used as a method to quantify aircraft-induced persistent contrails. These indices are capable of tracking long-term contrail formation and identify regions of airspace with the highest contrail formation rates. In this aper, an algorithm is proposed which is capable of using NASA Sherlock and Global Forecast System (GFS) datasets and computing CFIs over large geographic regions and long temporal intervals using NASA Ames’ High-End Computing Capability (HECC) supercomputing system. CFIs are computed using nowcast weather data and previously flown flight tracks. This paper calculated the CFIs of all twenty Air Route Traffic Control Centers in the National Airspace System on October 28th, 2019 and compared the distribution of non-zero CFIs with observed contrail data collected from GOES-16 Satellite data in order to assess the accuracy of the CFI system as a contrail prediction model. It was ultimately determined that the computed CFIs were broadly distributed in the same way as the GOES-16 contrail data and that the individual CFIs computed at the latitude/longitude points at which GOES-16 contrail masks were available had high precision and recall (at 0.75 and 0.86 respectively). While these validation results bode well for the accuracy of the CFI method, the number of provided GOES-16 masks was quite small. Future work should aim to increase the size of the GOES-16 dataset in order to perform a more comprehensive comparison between these two datasets.

Contrails↗
NASA NTRS2015

Effect of Interfacial Turbulence and Accommodation Coefficient on CFD Predictions of Pressurization and Pressure Control in Cryogenic Storage Tank

Laminar models agree closely with the pressure evolution and vapor phase temperature stratification but under-predict liquid temperatures. Turbulent SST k-w and k-e models under-predict the pressurization rate and extent of stratification in the vapor but represent liquid temperature distributions fairly well. These conclusions seem to equally apply to large cryogenic tank simulations as well as small scale simulant fluid pressurization cases. Appropriate turbulent models that represent both interfacial and bulk vapor phase turbulence with greater fidelity are needed. Application of LES models to the tank pressurization problem can serve as a starting point.

Condensation Evaporation↗
NASA NTRS1993

Effect of geometry, static stability, and mass distribution on the tumbling characteristics of generic flying-wing models

Results from an investigation to determine the low-speed tumbling characteristics of twelve generic flying-wing models are summarized. There is a concern that airplanes with flying-wing planforms could inadvertently enter an out-of-control tumbling motion under certain conditions. The objectives of this investigation were to: 1) identify the geometric and mass-related parameters that cause flying wings to be capable of sustained tumbling, 2) analyze some of the driving mechanisms that cause tumbling, and 3) determine the feasibility of using computer simulations to predict the tumbling characteristics of flying wings. Free-tumble and free-to-pitch tests were conducted with dynamically-scaled, generic flying wing models. The use of computer simulations as a predictive tool for tumbling was explored. Results indicated that center-of-gravity location, mass distribution, and geometric aspect ratio strongly affected the tumbling characteristics of the models tested and that positive static stability did not necessarily preclude tumbling. The magnitude of dynamic effects were found to be of the same order as static effects for the models undergoing autorotation-in-pitch. The simulations indicated that the dynamic terms in the equations of motion used to predict tumbling must be obtained using experimental methods that account for the large amplitude/high pitch-rate environment that characterizes tumbling.

Fremaux, C. M.↗
NASA NTRS1993

GGOT total pressure loss control concept evaluation

Total pressure loss is one of the most important parameters in the design of a turbine. This parameter effects not only the turbine performance, but consequently the engine power balance and engine performance. Computational Fluid Dynamics (CFD) can be an effective tool in predicting turbine total pressure loss, and also for performing sensitivity studies to achieve an optimal design with respect to pressure loss. In the present study, the AEROVISC code was used to predict the total pressure loss in the Turbine Technology Team Gas Generator Oxidizer Turbine (GGOT). The objectives in this study are two-fold. It is first necessary to determine an optimal methodology in predicting total pressure loss. The type of grid, grid density and distribution are parameters which may affect the loss prediction. Also, the effect of using a standard K-epsilon turbulence model with wall functions versus a two-layer turbulence model needs to be investigated. The use of grid embedding to resolve areas with high flow gradients needs to be explored. The second objective of the study is to apply the optimal methodology toward evaluating different tip leakage control concepts.

Blumenthal, R. F.↗
NASA NTRSDate not supplied

Multi-Anvil Experimentation Applied to Planetary Differentiation

Planets undergo differentiation that includes segregation of metal from silicate at high temperatures and pressures ranging from deep planetary core pressures (>300 GPa for Earth)to very shallow conditions of asteroids (<100 MPa).The multi-anvil solid media apparatus accesses the middle part of this range from 3 to 30 GPa –pressure relevant to the interior of Mercury, Venus, Earth, Earth’s Moon, and Mars. Early planets are thought to have experienced high temperatures from a combination of heat sources including radioactive decay, gravitational and accretional heating, and impact processes. These heating events led to melting of mantles and cores, thus requiring an understanding of solid-liquid equilibria in metal-silicate systems. In 2006 we established a multi-anvil facility at NASA-JSC combining an 880 ton press and a Kawai/Walker type module from Rockland Research. Our high PT work has been greatly facilitated by use of the COMPRES multi-anvil assemblies (1). Our recent work has included studies of element partitioning between liquid metal and liquid silicate(e.g., 2), as well as between minerals and melts(e.g., 3), both of which have led to better constraints on the timing and conditions of planetary differentiation(e.g. 4). Several examples involving sustained efforts will be summarized below and for the presentation. The distribution of siderophile (iron-loving) elements between core and mantle is controlled by metal-silicate equilibrium across a wide range of pressures. Therefore, experimentation across this pressure range helps to calibrate elemental partitioning models that can be applied to planets, and used to predict mantle chemistry and composition during planetary differentiation. Our studies have focused on a wide range of siderophile elements (refractory Ni, Co, W, Mo; volatile P, Ga, Cu, Sn, Sb; highly siderophile Au, Pd) that have constrained partitioning, valence, and isotopic fractionation, and applied to Earth, Moon, and Mars. When molten mantles (magma oceans) cool enough to initiate crystallization, the solids precipitate at depth and in large planets this involves high pressure phases like garnet, majorite, akimotoite, and ringwoodite. As these solids precipitate they can segregate from liquid by density contrasts, thus causing elemental fractionation which can be used to decipher timing of differentiation. Mineral/melt and metal/silicate equilibria in our lab have helped to better understand high pressure fractionation of isotopic parent/daughter pairs Hf/W, Mn/Cr, Pd/Ag, Pt/Os, Re/Os, and U/Pb, and their application to Earth, Moon and Mars. There remains great potential for multi-anvil experimentation to shed light on many pressure–dependent aspects of planetary evolution such as core formation, high pressure phase equilibria, redox equilibria, and volatile evolution and storage. References1. Leinenweber, K., et al.(2012) American Mineralogist,97, 353–368. 2.Righter, K., et al.(2020) Geochem. Persp. Lett.15, 1-6.3. Righter, K., et al.(2020) Met. Planet. Sci 55, 2741-2757.4. Righter, K., et al.(2020)Earth and Planetary Science Letters,552, 116590.

pressure↗
NASA NTRS2001

Vibroacoustic Model Validation for a Curved Honeycomb Composite Panel

Finite element and boundary element models are developed to investigate the vibroacoustic response of a curved honeycomb composite sidewall panel. Results from vibroacoustic tests conducted in the NASA Langley Structural Acoustic Loads and Transmission facility are used to validate the numerical predictions. The sidewall panel is constructed from a flexible honeycomb core sandwiched between carbon fiber reinforced composite laminate face sheets. This type of construction is being used in the development of an all-composite aircraft fuselage. In contrast to conventional rib-stiffened aircraft fuselage structures, the composite panel has nominally uniform thickness resulting in a uniform distribution of mass and stiffness. Due to differences in the mass and stiffness distribution, the noise transmission mechanisms for the composite panel are expected to be substantially different from those of a conventional rib-stiffened structure. The development of accurate vibroacoustic models will aide in the understanding of the dominant noise transmission mechanisms and enable optimization studies to be performed that will determine the most beneficial noise control treatments. Finite element and boundary element models of the sidewall panel are described. Vibroacoustic response predictions are presented for forced vibration input and the results are compared with experimental data.

Buehrle, Ralph D.↗
NASA NTRS2000

A Validation Summary of the NCC Turbulent Reacting/non-reacting Spray Computations

This pper provides a validation summary of the spray computations performed as a part of the NCC (National Combustion Code) development activity. NCC is being developed with the aim of advancing the current prediction tools used in the design of advanced technology combustors based on the multidimensional computational methods. The solution procedure combines the novelty of the application of the scalar Monte Carlo PDF (Probability Density Function) method to the modeling of turbulent spray flames with the ability to perform the computations on unstructured grids with parallel computing. The calculation procedure was applied to predict the flow properties of three different spray cases. One is a nonswirling unconfined reacting spray, the second is a nonswirling unconfined nonreacting spray, and the third is a confined swirl-stabilized spray flame. The comparisons involving both gas-phase and droplet velocities, droplet size distributions, and gas-phase temperatures show reasonable agreement with the available experimental data. The comparisons involve both the results obtained from the use of the Monte Carlo PDF method as well as those obtained from the conventional computational fluid dynamics (CFD) solution. Detailed comparisons in the case of a reacting nonswirling spray clearly highlight the importance of chemistry/turbulence interactions in the modeling of reacting sprays. The results from the PDF and non-PDF methods were found to be markedly different and the PDF solution is closer to the reported experimental data. The PDF computations predict that most of the combustion occurs in a predominantly diffusion-flame environment. However, the non-PDF solution predicts incorrectly that the combustion occurs in a predominantly vaporization-controlled regime. The Monte Carlo temperature distribution shows that the functional form of the PDF for the temperature fluctuations varies substantially from point to point. The results also bring to the fore some of the deficiencies associated with the use of assumed-shape PDF methods in spray computations.

Raju, M. S.↗
NASA NTRS2007

Space Technology 7 : Micropropulsion and Mass Distribution

The NASA New Millennium Program Space Technology 7 (ST7) project will validate technology for precision spacecraft control. The ST7 disturbance reduction system (DRS) will contain new micropropulsion technology to be flown as part of the European Space Agency's LISA (laser interferometer space antenna) Pathfinder project. After launch into a low Earth orbit in early 2010, the LISA Pathfinder spacecraft will be maneuvered to a halo orbit about the Earth-Sun LI Lagrange point for operations. The DRS will control the position of the spacecraft relative to a reference to an accuracy of one nanometer over time scales of several thousand seconds. To perform the control the spacecraft will use a new colloid thruster technology. The thrusters will operate over the range of 5 to 30 micro-Newtons with precision of 0.1 micro-Newton. The thrust will be generated by using a high electric field to extract charged droplets of a conducting colloid fluid and accelerating them with a precisely adjustable voltage. The control position reference will be provided by the European LISA Technology Package, which will include two nearly free-floating test masses. The test mass position and attitude will be sensed and adjusted using electrostatic capacitance bridges. The DRS will control the spacecraft position with respect to one test mass while minimizing disturbances on the second test mass. The dynamic control system will cover eighteen degrees of freedom, six for each of the test masses and six for the spacecraft. In the absence of other disturbances, the test masses will slowly gravitate toward local concentrations of spacecraft mass. The test mass acceleration must be minimized to maintain the acceleration of the enclosing drag-free spacecraft within the control authority of the micropropulsion system. Therefore, test mass acceleration must be predicted by accurate measurement of mass distribution, then offset by the placement of specially shaped balance masses near each test mass. The - acceleration is characterized by calculating the gravitational effect of over ten million modeled points of a nearly 500-kg spacecraft. This paper provides an overview of the mission technology and the process of precision mass modeling of the DRS equipment.

ST-7↗
NASA NTRS1990

Distributed deformation and block rotation in 3D

The authors address how block rotation and complex distributed deformation in the Earth's shallow crust may be explained within a stationary regional stress field. Distributed deformation is characterized by domains of sub-parallel fault-bounded blocks. In response to the contemporaneous activity of neighboring domains some domains rotate, as suggested by both structural and paleomagnetic evidence. Rotations within domains are achieved through the contemporaneous slip and rotation of the faults and of the blocks they bound. Thus, in regions of distributed deformation, faults must remain active in spite of their poor orientation in the stress field. The authors developed a model that tracks the orientation of blocks and their bounding faults during rotation in a 3D stress field. In the model, the effective stress magnitudes of the principal stresses (sigma sub 1, sigma sub 2, and sigma sub 3) are controlled by the orientation of fault sets in each domain. Therefore, adjacent fault sets with differing orientations may be active and may display differing faulting styles, and a given set of faults may change its style of motion as it rotates within a stationary stress regime. The style of faulting predicted by the model depends on a dimensionless parameter phi = (sigma sub 2 - sigma sub 3)/(sigma sub 1 - sigma sub 3). Thus, the authors present a model for complex distributed deformation and complex offset history requiring neither geographical nor temporal changes in the stress regime. They apply the model to the Western Transverse Range domain of southern California. There, it is mechanically feasible for blocks and faults to have experienced up to 75 degrees of clockwise rotation in a phi = 0.1 strike-slip stress regime. The results of the model suggest that this domain may first have accommodated deformation along preexisting NNE-SSW faults, reactivated as normal faults. After rotation, these same faults became strike-slip in nature.

Scotti, Oona↗
NASA NTRS2026

Development and Validation of a High-Vacuum Thermal Conductivity Testbed for Aerospace Interface Materials

Thermal Interface Materials (TIMs) are critical components in spacecraft thermal management systems, where thermal performance is strongly influenced by vacuum conditions, interface contact resistance, and layered metallic joint behavior. However, manufacturer-reported thermal conductivity values are often derived under idealized conditions and may not accurately represent performance within operational aerospace applications. To address this limitation, the Testbed for Advanced Interface Materials in Vacuum (TAIMV) was developed as a modular vacuum-compatible thermal conductivity characterization platform capable of evaluating aerospace-relevant TIM configurations under both ambient and high-vacuum environments. The testbed was derived from the ASTM C1044-16 guarded hot plate methodology and incorporates interchangeable layers of stainless steel coupon geometries, independently controlled main and guard heaters, embedded resistance temperature detectors (RTDs), thermocouples, multi-layer insulation (MLI), and a temperature-controlled cold plate to characterize through-thickness thermal gradients across layered interfaces. In the current configuration, interface compression is limited to the nominal contact pressure generated by the experimental stack assembly. Initial experimental campaigns were conducted at ambient pressure and below 1×10-5 torr for vacuum cases using multiple interface materials including Braycote 601EF and Krytox-based greases across a range of thermal operating conditions. In parallel, a coupled numerical Python thermal model was developed to predict temperature distribution throughout the stack while accounting for conduction, radiation, and parasitic heat transfer pathways and effective interface resistance effects. Experimental measurements and numerical predictions showed consistent thermal trends across multiple operating conditions and environmental states. Results also revealed measurable differences between ambient and vacuum thermal behavior, demonstrating the importance of interface resistance, parasitic heat transfer mechanisms, and stack geometry in determining effective thermal performance within layered thermal interfaces. The presented work establishes a foundation for future thermal model correlation efforts and expanded characterization of aerospace thermal interface materials under representative environmental conditions. Future work will focus on the integration of a load cell system to enable controlled pressure-dependent characterization of thermal interface materials under compressive loading. This capability will allow investigation of the influence of contact pressure on effective thermal conductivity, interface resistance, and thermal performance within layered aerospace thermal interfaces under representative operational conditions.

Thermal Development Testing↗
NASA NTRS1992

Semi-coupled flow and thermal analysis of the field joint during rapid pressurization of the redesigned solid rocket motor

A transient, semi-coupled, multi-dimensional thermal and flow analysis methodology was developed to predict the thermal/gas dynamic conditions in the field joint region of the Redesigned Solid Rocket Motor (RSRM). Transient temperature response, pressure history, and combustion gas flow rate (within the field joint region), were of principle interest, in the course of this study. The thermal environment in the field joint was modeled using SINDA, a finite difference based thermal network analyzer. The combustion gas flow boundary condition was generated using the FLAP code; this code performs a transient, lumped-parameter, control volume analysis to solve the mass, momentum, and energy conservation equations. The FLAP computer code was modified to account for erosion of the NBR insulation material, following ignition. An independent grid sensitivity study was conducted to determine an appropriate grid distribution near the wall. The predicted results, obtained using an optimum grid distribution and computer generated flow boundary condition, were compared with subscale test data.

Ghaffarian, Benny↗
NASA NTRS1983

Approximation in control of flexible structures, theory and application

The sense in which the feedback control law based on an approximate finite dimensional model of a continuous structure approximates a control law which is optimal for the distributed, or infinite dimensional, model of the structure is studied. From the analysis of the various control and stability issues associated with this basis question, useful information for designing finite dimensional compensators which produce near-optimal performance in infinite dimensional systems is gained. Some of the important predictions that can be made about large-order finite dimensional control laws, using the theory of infinite dimensional Riccati equations are indicated.

Gibson, J. S.↗
NASA NTRS2013

The Komplast Experiment: Space Environmental Effects after 12 Years in LEO (and Counting)

The Komplast materials experiment was designed by the Khrunichev State Research and Production Space Center, together with other Russian scientific institutes, and has been carried out by Mission Control Moscow since 18. Komplast panels fitted with material samples and sensors were located on the International Space Station (ISS) Functional Cargo Block (FGB) module exterior surface. Within the framework of this experiment, the purpose was to study the effect of the low earth orbit (LEO) environment on exposed samples of various materials. The panels were sent into orbit with the FGB when it launched on November 20, 1998. Panels #2 and #10 were retrieved during Russian extravehicular activity in February 2011 and sealed within cases to temporarily protect the samples from exposure to air until they could be studied on the ground. Panel #2 contained an experiment to detect micrometeoroid and orbital debris (MMOD) impacts, radiation and UV sensors, several pieces of electrical cable, and samples made from elastomeric and fluoroplastic materials. Panel #10 contained a temperature sensor, and both carbon composite and adhesive-bonded samples. A figure shows the location of panels #2 and #10 on the FGB module aft endcone. The panels were subsequently returned to Earth by Space Shuttle Discovery on the STS-133/ULF-5 mission after 12 years of LEO exposure and opened in an argon chamber at the Institute of Nuclear Physics at Moscow State University in July 2011. Based on the results of analyzing the readings from sensors located on Komplast panels and in studying material samples from the panels, the comprehensive effect of spaceflight factors on the FGB (at the locations of Panels #2 and #10) was evaluated. Total solar exposure was determined to be 960 +/- 200 kJ/square cm or 21,000 equivalent solar hours. Because of location of these two panels and the ISS flight attitude, atomic oxygen (AO) fluence was relatively low for such a long duration exposure, approximately 1.5x10 (exp 21) O atoms/sq. cm. Most of the AO fluence occurred during the early phase of ISS assembly. Temperatures ranged from a maximum of 107 C to a minimum of -80 C. The MMOD environment was determined, as is shown. Interestingly, the distribution of craters and low-velocity impact particles observed in the 5-50 micron size range was approx 2-3 orders of magnitude higher than that predicted by the ORDEM2000 model of natural and artificial origin microparticles in the ISS orbit. Contamination observations were also made, through the evaluation of optical properties on thermal control coatings and by the examination of visible deposits located near several samples on the panels, primarily from elastomeric samples. These elastomer samples were extensively investigated for their physical property changes and sealing capability. In addition, 16 samples of adhesive-bonded joints using three types of epoxy adhesive were evaluated studying fracture toughness, failure surface, and adhesive volume properties. Both rubber and adhesive-bonded specimens also underwent additional (post-flight) ground-based exposures to simulate a total 30 years in LEO prior to their evaluation. Overall, results indicate that space environmental effects will not adversely impact the service life of the FGB through 2028. Our investigation is complete and a summary of the results obtained from this uniquely long-duration exposure experiment will be presented.

Shaevich, S. K.↗
NASA NTRSDate not supplied

Automated Probabilistic Finite Element Model Calibration Tool Based on Uncertainty Quantification and Machine Learning

Qualification and certification of safety critical parts is a hurdle to the adoption of metallic additively manufactured components for aerospace vehicle applications. Challenges include variability in part properties due to inconsistent defect distribution and microstructure. Understanding of the process through finite element modeling (FEM), and process control through in-situ monitoring, may result in significant improvements; however, solutions useful to manufacturers will require large volumes of data and automated data utilization. Toward this end, a generalizable automated FEM calibration paradigm is developed. This paradigm leverages existing and novel tools from machine learning and uncertainty quantification to enable the automatic calibration of FEMs without requiring prior knowledge of the model performance across input parameter space, including meshing and solver settings, which can require time consuming manual model probing or cause noisy and inconsistent predictions. The result is a probabilistic distribution of calibrated and validated FEM input parameters targeting measured data.

Additive manufacturing model calibration finite el↗
NASA NTRS2018

Modeling the Distribution and Type of High-Latitude Natural Wetlands for Methane Studies

High latitude (>50N) natural wetlands emit a substantial amount of methane to the atmosphere, and are located in a region of amplified warming. Northern hemisphere high latitudes are characterized by cold climates, extensive permafrost, poor drainage, short growing seasons, and slow decay rates. Under these conditions, organic carbon accumulates in the soil, sequestering CO2 from the atmosphere. Methanogens produce methane from this carbon reservoir, converting stored carbon into a powerful greenhouse gas. Methane emission from wetland ecosystems depends on vegetation type, climate characteristics (e.g, precipitation amount and seasonality, temperature, snow cover, etc.), and geophysical variables (e.g., permafrost, soil type, and landscape slope). To understand how wetland methane dynamics in this critical region will respond to climate change, we have to first understand how wetlands themselves will change and therefore, what the primary controllers of wetland distribution and type are. Understanding these relationships permits data-anchored, physically-based modeling of wetland distribution and type in other climate scenarios, such as paleoclimates or future climates, a necessary first step toward modeling wetland methane emissions in these scenarios. We investigate techniques and datasets for predicting the distribution and type of high latitude (>50N) natural wetlands from a suite of geophysical and climate predictors. Hierarchical clustering is used to derive an empirical methane-centric wetland model. The model is applied in a multistep process first to predict the distribution of wetlands from relevant geophysical parameters, and then, given the predicted wetland distribution, to classify the wetlands into methane-relevant types using an expanded suite of climate and biogeophysical variables. As the optimum set of predictor variables is not known a priori, the model is applied iteratively, and each simulation is evaluated with respect to observed high-latitude wetlands.

Romanski, Joy↗
NASA NTRS2021

Machine Learning Models to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

This research uses machine-learned computational analyses to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is from a rodent model exposed to ≤ 15 cGy of individual Galactic Cosmic Radiation (GCR) ions: 4He, 16O, 28Si, 48Ti, or 56Fe, expected for a Lunar or Mars mission. This work investigates rats at a subject-based level and uses performance scores taken before irradiation to predict impairment in Attentional Set-shifting (ATSET) data post-irradiation. Here, the worst performing rats of the control group define the impairment thresholds based on population analyses via cumulative distribution functions, leading to the labeling of impairment for each subject. A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the Simple Discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the Compound Discrimination (CD) stage. On a subject-based level, implementing Machine Learning (ML) classifiers such as the Gaussian Naïve Bayes, Support Vector Machine, and Artificial Neural Networks identifies rats that have a higher tendency for impairment after GCR exposure. The algorithms employ the experimental prescreenperformance scores as multidimensional input features to predict each rodent’s susceptibility to cognitive impairment due to space radiation exposure. The receiver operating characteristic and the precision-recall curves of the ML models show a better prediction of impairment when 56Feis the ion in question in both SD and CD stages. They, however, do not depict impairment due to 4Hein SD and 28Siin CD, suggesting no dose-dependent impairment response in these cases. One key finding of our study is that prescreen performance scores can be used to predict the ATSET performance impairments. This result is significant to crewed space missions as it supports the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. Future research can focus on constructing ML ensemble methods to integrate the findings from the methodologies implemented in this study for morerobust predictionsof cognitive decrements due to space radiation exposure.

space radiation↗
NASA NTRS1992

Analytical estimates of radial segregation in Bridgman growth from low-level steady and periodic accelerations

Approximate analytical solutions are developed that are mathematically tractable but provide the elements of CFD models for estimating convective flows subjected to low-level accelerations. The estimates are applicable to dilute systems that have horizontal temperature gradients in the vertical Bridgman configuration. The Navier-Stokes momentum equation is solved in 1D and subsequently in 2D by the first-order perturbation method. The analysis used is the case of plane-front solidification of a dilute system in the vertical thermally stable configuration. The model is found to predict the degree of radial segregation within a factor of two for a range of material and processing parameters. The method provides detailed information on the effects of processing on solute distribution in the grown crystal which are of interest in the orbital experiments emphasizing the control of radial segregation.

Naumann, Robert J.↗