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

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At least 145 records · Page 8

Performance of J-33-A-21 and J-33-A-23 Compressors with and without Water Injection

In an investigation of the J-33-A-21 and the J-33-A-23 compressors with and without water injection, it was discovered that the compressors reacted differently to water injection although they were physically similar. An analysis of the effect of water injection on compressor performance and the consequent effect on matching of the compressor and turbine components in the turbojet engine was made. The analysis of component matching is based on a turbine flow function defined as the product of the equivalent weight flow and the reciprocal of the compressor pressure ratio.

Beede, William L.↗

Consequence analyses of sabotage-induced radiological releases in sodium-cooled fast microreactors

Analysis of three sodium-cooled fast microreactors (SFMs) with thermal powers of 10, 30, and 50 MWt showed that smaller reactors result in lower radiological consequences during a postulated sabotage-induced event because of their reduced core inventory. All SFMs used U-10Zr metal fuel enriched to 15 wt% high-assay low-enriched uranium and operated until their respective effective multiplication factor (k eff ) reduced to less than 1 or until the end of their operational lifespan. Sabotage scenarios were simulated at this point, when the fuel inventory within the core contains the highest-level of radioactivity. Radionuclide core inventories were calculated using the SCALE code at shutdown and 3 days post-shutdown. Dose consequence analyses were performed for three sabotage scenarios using the RASCAL tool. As microreactor developers plan for minimal on-site or complete off-site emergency response, it remains essential to evaluate their physical protection needs and potential hazards, including assessing postulated sabotage-induced events that could become more relevant. SFM licensees should identify a credible worst-case, major accident, estimate release source terms, and perform dose consequence analyses to evaluate site-specific physical protection measures. In conclusion, this recommendation supports a risk-informed, performance-based approach, aligning with applicable regulatory requirements, i.e., 10 CFR Parts 100 and 53 rulemaking in the United States.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Aerocapture Systems Analysis for a Titan Mission

Performance projections for aerocapture show a vehicle mass savings of between 40 and 80%, dependent on destination, for an aerocapture vehicle compared to an all-propulsive chemical vehicle. In addition aerocapture is applicable to multiple planetary exploration destinations of interest to NASA. The 2001 NASA In-Space Propulsion Program (ISP) technology prioritization effort identified aerocapture as one of the top three propulsion technologies for solar system exploration missions. An additional finding was that aerocapture needed a better system definition and that supporting technology gaps needed to be identified. Consequently, the ISP program sponsored an aerocapture systems analysis effort that was completed in 2002. The focus of the effort was on aerocapture at Titan with a rigid aeroshell system. Titan was selected as the initial destination for the study due to potential interest in a follow-on mission to Cassini/Huygens. Aerocapture is feasible, and the performance is adequate, for the Titan mission and it can deliver 2.4 times more mass to Titan than an all-propulsive system for the same launch vehicle.

Lockwood, Mary K.↗

Empirical Analysis and Automated Classification of Security Bug Reports

With the ever expanding amount of sensitive data being placed into computer systems, the need for effective cybersecurity is of utmost importance. However, there is a shortage of detailed empirical studies of security vulnerabilities from which cybersecurity metrics and best practices could be determined. This thesis has two main research goals: (1) to explore the distribution and characteristics of security vulnerabilities based on the information provided in bug tracking systems and (2) to develop data analytics approaches for automatic classification of bug reports as security or non-security related. This work is based on using three NASA datasets as case studies. The empirical analysis showed that the majority of software vulnerabilities belong only to a small number of types. Addressing these types of vulnerabilities will consequently lead to cost efficient improvement of software security. Since this analysis requires labeling of each bug report in the bug tracking system, we explored using machine learning to automate the classification of each bug report as a security or non-security related (two-class classification), as well as each security related bug report as specific security type (multiclass classification). In addition to using supervised machine learning algorithms, a novel unsupervised machine learning approach is proposed. An ac- curacy of 92%, recall of 96%, precision of 92%, probability of false alarm of 4%, F-Score of 81% and G-Score of 90% were the best results achieved during two-class classification. Furthermore, an accuracy of 80%, recall of 80%, precision of 94%, and F-score of 85% were the best results achieved during multiclass classification.

Cybersecurity↗

Non-planar MHD model for solar flare-generated disturbances in the heliospheric equatorial plane

An analysis, with a representative (canonical) example of solar-flare-generated equatorial disturbances, is made for the temporal and spatial changes in the solar wind plasma and magnetic field environment between the sun and 1 AU. The goal is to search for first-order global consequences rather than to make a parametric study. The analysis treats all three plasma velocity and magnetic field components in any convenient heliospheric plane of symmetry. The representative disturbance is examined for the canonical case in which the temporal and spatial changes in a homogeneous solar wind caused by a solar-flare-generated shock wave are described. All plasma and field parameters at three radial locations are examined. These are the central meridian and 33 deg W and 90 deg W of the flare's central meridian. It is found that the incorporation of a small meridional magnetic field in the ambient magnetic spiral field has negligible effect on the results. The magnetic field exhibits strong kinking within the interplanetary shocked flow, even reversed polarity that, coupled with low temperature and low density, suggests a plausible explanation for magnetic clouds' with accompanying double-streaming of electrons observed at directions approximately 90 deg to the heliocentric radius.

Wu, S. T.↗

A consistent dataset for the net income distribution for 190 countries and aggregated to 32 geographical regions from 1958 to 2015

Abstract. Data on income distributions within and across countries are becoming increasingly important for informing analysis of income inequality and understanding the distributional consequences of climate change. While datasets on income distribution collected from household surveys are available for multiple countries, these datasets often do not represent the same concept of inequality (or income concept) and therefore make comparisons across countries, over time and across datasets difficult. Here, we present a consistent dataset of income distributions across 190 countries from 1958 to 2015 measured in terms of net income. We complement the observed values in this dataset with values imputed from a summary measure of the income distribution, specifically the Gini coefficient. For the imputation, we use a recently developed nonparametric principal-component-based approach that shows an excellent fit to data on income distributions compared to other approaches. We also present another version of this dataset aggregated from the country level to 32 geographical regions. Our dataset is developed for the purpose of calibrating models such as integrated human–Earth system models with detailed data on income distributions. This dataset will enable more robust analysis of income distribution at multiple scales. The latest version of our data are available on Zenodo: https://doi.org/10.5281/zenodo.7093997 (Narayan et al., 2022b).

97 MATHEMATICS AND COMPUTING↗

Thermal analysis considerations for large space structures

A number of issues and needs relative to thermal analysis of large space structures and space stations are discussed. Some indications of trends in the Langley thermal-structural analysis research program consistent with the issues and needs are also presented. The main heat transfer mechanism in space is radiation; consequently, there is a need for a strong thrust on improved radiation analysis capability. Also the important interactions among temperatures, deformations, and controls need to be accounted for. Finite element analysis capability seems to be lagging behind lumped-parameter capability or heat pipe analysis. The Langley plan will include improving radiation analysis capability, evaluating the errors involved in certain approximate analysis and modeling techniques for large space trusses, and continuing the development of integrated thermal-structural finite elements with an emphasis on radiation heat transfer. Work will be initiated to develop finite element analysis techniques for heat pipes. Finally, optimization research activities will be oriented toward methods to design flexible orbiting structures to account for thermal and thermal deformation requirements.

Adelman, H. M.↗

Modeling the Risk of U.S. Offshore Oil & Gas Exploration-Well Drilling, Commercial Nuclear Plants, and Human Spaceflight

Nuclear power, offshore oil & gas exploration, and human spaceflight all have high consequence potential if something goes wrong. Each has had at least one major incident that pointed to a need for improved risk assessment. Careful risk analysis is very important for technologies having complexity, uncertainty, and high consequence potential. All rely on multiple barriers/controls/redundancy to minimize risk. NRC (Nuclear Regulatory Commission) has moved towards risk informed regulation with Probabilistic Risk Assessment (PRA) as a major input.

PRA↗

Surface Temperature Data Analysis

Small global mean temperature changes may have significant to disastrous consequences for the Earth's climate if they persist for an extended period. Obtaining global means from local weather reports is hampered by the uneven spatial distribution of the reliably reporting weather stations. Methods had to be developed that minimize as far as possible the impact of that situation. This software is a method of combining temperature data of individual stations to obtain a global mean trend, overcoming/estimating the uncertainty introduced by the spatial and temporal gaps in the available data. Useful estimates were obtained by the introduction of a special grid, subdividing the Earth's surface into 8,000 equal-area boxes, using the existing data to create virtual stations at the center of each of these boxes, and combining temperature anomalies (after assessing the radius of high correlation) rather than temperatures.

Hansen, James↗

Uncertainty Modeling for Mars Ascent Vehicle’s Aerodatabase Development

The design of the Mars Ascent Vehicle - Mars Sample Return (MAV-MSR) trajectories requires an accurate assessment of flight performance. Typically, these trajectories are developed by flight mechanics analysis to meet complex mission requirements and then flight performance assessed through Monte Carlo simulations. Consequently, it is crucial to develop an aerodynamic aerodatabase as an input model for flight mechanics analysis to provide static and dynamic force and moment coefficients under specific flight conditions. The force and moment coefficients in the MAV aerodatabase are determined using the FUN3D computational fluid dynamics solver. Firstly, an overview of the aerodatabase is presented to demonstrate its applicability to trajectory-defined simulations. This effort is followed by an initial attempt to quantify uncertainties in the force and moment coefficients necessary for updating the current aerodatabase. The uncertainty model identifies uncertainty adders and multipliers for coefficient-based forces and moments through a direct comparison between FUN3D and wind tunnel test data from NASA Marshall Space Center's 14x14 inch Trisonic Wind Tunnel. These uncertainties aim to encompass various changes in Mach number, angle of attack, and aerodynamic roll angle.

Uncertainty analysis↗

Uncertainty Modeling for Mars Ascent Vehicle’s Aerodynamic Database Development

The design of the Mars Ascent Vehicle - Mars Sample Return (MAV-MSR) trajectories requires an accurate assessment of flight performance. Typically, these trajectories are developed by flight mechanics analysis to meet complex mission requirements and then flight performance assessed through Monte Carlo simulations. Consequently, it is crucial to develop an aerodynamic aerodatabase as an input model for flight mechanics analysis to provide static and dynamic force and moment coefficients under specific flight conditions. The force and moment coefficients in the MAV aerodatabase are determined using the FUN3D computational fluid dynamics solver. Firstly, an overview of the aerodatabase is presented to demonstrate its applicability to trajectory-defined simulations. This effort is followed by an initial attempt to quantify uncertainties in the force and moment coefficients necessary for updating the current aerodatabase. The uncertainty model identifies uncertainty adders and multipliers for coefficient-based forces and moments through a direct comparison between FUN3D and wind tunnel test data from NASA Marshall Space Center's 14x14 inch Trisonic Wind Tunnel. These uncertainties aim to encompass various changes in Mach number, angle of attack, and aerodynamic roll angle.

Uncertainty analysis↗

Accounting for Point Estimate Uncertainty in Space Systems Reliability and Risk Analysis

Understanding and accounting for uncertainty in risk analysis is a critical step in the management and communication of risk in engineered systems. The component and system-level analysis to determine the probability of a negative outcome and its consequence is often quantified by a point estimate. Many Program and Enterprise decisions involving technical concerns and issues rely on reliability engineering activities to produce quantified risk analysis to inform the decision making process. At NASA, it is common to use a Probabilistic Risk Analysis (PRA) to inform the overall risk to Loss of Mission or Loss of Crew that involves integration across all spacecraft subsystem fault trees to produce an overall probability of mission failure. The point estimate is an estimate of this overall probability and is an immediate result of a fault tree model. It is the result of a model where the probability of each event is taken to be equal to its mean. The value provides an approximation of the overall mean without running any uncertainty calculations (e.g., no sampling). Using only the point estimate can lead to a false sense of precision and the point estimate may not match the resulting mean when uncertainty is taken into consideration. This paper will explore five conditions that can cause the PRA model mean to diverge from the point estimate and will provide engineers and managers insight into the importance of understanding uncertainty in the elements of PRA models.

Paul J Collier↗

Exploring the Utility of Machine Learning-Based Passive Microwave Brightness Temperature Data Assimilation over Terrestrial Snow in High Mountain Asia

This study explores the use of a support vector machine (SVM) as the observation operator within a passive microwave brightness temperature data assimilation framework (herein SVM-DA) to enhance the characterization of snow water equivalent (SWE) over High Mountain Asia (HMA). A series of synthetic twin experiments were conducted with the NASA Land Information System (LIS) at a number of locations across HMA. Overall, the SVM-DA framework is effective at improving SWE estimates (~70% reduction in RMSE relative to the Open Loop) for SWE depths less than 200 mm during dry snowpack conditions. The SVM-DA framework also improves SWE estimates in deep, wet snow (~45% reduction in RMSE) when snow liquid water is well estimated by the land surface model, but can lead to model degradation when snow liquid water estimates diverge from values used during SVM training. In particular, two key challenges of using the SVM-DA framework were observed over deep, wet snowpacks. First, variations in snow liquid water content dominate the brightness temperature spectral difference (TB) signal associated with emission from a wet snowpack, which can lead to abrupt changes in SWE during the analysis update. Second, the ensemble of SVM-based predictions can collapse (i.e., yield a near-zero standard deviation across the ensemble) when prior estimates of snow are outside the range of snow inputs used during the SVM training procedure. Such a scenario can lead to the presence of spurious error correlations between SWE and TB, and as a consequence, can result in degraded SWE estimates from the analysis update. These degraded analysis updates can be largely mitigated by applying rule-based approaches. For example, restricting the SWE update when the standard deviation of the predicted TB is greater than 0.05 K helps prevent the occurrence of filter divergence. Similarly, adding a thin layer (i.e., 5 mm) of SWE when the synthetic TB is larger than 5 K can improve SVM-DA performance in the presence of a precipitation dry bias. The study demonstrates that a carefully constructed SVM-DA framework cognizant of the inherent limitations of passive microwave-based SWE estimation holds promise for snow mass data assimilation.

Kwon, Yonghwan↗

ECAR-7932 Rev 0 Large Eddy Simulation of MARVEL Reactor Core Subchannel to Evaluate Model Uncertainty of Reynolds-Averaged Navier-Stokes Equation Based Computational Fluid Dynamics Analysis

In the previous work (ECAR-7210), the peak cladding temperature of the MARVEL microreactor has been evaluated by steady-state Reynolds-Averaged Navier-Stokes (RANS) based computational fluid dynamics (CFD) simulations. Although numerical uncertainties of RANS-based CFD simulations has been assessed in ECAR-7210, the model uncertainty of RANS turbulence models must be investigated to resolve the issues related to inaccurate prediction of turbulent heat flux and flow pulsation in a tight lattice rod bundle using the steady-state RANS simulations. Consequently, this ECAR conducted a high-fidelity CFD analysis utilizing Large Eddy Simulation (LES) to generate reference data and investigated the model uncertainty of RANS-based CFD simulations.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Parallel inhomogeneity and the Alfven resonance. 1: Open field lines

In light of a recent demonstration of the general nonexistence of a singularity at the Alfven resonance in cold, ideal, linearized magnetohydrodynamics, we examine the effect of a small density gradient parallel to uniform, open ambient magnetic field lines. To lowest order, energy deposition is quantitatively unaffected but occurs continuously over a thickened layer. This effect is illustrated in a numerical analysis of a plasma sheet boundary layer model with perfectly absorbing boundary conditions. Consequences of the results are discussed, both for the open field line approximation and for the ensuing closed field line analysis.

Hansen, P. J.↗

Managing the Digital Thread for Structural Applications With Fit for Purpose Materials

With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Consequently, at NASA Glenn Research Center a robust information management system that manages the digital thread across the full material life (i.e., capture, analysis, maintenance, and dissemination of data) cycle directed at the design of ‘fit-for-purpose materials’ is under development. To this end the Application Table has been incorporated within NASA Glenn Research Center’s ICME Information Management framework within the ANSYS Granta MI tool. The Application Table provides a place where material and structural application information/requirements can be linked to marry the “design-the-material” (structural engineering) and the “design-with-material” (material science) paradigms and thereby enable application-driven design and optimization of materials and structures. In additional several associated toolsets, specifically: AIMAOS (Automated Information Management Across Organizations and Scales), Py MILab, and JARIMIS (Just A Rather Intelligent Material Interrogation System) are also under development to assist in the judicious automation of this process. AIMOAS offers users an interactive graphical user interface for connecting material information management systems with both commercial and in-house simulation tools at various length scales to enable such automation in the handoff across scales and maintenance of material digital twins and the digital thread. Py MILab, is an automatic framework for the capture, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. Finally, JARIMIS is an expert system that integrates various materials informatics tools (e.g., MicroNet, Surrogate ML models, ANSYS Granta MI, etc.) to enable inverse design of materials and facilitate the application of machine learning (ML) and data science with human in the loop decision making to rapidly discover and optimize new materials.

Digital Transformation↗

Generation of shear flows induced by AE / EPM in LHD plasma

The generation of shear flows (SFs) by Alfven Eigenmodes (AEs) and energetic particle modes (EPMs) have important effects on the operation of future nuclear fusion reactors, because SFs regulate the saturation of the AEs/EPMs, the transport of EPs and thermal plasma, as well as the formation of transport barriers among other consequences. The aim of this study is the analysis of SFs generation during the saturation phase of AEs and EPMs in LHD plasma. Experiments performed in the 23rd and 24th LHD experimental campaigns are dedicated to explore the destabilization of AEs/EPMs in discharges with different heating patterns, thermal plasma and magnetic field configurations. In particular, the shots 176490 and 179697 show the destabilization of MHD bursts and energetic-ion-driven resistive interchange modes (EIC), respectively. Charge exchange spectroscopy measurements in both discharges indicate that the generation of SFs by AE/EPM is uncorrelated with the perturbation induced by the neutral beam injector (NBI). Nonlinear simulations performed using the gyro-fluid code FAR3d show the generation of zonal structures, especially SFs, induced during the saturation phase of Toroidal Alfven Eigenmodes (TAEs) triggered in the MHD burst as well as by the 1/1 EIC in the bursting phase. The simulations indicate that SFs are caused by the radial electric fields powered by energy transfers from the unstable AE/EPM towards the thermal plasma. The strongest SFs are measured during the EIC bursting phase once the 1/1 EPM overlaps with nearby resonances at the plasma periphery. Likewise, the largest SFs during the MHD burst are observed once TAEs radially overlap in the inner-middle plasma region.

AE↗

The redshift-magnitude relation for quasi-stellar objects.

It is shown that the best-fitting slope of the redshift-magnitude relation for the most luminous quasi-stellar object in each redshift range is 4.3 plus or minus 0.4. However, the steepness of this slope is due primarily to the lowest redshift range including 3C 273, without which it is 2.1 plus or minus 0.6. The slopes of the second and third brightest QSOs are 3.1 plus or minus 0.6 and 3.2 plus or minus 0.6, respectively, markedly less than the slope of 5 which is expected for a Friedmann universe with q(0) = +1. Although the departure of the slope from 5 mag per decade is statistically significant at about 95% confidence, due to the heterogeneity and incompleteness of the sample there may be a systematic selectional bias not accounted for either in this analysis or in that of Bahcall and Hills. Consequently, no definite pronouncement can be made until a complete sample of adequate size is examined.

Burbidge, G. R.↗