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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Cosmic Pathways for Compact Groups in the Milli-Millennium Simulation

We detected 10 compact galaxy groups (CGs) at z=0 in the semianalytic galaxy catalog of Guo et al. for themilli-Millennium Cosmological Simulation (sCGs in mGuo2010a). We aimed to identify potential canonicalpathways for compact group evolution and thus illuminate the history of observed nearby CGs. By constructingmerger trees for z=0 sCG galaxies, we studied the cosmological evolution of key properties and compared themwith z=0 Hickson CGs (HCGs). We found that, once sCG galaxies come within 1 (0.5) Mpc of their mostmassive galaxy, they remain within that distance until z=0, suggesting sCG "birth redshifts." At z=0 stellarmasses of sCG most massive galaxies are within 1010M*/Me1011. In several cases, especially in the twofour- and five-member systems, the amount of cold gas mass anticorrelates with stellar mass, which in turncorrelates with hot gas mass. We define the angular difference between group members' 3D velocity vectors,vel, and note that many of the groups are long-lived because their small values of vel indicate a significantparallel component. For triplets in particular, vel values range between 20° and 40° so that galaxies are comingtogether along roughly parallel paths, and pairwise separations do not show large pronounced changes after closeencounters. The best agreement between sCG and HCG physical properties is for M* galaxy values, but HCGvalues are higher overall, including for star formation rates (SFRs). Unlike HCGs, due to a tail at low SFR and M*and a lack of M*1011Me galaxies, only a few sCG galaxies are on the star-forming main sequence

Tzanavaris, Panayiotis↗
DOE OSTI2020

Effect of the orientation of Rydberg atoms on their collisional ionization cross section

Collisional ionization between two Rydberg atoms in relative motion is examined. A classical trajectory Monte Carlo method is used to determine the cross sections associated with Penning ionization. The dependence of the ionization cross section on the magnitude and the direction of orbital angular momentum of the electrons and the direction of the Laplace-Runge-Lenz vector of the electrons is studied. For a given magnitude of angular momentum, there can exist a difference of a factor of up to ~2.5 in the ionization cross section between the orientations with the highest and the lowest ionization cross section. As a result, the case of exchange ionization is examined and its dependence on the magnitude of angular momentum is studied.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Representativity error scaling of models of the high temperature test facility

Error scaling is a critical step toward the validation of modeling capabilities for high-temperature gas-cooled reactors (HTGRs). Extensive effort is being made to bring HTGRs into the validation basis of numerous thermal-hydraulics codes. Here, this paper demonstrates how systems-level codes can be leveraged to perform error scaling analyses between an experimental facility and a plant-to-be facility. Specifically, we focus on two conduction cooldown experiments from the High Temperature Test Facility (HTTF) and the General Atomics 350 MW th modular high-temperature gas-cooled reactor (MHTGR-350). The error scaling methodology employed in this study is representativity, which in the context of this work was used to quantify how well experiments captured the physics of the plant facility by comparing sensitivity vectors between the two facilities. In addition, two different RELAP5–3D models of the HTTF were included in the comparison to determine if modeling methodologies notably impact the representativity results. The key figures of merit are the maximum block temperature and the coolant outlet temperature. The time-dependent maximum block temperature had a low representativity of below 0.1 for both models across both transients. The coolant outlet temperature had a higher representativity of around 0.6 for both models during the pressurized conduction cooldown, but it was below 0.2 for the depressurized conduction cooldown. Overall, the HTTF experiments were not representative of the transients in the MHTGR-350. However, these results can play a significant role in informing future potential experiments for HTGR systems that iterate on what the HTTF accomplished.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1994

Controlling telerobots with video data and compensating for time-delayed video using Omniview

Remote viewing is critical for teleoperations, but the inherent limitations of standard video reduce the operator's effectiveness. These limitations have been compensated for in many ways, from using the operator's adaptability, to augmenting his capability with feedback from a variety of sensors and simulations. Omniview can overcome some of these limitations and improve the operator's efficiency without adding additional sensors or computational burden. It can minimize the potential collisions with facility equipment, provide peripheral vision, and display multiple images simultaneously from a single input device. The Omniview technology provides electronic pan, tilt, magnify, and rotational orientation within a hemispherical field-of-view without any moving parts. Image sizes, viewing directions, scale, offset, etc., may be adjusted to fit operator needs. This paper discusses the derivation of the image transformation, the design of the electronics, and two applications to telepresence that are under development. These are Video Emulated Tweening (VET), and Manipulator Guidance and Positioning (ManGAP). The VET effort uses Omniview to compensate for time-delayed video in teleoperation of remote vehicles. In ManGAP two Omniview systems are used to provide two sets of orientation vectors to points in the field-of-view (FOV). These vectors then provide absolute position information to both control the position of the telerobot, and to avoid collisions with the work sight equipment.

Kuban, Dan↗
DOE OSTI2020

Data-driven Cyberattack Detection for Photovoltaic (PV) Systems through Analyzing Micro-PMU Data

With increasing exposure to software-based sensing and control, Photovoltaic (PV) systems are facing higher risks of cyber attacks. Here, to ensure the system stability and minimize potential economic losses, it is imperative to monitor operating states and detect attacks at the early stage. To meet this demand, Micro-Phasor Measurement Units (μPMU) are increasingly popular in monitoring distribution networks. However, due to the relatively low sampling rate, μPMU has not yet been used to detect and classify cyber-attacks in power electronics enabled smart grid. To our knowledge, this is one of the first attempts to use μPMU to detect cyber attacks that degrade the performance of power electronics systems. We propose to apply data-driven methods on micro-PMU data to implement attack detection. We have evaluated data-driven methods, including decision tree (DT), K-nearest neighbor (KNN), support vector machine (SVM), artificial neural network (ANN), long short-term memory (LSTM) and convolutional neural network (CNN). The proposed CNN model achieves the required performances with the highest 99.23% accuracy and 0.9963 F 1 score.

14 SOLAR ENERGY↗
NASA NTRS1996

The X-31A quasi-tailless flight test results

A quasi-tailless flight investigation was launched using the X-31A enhanced fighter maneuverability airplane. In-flight simulations were used to assess the effect of partial to total vertical tail removal. The rudder control surface was used to cancel the stabilizing effects of the vertical tail, and yaw thrust vector commands were used to restabilize and control the airplane. The quasi-tailless mode was flown supersonically with gentle maneuvering and subsonically in precision approaches and ground attack profiles. Pilot ratings and a full set of flight test measurements were recorded. This report describes the results obtained and emphasizes the lessons learned from the X-31A flight test experiment. Sensor-related issues and their importance to a quasi-tailless simulation and to ultimately controlling a directionally unstable vehicle are assessed. The X-31A quasi-tailless flight test experiment showed that tailless and reduced tail fighter aircraft are definitely feasible. When the capability is designed into the airplane from the beginning, the benefits have the potential to outweigh the added complexity required.

Bosworth, John T.↗
DOE OSTI2024

Exploring Climate-Disease Connections in Geopolitical Versus Ecological Regions: The Case of West Nile Virus in the United States

Many infectious disease forecasting models in the United States (US) are built with data partitioned into geopolitical regions centered on human activity as opposed to regions defined by natural ecosystems; although useful for data collection and intervention, this has the potential to mask biological relationships between the environment and disease. We explored this concept by analyzing the correlations between climate and West Nile virus (WNV) case data aggregated to geopolitical and ecological regions. We compared correlations between minimum, maximum, and mean annual temperature; precipitation; and annual WNV neuroinvasive disease (WNND) case data from 2005 to 2019 when partitioned into (a) climate regions defined by the National Oceanic and Atmospheric Administration (NOAA) and (b) Level I ecoregions defined by the Environmental Protection Agency (EPA). We found that correlations between climate and WNND in NOAA climate regions and EPA ecoregions were often contradictory in both direction and magnitude, with EPA ecoregions more often supporting previously established biological hypotheses and environmental dynamics underlying vector-borne disease transmission. Using ecological regions to examine the relationships between climate and disease cases can enhance the predictive power of forecasts at various scales, motivating a conceptual shift in large-scale analyses from geopolitical frameworks to more ecologically meaningful regions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Prototypes of Nonrelativistic Spin Splitting and Polarization in Symmetry Broken Antiferromagnets

Antiferromagnets that break both space-time reversal and translation-spin-rotation symmetries were recently predicted [L.-D. Yuan, Z. Wang, J.-W. Luo, E. I. Rashba, and A. Zunger, Phys. Rev. B 102, 014422 (2020)] to possess splitting between the otherwise spin-degenerate energy bands even without the relativistic spin-orbit coupling (SOC). Here, we point out that such nonrelativistic spin splitting (NRSS)—in particular, “spin splitting type 4” (SST-4) symmetry-broken antiferromagnets—can be divided into subgroups having distinct patterns of spin splitting and spin textures, depending on additional auxiliary symmetries of spin interconversion and polarity. These SST-4 subgroups include the 𝛼-type (no spin-interconverting symmetry) having spin splitting at the Brillouin zone center, as well as the 𝛽 subgroup in which a rotation symmetry is applied and determines the alternating spin texture and the 𝛾 subgroup having exclusively reflection spin-interconverting symmetry. Unlike ferrimagnets, the 𝛼-type compounds are shown to have tiny net magnetization at finite temperature and thus avoid the adverse effect of the stray field. The 𝛼 and 𝛽 subgroups can be either polar or nonpolar, whereas the 𝛾 subgroup is polar only, providing a basis for possible switching by external fields. The combination of NRSS-enabling and auxiliary symmetries is used here as a filter for identifying previously synthesized compounds as specific prototypes. Their characteristic splitting and spin polarization are calculated by density functional theory to the benefit of potential future experimental testing. Interesting results are as follows: (i) SOC-independent NRSS can exceed the magnitude of the SOC-induced Rashba and Dresselhaus spin splitting in semiconductors. (ii) Examples of predicted 𝛼-type insulating compounds include BiCrO 3 (nonpolar) and Mn 2 ⁢ScSbO 6 (polar), the latter having spin splitting of 158 meV and 160 meV in the valence and conduction bands, respectively. (iii) The 𝛽-type (Cu 2 ⁢Y 2 ⁢O 5 and FeF 2 ) and 𝛾-type compounds (Mn 4 ⁢Nb 2 ⁢O 9 and FeScO 3 ) are distinguished both by their auxiliary symmetries and polarity. The spin textures of 𝛾-type compounds are mirror reflected with spin degeneracy of the wave vectors on that mirror. These observations will likely broaden the experimental playing field of NRSS physics significantly.

antiferromagnets↗
DOE OSTI2020

Integrating Predictions for Improving Defect Classification Accuracy in NDT-based Assessment of Concrete - 20229

There is an increasing need to create predictive models for defect classification in concrete using the output of non-destructive testing (NDT) techniques. Recent advancement of machine-learning algorithms has offered several techniques for developing classification models for different types of data sets. However, the performance of these algorithms is very uncertain, mainly when applied to small and noisy datasets. For example, when human access is limited (e.g., nuclear facility), robot-based NDT is preferred. But compared to manual tests with humans present on site, the data sets are small, and more noise can exist. Therefore, it is imperative to develop new approaches to ensure a consistently high classification accuracy for inadequate data sets. This study explores the classification performance on NDT dataset using classifiers from different machine-learning algorithms, namely k-Nearest Neighbor (kNN), Decision Tree, Naive Bayes, Logistic Regression, and Support Vector Machine (SVM). The authors further integrated the predictions from these classifiers using proposed methods. The integration strategy combines the output of the classifiers based on two different measures, accuracy, and performance (ACC and PERF), using equations such as sum, average, and square-root-of-sums-of-squares (SRSS). Our results reveal varying classification accuracies across individual classifiers with different misclassifications across the test data set. The integration strategy provided significant improvement in the classification accuracy compared to the individual classifiers. Furthermore, the results indicate minimal variation across the integration methods as compared to the variation across the individual classifiers. To conclude, prediction integration offers a unique approach for combining the output of multiple classifiers to create redundancies with the potential of achieving high classification performance and improved reliability in predictive models for defect detection in concrete. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2009

Honeycomb vs. Foam: Evaluating Potential Upgrades to ISS Module Shielding

The presence of honeycomb cells in a dual-wall structure is advantageous for mechanical performance and low weight in spacecraft primary structures but detrimental for shielding against impact of micrometeoroid and orbital debris particles (MMOD). The presence of honeycomb cell walls acts to restrict the expansion of projectile and bumper fragments, resulting in the impact of a more concentrated (and thus lethal) fragment cloud upon the shield rear wall. The Multipurpose Laboratory Module (MLM) is a Russian research module scheduled for launch and ISS assembly in 2011 (currently under review). Baseline shielding of the MLM is expected to be predominantly similar to that of the existing Functional Energy Block (FGB), utilizing a baseline triple wall configuration with honeycomb sandwich panels for the dual bumpers and a thick monolithic aluminum pressure wall. The MLM module is to be docked to the nadir port of the Zvezda service module and, as such, is subject to higher debris flux than the FGB module (which is aligned along the ISS flight vector). Without upgrades to inherited shielding, the MLM penetration risk is expected to be significantly higher than that of the FGB module. Open-cell foam represents a promising alternative to honeycomb as a sandwich panel core material in spacecraft primary structures as it provides comparable mechanical performance with a minimal increase in weight while avoiding structural features (i.e. channeling cells) detrimental to MMOD shielding performance. In this study, the effect of replacing honeycomb sandwich panel structures with metallic open-cell foam structures on MMOD shielding performance is assessed for an MLM-representative configuration. A number of hypervelocity impact tests have been performed on both the baseline honeycomb configuration and upgraded foam configuration, and differences in target damage, failure limits, and derived ballistic limit equations are discussed.

Ryan, Shannon J.↗
DOE OSTI2024

Search for light long-lived neutral particles from Higgs boson decays via vector-boson-fusion production from pp collisions at $\sqrt{s}=13$ TeV with the ATLAS detector

A search is reported for long-lived dark photons with masses between 0.1 GeV and 15 GeV, from exotic decays of Higgs bosons produced via vector-boson-fusion. Events that contain displaced collimated Standard Model fermions reconstructed in the calorimeter or muon spectrometer are probed. This search uses the full LHC Run 2 (2015–2018) data sample collected in proton–proton collisions at $\sqrt{s}=13$ TeV, corresponding to an integrated luminosity of 139 fb –1 . Dominant backgrounds from Standard Model processes and non-collision sources are estimated using data-driven techniques. The observed event yields in the signal regions are consistent with the expected background. Upper limits on the Higgs boson to dark photon branching fraction are reported as a function of the dark photon mean proper decay length or of the dark photon mass and the coupling between the Standard Model and the potential dark sector. This search is combined with previous ATLAS searches obtained in the gluon–gluon fusion and WH production modes. A branching fraction above 10% is excluded at 95% CL for a 125 GeV Higgs boson decaying into two dark photons for dark photon mean proper decay lengths between 173 and 1296 mm and mass of 10 GeV.

Aad, G. (ORCID:0000000266654934)↗
NASA NTRS1986

Viscous wing theory development. Volume 1: Analysis, method and results

Viscous transonic flows at large Reynolds numbers over 3-D wings were analyzed using a zonal viscid-inviscid interaction approach. A new numerical AFZ scheme was developed in conjunction with the finite volume formulation for the solution of the inviscid full-potential equation. A special far-field asymptotic boundary condition was developed and a second-order artificial viscosity included for an improved inviscid solution methodology. The integral method was used for the laminar/turbulent boundary layer and 3-D viscous wake calculation. The interaction calculation included the coupling conditions of the source flux due to the wing surface boundary layer, the flux jump due to the viscous wake, and the wake curvature effect. A method was also devised incorporating the 2-D trailing edge strong interaction solution for the normal pressure correction near the trailing edge region. A fully automated computer program was developed to perform the proposed method with one scalar version to be used on an IBM-3081 and two vectorized versions on Cray-1 and Cyber-205 computers.

Chow, R. R.↗
DOE OSTI2021

An adaptive Hessian approximated stochastic gradient MCMC method

Bayesian approaches have been successfully integrated into training deep neural networks. One popular family is stochastic gradient Markov chain Monte Carlo methods (SG-MCMC), which have gained increasing interest due to their ability to handle large datasets and the potential to avoid overfitting. Although standard SG-MCMC methods have shown great performance in a variety of problems, they may be inefficient when the random variables in the target posterior densities have scale differences or are highly correlated. Here, we present an adaptive Hessian approximated stochastic gradient MCMC method to incorporate local geometric information while sampling from the posterior. The idea is to apply stochastic approximation (SA) to sequentially update a preconditioning matrix at each iteration. The preconditioner possesses second-order information and can guide the random walk of a sampler efficiently. Instead of computing and saving the full Hessian of the log posterior, we use limited memory of the samples and their stochastic gradients to approximate the inverse Hessian-vector multiplication in the updating formula. Moreover, by smoothly optimizing the preconditioning matrix via SA, our proposed algorithm can asymptotically converge to the target distribution with a controllable bias under mild conditions. To reduce the training and testing computational burden, we adopt a magnitude-based weight pruning method to enforce the sparsity of the network. Our method is user-friendly and demonstrates better learning results compared to standard SG-MCMC updating rules. The approximation of inverse Hessian alleviates storage and computational complexities for large dimensional models. Numerical experiments are performed on several problems, including sampling from 2D correlated distribution, synthetic regression problems, and learning the numerical solutions of heterogeneous elliptic PDE. The numerical results demonstrate great improvement in both the convergence rate and accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A Finite-Time Ensemble Method for Mixed Layer Model Comparison

Here, this work evaluates the fidelity of various upper-ocean turbulence parameterizations subject to realistic monsoon forcing and presents a finite-time ensemble vector (EV) method to better manage the design and numerical principles of these parameterizations. The EV method emphasizes the dynamics of a turbulence closure multimodel ensemble and is applied to evaluate 10 different ocean surface boundary layer (OSBL) parameterizations within a single-column (SC) model against two boundary layer large-eddy simulations (LES). Both LES include realistic surface forcing, but one includes wind-driven shear turbulence only, while the other includes additional Stokes forcing through the wave-average equations that generate Langmuir turbulence. The finite-time EV framework focuses on what constitutes the local behavior of the mixed layer dynamical system and isolates the forcing and ocean state conditions where turbulence parameterizations most disagree. Identifying disagreement provides the potential to evaluate SC models comparatively against the LES. Observations collected during the 2018 monsoon onset in the Bay of Bengal provide a case study to evaluate models under realistic and variable forcing conditions. The case study results highlight two regimes where models disagree 1) during wind-driven deepening of the mixed layer and 2) under strong diurnal forcing.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1986

Independent Orbiter Assessment (IOA): Analysis of the guidance, navigation, and control subsystem

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) is presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. The independent analysis results corresponding to the Orbiter Guidance, Navigation, and Control (GNC) Subsystem hardware are documented. The function of the GNC hardware is to respond to guidance, navigation, and control software commands to effect vehicle control and to provide sensor and controller data to GNC software. Some of the GNC hardware for which failure modes analysis was performed includes: hand controllers; Rudder Pedal Transducer Assembly (RPTA); Speed Brake Thrust Controller (SBTC); Inertial Measurement Unit (IMU); Star Tracker (ST); Crew Optical Alignment Site (COAS); Air Data Transducer Assembly (ADTA); Rate Gyro Assemblies; Accelerometer Assembly (AA); Aerosurface Servo Amplifier (ASA); and Ascent Thrust Vector Control (ATVC). The IOA analysis process utilized available GNC hardware drawings, workbooks, specifications, schematics, and systems briefs for defining hardware assemblies, components, and circuits. Each hardware item was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode.

Trahan, W. H.↗
NASA NTRS2002

Characterization of Truncated Tumor-Associated NADH Oxidase (ttNOX)

Bacterial, plant and animal cells possess novel surface proteins that exhibit both NADH oxidation (NOX) or hydroquinone and protein disulfide-thiol interchange. These enzymatic activities alternate to yield oscillating patterns wjth period lengths of approximately 24 minutes. The catalytic period of NOX proteins are temperature compensated and gravity responsive. We report the cloning, expression and characterization of truncated tumor-associated NADH oxidase (ttNOX), in which the membrane spanning region has been deleted. The cDNA (originated from HeLa cells) was cloned into pET-34b and pET-14b (Novagen) vectors for E. coli expression. Optimized expression and purification protocols yielded greater than 300mg per liter of culture with greater than 95% purity. Circular dichroism data was collected from a 2.7mg/ml solution in a 0.1mm cuvette with variable scanning using an Olis RSM CD spectrophotometer. The ellipticity values were scanned from 190 to 260nm. The spectra recorded have characteristics for alpha proteins with band maxima at 216nm and a possible shoulder at 212nm at 12OC and 250 C. Protein crystal screens are in progress and, to date, only small crystals have been observed. The regular periodic oscillatory change in the ttNOX protein is indicative of a possible time-keeping functional role. A single protein possessing alternating catalytic activities, with a potential biological clock function, is unprecedented and structural determination is paramount to understanding this role.

Karr, Laurel J.↗
NASA NTRS1987

The scaling of model test results to predict intake hot gas reingestion for STOVL aircraft with augmented vectored thrust engines

The difficulties of modeling the complex recirculating flow fields produced by multiple jet STOVL aircraft close to the ground have led to extensive use of experimental model tests to predict intake Hot Gas Reingestion (HGR). Model test results reliability is dependent on a satisfactory set of scaling rules which must be validated by fully comparable full scale tests. Scaling rules devised in the U.K. in the mid 60's gave good model/full scale agreement for the BAe P1127 aircraft. Until recently no opportunity has occurred to check the applicability of the rules to the high energy exhaust of current ASTOVL aircraft projects. Such an opportunity has arisen following tests on a Tethered Harrier. Comparison of this full scale data and results from tests on a model configuration approximating to the full scale aircraft geometry has shown discrepancies between HGR levels. These discrepancies although probably due to geometry and other model/scale differences indicate some reexamination of the scaling rules is needed. Therefore the scaling rules are reviewed, further scaling studies planned are described and potential areas for further work are suggested.

Penrose, C. J.↗
DOE OSTI2025

Machine Learned Empirical Numerical Integrator from Simulated Data

Recently, a number of state-of-the-art surrogate machine learning (ML) models have been designed for global weather and climate prediction, which have been trained using reanalysis data products. Reanalysis data products are constructed using numerical model simulations that combine numerical integration of partial differential equations and parameterization schemes. These products are typically only archived and made available using coarsened spatial and temporal resolutions. This study explores the impact of the numerical generation methods used to produce the training datasets and the temporal resolution of those datasets on machine learning surrogate models. Using the nonlinear vector autoregression (NVAR) machine as an explainable ML technique, simple dynamical systems are emulated with ML models trained on data produced by three classical numerical integration schemes. NVAR is validated as a skillful ML method, capable of producing accurate predictions and, more importantly, reconstructing both the underlying dynamics and the numerical integration scheme used to generate the training data. However, the machine fails to generalize predictions on unseen test data generated by different numerical integration schemes, despite the underlying dynamical system being the same. This result provides a word of caution for the growing field of machine learning emulation of weather and climate dynamics. Furthermore, we illustrate using NVAR that training on temporally coarsened data may increase the required complexity of ML models and potentially introduce new numerical challenges. Finally, we discover that empirical integration schemes with arbitrary time-stepping sizes can be constructed directly from the data, which implies a potential for the development of empirical numerical integration schemes.

54 ENVIRONMENTAL SCIENCES↗