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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Topological symplectic Kondo effect

Multiple conduction channels interacting with a quantum impurity—a spin in the conventional “multichannel Kondo effect” or a topological mesoscopic device (“topological Kondo effect”)—has been proposed as a platform to realize anyonic quasiparticles. However, the above implementations require either perfect channel symmetry or the use of Majorana fermions. Here, in this work, we propose a Majorana-free mesoscopic setup which implements the Kondo effect of the symplectic Lie group and can harbor emergent anyons (including Majorana fermions, Fibonacci anyons, and parafermions) even in the absence of perfect channel symmetry. In addition to the detailed prescription of the implementation, we present the strong coupling solution by mapping the model to the multichannel Kondo effect associated to an internal symmetry and exploit conformal field theory to predict the nontrivial scaling of a variety of observables, including conductance, as a function of temperature. This work does not only open the door for robust Kondo-based anyon platforms, but also sheds light on the physics of strongly correlated materials with competing order parameters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Multi-shock design tools in double shell models

The essence of the project was to implement a program in python that demonstrated certain models put forth by fusion physicists. Across the time spent at Los Alamos National Laboratory, much was spent programming. Though fundamentally programmatical in nature, the task contained considerable difficulty hid within mathematically deriving and manipulating the models while maintaining data discretization. The result of solving these complications gave invaluable experience in applied mathematics. The final product, a piece of lengthy code, ended up having the full range of desired capabilities, with plans for more. Given the laser power history from a pulse shot on NIF, Omega, or any other Inertial Confinement Fusion facility, the code maps the terrain of radiation temperature inside the hohlraum throughout the period of the shot. Additionally, shock wave convergence prediction was implemented as additional capability. As the name of the project suggests, this tool acts as a compass of direction for researchers designing laser power profiles. Further development of this tool will undoubtedly assist in the research conducted on single and double-shell indirect ICF, consequently expanding the capabilities of operating stewardship over the national nuclear stockpile.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1987

The effect of increased horizontal resolution on GLA Fourth Order model forecasts

A benchmark series of ten-day weather forecasts has been run with the GLA Fourth Order GCM with both a 4 deg latitude by 5 deg longitude resolution and a 2 deg latitude by 2.5 deg longitude resolution. Ensemble statistics of forecast skill and maps of systematic error fields have been generated for both resolutions. The enhanced resolution added 24 hours of useful predictive skill to the sea level pressure forecasts and 6 hours to the 500 mb height forecasts, but 5 to 6 days into the forecasts the advantage of the finer resolution was lost. The systematic error fields showed that by 8 days the 'climate drift' of the 2 x 2.5 deg forecasts had become pronounced and had caused the loss of predictive skill relative to the 4 x 5 deg forecasts. Additional results indicate that a gravity wave drag parameterization scheme might alleviate the climate drift problem.

Helfand, H. M.↗
NASA NTRS1993

Kinetic parameters from thermogravimetric analysis

High performance polymeric materials are finding increased use in aerospace applications. Proposed high speed aircraft will require materials to withstand high temperatures in an oxidative atmosphere for long periods of time. It is essential that accurate estimates be made of the performance of these materials at the given conditions of temperature and time. Temperatures of 350 F (177 C) and times of 60,000 to 100,000 hours are anticipated. In order to survey a large number of high performance polymeric materials on a reasonable time scale, some form of accelerated testing must be performed. A knowledge of the rate of a process can be used to predict the lifetime of that process. Thermogravimetric analysis (TGA) has frequently been used to determine kinetic information for degradation reactions in polymeric materials. Flynn and Wall studied a number of methods for using TGA experiments to determine kinetic information in polymer reactions. Kinetic parameters, such as the apparent activation energy and the frequency factor, can be determined in such experiments. Recently, researchers at the McDonnell Douglas Research Laboratory suggested that a graph of the logarithm of the frequency factor against the apparent activation energy can be used to predict long-term thermo-oxidative stability for polymeric materials. Such a graph has been called a kinetic map. In this study, thermogravimetric analyses were performed in air to study the thermo-oxidative degradation of several high performance polymers and to plot their kinetic parameters on a kinetic map.

Kiefer, Richard L.↗
NASA NTRS1994

Recent space shuttle observations of the South Atlantic anomaly and the radiation belt models

Active ingredients consisting of Tissue Equivalent Proportional Counter (TEPC) and a Proton and Heavy Ion Detector (PHIDE) have been carried on a number of Space Shuttle flights. These instruments have allowed us to map out parts of the South Atlantic Particle Anomaly (SAA) and to compare some of it's features with predictions of the AP-8 energetic proton flux models. We have observed that consistent with the generally observed westward drift of the surface features of the terrestial magnetic field of the SAA has moved west by about 6.9 degrees longitude between the epoch year 1970 of the AP-8 solar maximum model and the Space Shuttle observations made twenty years later. However, calculations indicate that except for relatively brief periods following very large magnetic storms the SAA seems to occupy the same position in L-space as in 1970. After the great storm of 24 March 1991 reconfiguration of the inner radiation belt and/or proton injection into the inner belt, a second energetic proton belt was observed to form at approximately equal to 2. As confirmed by a subsequent flight observations, this belt was shown to persist at least for six months. Our measurements also indicate an upward shift in the L location of the primary belt from L = 1.4 to L = 1.5. In addition we confirm through direct real time observations the existence and the approximate magnitude of the East-West effect. If the need exists for improved and updated radiation belt models in the Space Station era, these observations point out the specific features that should be considered and incorporated when this task is undertaken.

Konradi, A.↗
NASA NTRS2002

Induced Moment Effects of Formation Flight Using Two F/A-18 Aircraft

Previous investigations into formation flight have shown the possibility for significant fuel savings through drag reduction. Using two F/A-18 aircraft, NASA Dryden Flight Research Center has investigated flying aircraft in autonomous formation. Positioning the trailing airplane for best drag reduction requires investigation of the wingtip vortex effects induced by the leading airplane. A full accounting of the vortex effect on the trailing airplane is desired to validate vortex-effect prediction methods and provide a database for the design of a formation flight autopilot. A recent flight phase has mapped the complete wingtip vortex effects at two flight conditions with the trailing airplane at varying distances behind the leading one. Force and moment data at Mach 0.56 and an altitude of 25,000 ft and Mach 0.86 and an altitude of 36,000 ft have been obtained with 20, 55, 110, and 190 ft of longitudinal distance between the aircraft. The moments induced by the vortex on the trailing airplane were well within the pilot's ability to control. This report discusses the data analysis methods and vortex-induced effects on moments and side force. An assessment of the impact of the nonlinear vortex effects on the design of a formation autopilot is offered.

Hansen, Jennifer L.↗
DOE OSTI2025

Machine Learning for Predicting Multipactor Susceptibility in Planar RF Structures

Multipactor discharge is a persistent challenge in high-power microwave (HPM) and accelerator systems, where secondary electron avalanches can cause heating, vacuum degradation, and failure. This work presents the first supervised machine learning (ML) framework for multipactor prediction, trained on high-fidelity 3D Particle-in-Cell (PIC) simulation data in planar geometries. The model maps operational, geometric, and material-dependent secondary electron yield (SEY) parameters to the time-averaged electron growth rate, enabling rapid reconstruction of susceptibility charts. Among the models evaluated, tree-based ensemble methods such as Random Forest and Extra Trees demonstrate superior generalization to unseen materials compared to neural networks such as multilayer perceptron (MLP). Performance metrics, including Intersection over Union (IoU), Structural Similarity Index Measure (SSIM), and Pearson correlation, show close agreement with simulation benchmarks. Principal Component Analysis attributes generalization limits to material feature-space disjointedness.

43 PARTICLE ACCELERATORS↗
NASA NTRS1990

Infrared and radio measurements of the density structure of compact H II regions

The density structure of compact H II regions is studied by comparing the ratio of the S III forbidden 33.47-micron and 18.71-micron emission lines and 5-GHz continuum maps. Electron densities are computed for DR 22, G29.9 - 0.0, G75.84 + 0.4, M8, M42, S158, W3, and W33. For DR 22, M42, and W3, the electron densities determined from the IR data are consistent with those derived from radio observations. The densities for S158 and M8 are quite low, implying that the S III emission is dominated by the diffuse ionized gas observed in the radio continuum. For G29.9 - 0.0, G75.84 + 0.4, and W33, the S III data give higher densities than predicted from radio observations. This implies that either these nebulae are filled with dense clumps of ionized gas which are not resolved in the radio maps, or that the S III zone is confined to the small, dense cores found in the radio maps of all three nebulae.

Megeath, S. T.↗
NASA NTRS2006

An Assessment of NASA Glenn's Aeroacoustic Experimental and Predictive Capabilities for Installed Cooling Fans: Aerodynamic Performance - Part 1

Driven by the need for low production costs, electronics cooling fans have evolved differently than the bladed components of gas turbine engines which incorporate multiple technologies to enhance performance and durability while reducing noise emissions. Drawing upon NASA Glenn's experience in the measurement and prediction of gas turbine engine aeroacoustic performance, tests have been conducted to determine if these tools and techniques can be extended for application to the aerodynamics and acoustics of electronics cooling fans. An automated fan plenum installed in NASA Glenn's Acoustical Testing Laboratory was used to map the overall aerodynamic and acoustic performance of a spaceflight qualified 80 mm diameter axial cooling fan. In order to more accurately identify noise sources, diagnose performance limiting aerodynamic deficiencies, and validate noise prediction codes, additional aerodynamic measurements were recorded for two operating points: free delivery and a mild stall condition. Non-uniformities in the fan s inlet and exhaust regions captured by Particle Image Velocimetry measurements, and rotor blade wakes characterized by hot wire anemometry measurements provide some assessment of the fan aerodynamic performance. The data can be used to identify fan installation/design changes which could enlarge the stable operating region for the fan and improve its aerodynamic performance and reduce noise emissions.

VanZante, Dale E.↗
NASA NTRS2020

Chrono-Validation of Near-Real-Time Landslide Susceptibility Models via Plugin Statistical Simulations

The idea behind any validation scheme in landslide susceptibility studies is to test whether a model calibrated on a certain data can predict an unknown dataset of the same nature (landslide presences/absences and covariates). Almost the entirety of landslide susceptibility studies are validated by subsetting a single dataset into a training and test sets. This dataset usually corresponds either to event-specific or to historical inventories. Very rarely, a multi-temporal inventory is available and, in the few cases where this condition is met, the validation practices involve training a model on a specific landslide inventory, deriving a single predictive equation and validating it on a subsequent landslide inventory. This commonly leads landslide predictive studies, even those with a strong statistical rigor, to neglect the uncertainty estimation in their modeling scheme. In statistics, validation can also be performed via statistical simulations. This means that after fitting a given model, one can generate any number of predictive functions and test their predictive skills on any type and number of unknown datasets. In this work, we take a similar direction and we apply it to model and validate three separate co-seismic inventories, including an uncertainty estimation phase. We mapped these inventories within the same area in Indonesia, for three earthquakes occurred in 2012, 2017 and 2018. Specifically, we build three event-specific Bayesian Generalize Additive Models of the binomial family. From each model we then simulate 1000 predictive realizations over the remaining two inventories, by using a plug-in scheme where all the morphometric covariates are kept fixed and only the ground motion is replaced according to the prediction target. By doing so, we introduce a new analytical tool for near-real-time landslide predictive purposes, which is able to produce a probabilistic model which stands in between the definitions of susceptibility and hazard. In fact, our model is able to accurately estimate “where” and “when” - although not “how frequently” - landslide have occurred by featuring the multitemporal information of the trigger. In our findings, the simulations are quite similar to the fitted models; and the nine combinations we analyse produce excellent performance. This result confirms the assumption that “the past is the key to the future”, as we show that the relative contribution of each variable and their interactions in each probabilistic model remains practically the same across temporal replicates. This information is not trivial because it supports the routines implemented in global near-real-time applications.

Temporal validation↗
NASA NTRS2017

Mapping Vinyl Cyanide and Other Nitriles in Titan's Atmosphere Using ALMA

Vinyl cyanide (C2H3CN) is theorized to form in Titan's atmosphere via high-altitude photochemistry and is of interest regarding the astrobiology of cold planetary surfaces due to its predicted ability to form cell membrane-like structures (azotosomes) in liquid methane. In this work, we follow up on the initial spectroscopic detection of C2H3CN on Titan by Palmer et al. with the detection of three new C2H3CN rotational emission lines at submillimeter frequencies. These new, high-resolution detections have allowed for the first spatial distribution mapping of C2H3CN on Titan. We present simultaneous observations of C2H5CN, HC3N, and CH3CN emission, and obtain the first (tentative) detection of C3H8 (propane) at radio wavelengths. We present disk-averaged vertical abundance profiles, two-dimensional spatial maps, and latitudinal flux profiles for the observed nitriles. Similarly to HC3N and C2H5CN, which are theorized to be short-lived in Titan's atmosphere, C2H3CN is most abundant over the southern (winter) pole, whereas the longer-lived CH3CN is more concentrated in the north. This abundance pattern is consistent with the combined effects of high-altitude photochemical production, poleward advection, and the subsequent reversal of Titan's atmospheric circulation system following the recent transition from northern to southern winter. We confirm that C2H3CN and C2H5CN are most abundant at altitudes above 200 km. Using a 300 km step model, the average abundance of C2H3CN is found to be 3.03 +/- 0.29ppb, with a C2H5CN/C2H3CN abundance ratio of 2.43 +/- 0.26. Our HC3N and CH3CN spectra can be accurately modeled using abundance gradients above the tropopause, with fractional scale-heights of 2.05 +/- 0.16 and 1.63 +/- 0.02, respectively.

Lai, J. C.-Y.↗
NASA NTRS1973

Solar flare predictions and warnings

The real-time solar monitoring information supplied to support SPARCS-equipped rocket launches, the routine collection and analysis of 3.3-mm solar radio maps, short-term flare forecasts based on these maps, longer-term forecasts based on the recurrence of active regions, and results of the synoptic study of solar active regions at 3.3-mm wavelength are presented. Forecasted flares in the 24-hour forecasts were 81% accurate, and those in the 28-day forecasts were 97% accurate. Synoptic radio maps at 3.3-mm wavelength are presented for twenty-three solar rotations in 1967 and 1968, as well as synoptic flare charts for the same period.

White, K. P., III↗
NASA NTRS1981

Predicting and monitoring duststorms

Information on duststorms is processed by terminal receiving signals from two geosynchronous satellites. Data is correlated with that of other agencies to produce color maps depicting storm area. Series of maps reveals storm direction, warning regions up to 24 hours before they are struck.

Woiceshyn, P. M.↗
DOE OSTI2022

Microstructure-Sensitive Uncertainty Quantification for Crystal Plasticity Finite Element Constitutive Models Using Stochastic Collocation Methods

Uncertainty quantification (UQ) plays a major role in verification and validation for computational engineering models and simulations, and establishes trust in the predictive capability of computational models. In the materials science and engineering context, where the process-structure-property-performance linkage is well known to be the only road mapping from manufacturing to engineering performance, numerous integrated computational materials engineering (ICME) models have been developed across a wide spectrum of length-scales and time-scales to relieve the burden of resource-intensive experiments. Within the structure-property linkage, crystal plasticity finite element method (CPFEM) models have been widely used since they are one of a few ICME toolboxes that allows numerical predictions, providing the bridge from microstructure to materials properties and performances. Several constitutive models have been proposed in the last few decades to capture the mechanics and plasticity behavior of materials. While some UQ studies have been performed, the robustness and uncertainty of these constitutive models have not been rigorously established. In this work, we apply a stochastic collocation (SC) method, which is mathematically rigorous and has been widely used in the field of UQ, to quantify the uncertainty of three most commonly used constitutive models in CPFEM, namely phenomenological models (with and without twinning), and dislocation-density-based constitutive models, for three different types of crystal structures, namely face-centered cubic (fcc) copper (Cu), body-centered cubic (bcc) tungsten (W), and hexagonal close packing (hcp) magnesium (Mg). Our numerical results not only quantify the uncertainty of these constitutive models in stress-strain curve, but also analyze the global sensitivity of the underlying constitutive parameters with respect to the initial yield behavior, which may be helpful for robust constitutive model calibration works in the future.

36 MATERIALS SCIENCE↗
NASA NTRS2003

Predictability of Malaria Transmission Intensity in the Mpumalanga Province, South Africa, Using Land Surface Climatology and Autoregressive Analysis

There has been increasing effort in recent years to employ satellite remotely sensed data to identify and map vector habitat and malaria transmission risk in data sparse environments. In the current investigation, available satellite and other land surface climatology data products are employed in short-term forecasting of infection rates in the Mpumalanga Province of South Africa, using a multivariate autoregressive approach. The climatology variables include precipitation, air temperature and other land surface states computed by the Off-line Land-Surface Global Assimilation System (OLGA) including soil moisture and surface evaporation. Satellite data products include the Normalized Difference Vegetation Index (NDVI) and other forcing data used in the Goddard Earth Observing System (GEOS-1) model. Predictions are compared to long- term monthly records of clinical and microscopic diagnoses. The approach addresses the high degree of short-term autocorrelation in the disease and weather time series. The resulting model is able to predict 11 of the 13 months that were classified as high risk during the validation period, indicating the utility of applying antecedent climatic variables to the prediction of malaria incidence for the Mpumalanga Province.

Grass, David↗
DOE OSTI2024

Prediction of Distributed River Sediment Respiration Rates Using Community-Generated Data and Machine Learning

River sediment microbial respiration is a key indicator of ecosystem functioning and the biogeochemical fluxes across this critical zone link surface and subsurface waters. As such, there is tremendous interest in measuring and mapping these respiration rates. Respiration observations are expensive and labor intensive; there is limited data available to the community. An open science, collaborative initiative is collecting samples for respiration rate analysis and multi-scale metadata; this evolving data set is being used for making machine learning (ML) predictions at unsampled sites to help inform continued community engagement. However, it is a challenge to find an optimum configuration for ML models to work with this feature-rich (i.e., 100+ possible input variables) data set. Here, we present results from a two-tiered approach to managing the analysis of this complex data set: (a) a stacked ensemble of models that automatically optimizes hyperparameters and manages the training of many models and (b) feature permutation importance to detect the most important features in the models. The major elements of this workflow are modular, portable, open, and cloud-based thus making this implementation a potential template for other applications. The models developed here predict that sediment organic matter chemistry is one of the most important features for predicting sediment respiration rate. Other larger-scale, important features fall into the categories of climatic, ecological, geological, and fluvial settings. Leveraging these larger-scale features to generate data-driven estimates of river sediment respiration rates reveals spatially consistent but heterogeneous patterns across the river network of the Columbia River Basin.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Testing the parametric model for self-interacting dark matter using matched halos in cosmological simulations

Here, we systemically evaluate the performance of the self-interacting dark matter (SIDM) halo model proposed in Ref.Yang et al. (2023) with matched halos from high-resolution cosmological CDM and SIDM simulations. The model incorporates SIDM effects along mass evolution histories of CDM halos and it is applicable to both isolated halos and subhalos. We focus on the accuracy of the model in predicting halo density profiles at z = 0 and the evolution of maximum circular velocity. We find the model predictions agree with the simulations within 10%–50% for most of the simulated (sub)halos, 50%–100% for extreme cases. This indicates that the model effectively captures the gravothermal evolution of the halos with very strong, velocity-dependent self-interactions. For an example application, we apply the model to study the impact of various SIDM scenarios on strong lensing perturber systems, demonstrating its utility in predicting SIDM effects for small-scale structure analyses. Our findings confirm that the model is an effective tool for mapping CDM halos into their SIDM counterparts.

Yang, Daneng [Chinese Academy of Sciences, Nanjing↗
DOE OSTI2020

Centroidal Voronoi tessellation based methods for optimal rain gauge location prediction

With more satellite and model precipitation data becoming available, new analytical methods are needed that can take advantage of emerging data patterns to make well informed predictions in many hydrological applications. Herein we propose a new strategy where we extract precipitation variability patterns and use correlation map to build the resulting density map that serves as an input to centroidal Voronoi tessellation construction that optimizes placement of precipitation gauges. We provide results of numerical experiments based on the data from the Alto-Adige region in Northern Italy and Oklahoma and compare them against actual gauge locations. This method provides an automated way for choosing new gauge locations and can be generalized to include physical constraints and to tackle other types of resource allocation problems.

54 ENVIRONMENTAL SCIENCES↗