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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Determination of Chemical Kinetic Rate Constants of a Model for Carbothermal Processing of Lunar Regolith Simulant Using Methane

We have previously developed a chemical conversion model of the carbothermal processing of lunar regolith using methane to predict the rate of production of carbon monoxide. In this carbothermal process, gaseous methane is pyrolyzed as it flows over the hot surface of a molten zone of lunar regolith and is converted to carbon and hydrogen. Hydrogen is carried away by the exiting stream of gases and carbon is deposited on the melt surface. The deposited carbon mixes with the melt and reacts with the metal oxides in it to produce carbon monoxide that bubbles out of the melt. In our model, we assume that the flux of carbon deposited is equal to the product of the surface reaction rate constant gamma and the concentration of methane adjacent to the melt surface. Similarly, the rate of consumption of carbon per unit volume in the melt is equal to the product of the melt reaction rate constant k and the concentrations of carbon and metal oxide in the melt. In this paper, we describe our effort to determine gamma and k by comparison of the predictions from our model with test data obtained by ORBITEC (Orbital Technologies Corporation). The concentration of methane adjacent to the melt surface is a necessary input to the model. It is inferred from the test data by a mass balance of methane, adopting the usual assumptions of the continuously-stirred-tank-reactor model, whereby the average concentration of a given gaseous species equals its exit concentration. The reaction rates gamma and k have been determined by a non-linear least-squares fit to the test data for the production of carbon monoxide and the fraction of the incoming methane that is converted. The comparison of test data with our model predictions using the determined chemical kinetic rate constants provides a consistent interpretation of the process over the full range of temperatures, pressures, and methane flow rates used in the tests, thereby increasing our confidence to use the model for scale-up purposes.

Balasubramaniam, R↗
DOE OSTI2026

Variable rate neural compression for sparse detector data

Particle colliders produce data at extraordinary rates, posing major challenges for transmission and storage. High-throughput compression algorithms are therefore essential. In the sPHENIX experiment taking data at the Relativistic Heavy Ion Collider, a time projection chamber records three-dimensional (3D) particle trajectories that are highly sparse, making conventional learning-free lossy compression ineffective. Convolutional neural networks have surpassed traditional methods in compression ratio and accuracy. However, they fail to exploit sparsity for efficiency. To address these gaps, we present BCAE-VS, a bicephalous convolutional autoencoder with variable compression ratio for sparse data, which adapts compression to input complexity through key-point identification and sparse convolution. BCAE-VS achieves higher accuracy and compression ratios than prior neural approaches while being orders of magnitude smaller. Moreover, its throughput increases with sparsity—a property not observed in other methods. Although it was developed for collider experiments, BCAE-VS readily extends to other sparse data domains, such as light detection and ranging (LiDAR) sensing and 3D microscopy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1999

Comparisons of Monthly Oceanic Rainfall Derived from TMI and SSM/I

A technique for estimating monthly oceanic rainfall rate using multi-channel microwave measurements has been developed. There are three prominent features of this algorithm. First, the knowledge of the form of the rainfall intensity probability density function used to augment the measurements. Second, utilizing a linear combination of the 19.35 and 22.235 GHz channels to de-emphasize the effect of water vapor. Third, an objective technique has been developed to estimate the rain layer thickness from the 19.35 and 22.235 GHz brightness temperature histograms. This technique is applied to the SSM/I data since 1987 to infer monthly rainfall for the Global Precipitation Climatology Project (GPCP). A modified version of this algorithm is now being applied to the TRMM Microwave Imager (TMI) data. TMI data with better spatial resolution and 24 hour sampling (vs. sun-synchronized sampling, which is limited to two narrow intervals of local solar time for DMSP satellites) prompt us to study the similarity and difference between these two rainfall estimates. Six months of rainfall data (January to June 1998) are used in this study. Means and standard deviations are calculated. Paired student t-tests are administrated to evaluate the differences between rainfall estimates from SSM/I and TMI data. Their differences are discussed in the context of global satellite rainfall estimation.

Chang, A. T. C.↗
NASA NTRS2000

Monthly Oceanic Rainfall Derived from Space-Borne Microwave Data

A technique for estimating monthly oceanic rainfall rate using multi-channel microwave measurements has been developed. This technique is applied to the Special Sensor Microwave Imager (SSM/I) data since 1987 to infer monthly rainfall for the Global Precipitation Climatology Project (GPCP). A modified version of this algorithm is now being applied to the TRMM Microwave Imager (TMI) data. There are three prominent features of this algorithm. First, the knowledge of the form of the rainfall intensity probability density function used to augment the measurements. Second, utilizing a linear combination of the 19.35 and 22.235 GHz channels to deemphasize the effect of water vapor. Third, an objective technique has been developed to estimate the rain layer thickness from the 19.35 and 22.23 5 GHz brightness temperature histograms, TMI data with better spatial resolution and 24 hour sampling (vs. sun-synchronized sampling, which is limited to two narrow intervals of local solar time for DMSP satellites) prompt us to study the similarity and difference between these two rainfall estimates. One year of rainfall data (January to December 1998) are used in this study. The mean differences of these two rain estimates are typically less than 15%. Statistical tests are administrated to evaluate the differences between rainfall estimates from SSM/I and TMI data. Differences between TMI and SSM/I rain estimates are discussed in the context of radiative transfer calculations and rainfall estimate algorithm.

Chang, Alfred T. C.↗
DOE OSTI2024

Developing Asparagaceae1726: An Asparagaceae‐specific probe set targeting 1726 loci for Hyb‐Seq and phylogenomics in the family

Abstract Premise Target sequence capture (Hyb‐Seq) is a cost‐effective sequencing strategy that employs RNA probes to enrich for specific genomic sequences. By targeting conserved low‐copy orthologs, Hyb‐Seq enables efficient phylogenomic investigations. Here, we present Asparagaceae1726—a Hyb‐Seq probe set targeting 1726 low‐copy nuclear genes for phylogenomics in the angiosperm family Asparagaceae—which will aid the often‐challenging delineation and resolution of evolutionary relationships within Asparagaceae. Methods Here we describe and validate the Asparagaceae1726 probe set (https://github.com/bentzpc/Asparagaceae1726) in six of the seven subfamilies of Asparagaceae. We perform phylogenomic analyses with these 1726 loci and evaluate how inclusion of paralogs and bycatch plastome sequences can enhance phylogenomic inference with target‐enriched data sets. Results We recovered at least 82% of target orthologs from all sampled taxa, and phylogenomic analyses resulted in strong support for all subfamilial relationships. Additionally, topology and branch support were congruent between analyses with and without inclusion of target paralogs, suggesting that paralogs had limited effect on phylogenomic inference. Discussion Asparagaceae1726 is effective across the family and enables the generation of robust data sets for phylogenomics of any Asparagaceae taxon. Asparagaceae1726 establishes a standardized set of loci for phylogenomic analysis in Asparagaceae, which we hope will be widely used for extensible and reproducible investigations of diversification in the family.

Plant Sciences↗
DOE OSTI2020

Enabling Highly Efficient Capsule Networks Processing Through A PIM-Based Architecture Design

In recent years, the CNNs have achieved great successes in the image processing tasks, e.g., image recognition and object detection. Unfortunately, traditional CNN's classication is found to be easily misled by increasingly complex image features due to the usage of pooling operations, hence unable to preserve accurate position and pose information of the objects. To address this challenge, a novel neural network structure called Capsule Network has been proposed, which introduces equivariance through capsules to signicantly enhance the learning ability for image segmentation and object detection. Due to its requirement of performing a high volume of matrix operations, CapsNets have been generally accelerated on modern GPU platforms that provide highly optimized software library for common deep learning tasks. However, based on our performance characterization on modern GPUs, CapsNets exhibit low effciency due to the special program and execution features of their routing procedure, including massive unshareable intermediate variables and intensive syn- chronizations, which are very dicult to optimize at software level. To address these challenges, we propose a hybrid computing architecture design named PIM-CapsNet. It preserves GPU's on-chip computing capability for accelerating CNN types of layers in CapsNet, while pipelining with an off-chip in-memory acceleration solution that effectively tackles routing procedure's ineffciency by leveraging the processing-in-memory capability of today's 3D stacked memory. Using routing procedure's inherent parallellization feature, our design enables hierarchical improvements on CapsNet inference effciency through minimizing data movement and maximizing parallel processing in memory. Evaluation results demonstrate that our proposed design can achieve substantial improvement on both performance and energy savings for CapsNet inference, with almost zero accuracy loss. The results also suggest good performance scalability in optimizing the routing procedure with increasing network size.

Zhang, Xingyao↗
DOE OSTI2023

Nonparametric Inference for the Reproductive Rate in Generalized Compartmental Models

We develop a tractable nonparametric model for the time-varying reproductive rate of infectious diseases that combines the structure of a deterministic compartmental model and a stochastic model for incidence data. We use Bayesian inference to estimate, with uncertainty, the reproductive rate of the Coronavirus 2019 outbreak in the U.S. states of California, Florida, Michigan, New Mexico, New York, and Texas from January 2020 to March 2022. Employing the inferred reproductive rates, we estimate the posterior distribution of the time-varying reproduction numbers for each state. Compering the time-varying reproduction numbers across the states, we identify some epidemic waves, potentially driven from changes in human behavior and virus mutations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1988

Tropopause adjustment to tropical cyclones as inferred from satellite ozone observations

Data from the Total Ozone Mapping Spectrometer on the Nimbus-7 are used to map the climatological total ozone within and around tropical cyclones. A tropical cyclone numerical model is used to interpret total ozone patterns. The total ozone maps are used to diagnose storm intensity and to differentiate between intesifying and weakening tropical cyclones. The tropical cyclone intensity versus total ozone anomaly distribution is examined and examples of mapping the total ozone of tropical cyclones in the period 1979-1982 are presented.

Rodgers, Edward B.↗
NASA NTRS1994

Rotational Relaxation in Nonequilibrium Freejet Expansions of Heated Nitrogen

Rotational temperatures have been measured in rarefied, nonequilibrium, heated freejet expansions of nitrogen using the electron beam fluorescence technique at the University of California at Berkeley Low Density Wind Tunnel facility. Spectroscopic measurements of the (0,0) band of the first negative system of nitrogen reveal the nonequilibrium behavior in the flowfield upstream of, and through the Mach disk, which forms as the freejet expands into a region of finite back pressure. Results compare well with previous freejet expansion data and computations regarding location of the Mach disk and terminal rotational temperature in the expansion. Measurements are also presented for shock thickness based on the rotational temperature changes in the flow. Thickening shock layers, departures of rotational temperature from equilibrium in the expansion region, and downstream rotational temperature recovery much below that of an isentropic normal shock provide indications of the rarefied, nonequilibrium flow behavior. The data are analyzed to infer constant values of the rotational-relaxation collision number from 2.2 to 6.5 for the various flow conditions. Collision numbers are also calculated in a consistent manner for data from other investigations for which is seen a qualitative increase with increasing temperature. Rotational-relaxation collision numbers are seen as not fully descriptive of the rarefied freejet flows. This may be due to the high degree of nonequilibrium in the flowfields, and/or to the use of a temperature-insensitive rotational-relaxation collision number model in the data analyses.

Gochberg, Lawrence A.↗
DOE OSTI2022

Time-resolved CO 2 , CO, and N 2 vibrational population measurements in Ns pulse discharge plasmas

Abstract Time-resolved CO 2 and N 2 vibrational populations and translational-rotational temperature are measured in a CO 2 –N 2 plasma sustained by a ns pulse discharge burst in plane-to-plane geometry. Time-resolved, absolute number density of CO generated in the plasma is also inferred from the experimental data. CO 2 and CO vibrational populations are measured by mid-IR, tunable quantum cascade laser absorption spectroscopy, and N 2 vibrational populations are measured by the ns broadband vibrational CARS. Transient excitation of N 2 and CO 2 asymmetric stretch vibrational energy modes is detected during the discharge burst. The time-resolved rate of CO generation does not correlate with N 2 or CO 2 ( ν 3 ) vibrational temperatures, indicating that CO 2 dissociation via the vibrational excitation is insignificant at the present conditions. The rate of CO generation decreases gradually during the discharge burst. The estimated specific energy cost of the CO product is close to that of N atoms in pure nitrogen, measured previously at similar operating conditions. Comparison of the experimental data with the kinetic modeling analysis indicates that CO 2 dissociation in collisions with electronically excited N 2 molecules is the dominant channel of CO generation at the present conditions, although the inferred CO yield in these processes is significantly lower than 1. The effect of vibrational energy transfer between N 2 and CO 2 on the plasma chemical processes is insignificant. The kinetic model underpredicts a rapid reduction of the N 2 and CO 2 ( ν 3 ) vibrational temperatures during the later half of the discharge burst and in the afterglow. V–T relaxation of N 2 by N and O atoms generated in the ns pulse discharge plasma does not affect the vibrational relaxation rate in a significant way. However, rapid V–T relaxation of CO 2 by O atoms has a significant effect on the relaxation rate. The difference between the experimental data and the modeling predictions may be due to the unknown scaling of the CO 2 –O V–T rates with the vibrational quantum number.

Physics↗
DOE OSTI2023

Bayesian inference for the seismic moment tensor using regional waveforms and a data-derived distribution of velocity models

The largest source of uncertainty in any source inversion is the velocity model used to construct the transfer function employed in the forward model that relates observed ground motion to the seismic moment tensor. However, standard inverse procedures often does not quantify uncertainty in the seismic moment tensor due to error in the Green’s functions from uncertain event location and Earth structure. We attempt to incorporate this uncertainty into an estimation of the seismic moment tensor using a distribution of velocity models calculated in a prior effort based on different and complementary data sets. The posterior distribution of velocity models is then used to construct Green’s functions for use in Bayesian inference of an unknown seismic moment tensor using regional waveform data. The combined likelihood is estimated using data-specific error models and the posterior of the seismic moment tensor is estimated and can be interpreted in terms of most-probable source-type.

58 GEOSCIENCES↗
NASA NTRS2014

Learning Extended Finite State Machines

We present an active learning algorithm for inferring extended finite state machines (EFSM)s, combining data flow and control behavior. Key to our learning technique is a novel learning model based on so-called tree queries. The learning algorithm uses the tree queries to infer symbolic data constraints on parameters, e.g., sequence numbers, time stamps, identifiers, or even simple arithmetic. We describe sufficient conditions for the properties that the symbolic constraints provided by a tree query in general must have to be usable in our learning model. We have evaluated our algorithm in a black-box scenario, where tree queries are realized through (black-box) testing. Our case studies include connection establishment in TCP and a priority queue from the Java Class Library.

Register Automata↗
DOE OSTI2026

A Statistician’s Overview of Physics-Informed Neural Networks for Spatio-Temporal Data

The recent success of deep neural network models with physical constraints (so-called, Physics-Informed Neural Networks, PINNs) has led to renewed interest in the incorporation of mechanistic information in predictive models. Statisticians and others have long been interested in this problem, which has led to several practical and innovative solutions dating back decades. In this overview, we focus on the problem of data-driven prediction and inference of dynamic spatio-temporal processes that include mechanistic information, such as would be available from partial differential equations, with a strong focus on the quantification of uncertainty associated with data, process, and parameters. Here, we give a brief review of several paradigms and focus our attention on Bayesian implementations given they naturally accommodate uncertainty quantification. We then show that it is straight-forward to include the Bayesian PINN (B-PINN) within the Bayesian hierarchical model (BHM) framework that has long been considered for modeling dynamic spatio-temporal processes. Such a BHM-PINN is illustrated via a simulation study in which a latent nonlinear Burgers’ equation PDE governs the dynamics of Poisson distributed spatio-temporal data. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.

Bayesian↗
NASA NTRS2000

Freja Studies of the Current-Voltage Relation in Substorm-Related Events

Field-aligned currents and electrostatic potentials play important roles in the coupling between the magnetosphere and the ionosphere. If one assumes that the ionosphere-magnetosphere potential difference is mainly due to the mirror force, one can use the single particle adiabatic kinetic theory to describe the system. From this theory, a linear relationship j(sub II) = KV between field-aligned current density j(sub II) and potential drop V along the same field line can be derived, provided that the potential drop is not too large and not too small. With rare exceptions, observational tests of this relation have mainly concentrated on quiet magnetospheric situations, with acceleration voltages V approx. less than 5 kV. Here we use observations from the Freja satellite of precipitating auroral electrons at 1.700 km altitude to study substorm related events, with acceleration voltages up to 20 keV. The observations are found to be consistent with a linear current-voltage relation even i n these conditions, although with values of the field aligned K lower than previously reported (1-5 x 10(exp 11 S/sq m). This can be explained by lower densities and higher characteristic electron energies in the magnetospheric source region of the precipitating electrons. We analyze the data by three different methods, which are all found to be in general agreement. The results are in agreement with a previous study, where the spectra of precipitating electrons --were indirectly inferred by inversion of data from the EISCAT incoherent scatter radar, thereby validating the use of radar data for studies of auroral electrons. Comparisons with previous studies are made, emphasizing the dependence of the results on the type of auroral structure and magnetospheric conditions.

Olsson, A.↗
NASA NTRS1983

A study of solar activity-ozone relationship from Nimbus-4 BUV data

The total O3 and the O3 mixing ratio at various pressure levels in the stratosphere measured from the Nimbus-4 BUV experiment over a 7-yr period (1970 to 1977) comprises a comprehensive data base available to study the possible effects of solar variability on stratospheric O3. It is shown that with the decrease in solar activity from 1970 to 1976, the globally averaged O3 inferred from Nimbus-4 data decreases from about 10 to 12 percent in the upper stratosphere to about 1 to 3 percent in the lower stratosphere. The systematic decrease in O3 seems to be correlated with the conventional indices of solar activity; however, it is difficult to account for the observed changes at various pressure levels with the current understanding of the photochemical models and the solar UV flux variations over a solar cycle.

Chandra, S.↗
DOE OSTI2021

Attend and Decode: 4D fMRI Task State Decoding Using Attention Models

Source code for Brain Attend and Decode paper. Functional magnetic resonance imaging (fMRI) is a neuroimaging modality that captures the blood oxygen level in a subject's brain while the subject either rests or performs a variety of functional tasks under different conditions. Given fMRI data, the problem of inferring the task, known as task state decoding, is challenging due to the high dimensionality (hundreds of million sampling points per datum) and complex spatio-temporal blood flow patterns inherent in the data. In this work, we propose to tackle the fMRI task state decoding problem by casting it as a 4D spatiotemporal classification problem. We present a novel architecture called Brain Attend and Decode (BAnD), that uses residual convolutional neural networks for spatial feature extraction and self-attention mechanisms for temporal modeling. We achieve significant performance gain compared to previous works on a 7-task benchmark from the large-scale Human Connectome Project-Young Adult (HCP-YA) dataset. We also investigate the transferability of BAnD's extracted features on unseen HCP tasks, either by freezing the spatial feature extraction layers and retraining the temporal model, or finetuning the entire model. The pre-trained features from BAnD are useful on similar tasks while finetuning them yields competitive results on unseen tasks/conditions.

Ng, BrendaM.↗
NASA NTRS2010

The Abundance Pattern in the Hot ISM of NGC 4472: Insights and Anomalies

Important clues to the chemical and dynamical history of elliptical galaxies are encoded in the abundances of heavy elements in the X-ray emitting plasma. We derive the hot ISM abundance pattern in inner (0.2.3R(sub e)) and outer (2.3.4.6R(sub e)) regions of NGC 4472 from analysis of Suzaku spectra, supported by analysis of co- spatial XMM-Newton spectra. The low background and relatively sharp spectral resolution of the Suzaku XIS detectors, combined with the high luminosity and temperature in NGC 4472, enable us to derive a particularly extensive abundance pattern that encompasses O, Ne, Mg, Al, Si, S, Ar, Ca, Fe, and Ni in both regions. We apply simple chemical evolution models to these data, and conclude that the abundances are best explained by a combination of alpha-element enhanced stellar mass loss and direct injection of Type Ia supernova (SNIa) ejecta. We thus confirm the inference, based on optical data, that the stars in elliptical galaxies have supersolar [alpha/Fe] ratios, but find that that the present-day SNIa rate is approximately 4.6 times lower than the standard value. We find SNIa yield sets that reproduce Ca and Ar, or Ni, but not all three simultaneously. The low abundance of O relative to Ne and Mg implies that standard core collapse nucleosynthesis models overproduce O by approximately 2.

Loewenstein, Michael↗
NASA NTRS2001

Exploration of Solar Wind Acceleration Region Using Interplanetary Scintillation of Water Vapor Maser Source and Quasars

Single-station observations of interplanetary scintillation UPS) at three microwave frequencies 2, 8, and 22GHz, were carried out between 1989 and 1998 using a large (34-micro farad) radio telescope at the Kashima Space Research Center of the Communications Research Laboratory. The aim of these observations was to explore the near-sun solar wind, which is the key region for the study of the solar wind acceleration mechanism. Strong quasars, 3C279 and 3C273B, were used for the Kashima IPS observations at 2 and 8GHz, and a water-vapor maser source, IRC20431, was used for the IPS observations at 22GHz. Solar wind speeds derived from Kashima IPS data suggest that the solar wind acceleration takes place at radial distances between 10 and 30 solar radii (Rs) from the sun. The properties of the turbulence spectrum (e.g. anisotropy, spectral index, inner scale) inferred from the Kashima data were found to change systematically in the solar wind acceleration region. While the solar wind in the maximum phase appears to be dominated by the slow wind, fast and rarefied winds associated with the coronal holes were found to develop significantly at high latitudes as the solar activity declined. Nevertheless, the Kashima data suggests that the location of the acceleration region is stable throughout the solar cycle.

Tokumaru, Munetoshi↗