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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Insights into the Oxidative Degradation Mechanism of Solid Amine Sorbents for CO 2 Capture from Air: Roles of Atmospheric Water

Abstract Direct air capture (DAC) processes for extraction of CO 2 from ambient air are unique among chemical processes in that they operate outdoors with minimal feed pretreatments. Here, the impact of humidity on the oxidative degradation of a prototypical solid supported amine sorbent, poly(ethylenimine) (PEI) supported on Al 2 O 3 , is explored in detail. By combining CO 2 adsorption measurements, oxidative degradation rates, elemental analyses, solid‐state NMR and in situ IR spectroscopic analysis in conjunction with 18 O labeling of water, a comprehensive picture of sorbent oxidation is achieved under accelerated conditions. We demonstrated that the presence of water vapor can play an important role in accelerating the degradation reactions. From the study we inferred the identity and kinetics of formation of the major oxidative products, and the role(s) of humidity. Our data are consistent with a radical mediated autooxidative degradation mechanism.

Carneiro, Juliana S. A.↗
DOE OSTI2023

Insights into the Oxidative Degradation Mechanism of Solid Amine Sorbents for CO 2 Capture from Air: Roles of Atmospheric Water

Direct air capture (DAC) processes for extraction of CO 2 from ambient air are unique among chemical processes in that they operate outdoors with minimal feed pretreatments. Here, the impact of humidity on the oxidative degradation of a prototypical solid supported amine sorbent, poly(ethylenimine) (PEI) supported on Al 2 O 3 , is explored in detail. By combining CO 2 adsorption measurements, oxidative degradation rates, elemental analyses, solid-state NMR and in situ IR spectroscopic analysis in conjunction with 18 O labeling of water, a comprehensive picture of sorbent oxidation is achieved under accelerated conditions. Here we demonstrated that the presence of water vapor can play an important role in accelerating the degradation reactions. From the study we inferred the identity and kinetics of formation of the major oxidative products, and the role(s) of humidity. Our data are consistent with a radical mediated autooxidative degradation mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

GIGA-Lens: Fast Bayesian Inference for Strong Gravitational Lens Modeling

We present GIGA-Lens: a gradient-informed, GPU-accelerated Bayesian framework for modeling strong gravitational lensing systems, implemented in TensorFlow and JAX. The three components, optimization using multistart gradient descent, posterior covariance estimation with variational inference, and sampling via Hamiltonian Monte Carlo, all take advantage of gradient information through automatic differentiation and massive parallelization on graphics processing units (GPUs). We test our pipeline on a large set of simulated systems and demonstrate in detail its high level of performance. The average time to model a single system on four Nvidia A100 GPUs is 105 s. The robustness, speed, and scalability offered by this framework make it possible to model the large number of strong lenses found in current surveys and present a very promising prospect for the modeling of ${ \mathcal O }({10}^{5})$ lensing systems expected to be discovered in the era of the Vera C. Rubin Observatory, Euclid, and the Nancy Grace Roman Space Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2016

Magnetic-Island Contraction and Particle Acceleration in Simulated Eruptive Solar Flares

The mechanism that accelerates particles to the energies required to produce the observed high-energy impulsive emission in solar flares is not well understood. Drake et al. proposed a mechanism for accelerating electrons in contracting magnetic islands formed by kinetic reconnection in multi-layered current sheets (CSs). We apply these ideas to sunward-moving flux ropes (2.5D magnetic islands) formed during fast reconnection in a simulated eruptive flare. A simple analytic model is used to calculate the energy gain of particles orbiting the field lines of the contracting magnetic islands in our ultrahigh-resolution 2.5D numerical simulation. We find that the estimated energy gains in a single island range up to a factor of five. This is higher than that found by Drake et al. for islands in the terrestrial magnetosphere and at the heliopause, due to strong plasma compression that occurs at the flare CS. In order to increase their energy by two orders of magnitude and plausibly account for the observed high-energy flare emission, the electrons must visit multiple contracting islands. This mechanism should produce sporadic emission because island formation is intermittent. Moreover, a large number of particles could be accelerated in each magneto hydro dynamic-scale island, which may explain the inferred rates of energetic-electron production in flares. We conclude that island contraction in the flare CS is a promising candidate for electron acceleration in solar eruptions.

Guidoni, S. E.↗
DOE OSTI2021

Binary Complex Neural Network Acceleration on FPGA

Being able to learn from complex data with phase information is imperative for many signal processing applications. Today’s real-valued deep neural networks (DNNs) have shown efficiency in latent information analysis but fall short when applied to the complex domain. Deep complex networks (DCN) , in contrast, can learn from complex data, but have high computational costs; therefore, they cannot satisfy the instant decision making requirements of many deployable systems dealing with short observations or short signal bursts. Recent, Binarized Complex Neural Network (BCNN), which integrates DCNs with binarized neural networks (BNN), shows great potential in classifying complex data in real-time. In this paper, we propose a structural pruning based accelerator of BCNN, which is able to provide more than 5000 frames/s inference throughput on edge devices. The high performance comes from both the algorithm and hardware sides. On the algorithm side, we conduct structural pruning to the original BCNN models and obtain 20 × pruning rates with negligible accuracy loss; on the hardware side, we propose a novel 2D convolution operation accelerator for the binary complex neural network. Experimental results show that the proposed design works with over 90% utilization and is able to achieve the inference throughput of 5882 frames/s and 4938 frames/s for complex NIN-Net and ResNet-18 using CIFAR-10 dataset and Alveo U280 Board.

Peng, Hongwu↗
NASA NTRS2001

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

Single-station observations of interplanetary scintillation (IPS) at three microwave frequencies; 2 GHz, 8 GHz and 22 GHz have been carried out between 1989 and 1998 using a large (34 m farad) radio telescope at the Kashima Space Research Center of the Communications Research Laboratory. The aim of these observations is 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 Kashima IPS observations at 2 GHz and 8 GHz, and a water vapor maser source, IRC20431 was used for the IPS observations at 22 GHz. Solar wind velocities derived from Kashima IPS data suggest that the solar wind acceleration takes place at radial distances between 10 and 30 solar radii (R(sub s)) from the sun. Properties of the turbulence spectrum (e.g. anisotropy, spectral index, inner scale) inferred from Kashima data are 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 coronal holes are found to develop significantly at high latitudes as the solar activity declines. Nevertheless, Kashima data suggests that the location of the acceleration region is stable throughout the solar cycle.

Tokumaru, Munetoshi↗
DOE OSTI2026

pop-cosmos : redshifts and physical properties of KiDS-1000 galaxies

ABSTRACT Principled Bayesian inference of galaxy properties has not previously been performed for wide-area weak-lensing surveys with millions of sources. We address this gap by applying the pop-cosmos generative model to perform spectral energy distribution (SED) fitting for 4 million KiDS (Kilo-Degree Survey)-1000 galaxies. Calibrated on deep COSMOS2020 photometric data, pop-cosmos specifies a physically motivated prior over the galaxy population up to $z \simeq 6$ in stellar population synthesis (SPS) parameter space. Using the Speculator SPS emulator with GPU (graphics processing unit)-accelerated Markov Chain Monte Carlo sampling, we perform full posterior inference at 8.2 GPU seconds per galaxy, obtaining joint constraints on galaxy redshifts and physical properties. We validate photometric redshifts against $\sim \!185\,\!000$ KiDS galaxies cross-matched to Dark Energy Spectroscopic Instrument Data Release 1 spectroscopic samples, achieving low bias ($2\times 10^{-3}$), scatter ($\sigma _{\mathrm{MAD}}=0.03$), and outlier fraction (3.2 per cent) for the Bright Galaxy Survey, with comparable performance (bias $3\times 10^{-2}$, $\sigma _{\mathrm{MAD}}=0.05$, 1.0 per cent outliers) for luminous red galaxies (LRGs). Within the LRG sample, we identify massive, dusty, star-forming contaminants at $z \simeq 0.4$ satisfying standard colour selections for quenched populations. We infer trends in stellar mass, star formation, metallicity, and dust across five tomographic redshift bins consistent with established scaling relations. Using specific star formation rate constraints, we identify $\sim$7 per cent of KiDS-1000 galaxies as quenched, versus 37 per cent implied by conservative colour cuts. This enables the construction of weak-lensing samples defined by physical properties while mitigating intrinsic alignment systematics and preserving statistical power. Our analysis validates pop-cosmos out of sample, establishing it as a scalable approach for galaxy evolution and cosmological analyses with photometric surveys.

Halder, Anik [Institute of Astronomy and Kavli Ins↗
DOE OSTI2023

BitGNN: Unlocking the Performance Potential of Binary Graph Neural Networks on GPUs

Graph Neural Networks (GNNs) have shown compelling results in many graph-based learning tasks. They are, however, time-consuming. Recent work has shown a promising direction in improving GNN speed and shrinking the size — network binarization, which binarizes network values and operations. Prior work, however, mainly focused on algorithm designs, leaving it open on how to fully materialize the performance potential. This work fills the gap by proposing techniques to best map binary GNNs and their computations to fit the nature of bit manipulations, optimizations and algorithms to maximize BSpMM kernel efficiency, and solutions to other factors influencing the end-to-end time on GPUs. Results on real-world graphs show that the proposed techniques outperform state of-the-art binary GNN implementations by 21-67× with little accuracy loss.

Chen, Jou-An↗
DOE OSTI2025

ASCR Workshop Position Paper: Challenges and Opportunities in High Energy Physics

High energy particle physics and cosmology concern themselves with estimating fundamental parameters of nature, such as the masses and interactions of fundamental particles like the Higgs boson and the rate of expansion of the universe. In doing so, they analyze exabyte-scale datasets, some of the largest in all of science, and face many challenges in subsequent data analysis. These challenges are shared between the two disciplines, but we focus on particle physics to highlight one specific domain. In particle physics, the standard method for estimating parameters involves performing Monte Carlo (MC) integration as a function of both parameters of interest and nuisance parameters using an expensive simulator, counting the number of observed collision events (i.i.d. samples) from an experiment in the corresponding integration domains, and forming a Poisson likelihood function. This likelihood function is then used in a Frequentist manner to construct a maximum likelihood point estimate (MLE) and confidence set for the parameters. To sufficiently populate the high-dimensional integration domains, simulators consume billions of CPU-hours annually and produce hundreds of petabytes of intermediate output data. Several techniques have been developed to: optimize definitions of the integration domains so as to be maximally sensitive to a particular subset of parameters, efficiently estimate the integrals, and build robust surrogate models by interpolating between integral evaluations at different parameter points. One can view this whole endeavor as classical Simulation-Based Inference (SBI).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1990

Artificial electron beams in the magnetosphere and ionosphere

The Plasma Diagnostics Payload of the Echo 7 satellite carried TV cameras and photometers by means of which the luminosity around an electron beam in the polar ionosphere could be studied. It was found that, while the beam Larmor spiral could be clearly seen near 100 km, above this only a column due to suprathermal electrons was observable. At high altitudes, the emission of neutral gas both generated powerful luminosity and substantially reduced accelerator potentials. An analysis of conjugate echoes indicates that inferred magnetospheric electric fields do not map well into the ionosphere, as well as the presence of strong pitch-angle scattering.

Winckler, John R.↗
NASA NTRS1993

Light ion flow in the nightside ionosphere of Venus

The flow characteristics of the light ions H(+) and He(+) have been studied in the midnight region of the ionosphere of Venus. Measurements of ion composition, electron and ion temperatures and magnetic fields by instruments onboard the Pioneer Venus Orbiter have been used in rite electron and ion equations of conservation of mass and momentum to derive the vertical flow velocities of H(+) and He(+). When average height profiles of the measured quantities were used, H(+) was found to flow upward, accelerating to speeds of almost 1 km/s at the ion-exobase. In a similar fashion, He(+) was found to flow downward into the neutral atmosphere where it is readily quenched by charge transfer reactions. The polarization electric field played an important role in forcing H(+) upward, but did not contribute enough to the He(+) force balance to produce upward flow. At the ion-exobase, the outward electric polarization force on H(+) was shown to be five times the gravitational force. Using an analogy with the terrestrial ion-exosphere, H(+) was inferred to flow upward into the ionotail of Venus and accelerate to escape speeds. A planet averaged escape flux of 1.4 x 10 exp 7/sq cm/s was calculated, which is comparable to hydrogen loss rates estimated by other investigators.

Hartle, R. E.↗
DOE OSTI2020

Concurrent Relaxation through Accelerated Deep Learning

CRADL captures performance metrics of machine learning algorithms operating on mesh data from multiphysics codes This proxy application is a tool to explore scalability of inference on HPC platforms, and also gather performance metrics for inference on new machine learning specific hardware. CRADL is designed to give users as fine a control as possible over an inference simulation. Users may select the number of cycles, amount of data, and batch size to pass to the accelerator of choice. Additionally the user may select a number of performance optimization libraries and flags. CRADL comes packaged with a repository of anonymized multi-physics simulation data, as well as a pretrained model for inference. The code allows a user to load their own pre-trained model and data if they wish. The code can operate in multiple parallelization schemes, with performance enhancing options such as half-precision libraries, PyTorch benchmarking, and pinned memory with non-blocking data transfers.

Zieb, KristoferJ.↗
DOE OSTI2022

Deep learning-accelerated 3D carbon storage reservoir pressure forecasting based on data assimilation using surface displacement from InSAR

Fast forecasting of the reservoir pressure distribution during geologic carbon storage (GCS) by assimilating monitoring data is a challenging problem. Due to high drilling cost, GCS projects usually have spatially sparse measurements from few wells, leading to high uncertainties in reservoir pressure prediction. To address this challenge, we use low-cost Interferometric Synthetic-Aperture Radar (InSAR) data as monitoring data to infer reservoir pressure build up. We develop a deep learning-accelerated workflow to assimilate surface displacement maps interpreted from InSAR and to forecast dynamic reservoir pressure. Employing an Ensemble Smoother Multiple Data Assimilation (ES-MDA) framework, the workflow updates three-dimensional (3D) geologic properties and predicts reservoir pressure with quantified uncertainties. We use a synthetic commercial-scale GCS model with bimodally distributed permeability and porosity to demonstrate the efficacy of the workflow. A two-step CNN-PCA approach is employed to parameterize the bimodal fields. The computational efficiency of the workflow is boosted by two residual U-Net based surrogate models for surface displacement and reservoir pressure predictions, respectively. The workflow can complete data assimilation and reservoir pressure forecasting in half an hour on a personal computer.

25 ENERGY STORAGE↗
NASA NTRS1986

Radio emission from binary stars

Radio emission from binary star systems; characteristics of the binary systems inferred from the radio observations; and the reasons for the activity are reviewed. Binary stars with two main sequence stars, with one normal star and a white dwarf, and those containing a neutron star or a black hole are described. Energy may be directly available as matter falls into the potential well of a compact object. Electromagnetic induction effects may occur due to relative motions of magnetic fields and matter. By enforcing rapid rotation, binaries can induce strong dynamo action and hence generate free energy in the form of intense, complex, evolving magnetic fields. Whatever the source of energy, the observations at radio and X-ray wavelengths demonstrate that electrons are accelerated to high energies (mildly relativistic and, ultrarelativistic). Observed or inferred radio brightness temperatures range up to 10 to the 15th power K or more, implying coherent emission for sources brighter than 10 billion K.

Dulk, George A.↗
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↗
DOE OSTI2024

Four-dimensional phase space tomography from one-dimensional measurements of a hadron beam

In this paper, we use one-dimensional measurements to infer the four-dimensional phase space density of an accumulated proton beam in the Spallation Neutron Source (SNS) accelerator. The reconstruction was performed by maximizing the distribution’s entropy subject to the measurement constraints and thus represents the most conservative inference from the data. The reconstructed distribution reproduces the measured profiles down to the noise level, and simulations indicate that the problem is reasonably well constrained. Similar measurements could serve as benchmarks for beam dynamics simulations in the SNS or hadron accelerators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Uncertainties in Density and Simulation Parameters for Radiographic Reconstructions Using Machine Learning

We will develop new and improved methods that will enable a fuller and more extensive use of experimental data, such as from radiographic imaging, towards better characterizing and reducing uncertainties in predictive modeling of weapons performance. We will achieve this by leveraging recent developments in the areas of computational imaging, statistical and machine learning, and reduced order modeling. Key new aspects of our approach include (a) a coupling of deep learning based density reconstruction with fast hydrodynamics simulators that will permit the development of certain guarantees on extrapolatability and bounds on certain other hydrodynamics-related para- metric uncertainties and (b) a dual approach towards better characterizing uncertainties in density reconstruction using deep learning based surrogates to accelerate Bayesian reconstructions on the one hand and using variational inference and Bayesian machine learning on the other hand.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS2014

A Vortical Dawn Flank Boundary Layer for Near-Radial IMF: Wind Observations on 24 October 2001

We present an example of a boundary layer tailward of the dawn terminator which is entirely populated by rolled-up flow vortices. Observations were made by Wind on 24 October 2001 as the spacecraft moved across the region at the X plane approximately equal to −13 Earth radii. Interplanetary conditions were steady with a near-radial interplanetary magnetic field (IMF). Approximately 15 vortices were observed over the 1.5 hours duration of Wind's crossing, each lasting approximately 5 min. The rolling up is inferred from the presence of a hot tenuous plasma being accelerated to speeds higher than in the adjoining magnetosheath, a circumstance which has been shown to be a reliable signature of this in single-spacecraft observations. A blob of cold dense plasma was entrained in each vortex, at whose leading edge abrupt polarity changes of field and velocity components at current sheets were regularly observed. In the frame of the average boundary layer velocity, the dense blobs were moving predominantly sunward and their scale size along the X plane was approximately 7.4 Earth radii. Inquiring into the generation mechanism of the vortices, we analyze the stability of the boundary layer to sheared flows using compressible magnetohydrodynamic Kelvin-Helmholtz theory with continuous profiles for the physical quantities. We input parameters from (i) the exact theory of magnetosheath flow under aligned solar wind field and flow vectors near the terminator and (ii) the Wind data. It is shown that the configuration is indeed Kelvin-Helmholtz (KH) unstable. This is the first reported example of KH-unstable waves at the magnetopause under a radial IMF.

Magnetosheath↗