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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Evaluation of The Thermophysical Properties and Microstructure of UPu{sub 24}Zr{sub 15} Metallic Fuel

Featuring high burn-up, high fissile and fertile isotopic density, inherent safety characteristics, and favorable thermal response, actinide transmutation metallic fuels are considered to be among the most promising fuel classes for next generation fast reactors. During reactor operation, it is anticipated that fluctuations in chemical potential along the temperature gradient will lead to migration and redistribution of constituents between radial zones of the cylindrical fuel pin, resulting in compositional inhomogeneity and hence unpredictable fuel performance. Limited experimental fuel performance data is available for fuel selection and certification, therefore different compositions of options uranium-plutonium-zirconium (UPu- Zr) alloys have been investigated. Several complementary techniques, including scanning and transmission electron microscopy (SEM and TEM, respectively), differential scanning calorimetry (DSC), and laser flash diffusivity (LFD) techniques were used to characterize the phase distribution, microstructure, and thermophysical properties of unirradiated U-Pu-Zr fuels in both the as-cast and annealed condition. This information is necessary to understand the irradiated microstructure, properties, and performance of U-Pu-Zr fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1991

Unstructured grid generation using the distance function

A new class of methods for obtaining level sets to generate unstructured grids is presented. The consecutive grid levels are computed using the distance functions, which corresponds to solving the Hamilton-Jacobi equations representing the equations of motion of fronts propagating with curvature-dependent speed. The relationship between the distance function and the governing equations will be discussed as well as its application to generating grids. Multi-ply connected domains and complex geometries are handled naturally, with a straightforward generalization to several space dimensions. The grid points for the unstructured grid are obtained simultaneously with the grid levels. The search involved in checking for overlapping triangles is minimized by triangulating the entire domain one level at a time.

Bihari, Barna L.↗
NASA NTRS1988

A study of cloud-generated radiative heating and its generation of available potential energy. I - Theoretical background. II - Results for a climatological zonal mean January

The effect of radiative heating and cooling by clouds on the available potential energy (APE) is theoretically discussed. It is shown that the cloud radiative contribution to the generation of APE is determined by the net cloud radiative heating and the efficiency factor, which is a function of the temperature distribution of the atmosphere. Results are presented for low and middle cloud effects for three atmospheric layers. Cloud radiative heating is found to be a single function of cloud optical thickness for all classes designed in terms of cloud top heights and optical thickness. Low clouds at low latitudes destroy APE an midclouds generate APE. A concept is developed to relate the cloud radiative heating to cloud heights and optical depths. Cloud-generated radiative heating is computed for January zonal mean conditions for low and midclouds. For both cases, the strongest influence is found in the low troposphere, with marked differences in signs and magnitudes. At extratropical latitudes, both cloud classes generate net radiative cooling. In the tropics, the effect of low cloud changes from net cooling to the net heating as the optical thickness increases, and midclouds cause net heating. A mechanism is described whereby this dependence produces a strong positive feedback effect on the development of SST anomalies in the tropical oceans.

Stuhlmann, R.↗
DOE OSTI2022

AICCA: AI-Driven Cloud Classification Atlas

Clouds play an important role in the Earth’s energy budget, and their behavior is one of the largest uncertainties in future climate projections. Satellite observations should help in understanding cloud responses, but decades and petabytes of multispectral cloud imagery have to date received only limited use. This study describes a new analysis approach that reduces the dimensionality of satellite cloud observations by grouping them via a novel automated, unsupervised cloud classification technique based on a convolutional autoencoder, an artificial intelligence (AI) method good at identifying patterns in spatial data. Our technique combines a rotation-invariant autoencoder and hierarchical agglomerative clustering to generate cloud clusters that capture meaningful distinctions among cloud textures, using only raw multispectral imagery as input. Cloud classes are therefore defined based on spectral properties and spatial textures without reliance on location, time/season, derived physical properties, or pre-designated class definitions. We use this approach to generate a unique new cloud dataset, the AI-driven cloud classification atlas (AICCA), which clusters 22 years of ocean images from the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua and Terra instruments—198 million patches, each roughly 100 km × 100 km (128 × 128 pixels)—into 42 AI-generated cloud classes, a number determined via a newly-developed stability protocol that we use to maximize richness of information while ensuring stable groupings of patches. AICCA thereby translates 801 TB of satellite images into 54.2 GB of class labels and cloud top and optical properties, a reduction by a factor of 15,000. The 42 AICCA classes produce meaningful spatio-temporal and physical distinctions and capture a greater variety of cloud types than do the nine International Satellite Cloud Climatology Project (ISCCP) categories—for example, multiple textures in the stratocumulus decks along the West coasts of North and South America. We conclude that our methodology has explanatory power, capturing regionally unique cloud classes and providing rich but tractable information for global analysis. AICCA delivers the information from multi-spectral images in a compact form, enables data-driven diagnosis of patterns of cloud organization, provides insight into cloud evolution on timescales of hours to decades, and helps democratize climate research by facilitating access to core data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2010

Parametric Geometry, Structured Grid Generation, and Initial Design Study for REST-Class Hypersonic Inlets

Computational design and analysis of three-dimensional hypersonic inlets with shape transition has been a significant challenge due to the complex geometry and grid required for three-dimensional viscous flow calculations. Currently, the design process utilizes an inviscid design tool to produce initial inlet shapes by streamline tracing through an axisymmetric compression field. However, the shape is defined by a large number of points rather than a continuous surface and lacks important features such as blunt leading edges. Therefore, a design system has been developed to parametrically construct true CAD geometry and link the topology of a structured grid to the geometry. The Adaptive Modeling Language (AML) constitutes the underlying framework that is used to build the geometry and grid topology. Parameterization of the CAD geometry allows the inlet shapes produced by the inviscid design tool to be generated, but also allows a great deal of flexibility to modify the shape to account for three-dimensional viscous effects. By linking the grid topology to the parametric geometry, the GridPro grid generation software can be used efficiently to produce a smooth hexahedral multiblock grid. To demonstrate the new capability, a matrix of inlets were designed by varying four geometry parameters in the inviscid design tool. The goals of the initial design study were to explore inviscid design tool geometry variations with a three-dimensional analysis approach, demonstrate a solution rate which would enable the use of high-fidelity viscous three-dimensional CFD in future design efforts, process the results for important performance parameters, and perform a sample optimization.

Ferlemann, Paul G.↗
DOE OSTI2025

FLORIS Wake Map [SWR-25-71]

The FLORIS Wake Map repository is a set of tools for creating maps of cluster wake impacts based on NREL's FLORIS software and modeling tool (https://github.com/nrel/floris). The floriswakemap package comprises two main modules: the wake_map module, dedicated to the WakeMap class, and the area_selector module, dedicated to the AreaSelector class. The WakeMap class is used to generate maps of wake impacts on both new and existing clusters, while the AreaSelector class provides selections of candidate areas for new developments based on an instantiated WakeMap object.

Sinner, Michael (Misha) [National Renewable Energy↗
NASA NTRS1976

Autocorrelation peaks in congruential pseudorandom number generators

The complete correlation structure of several congruential pseudorandom number generators (PRNG) of the same type and small cycle length was studied to deal with the problem of congruential PRNG almost repeating themselves at intervals smaller than their cycle lengths, during simulation of bandpass filtered normal random noise. Maximum period multiplicative and mixed congruential generators were studied, with inferences drawn from examination of several tractable members of a class of random number generators, and moduli from 2 to the 5th power to 2 to the 9th power. High correlation is shown to exist in mixed and multiplicative congruential random number generators and prime moduli Lehmer generators for shifts a fraction of their cycle length. The random noise sequences in question are required when simulating electrical noise, air turbulence, or time variation of wind parameters.

Neuman, F.↗
NASA NTRS2015

Development of an Exploration-Class Cascade Distillation Subsystem: Performance Testing of the Generation 1.0 Prototype

The ability to recover and purify water is crucial for realizing long-term human space missions. The National Aeronautics and Space Admininstration and Honeywell co-developed a five-stage vacuum rotary distillation water recovery system referred to as the Cascade Distillation Subsystem (CDS). Over the past three years, NASA's Advanced Exploration Systems (AES) Water Recovery Project (WRP) has been working toward the development of a flight-forward CDS design. In 2012 the original CDS prototype underwent a series of incremental upgrades and tests intened to both demonstrate the feasibility of a on-orbit demonstration of the system and to collect operational and performance data to be used to inform a second generation design. The latest testing of the CDS Generation 1.0 prototype was conducted May 29 through July 2, 2014. Initial system performance was benchmarked by processing deionized water and sodium chloride. Following, the system was challenged with analogue urine waste stream solutions stabilized with an Oxone-based and the two International Space Station baseline and alternative pretreatment solutions. During testing, the system processed more than 160 kilograms of wastewater with targeted water recoveries between 75 and 85% depending on the specific waste stream tested. For all wastewater streams, contaminant removals from wastewater feed to product water distillate, were estimated at greater than 99%. The average specific energy of the system was less than 120 Watt-hours/kilogram. The following paper provides detailed information and data on the performance of the CDS as challenged per the WRP test objectives.

Callahan, Michael R.↗
DOE OSTI2022

Realistic galaxy image simulation via score-based generative models

ABSTRACT We show that a denoising diffusion probabilistic model (DDPM), a class of score-based generative model, can be used to produce realistic mock images that mimic observations of galaxies. Our method is tested with Dark Energy Spectroscopic Instrument (DESI) grz imaging of galaxies from the Photometry and Rotation curve OBservations from Extragalactic Surveys (PROBES) sample and galaxies selected from the Sloan Digital Sky Survey. Subjectively, the generated galaxies are highly realistic when compared with samples from the real data set. We quantify the similarity by borrowing from the deep generative learning literature, using the ‘Fréchet inception distance’ to test for subjective and morphological similarity. We also introduce the ‘synthetic galaxy distance’ metric to compare the emergent physical properties (such as total magnitude, colour, and half-light radius) of a ground truth parent and synthesized child data set. We argue that the DDPM approach produces sharper and more realistic images than other generative methods such as adversarial networks (with the downside of more costly inference), and could be used to produce large samples of synthetic observations tailored to a specific imaging survey. We demonstrate two potential uses of the DDPM: (1) accurate inpainting of occluded data, such as satellite trails, and (2) domain transfer, where new input images can be processed to mimic the properties of the DDPM training set. Here we ‘DESI-fy’ cartoon images as a proof of concept for domain transfer. Finally, we suggest potential applications for score-based approaches that could motivate further research on this topic within the astronomical community.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations

We developed a new class of physics-informed generative adversarial networks (PI-GANs) to solve forward, inverse, and mixed stochastic problems in a unified manner based on a limited number of scattered measurements. Unlike standard GANs relying solely on data for training, here we encoded into the architecture of GANs the governing physical laws in the form of stochastic differential equations (SDEs) using automatic differentiation. In particular, we applied Wasserstein GANs with gradient penalty (WGAN-GP) for its enhanced stability compared to vanilla GANs. We first tested WGAN-GP in approximating Gaussian processes of different correlation lengths based on data realizations collected from simultaneous reads at sparsely placed sensors. We obtained good approximation of the generated stochastic processes to the target ones even if there is a mismatch between the input noise dimensionality and the effective dimensionality of the target stochastic processes. We also studied the overfitting issue for both the discriminator and the generator, and we found that overfitting occurs also in the generator in addition to the discriminator as previously reported. Subsequently, we considered the solution of elliptic SDEs requiring approximations of three stochastic processes, namely the solution, the forcing, and the diffusion coefficient. Here again, we assumed data collected from simultaneous reads at a limited number of sensors for the multiple stochastic processes. Furthermore, three generators were used for the PI-GANs: two of them were feed forward deep neural networks (DNNs), while the other one was the neural network induced by the SDE. For the case where we have one group of data, we employed one feed forward DNN as the discriminator, while for the case of multiple groups of data we employed multiple discriminators in PI-GANs. We solved forward, inverse, and mixed problems without changing the framework of PI-GANs, obtaining both the means and the standard deviations of the stochastic solution and the diffusion coefficient in good agreement with benchmarks. In this work, we have demonstrated the effectiveness of PI-GANs in solving SDEs for about 120 dimensions. In principle, PI-GANs could tackle very high dimensional problems given more sensor data with low-polynomial growth in computational cost.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Flow field analysis for a class of waverider configurations

A package of computer codes for analysis of flow fields for waverider configurations is described. The package consists of a surface/volume grid generator and a finite-volume flow solver. The grid generator defines body geometries and computational grids by an algebraic homotopy procedure. The algebraic procedure is versatile in its application and can readily generate configurations in the class of blended wing-body geometries. This code has the ability to produce a wide variety of geometries in the given class with varying geometrical attributes. The flow solver employs a finite-volume formation and solves the explicit, Runge-Kutta integration technique. The method or flow simulation incorporates several techniques for acceleration of the convergence of the interaction process and an entropy corrected enthalpy damping procedure for efficient computation of high Mach number flows.

Moitra, Anutosh↗
DOE OSTI2016

FcTp( R ) ( R = i Pr or t Bu): third-generation ferrocenyl scorpionates

Scorpionate (or trispyrazolylborate) ligands have seen much structural variation due to the relative ease of modifying their electronic and steric effects. Second-generation scorpionates were created by increasing the bulk in the 3-position of the pyrazole (pz) ring. A new class of third-generation scorpionates was obtained by modifying the remaining boron substituent. A series of thallium(I) and cobalt(II) complexes of the ferrocenyltris(3- R -pyrazolyl)borate ligand [FcTp R ; R = isopropyl ( i Pr) or tert -butyl ( t Bu)] have been synthesized in order to expand the range of redox-active third-generation scorpionates. These are [ferrocenyltris(3- tert -butylpyrazol-1-yl-κ N 2 )borato]thallium(I), [FeTl(C 5 H 5 )(C 26 H 37 BN 6 )], [ferrocenyltris(3-isopropylpyrazol-1-yl-κ N 2 )borato]thallium(I), [FeTl(C 5 H 5 )(C 23 H 31 BN 6 )], chlorido[ferrocenyltris(3- tert -butylpyrazol-1-yl-κ N 2 )borato]cobalt(II), [CoFe(C 5 H 5 )(C 26 H 37 BN 6 )Cl], [ferrocenyltris(3- tert -butylpyrazol-1-yl-κ N 2 )borato]iodidocobalt(II) benzene disolvate, [CoFe(C 5 H 5 )(C 26 H 37 BN 6 )I]·2C 6 H 6 , and [ferrocenyltris(3-isopropylpyrazol-1-yl-κ N 2 )borato]iodidocobalt(II), [CoFe(C 5 H 5 )(C 23 H 31 BN 6 )I]. The structures demonstrate that the metal coordination site can easily be modified by using bulkier substituents at the pz 3-position.

Chemistry↗
NASA NTRS2020

A Path Towards Quantum Advantage in Training Deep Generative Models with Quantum Annealing

A class of quantum-classical hybrid machine-learning algorithms can be obtained by integrating classical deep generative models with quantum probability distributions as 'priors' over their latent variables. We introduce a hybrid implementation of variational autoencoders (QVAE) and also present a technique to hybridize flow-based invertible generative models. We demonstrate the use of D-Wave quantum annealers as physical simulators of quantum Boltzmann machines (QBM) to perform quantum-assisted training of QVAE. Latent-space QBM develop slowly mixing modes, opening a path to obtain quantum advantage in generative modeling with available quantum devices.

Vinci, Walter↗
DOE OSTI2022

ThunderSecure: deploying real-time intrusion detection for 100G research networks by leveraging stream-based features and one-class classification network

Nowadays, data generated by large-scale scientific experiments are on the scale of petabytes per month. These data are transferred through dedicated high-bandwidth networks (40/100G) across distributed sites for processing, storage, and analysis. Like general purpose networks, research networks experience intrusions. However, monitoring anomalies in such high-speed network traffics is challenging given current cyber-infrastructure. Moreover, traditional network intrusion detection systems (NIDS) are signature based. However, anomaly patterns are difficult to define and that rulesets are often not updated frequently enough to reflect the changes of attack behaviors. We present ThunderSecure, a high-throughput, unsupervised learning-based intrusions detection system for 100G research networks. ThunderSecure implements an efficient packet processing and detection pipeline using multi-cores and GPUs. It extracts statistical and temporal features from real-time network data streams and feeds them to a one-class anomaly detection network. A baseline of normal distribution will be created based on the training observation. Testing traffic deviated from the learned profile will be marked as anomalies. We trained ThunderSecure on hundreds of billions of science data packets mirrored from two 100G network connections at Fermi National Accelerator Laboratory. The detection performance was evaluated on traffic captured from the same research network days and weeks after the training with different types of attack flows injected. Results show that ThunderSecure can recognize science data traffic captured long after the training and made nearly certain detection on the segment of the streams where anomalous flows were injected.

100G research network↗
DOE OSTI2021

Bias Characterization, Vertical Interpolation, and Horizontal Interpolation for Distributed Wind Siting Using Mesoscale Wind Resource Estimates

Much like their counterparts in utility-scale wind energy, developers of industrial, small-scale and distributed wind turbine deployments need to understand and accurately characterize the wind resource to properly assess the power generation and financial ramifications during siting and planning. National Renewable Energy Laboratory’s WIND (Wind Integration National Dataset) Toolkit (WTK) provides a best-in-class wind resource dataset generated using the Weather Research and Forecasting (WRF) model. This dataset includes parameters such as the wind speed, wind direction, and temperature at various heights, plus atmospheric stability near the surface. This data is available at 2-km spatial resolution and five-minute temporal resolution across 7 years, from 2007 to 2013 through a publicly accessible API interface. The Tools Assessing Performance (TAP) project seeks to extend this dataset to allow long term resource estimates and leverage it to better equip distributed wind equipment manufacturers, owner-operators, and installation professionals with better tools for practical siting applications. In this report, we present the results from our investigation within the TAP project focused on characterization of bias in WTK-based wind speed estimates and evaluation of vertical and horizontal interpolation techniques. We discuss the tradeoffs between different techniques and their combinations, as well as describe the lower bounds we determine for the studied validation errors. While the specific estimates we present are specific to WTK and the validation dataset we have chosen for this investigation (NREL's Wind Resource Meteorological Database), the overall analysis and the studied techniques are general enough to be applied to a broader set of wind datasets, both simulation-based and observational.

17 WIND ENERGY↗
DOE OSTI2025

PROTOCALC, a W -band Polarized Calibrator for Cosmic Microwave Background Telescopes: Application to Simons Observatory and CLASS

Current- and next-generation cosmic microwave background (CMB) experiments will measure polarization anisotropies with unprecedented sensitivities. The need for high precision in these measurements underscores the importance of gaining a comprehensive understanding of instrument properties, with a particular emphasis on the study of the beam properties, and especially their polarization characteristics and the measurement of the polarization angle. In this context, a major challenge lies in the scarcity of millimeter polarized astrophysical sources with sufficient brightness and calibration knowledge to meet the stringent accuracy requirements of future CMB missions. This led to the development of a drone-borne calibration source designed for the frequency band centered on approximately 90 GHz, matching a commonly used channel in ground-based CMB measurements. The Prototype Calibrator for Cosmology, PROTOCALC, has undergone thorough in-lab testing, and its properties have been subsequently modeled through simulation software integrated into the standard Simons Observatory analysis pipeline. Moreover, the PROTOCALC system has been tested in the field, having been deployed twice on calibration campaigns with CMB telescopes in the Atacama Desert. The data collected constrain the roll angle of the source with a statistical accuracy of 0$^°_•$045.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1990

Conceptual second-generation lunar equipment

The spring 1990 Introduction to Design class was asked to conceptually design second-generation lunar vehicles and equipment as a semester design project. The basic assumption made in designing second-generation lunar vehicles and equipment was that a network of permanent lunar bases already existed. The designs were to facilitate the transportation of personnel and materials. The eight topics to choose from included flying vehicles, ground-based vehicles, robotic arms, and life support systems. Two teams of two or three members competed on each topic and results were exhibited at a formal presentation. A clean-propellant powered lunar flying transport vehicle, an extra-vehicular activity life support system, a pressurized lunar rover for greater distances, and a robotic arm design project are discussed.

Source record↗
DOE OSTI2015

Ion cyclotron resonance heating systems upgrade toward high power and CW operations in WEST

The design of the WEST (Tungsten-W Environment in Steady-state Tokamak) Ion cyclotron resonance heating antennas is based on a previously tested conjugate-T Resonant Double Loops prototype equipped with internal vacuum matching capacitors. The design and construction of three new WEST ICRH antennas are being carried out in close collaboration with ASIPP, within the framework of the Associated Laboratory in the fusion field between IRFM and ASIPP. The coupling performance to the plasma and the load-tolerance have been improved, while adding Continuous Wave operation capability by introducing water cooling in the entire antenna. On the generator side, the operation class of the high power tetrodes is changed from AB to B in order to allow high power operation (up to 3 MW per antenna) under higher VSWR (up to 2:1). Reliability of the generators is also improved by increasing the cavity breakdown voltage. The control and data acquisition system is also upgraded in order to resolve and react on fast events, such as ELMs. A new optical arc detection system comes in reinforcement of the V{sub r}/V{sub f} and SHAD systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗