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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Maximum Reasonable Radioxenon Releases from Medical Isotope Production Facilities and Their Effect on Monitoring Nuclear Explosions

Fission gases such as 133Xe are used extensively for monitoring the world for signs of nuclear testing in systems such as the International Monitoring System (IMS). These gases are also produced by nuclear reactors and by fission production of 99Mo for medical use. Recently, medical isotope production facilities have been identified as the major contributor to the background of radioactive xenon isotopes (radioxenon) in the atmosphere (Saey, et al., 2009). These releases pose a potential future problem for monitoring nuclear explosions if not addressed. As a starting point, a maximum acceptable daily xenon emission rate was calculated, that is both scientifically defendable as not adversely affecting the IMS, but also consistent with what is possible to achieve in an operational environment. This study concludes that an emission of 5×109 Bq/day from a medical isotope production facility would be both an acceptable upper limit from the perspective of minimal impact to monitoring stations, but also appears to be an achievable limit for large isotope producers.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

Graphs, matrices, and the GraphBLAS: Seven good reasons

The analysis of graphs has become increasingly important to a wide range of applications. Graph analysis presents a number of unique challenges in the areas of (1) software complexity, (2) data complexity, (3) security, (4) mathematical complexity, (5) theoretical analysis, (6) serial performance, and (7) parallel performance. Implementing graph algorithms using matrix-based approaches provides a number of promising solutions to these challenges. The GraphBLAS standard (istcbigdata.org/GraphBlas) is being developed to bring the potential of matrix based graph algorithms to the broadest possible audience. The GraphBLAS mathematically defines a core set of matrix-based graph operations that can be used to implement a wide class of graph algorithms in a wide range of programming environments. This paper provides an introduction to the GraphBLAS and describes how the GraphBLAS can be used to address many of the challenges associated with analysis of graphs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

10,000 - A reason to study granular heat convection

In sheared granular media, particle motion is characterized by vortex-like structures; here this is demonstrated experimentally for disks system undergoing indefinite deformation during simple shear, as often imposed by the rock masses hosting earthquake fault gouges. In traditional fluids it has been known for years that vortices represent a major factor of heat transfer enhancement via convective internal mixing, but in analyses of heat transfer through earthquake faults and base planes of landslides this has been continuously neglected. Can research proceed by neglecting heat convection by internal mixing? Our answer is astonishingly far from being yes.

58 GEOSCIENCES↗
DOE OSTI2013

THE 2011 ERUPTION OF THE RECURRENT NOVA T PYXIDIS: THE DISCOVERY, THE PRE-ERUPTION RISE, THE PRE-ERUPTION ORBITAL PERIOD, AND THE REASON FOR THE LONG DELAY

We report the discovery by M. Linnolt on JD 2,455,665.7931 (UT 2011 April 14.29) of the sixth eruption of the recurrent nova T Pyxidis. This discovery was made just as the initial fast rise was starting, so with fast notification and response by observers worldwide, the entire initial rise was covered (the first for any nova), and with high time resolution in three filters. The speed of the rise peaked at 9 mag day{sup -1}, while the light curve is well fit over only the first two days by a model with a uniformly expanding sphere. We also report the discovery by R. Stubbings of a pre-eruption rise starting 18 days before the eruption, peaking 1.1 mag brighter than its long-time average, and then fading back toward quiescence 4 days before the eruption. This unique and mysterious behavior is only the fourth known (with V1500 Cyg, V533 Her, and T CrB) anticipatory rise closely spaced before a nova eruption. We present 19 timings of photometric minima from 1986 to 2011 February, where the orbital period is fast increasing with P/ P-dot =+313,000 yr. From 2008 to 2011, T Pyx had a small change in this rate of increase, so that the orbital period at the time of eruption was 0.07622950 {+-} 0.00000008 days. This strong and steady increase of the orbital period can only come from mass transfer, for which we calculate a rate of (1.7-3.5) Multiplication-Sign 10{sup -7} M{sub Sun} yr{sup -1}. We report 6116 magnitudes between 1890 and 2011, for an average B = 15.59 {+-} 0.01 from 1967 to 2011, which allows for an eruption in 2011 if the blue flux is nearly proportional to the accretion rate. The ultraviolet-optical-infrared spectral energy distribution is well fit by a power law with f{sub {nu}}{proportional_to}{nu}{sup 1.0}, although the narrow ultraviolet region has a tilt with a fit of f{sub {nu}}{proportional_to}{nu}{sup 1/3}. We prove that most of the T Pyx light is not coming from a disk, or any superposition of blackbodies, but rather is coming from some nonthermal source. We confirm the extinction measure from IUE with E(B - V) = 0.25 {+-} 0.02 mag.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Reasons for high-temperature superconductivity in the electron–phonon system of hydrogen sulfide

We have calculated the electron and phonon spectra, as well as the densities of the electron and phonon states, of the stable orthorhombic structure of hydrogen sulfide SH{sub 2} in the pressure interval 100–180 GPa. It is found that at a pressure of 175 GPa, a set of parallel planes of hydrogen atoms is formed due to a structural modification of the unit cell under pressure with complete accumulation of all hydrogen atoms in these planes. As a result, the electronic properties of the system become quasi-two-dimensional. We have also analyzed the collective synphase and antiphase vibrations of hydrogen atoms in these planes, leading to the occurrence of two high-energy peaks in the phonon density of states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Possible version of the compression degradation of the thermonuclear indirect-irradiation targets at the national ignition facility and a reason for the failure of ignition

The main parameters of compression of a target and tendencies at change in the irradiation conditions are determined by analyzing the published results of experiments at the megajoule National Ignition Facility (NIF) on the compression of capsules in indirect-irradiation targets by means of the one-dimensional RADIAN program in the spherical geometry. A possible version of the “failure of ignition” of an indirect-irradiation target under the NIF conditions is attributed to radiation transfer. The application of onedimensional model to analyze the National Ignition Campaign (NIC) experiments allows identifying conditions corresponding to the future ignition regime and distinguishing them from conditions under which ignition does not occur.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

On the reason for the kink in the rigidity spectra of cosmic-ray protons and helium nuclei near 230 GV

A three-component phenomenological model describing the specific features of the spectrum of cosmic-ray protons and helium nuclei in the rigidity range of 30–2×10{sup 5} GV is proposed. The first component corresponds to the constant background; the second, to the variable “soft” (30–500 GV) heliospheric source; and the third, to the variable “hard” (0.5–200 TV) source located inside a local bubble. The existence and variability of both sources are provided by the corresponding “surfatron accelerators,” whose operation requires the presence of an extended region with an almost uniform (in both magnitude and direction) magnetic field, orthogonally (or obliquely) to which electromagnetic waves propagate. The maximum energy to which cosmic rays can be accelerated is determined by the source size. The soft source with a size of ∼100 AU is located at the periphery of the heliosphere, behind the front of the solar wind shock wave. The hard source with a size of >0.1 pc is located near the boundary of an interstellar cloud at a distance of ∼0.01 pc from the Sun. The presence of a kink in the rigidity spectra of p and He near 230 GV is related to the variability of the physical conditions in the acceleration region and depends on the relation between the amplitudes and power-law exponents in the dependences of the background, soft heliospheric source, and hard near galactic source. The ultrarelativistic acceleration of p and He by an electromagnetic wave propagating in space plasma across the external magnetic field is numerically analyzed. Conditions for particle trapping by the wave and the dynamics of the particle velocity and momentum components are considered. The calculations show that, in contrast to electrons and positrons (e{sup +}), the trapped protons relatively rapidly escape from the effective potential well and cease to accelerate. Due to this effect, the p and He spectra are softer than that of e{sup +}. The possibility that the spectra of accelerated protons deviate from standard power-law dependences due to the surfatron mechanism is discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

FPDetect: Efficient Reasoning About Stencil Programs Using Selective Direct Evaluation

We present FPDetect, a low-overhead approach for detecting logical errors and soft errors affecting stencil computations without generating false positives. We develop an offline analysis that tightly estimates the number of floating-point bits preserved across stencil applications. This estimate rigorously bounds the values expected in the data space of the computation. Violations of this bound can be attributed with certainty to errors. FPDetect helps synthesize error detectors customized for user-specified levels of accuracy and coverage. FPDetect also enables overhead reduction techniques based on deploying these detectors coarsely in space and time. Experimental evaluations demonstrate the practicality of our approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Towards On-Chip Learning for Low Latency Reasoning with End-to-End Synthesis

The Software Defined Architectures (SODA) Synthesizer is an open-source compiler-based tool able to automatically generate domain-specialized systems targeting Application-Specific Integrated Circuits (ASICs) or Field Programmable Gate Arrays (FPGAs) starting from high-level programming. SODA is composed of a frontend, SODA-OPT, which leverages the multilevel intermediate representation (MLIR) framework to interface with productive programming tools (e.g., machine learning frame-works), identify kernels suitable for acceleration, and perform high-level optimizations, and of a state-of-the-art high-level synthesis backend, Bambu from the PandA framework, to generate custom accelerators. One specific application of the SODA Synthesizer is the generation of accelerators to enable ultra-low latency inference and control on autonomous systems for scientific discovery (e.g., electron microscopes, sensors in particle accelerators, etc.). This paper provides an overview of the flow in the context of the generation of accelerators for edge processing to be integrated in transmission electron microscopy (TEM) devices, focusing on use cases from precision material synthesis. We show the tool in action with an example of design space exploration for inference on reconfigurable devices with a conventional deep neural network model (LeNet). Finally, we discuss the research directions and opportunities enabled by SODA in the area of autonomous control for scientific experimental workflows.

Castellana, Vito G.↗
DOE OSTI2024

Digital Analytics, Causal Knowledge Acquisition and Reasoning for Technical Language Processing

Complex engineering systems such as nuclear power plants (NPPs) generate and collect large amounts of equipment reliability (ER) data elements that contain information on the status of components, assets, and systems. Some of this information is textual in form and can be found in documents such as incident reports (IRs) and work orders (WOs). Analyses of textual data in current NPPs-using natural language processing (NLP) methods-have been expanded over the last decade, and it is only recently that the true potential of such analyses has emerged. So far, applications of NLP methods have mostly been limited to classification and prediction, the goal being to identify the nature of the textual element (e.g., safety or non-safety related). Here, we target a more complex problem: automatically extracting knowledge from a textual element in order to assist system engineers in conducting system health assessments. Knowledge extraction is a very broad concept, and its definition may vary depending on the application context. Our methods are a blend of both rule-based and machine learning (ML) algorithms. For our purposes, knowledge extraction means identifying the systems or assets mentioned in a given textual element, as well as the type of event described (e.g., component failure or maintenance activity). In addition, we want to capture details such as measured quantities and the temporal/cause-effect relations between events. In this tool, we also demonstrate how textual data elements are preprocessed in order to handle typos, acronyms, and abbreviations. One main feature of these methods is that they are not based solely on data, but are in fact model-based. In other words, they also rely on MBSE models that are designed to capture-from a functional point of view-the architecture of the systems/assets under consideration. The main purpose of such models is to digitally emulate system engineers' knowledge of system and asset architecture and to identify dependencies among systems, assets, and components. Provided these models, analyses of textual and numeric ER data can be performed by first identifying the OPM model elements to which the ER data elements are referring. The relationships between ER data elements are then identified by checking for any temporal or logical dependencies.

Mandelli, Diego [Idaho National Laboratory (INL), ↗
DOE OSTI2025

AR4IR (Automated Reasoning for Incident Response) [SWR-24-103]

A basic formal methods tool with the ability to aid and/or automate a utilities’ incidence response and instills confidence that the proposed action satisfies the system’s physical constraints, the organization’s cyber policies, and will not cause violations of technical standards.

Etigowni, Sriharsha [National Renewable Energy Lab↗
DOE OSTI2025

A Probabilistic Reasoner Based on Bayes Risk for Damage Detection in Structural Systems

Structural health monitoring (SHM) systems are used to inform operation of structural systems subject to loads and environments that may affect their integrity. SHM systems rely on continuous monitoring of the structure to determine its health state. These systems are often coupled with a model of the deployed structure to determine the consequences of changes in the system by forecasting the response to future states. These models, which may be thought of as digital twins, need to be updated to reflect the latest state of the structural system. This work makes use of an uncertainty-aware machine learning model that enforces distance preservation of the original input space to determine deviations from the training data input space distributions. This workflow enables domain shift detection to determine whether damage is present in the structure. The uncertainty metrics generated by this network are then used in a Bayes risk framework to design an optimal damage detector given cost and risk considerations. The approach is demonstrated on a computational example with simulated damage.

Najera-Flores, David [ATA Engineering, Inc.]↗