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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Calculation of Self-Sputtering Yield under Ion Bombardment of Solids: Computer Simulation and Theory

We developed a computer simulation program for investigation of solid self-sputtering under ion bombardment. The program is based on binary collision approximation, truncated Coulomb potential, and the model of local inelastic losses proportional to energy. As a result of simulation, the self-sputtering yield is calculated as a function of atomic number and ion energy. To verify the cascade simulation code, we created a self-sputtering theory for the case of hard sphere potential. Simulation results show good agreement with both experimental data and theory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Data systems for the Linac coherent light source

Abstract The data systems for X-ray free-electron laser (FEL) experiments at the Linac coherent light source (LCLS) are described. These systems are designed to acquire and to reliably transport shot-by-shot data at a peak throughput of 5 GB/s to the offline data storage where experimental data and the relevant metadata are archived and made available for user analysis. The analysis and monitoring implementation (AMI) and Photon Science ANAlysis (psana) software packages are described. Psana is open source and freely available.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A perspective on Bayesian methods applied to materials discovery and design

For more than two decades, there has been increasing interest in developing frameworks for the accelerated discovery and design of novel materials that could enable promising and transformative technologies. The Integrated Computational Materials Engineering (ICME) program called for integrating computational tools to establish linkages along process-structure-property-performance (PSPP) chains. The Materials Genome Initiative called for integrating experiments and computations within data science frameworks as a strategy to accelerate the materials development cycle. While these frameworks and paradigms have been quite influential, traditional ICME or data science-based approaches tend to have some limitations, mainly when querying the materials space is costly and very little information is available. Bayesian methods are more suitable in this context due to their efficiency gains. To this end, the materials discovery problem is framed as a Bayesian Optimization (BO). Different examples in which BO has been applied to solve materials discovery problems are presented. The methods/examples discussed include BO under model uncertainty, multi-information source BO, multi-objective and multi-constraint BO, and batch BO. Bayesian Materials Discovery is a promising area of research that is likely to become more influential as more attention is put on autonomous materials discovery platforms. Therefore, a discussion is provided on the potential development of such methods to increase the ability of existing platforms in materials discovery. Here, the ultimate goal is to pave the way to autonomous materials discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Denoising Seismograms in the Time Domain Using a Deep Learning Model

Deep learning has emerged as a transformative tool for enhancing the extraction of reliable information from seismograms, addressing the increasing demand for precise and efficient seismic data analysis. We introduce an innovative encoder–decoder deep learning model, named WaveDenoiser, designed for noise reduction in the time domain, thereby eliminating the need for spectrogram computations that have been used for existing deep learning tools and significantly improving processing speed. Utilizing the benchmark dataset that is Stanford Earthquake Dataset, we developed three models of varying sizes: base, medium, and large. Notably, the large (referred to as WaveDenoiser) model demonstrated superior performance, achieving a median signal‐to‐noise ratio improvement of 8.8 dB on in‐distribution unseen data (in the same geographic region) and 7.7 dB on out‐distribution unseen data (in a new geographic region), outpacing both the base and medium models. Further evaluation of the WaveDenoiser model revealed a reduction in median arrival‐time errors by 0.02 s for P waves and 0.01 s for S waves when processing waveforms prior to phase picking using PhaseNet on in‐distribution unseen data. When tested on out‐distribution unseen data, the model also effectively reduced the P‐wave median arrival‐time error by 0.02 and 0.01 s in median arrival‐time error for S waves. Importantly, the application of WaveDenoiser resulted in a significant reduction of phase picking outliers by 1.1% to 3.6% for both P and S waves. In addition, we achieved over five times acceleration in processing speed compared with the seisBench implementation of DeepDenoiser. Our findings underscore the potential of WaveDenoiser as a powerful tool for improving seismic data analysis and processing efficiency.

P-waves↗
DOE OSTI2021

High-Quality Revision of the Israeli Seismic Bulletin

Seismic bulletins, with trustworthy phase picks, origin times, and source locations are key for regional seismic studies, such as travel-time (TT) tomography, attenuation tomography, and anisotropy studies. To lay the groundwork for such studies in Israel, we revised the seismic bulletin of Israel and the surrounding area and obtained a trustworthy TT data set. From the earthquake and explosion bulletins of the Geophysical Institute of Israel, we compiled a starting data set of about 123,000 earthquakes and explosions that occurred during the past 40 yr. After screening out the poorly recorded events, we were left with a data set of ~38,000 well-recorded events. We then revised the remaining data set in two consecutive steps. In the first, we reviewed and updated station metadata, including changes in station metadata parameters over time. In the second step, we jointly relocated a list of selected seismic events, using the Bayesian hierarchical location software package (BayesLoc) of Myers et al. (2007) that performs joint relocation of multiple events. We observed striking dissimilarities between the spatial distributions of the newly relocated catalog and the initial locations. Although the depth distribution of the starting catalog is trimodal with peaks at 0, 5, and 10 km, the distribution in this study is unimodal, with a broad peak between 7.5 and 12.5 km. By differencing the observed arrival times and the origin times obtained through relocation with BayesLoc, we obtained a revised TT database that consists of 261,336 Pg, 132,876 Pn, 114,816 Sg, and 60,394 Sn arrivals, from a set of 30,458 jointly relocated seismic sources. In this work, we compared prerevision and postrevision TTs as a function of epicentral distance and concluded that the revised data set contains far fewer outliers and inconsistencies than the original data set. The revised TT data set may be used for seismic studies, such as TT tomography, attenuation tomography, and anisotropy studies.

58 GEOSCIENCES↗
DOE OSTI2025

Cardinal: Seismic and Geoacoustic Array Processing

Data collected via seismic and infrasound array deployments are leveraged in the geosciences to detect and characterize a myriad of natural and anthropogenic sources. These deployments consist of numerous sensors placed in a predetermined configuration to amplify signal strength and improve the efficacy of array processing techniques used to measure signal directionality and waveform coherence. High‐fidelity feature extraction is often predicated on interstation distance as well as the frequency content and wavelength of an incident signal. Numerous array processing softwares analyze data in sequential frequency bands to obtain a more detailed characterization of a signal. However, current algorithms are limited in their ability to determine optimal array configuration for each band. We introduce an open‐source Python code, called Cardinal, to process seismic and infrasound array data in discretized time–frequency space with the option of applying an adaptive array design to determine optimal subarray configuration for each frequency band. To reduce computational time, the array processing step can be run in parallel using multithreading. Furthermore, the software has the capability to aggregate array processing results from different time–frequency pixels to produce separate sets of detections, or families, with added utility via the application of an adaptive semblance threshold, which aids in isolating signals‐of‐interest from coherent background noise. Upon appropriate configuration, Cardinal exhibits the potential to combine distinct seismic and infrasound phases into separate families.

Adaptive Array↗
DOE OSTI2021

Thermal Effects on Far-Field Distributed Acoustic Strain-Rate Sensors

Summary Fiber-optic cables cemented outside of the casing of an unconventional well measure crosswell strain changes during fracturing of neighboring wells with low-frequency distributed acoustic sensing (LF-DAS). As a hydraulic fracture intersects an observation well instrumented with fiber-optic cables, the fracture fluid injected at ambient temperatures can cool a section of the sensing fiber. Often, LF-DAS and distributed temperature sensing (DTS) cables are run in tandem, enabling the detection of such cooling events. The increasing use of LF-DAS for characterizing unconventional hydraulic fracture completions demands an investigation of the effects of temperature on the measured strain response by LF-DAS. Researchers have demonstrated that LF-DAS can be used to extract the temporal derivative of temperature for use as a differential-temperature-gradient sensor. However, differential-temperature-gradient sensing is predicated on the ability to filter strain components out of the optical signal. In this work, beginning with an equation for optical phase shift of LF-DAS signals, a model relating strain, temperature, and optical phase shift is explicitly developed. The formula provides insights into the relative strength of strain and temperature effects on the phase shift. The uncertainty in the strain-rate measurements due to thermal effects is estimated. The relationship can also be used to quantify uncertainties in differential-temperature-gradient sensors due to strain perturbations. Additionally, a workflow is presented to simulate the LF-DAS response accounting for both strain and temperature effects. Hydraulic fracture geometries are generated with a 3D fracture simulator for a multistage unconventional completion. The fracture width distributions are imported by a displacement discontinuity method (DDM) program to compute the strain rates along an observation well. An analytic model is used to approximate the temperature in the fracture. Using the derived formulae for optical phase shift, the model outputs are then used to compute the LF-DAS response at a fiber-optic cable, enabling the generation of waterfall plots including both strain and thermal effects. The model results suggest that before, during, and immediately following a fracture intersecting a well instrumented with fiber, the strain on the fiber drives the LF-DAS signal. However, at later times, as completion fluid cools the observation well, the temperature component of the LF-DAS signal can be equal to or exceed the strain component. The modeled results are compared to a published field case in an attempt to enhance the interpretation of LF-DAS waterfall plots. Finally, we propose a sensing configuration to identify the events when “wet fractures” (fractures with fluids) intersect the observation well.

Engineering↗
DOE OSTI2013

A 75 MW S-Band Klystron

This program performed computational and preliminary mechanical design for a klystron producing 75 MW at 2.856 GHz using periodic permanent magnet (PPM) focusing. The performance specifications achieved were those for the Matter-Radiation Interactions in the Extremes (MaRIE) project at Los Alamos National Laboratory. The klystron is designed to provide 10 microsecond pulses at 60 Hz with 56 dB gain. The PPM-Focusing eliminates requirements for solenoids and their associated power supplies, cooling systems, interlocks, control and diagnostic instrumentation, and maintenance. The represents a significant in both acquisition and operating costs. It also increases reliability by eliminating many potential failure modes.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

X-Ray Detector Simulations - Oral Presentation

The free-electron laser at LCLS produces X-Rays that are used in several facilities. This light source is so bright and quick that we are capable of producing movies of objects like proteins. But making these movies would not be possible without a device that can detect the X-Rays and produce images. We need X-Ray cameras. The challenges LCLS faces include the X-Rays’ high repetition rate of 120 Hz, short pulses that can reach 200 femto-seconds, and extreme peak brightness. We need detectors that are compatible with this light source, but before they can be used in the facilities, they must first be characterized. My project was to do just that, by making a computer simulation program. My presentation discusses the individual detectors I simulated, the details of my program, and how my project will help determine which detector is most useful for a specific experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

RELAP5-3D Developmental Assessment. Comparison of Version 4.3.4i on Linux and Windows

Figures have been generated comparing the parameters used in the developmental assessment of the RELAP5-3D code, version 4.3i, compiled on Linux and Windows platforms. The figures, which are the same as those used in Volume III of the RELAP5-3D code manual, compare calculations using the semi-implicit solution scheme with available experiment data. These figures provide a quick, visual indication of how the code predictions differ between the Linux and Windows versions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Off-Gas Adsorption Model Capabilities and Recommendations

Off-gas treatment is required to reduce emissions from aqueous fuel reprocessing. Evaluating the products of innovative gas adsorption research requires increased computational simulation capability to more effectively transition from fundamental research to operational design. Early modeling efforts produced the Off-Gas SeParation and REcoverY (OSPREY) model that, while efficient in terms of computation time, was of limited value for complex systems. However, the computational and programming lessons learned in development of the initial model were used to develop Discontinuous Galerkin OSPREY (DGOSPREY), a more effective model. Initial comparisons between OSPREY and DGOSPREY show that, while OSPREY does reasonably well to capture the initial breakthrough time, it displays far too much numerical dispersion to accurately capture the real shape of the breakthrough curves. DGOSPREY is a much better tool as it utilizes a more stable set of numerical methods. In addition, DGOSPREY has shown the capability to capture complex, multispecies adsorption behavior, while OSPREY currently only works for a single adsorbing species. This capability makes DGOSPREY ultimately a more practical tool for real world simulations involving many different gas species. While DGOSPREY has initially performed very well, there is still need for improvement. The current state of DGOSPREY does not include any micro-scale adsorption kinetics and therefore assumes instantaneous adsorption. This is a major source of error in predicting water vapor breakthrough because the kinetics of that adsorption mechanism is particularly slow. However, this deficiency can be remedied by building kinetic kernels into DGOSPREY. Another source of error in DGOSPREY stems from data gaps in single species, such as Kr and Xe, isotherms. Since isotherm data for each gas is currently available at a single temperature, the model is unable to predict adsorption at temperatures outside of the set of data currently available. Thus, in order to improve the predictive capabilities of the model, there is a need for more single-species adsorption isotherms at different temperatures, in addition to extending the model to include adsorption kinetics. This report provides background information about the modeling process and a path forward for further model improvement in terms of accuracy and user interface.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

VERAView User's Guide

VERAView has been developed as an interactive graphical interface for the visualization and engineering analyses of output data from VERA. The python-based software is easy to install and intuitive to use, and provides instantaneous 2D and 3D images, 1D plots, and alpha-numeric data from VERA multi-physics simulations. This document provides a brief overview of the software and some description of the major features of the application, including examples of each of the encapsulated ‘widgets’ that have been implemented thus far. VERAView is still under major development and large changes in the software and this document are still anticipated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Program Fuzzing on High Performance Computing Resources

American Fuzzy Lop (AFL) is an evolutionary fuzzer that is strategically implemented as a tool for discovering bugs in software during vulnerability research. This work seeks to understand how to best implement AFL on the High-Performance Computing resources available on the unclassified network at Sandia National Laboratories. We investigate various methods of executing AFL, requesting varying numbers of tasks on single compute nodes with 36 physical cores and 72 total threads. A Python script called Blue Claw is presented as an automated testbed generator tool to assist in the tedious process of creating and executing experiments of any scale and duration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Probabalistic Modeling of Minibangs and Megabands (Final Report)

This project was original proposed as a fundamental advance in the treatment of probabilistic modeling as it applies to nuclear fission calculations of nuclear database inputs and produced particle distributions in heavy-ion collisions. However, funding decisions made within LLNL and the DOE Office of Science led to the project proceeding through three distinct stages. The first two, probabilistic calculations of the fission and jet energy loss relate follow directly from the proposed research. The fission task led to the development of a proof-of-principle Gaussian Process Emulator for time-dependent generator coordinate method (TDGCM) calculation for the fission of Pu-240. To study energy loss in heavy-ion collisions with a probabilistic model, we generated a training data set using the Pythia event generator superimposed on a heavy-ion background with a single quench-factor parameter. We then used kernel density estimation (KDE) to recover the distribution of quench-factors for a calibration data set. In the third stage, we proceeded to work through collaborations, collecting new data within the ATLAS experiment at the Large Hadron Collider (LHC), and further developing bayesian methodology within the Jet Energy-loss Tomography with a Statistically and Computationally Advanced Program Envelope (JETSCAPE) Collaboration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Multi-Node Program Fuzzing on High Performance Computing Resources

Significant effort is placed on tuning the internal parameters of fuzzers to explore the state space, measured as coverage, of binaries. In this work, we investigate the effects of the external environment on the resulting coverage after fuzzing two binaries with AFL for 24 hours. Parameters such as scaling to multiple nodes, node saturation, and parallel file system type on HPC resources are controlled in order to maximize coverage. It will be shown that employing a parallel file system such as IBM's General Parallel File System offers an advantage for fuzzing operations, since it contains enhancements for performance optimization. When combined with scaling to two and four nodes, while simultaneously restricting the number of coordinated AFL tasks per node on the low end (10-50% of available physical cores), coverage may be enhanced within a shorter period of time. Thus, controlling the external environment is a useful effort.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Density Tailored Capillary Discharge (Final Technical Report)

This final report describes efforts to validate a novel way to drive capillary discharges in order to achieve true matched guiding of a focused laser beam traveling along the capillary. Achieving such matched guiding is important for laser plasma accelerators, such as ones based upon laser wakefield acceleration. During this Phase II program, a computer model, which was specifically designed to predict the time-dependent behavior of the capillary discharge, was exercised to determine whether unconventional ways to drive the discharge may yield matched guiding. A custom power supply was built to drive the capillary discharge in the unconventional manner specified by the model. Experiments performed at STI Optronics seemed to support the predictions of this model; however, subsequent more accurate measurements performed at Lawrence Berkeley National Laboratory did not agree with the model predictions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Sandia Response to 2018 PESP Final Report [Memo]

The 2018 Predictive Engineering Science Panel (PESP) is pleased with Sandia's response to our 2018 PESP Final Report recommendations. We have read the response memorandum, applaud the overall Electromagnetic Radiation (EMR) Action Plan and Path Forward and compliment Sandia's progress to date. The panel identifies no pressing issues and proposes no course corrections. The panel does offer two high-level suggestions for the Advanced Simulation and Computing (ASC) Program Office.

42 ENGINEERING↗
DOE OSTI2023

Recent progress towards incorporating radiochemical analysis in LANL ASC codes

This document summarizes the recent progress towards incorporating charged-particle radiochemical (RadChem) analysis in different LANL codes within the Advanced Scientific Computing (ASC) Program. The first section is focused on xRAGE and the implementation of the necessary physics packages to build an in-line RadChem capability. The second section provides a summary of the current RadChem postprocessing capabilities.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗