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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

TXM-Sandbox : an open-source software for transmission X-ray microscopy data analysis

A transmission X-ray microscope (TXM) can investigate morphological and chemical information of a tens to hundred micrometre-thick specimen on a length scale of tens to hundreds of nanometres. It has broad applications in material sciences and battery research. TXM data processing is composed of multiple steps. A workflow software has been developed that integrates all the tools required for general TXM data processing and visualization. The software is written in Python and has a graphic user interface in Jupyter Notebook . Users have access to the intermediate analysis results within Jupyter Notebook and have options to insert extra data processing steps in addition to those that are integrated in the software. The software seamlessly integrates ImageJ as its primary image viewer, providing rich image visualization and processing routines. As a guide for users, several TXM specific data analysis issues and examples are also presented.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Data Center Facility Monitoring with Physics Aware Approach

U.S. Department of Energy's National Renewable Energy Laboratory (NREL) hosts one of the world's most energy-efficient HPC data centers; this system uses component-level warm-water liquid cooling to efficiently remove heat from the data center and capture it for reuse in the building or rejection to the atmosphere. Given the complexity of this system, building data-driven tools for holistically monitoring and operating the entire data center is a priority for ensuring maximal efficiency and resiliency. In this advanced smart facility, over one million metrics are recorded per minute using state-of-the-art streaming data architecture and software to capture and process the state of the system in real time. Here we detail two efforts to effectively analyze, visualize, and interpret this large volume streaming data. We have developed a novel, flexible system for identifying and visualizing individual metric anomalies and component performance across the data center through automatic metadata extraction and physically-motivated visualization for quick interpretation. Additionally, to directly connect system maintenance to data stream processing we explore a physics informed multi-metric drift and anomaly detection application to detect scale-build up in heat exchangers.

anomaly detection↗
DOE OSTI2024

Portable Acceleration of CMS Computing Workflows with Coprocessors as a Service

Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Hybrid metal additive/subtractive machine tools and applications

Additive manufacturing creates parts by depositing a preform, typically layer by layer. Subtractive manufacturing involves removing material from a preform to create parts. Hybrid machine tools combine both additive and subtractive processes in the same workspace. They can be used to create parts that meet functional tolerance and surface finish requirements, or to create features that are difficult to produce using additive or subtractive processes alone. Here, this paper describes hybrid metal additive/subtractive machine tools. It covers design considerations, sensors and controls, process management, programming and software, and the impact on the design space. It also identifies future research challenges.

42 ENGINEERING↗
DOE OSTI2024

Laue-DIALS: Open-source software for polychromatic x-ray diffraction data

Most x-ray sources are inherently polychromatic. Polychromatic (“pink”) x-rays provide an efficient way to conduct diffraction experiments as many more photons can be used and large regions of reciprocal space can be probed without sample rotation during exposure—ideal conditions for time-resolved applications. Analysis of such data is complicated, however, causing most x-ray facilities to discard >99% of x-ray photons to obtain monochromatic data. Key challenges in analyzing polychromatic diffraction data include lattice searching, indexing and wavelength assignment, correction of measured intensities for wavelength-dependent effects, and deconvolution of harmonics. We recently described an algorithm, Careless, that can perform harmonic deconvolution and correct measured intensities for variation in wavelength when presented with integrated diffraction intensities and assigned wavelengths. Here, we present Laue-DIALS, an open-source software pipeline that indexes and integrates polychromatic diffraction data. Laue-DIALS is based on the dxtbx toolbox, which supports the DIALS software commonly used to process monochromatic data. As such, Laue-DIALS provides many of the same advantages: an open-source, modular, and extensible architecture, providing a robust basis for future development. We present benchmark results showing that Laue-DIALS, together with Careless, provides a suitable approach to the analysis of polychromatic diffraction data, including for time-resolved applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A science-driven approach to optimize the design for a biological small-angle neutron scattering instrument

Biological small-angle neutron scattering (SANS) instruments facilitate critical analysis of the structure and dynamics of complex biological systems. However, with the growth of experimental demands and the advances in optical systems design, a new neutron optical concept is necessary to overcome the limitations of current instruments. This work presents an approach to include experimental objectives ( i.e. the science to be supported by a specific neutron scattering instrument) in the optimization of the neutron optical concept. The approach for a proposed SANS instrument at the Second Target Station of the Spallation Neutron Source at Oak Ridge National Laboratory, USA, is presented here. Further, the instrument is simulated with the McStas software package. The optimization process is driven by an evolutionary algorithm using McStas output data, which are processed to calculate an objective function designed to quantify the expected performance of the simulated neutron optical configuration for the intended purpose. Each McStas simulation covers the complete instrument, from source to detector, including realistic sample scattering functions. This approach effectively navigates a high-dimensional parameter space that is otherwise intractable; it allows the design of next-generation SANS instruments to address specific scientific cases and has the potential to increase instrument performance compared with traditional design approaches.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Signal Processing Based Method for Real-Time Anomaly Detection in High-Performance Computing

Performance anomalies can manifest as irregular execution times or abnormal execution events for many reasons, including network congestion and resource contention. Detecting such anomalies in real-time by analyzing the details of performance traces at scale is impractical due to the sheer volume of data High-Performance Computing (HPC) applications produce. In this paper, we propose formulating HPC performance anomaly detection as a signal-processing problem where anomalies can be treated as noise. We evaluate our proposed method in comparison with two other commonly used anomaly detection techniques of varying complexity based on their detection accuracy and scalability. Since real-time in-situ anomaly detection at a large scale requires lightweight methods that can handle a large volume of streaming data, we find that our proposed method provides the best trade-off. We then implement the proposed method in Chimbuko, the first online, distributed, and scalable workflow-level performance trace analysis framework. We compare our proposed signal-based anomaly detection algorithm with two other methods using a function of their accuracy, F1 score, and detection overhead. Our experiments demonstrate that our proposed approach achieves a 99% improvement for the benchmark datasets and a 93% improvement with Chimbuko traces.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Building and Sustaining a Community Resource for Best Practices in Scientific Software: The Story of BSSw.io

The development of scientific software—a cornerstone of long-term collaboration and scientific progress—parallels the development of other types of software but still poses distinct challenges, especially in high-performance computing. Although web searches yield numerous resources on software engineering, there is still a scarcity specifically for scientific software development. Here, this article introduces the Better Scientific Software site (https://bssw.io), a platform that hosts a community of researchers, developers, and practitioners who share their experiences and insights on scientific software development. Since 2017, this collaborative hub has gained traction within the scientific computing community, attracting a growing number of readers and contributors eager to share ideas and elevate their software development practices. In sharing the BSSw.io site’s story, we hope to encourage further growth of the BSSw.io community through both readership and contributors, with a long-term goal of fostering culture change by increasing emphasis on best practices in scientific software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

HighIQ

This software is for the processing of raw IQ data from radars and lidars that uses CUDA-compatible GPUs such as those in the Array of Things.

Jackson, RobertClyde↗
DOE OSTI2021

Models for synthetic data generation

The software includes a suite of probabilistic statistical/machine learning models that can generate discrete synthetic data. Each model is trained on a set of real (private) data and then it can be used to generate synthetic but statistically similar data. Once ready, the model can generate as many samples as we want. Finally, in addition to the actual models, the software includes code to process data, evaluate results (based on cross validation), and produce reports.

De Oliveira Sales, Ana Paula↗
DOE OSTI2022

EMSL-Computing/CoreMS-Portal

Software that orchestrate data processing and management for mass spectrometry workflows and data products. Stack presented contains a web application, data processing job scheduling, and data processing workers for data processing and management.

Corilo, Yuri↗
DOE OSTI2025

GenomeFace v1.0

GenomeFace is meta-genome binning software. Metagenomic binning, the process of grouping DNA sequences into taxonomic units, is critical for understanding the functions, interactions, and evolutionary dynamics of microbial communities. We propose a deep learning approach to binning using two neural networks, one based on composition and another on environmental abundance, dynamically weighting the contribution of each based on characteristics of the input data. Trained on over 43,000 prokaryotic genomes, our network for composition-based binning is inspired by metric learning techniques used for facial recognition. Using a task-specific, multi-GPU accelerated algorithm to cluster the embeddings produced by our network, our binner leverages marker genes observed to be universally present in nearly all taxa to grade and select optimal clusters of sequences from a hierarchy of candidates. We evaluate our approach on four simulated datasets with known ground truth. Our linear time integration of marker genes recovers more near complete genomes than state of the art but computationally infeasible solutions using them, while being over an order of magnitude faster. Finally, we demonstrate the scalability and acuity of our approach by testing it on three of the largest metagenome assemblies ever performed. Compared to other binners, we produced 47%-183% more near complete genomes. From these datasets, we find over the genomes of over 3000 new candidate species which have never been previously cataloged, representing a potential 4% expansion of the known bacterial tree of life.

Lettich, Richard [Lawrence Berkeley National Labor↗
DOE OSTI2026

Coupling of high-resolution mass spectrometer and photosynthesis system for comprehensive leaf volatile metabolite profiling

Background Leaf-level biogenic volatile organic compounds (BVOCs) emissions represent a major source of organic gases in the atmosphere, influencing both climate and air quality. These emissions are strongly driven by environmental perturbations, which affect individual plant- to ecosystem-level processes. Uncovering all the BVOCs and understanding how their emissions respond to altered environmental conditions provide critical insights into vegetation-driven changes in atmospheric chemistry. We developed a tandem instrumentation setup that integrates a proton transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS) with parts-per-trillion detection limits and a photosynthetic infrared gas exchange system for the untargeted survey of all the BVOCs. This novel system enables simultaneous, real-time monitoring of BVOC emissions and photosynthetic parameters at the leaf level, offering new opportunities to disentangle the physiological and environmental drivers of VOC release. Furthermore, we established the VOC Analysis and Processing Optimization Resource (VAPOR), an open-access software tool designed for rapid data post-processing and the analysis of the variability of hundreds of BVOCs. We assessed the performance of the tandem system under varying background conditions, using standard gas mixtures and a range of environmental factors. Results Blank emissions were substantially lower for major BVOCs (e.g., isoprene) compared to those observed in plant emissions. Despite this, the observation of background-level VOCs highlights the importance of routinely acquiring and accounting for blank measurements in analyses using the coupled instrumentation. Introduction of known VOC concentrations to the system demonstrated a linear response across different compounds with varying molecular compositions, indicating minimal gas loss regardless of chemical moieties within the coupled instrumentation. We applied the optimized system to investigate the physiological mechanisms driving BVOC emissions across different genotypes of poplar and pennycress. The high mass resolution capabilities of the PTR-ToF-MS, coupled with comprehensive VAPOR-driven data analysis, enabled the identification of several important BVOCs, including methanol and methanethiol; these BVOCs displayed substantial variation across pennycress genotypes and showed concentrations ~ 100–350% higher than the blank. Moreover, isoprene emissions varied significantly among poplar genotypes grown in different potting media. Conclusions Tandem instrumentation offers a powerful tool for profiling volatile molecular markers and elucidating their genetic and environmental underpinnings. This approach enhances our ability to predict BVOC emissions in response to genotype by environmental interactions and contributes to a deeper understanding of vegetation responses to environmental changes.

Biogenic volatile organic compounds↗
DOE OSTI2023

MASK4 Test Campaign for Sandia WaveBot Device

This data and report details the findings from a wave tank test focused on production of useful work of a wave energy converter (WEC) device. The experimental system and test were specifically designed to validate models for power transmission throughout the WEC system. Additionally, the validity of co-design informed changes to the power take-off (PTO) were assessed and shown to provide the expected improvements in system performance. These data describe the "MASK4" wave tank test of the Sandia WaveBot device. The WaveBot device has been tested a number of times in different permutations at the US Navy's Maneuvering and Sea Keeping (MASK) basin. Each test in this series is referred to as MASK1, MASK2, etc. The WaveBot device was first tested in one degree of freedom (heave) in 2016. This MASK1 test focused primarily on system identification and modeling. After MASK1, major modifications were performed to improve the overall real-time control and measurement system, improve the heave drive train, and add surge and pitch degrees of freedom. The second set of testing, which was broken up in to two stages: MASK2A and MASK2B, focused on bench testing and closed-loop control performance as well as nonlinear modeling. MASK3 then focused on multi-input, multi-output modeling and control for maximization of electrical power. The attached report presents the results from MASK4, which focuses on detailed modeling of the power conversion chain and validation co-design principles by way of the introduction of a magnetic spring. The test log, report, and data from the MASK4 test of the WaveBot augmented with a tunable magnetic spring. Processing codes can be found at the Github link below.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Coupling between interfacial charge and mechanical deformation at high temperatures in ceramics. Final report

Basic research, under this project, has led to new fundamental discoveries in the effect of electric field (and temperature) on diffusion kinetics, electroluminescence and electronic conductivity in ceramic materials. For example, yttria stabilized zirconia sinters in just seconds well below 1000°C, while, at the same time, exhibiting a highly non-linear rise in conductivity, and intense electroluminescence. The phenomenon has been shown to occur in nearly all ceramics whether they are ionic or electronic conductors, or insulators. The rise in conductivity leads to Joule heating but in-situ measurements with a platinum standard at APS and Brookhaven (NSLS-II) have shown that the temperatures are much below what would have been needed to sinter in a few seconds. We have explored the hypothesis that huge concentrations of Frenkel pairs of vacancies and interstitials are produced. While these point defects accelerate sintering (by the interstitials being transported to the pores and the vacancies to the grain boundaries), they may also produce electron-hole pairs which can impart high electrical conductivity or recombine to emit photons. Many measurements, including in-situ measurements of lattice expansion are consistent with this hypothesis. However, the energy barrier for generating Frenkels in zirconia for example is much larger than can be expected at temperature and electrical fields in these experiments. Most recent work suggests that short wavelength phonons play a critical role in the genesis of the “flash” phenomenon. For example, the Debye temperature has been shown to be the lower bound for initiating flash. Molecular dynamics simulations have shown that large concentrations of Frenkel pairs can form under the proliferation of “optical” phonons at the edge of the Brillouin zone, that is with a wavelength at or below the lattice parameter. This project has led to the development of new experimental techniques as well as a software hardware interface for process and control and data analysis in real time, with a time scale of less than one second. This approach spells a new paradigm in materials science research. It potential impact on high rate manufacturing is self evident.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Sandia GNU Radio Utilities

The Sandia Utilities form an RF toolkit extending the GNU Radio framework for straightforward interaction with bursty RF systems which can be cumbersome using built in capabilities of the framework or other open source extensions. Motivated by the abstract exercise of responding to a modulated burst of information with a unique modulated burst of information, the Sandia Utilities provide several dozen additional debug and signal processing blocks through four software modules. These blocks manifest their utility through a new general concept of operation for GNU Radio applications and extend many existing streaming capabilities to the PDU-based message passing API. Using these concepts and tools, it is straightforward to develop software capabilities to interact with existing and new bursty RF devices.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Improvements to the New CTH Code Verification & Validation Test Suite (FY2020)

The CTH multiphysics hydrocode, which is used for a wide range of important calculations, has undertaken in recent years to overhaul its software quality and testing processes. A key part of this effort entailed building a new, robust V&V test suite made up of traditional hydrocode verification problems, such as those listed in the ASC Tri-Lab Test Suite and the Enhanced Tri-Lab Test Suite, as well as validation problems for some of CTHs most frequently used equations of state, materials models, and other key capabilities. Substantial progress towards this goal was made in FY19. In FY20, this test suite has been expanded to include verification and validation tests of the Sesame and JWL equation of state models as well as the Mader verification problem from the Tri-Lab Test Suite and the Blake verification problem - a linear elastic analog to the Hunter problem from the Enhanced Tri-Lab Test Suite. This report documents CTH performance on the new test suite problems. Verification test results are compared to analytic solutions and, for most tests, convergence results are presented. Validation test results are compared to experimental data and mesh refinement studies are included. CTH performs well overall on the new test problems. Convergence rates for the Blake and Mader problems are comparable to those for similar ASC codes. The JWL and Sesame verification tests show good agreement with analytic solutions. Likewise, CTH simulation results show good agreement with experimental validation data for the Sesame and JWL equations of state for the materials tested. Future V&V work will focus on adding tests for other key capabilities like fracture and high explosive models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Discrete-event Simulation Process Model for the Pyrochemical Processing of Plutonium at Los Alamos National Laboratory

The pyrochemical metal production operations that occur in the Plutonium Facility at Los Alamos National Laboratory perform plutonium purification with the aim to provide plutonium metal for a variety of defense- and non-defense missions within the National Nuclear Security Administration. The demands and constraints associated with the pyrochemical processing of plutonium are complex, making decision analyses challenging for program managers who require plutonium production for their mission applications. The construction of a discrete-event simulation process model is proposed to measure and report the process capacity, material throughput, equipment requirements, and dose accumulation for operators of the pyrochemical metal production operations. The process model, constructed in the ExtendSim™ software, will represent the cause-and-effect relationships between the pyrochemical processing environment and the process constraints, including criticality limitations, material control and accountability measures, chemical analysis requirements, and equipment availability. An accurate representation of the pyrochemical metal production process capacity through simulation modeling will be helpful to program managers in their efforts to forecast plutonium availability for mission applications. Furthermore, the proposed process model will be vital for future analyses that will measure the interactions between the pyrochemical metal production operations and the aqueous reprocessing operations and their ability to minimize transuranic waste disposal.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗