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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 1,315 records · Page 73

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NASA NTRS1990

QUEST/Ada (Query Utility Environment for Software Testing of Ada): The development of a prgram analysis environment for Ada, task 1, phase 2

The results of research and development efforts are described for Task one, Phase two of a general project entitled The Development of a Program Analysis Environment for Ada. The scope of this task includes the design and development of a prototype system for testing Ada software modules at the unit level. The system is called Query Utility Environment for Software Testing of Ada (QUEST/Ada). The prototype for condition coverage provides a platform that implements expert system interaction with program testing. The expert system can modify data in the instrument source code in order to achieve coverage goals. Given this initial prototype, it is possible to evaluate the rule base in order to develop improved rules for test case generation. The goals of Phase two are the following: (1) to continue to develop and improve the current user interface to support the other goals of this research effort (i.e., those related to improved testing efficiency and increased code reliable); (2) to develop and empirically evaluate a succession of alternative rule bases for the test case generator such that the expert system achieves coverage in a more efficient manner; and (3) to extend the concepts of the current test environment to address the issues of Ada concurrency.

Brown, David B.↗

NASA NTRS2002

Goddard's New Data Analysis System

After evaluating the total lifetime costs of various commercial systems, it was determined that an in-house development would be more cost-effective in the long run. Matlab was chosen as the development platform, since it is now being taught to most engineering students. The presentation will discuss the specifications of the system.

Worth, Daniel B.↗

DOE OSTI2020

NREL's Advanced Distribution Management System (ADMS) Test Bed

NREL's advanced distribution management system (ADMS) test bed is a vendor-neutral resource for evaluating existing and future ADMS functionalities in a realistic laboratory setting. The test bed uses Opal-RT's ePHASORsim and eMEGAsim products interfaced with an OpenDSS power system simulation through the HELICS cosimulation platform developed by multiple DOE laboratories; and with power and controller hardware. NREL will present an overview of the test bed and the technologies included within it, and also some examples of how the test bed has been used to address industry challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Electrochemical Routes for the Valorization of Biomass-Derived Feedstocks: From Chemistry to Application

The drive to reduce consumption of fossil resources, coupled with expanding capacity for renewable electricity, invites the exploration of new routes to utilize this energy for the sustainable production of fuels, chemicals, and materials. Biomass represents a possible source of platform precursors for such commodities due to its inherent ability to fix CO2 in the form of multi-carbon organic molecules. Electrochemical methods for the valorization of biomass are thus intriguing, but there is a need to objectively evaluate this field and define the opportunity space by identifying pathways suited to electrochemistry. In this contribution we offer a comprehensive, critical review of recent advances in low-temperature (liquid phase), electrochemical reduction and oxidation of biomass-derived intermediates (polyols, furans, carboxylic acids, amino acids, and lignin), with emphasis on identifying the state-of-the-art for each documented reaction. Progress in computational modeling is also reviewed. We further suggest a number of possible reactions that have not yet been explored but which are expected to proceed based on established routes to transform specific functional groups. We conclude with a critical discussion of technological challenges for scale-up, fundamental research needs, process intensification opportunities (e.g., by pairing compatible oxidations and reductions), and new benchmarking standards that will be necessary to accelerate progress toward application in this still-nascent field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1990

Airborne/spaceborne radar - Panel report

Mobile radar platforms can provide unique observations of geophysical phenomena for scientific research and for operational applications such as reconnaissance and flight safety. Airborne or spaceborne radar can provide: (1) observations where it is often impractical or too costly to place a ground-based radar, (2) surveillance over a large area or over a long time period when the system of interest is moving, (3) the ability to adjust viewing angles to minimize uncertainties due to viewing geometry, for example, along a dual-Doppler baseline, (4) measurements to complement coincident observations from other remote and in situ sensors, and (5) evaluation of ground surface properties and their impact on the evolution of the boundary-layer and their role in storm systems, hydrology, and earth surface radiation balance. However, advances in signal processing, antenna design, power amplifiers, and other critical system components will be required if radar measurements from airborne and spaceborne platforms are to become a reality.

Jorgensen, David P.↗

DOE OSTI2016

First evaluation of the feasibility of MLC tracking using ultrasound motion estimation

Purpose: To quantify the performance of the Clarity ultrasound (US) imaging system (Elekta AB, Stockholm, Sweden) for real-time dynamic multileaf collimator (MLC) tracking. Methods: The Clarity calibration and quality assurance phantom was mounted on a motion platform moving with a periodic sine wave trajectory. The detected position of a 30 mm hypoechogenic sphere within the phantom was continuously reported via Clarity’s real-time streaming interface to an in-house tracking and delivery software and subsequently used to adapt the MLC aperture. A portal imager measured MV treatment field/MLC apertures and motion platform positions throughout each experiment to independently quantify system latency and geometric error. Based on the measured range of latency values, a prostate stereotactic body radiation therapy (SBRT) delivery was performed with three realistic motion trajectories. The dosimetric impact of system latency on MLC tracking was directly measured using a 3D dosimeter mounted on the motion platform. Results: For 2D US imaging, the overall system latency, including all delay times from the imaging and delivery chain, ranged from 392 to 424 ms depending on the lateral sector size. For 3D US imaging, the latency ranged from 566 to 1031 ms depending on the elevational sweep. The latency-corrected geometric root-mean squared error was below 0.75 mm (2D US) and below 1.75 mm (3D US). For the prostate SBRT delivery, the impact of a range of system latencies (400–1000 ms) on the MLC tracking performance was minimal in terms of gamma failure rate. Conclusions: Real-time MLC tracking based on a noninvasive US input is technologically feasible. Current system latencies are higher than those for x-ray imaging systems, but US can provide full volumetric image data and the impact of system latency was measured to be small for a prostate SBRT case when using a US-like motion input.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

A Cybersecurity Event Simulation Tool and Platform

Digital Instrumentation and Control Systems (ICSs) have replaced analog control systems in nuclear power plants raising cybersecurity concerns. To study and understand the cybersecurity risks of nuclear power plants both high fidelity models of the plant physics and controllers must be created, and a framework to test and evaluate cyber security events must be established. A testing and evaluation framework of cybersecurity events consists of a method of interfering with control systems, a simulation of the plant network, and a network packet capture and recording tool. Sandia National Labs (SNL) in collaboration with the University of New Mexico’s Institute for Space and Nuclear Power Studies (UNM-ISNPS) is developing such a cybersecurity testing framework.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

High resolution mobility spectrometry in a co-axial platform

Ion mobility spectrometry is an analytical technique that separate ions in the gas phase based on their interaction with a neutral buffer gas. Ion mobility spectrometry performs separations quickly (typically less than a second) and the ion mobilities are very reproducible across different laboratories. This project aimed at evaluating the performance of a new ion mobility device. The new device relies on conducting ion mobility separation in a curved geometry. The project explored the operation landscape of the device using ion trajectory simulations then fabricated and experimentally demonstrated the device's performance. Ion trajectory simulations on a set of tetraalkylammonium and phosphazene ions indicate that ions traveling a curved path length undergo mobility separation that is similar to a straight path. The ion mobility resolution of the curved device was found to be similar to that of a straight path of a similar length. The experimental validation of the new device confirmed the device's ability to separate ions according to their mobilities. Sets of mixtures (tetraalkylammonium ions, phosphazene ions, and peptide ions) were evaluated for separation and transmission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Captan+X Data Converter Integration

Fermi National Accelerator Laboratory's CAPTAN (Compact And Programmable daTa Acquisition Node) series provides a flexible hardware platform for data acquisition across a range of experiments and facilities. The latest iteration, CAPTAN+X, is built around a Kintex-7 FPGA supporting four FPGA Mezzanine Card (FMC) connections. As part of a broader laboratory effort to bring facility systems under a Model-Based Systems Engineering (MBSE) framework, CAPTAN+X is one of several systems slated to be incorporated into this modeling environment in the near term. A necessary step toward that goal is incorporating the platform's core functionality, which centers on integration with the LXD31K4 FMC, a data converter module combining dual AD9652 analog-to-digital converters and dual AD9142A digital-to-analog converters. Achieving compatibility required resolving pin-mapping conflicts between the LXD31K4's High Pin Count connector and the CAPTAN+X's available pin types, adapting a Board Support Project originally written for an UltraScale-class evaluation board to the Kintex-7 architecture, replacing incompatible primitives, restructuring clock distribution, and manually configuring chip initialization in place of an unsupported soft-processor-based approach. Functional verification of the ADC and DAC channels, followed by closed-loop testing combining both converters with real-time filtering, confirmed correct operation of the integrated system. These results establish a working hardware and firmware baseline for the CAPTAN+X platform, positioning it for future inclusion in the laboratory's growing MBSE modeling effort.

Espinoza, David [Illinois U., Urbana (main)]↗

DOE OSTI2026

CAPTAN+X Data Converter Integration

Espinoza, David [Illinois U., Urbana (main)]↗

DOE OSTI2020

Experiences in porting mini-applications to OpenACC and OpenMP on heterogeneous systems

This article studies mini-applications—Minisweep, GenASiS , GPP, and FF—that use computational methods commonly encountered in HPC. We have ported these applications to develop OpenACC and OpenMP versions, and evaluated their performance on Titan (Cray XK7 with K20x GPUs), Cori (Cray XC40 with Intel KNL), Summit (IBM AC922 with Volta GPUs), and Cori-GPU (Cray CS-Storm 500NX with Intel Skylake and Volta GPUs). Our goals are for these new ports to be useful to both application and compiler developers, to document and describe the lessons learned and the methodology to create optimized OpenMP and OpenACC versions, and to provide a description of possible migration paths between the two specifications. Cases where specific directives or code patterns result in improved performance for a given architecture are highlighted. Here, we also include discussions of the functionality and maturity of the latest compilers available on the above platforms with respect to OpenACC or OpenMP implementations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

OpenMSI Arrayed Analysis Toolkit: Analyzing Spatially Defined Samples Using Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) has primarily been applied in localizing biomolecules within biological matrices. Although well-suited, the application of MSI for comparing thousands of spatially defined spotted samples has been limited. One reason for this is a lack of suitable and accessible data processing tools for the analysis of large arrayed MSI sample sets. In this paper, the OpenMSI Arrayed Analysis Toolkit (OMAAT) is a software package that addresses the challenges of analyzing spatially defined samples in MSI data sets. OMAAT is written in Python and is integrated with OpenMSI (http://openmsi.nersc.gov), a platform for storing, sharing, and analyzing MSI data. By using a web-based python notebook (Jupyter), OMAAT is accessible to anyone without programming experience yet allows experienced users to leverage all features. OMAAT was evaluated by analyzing an MSI data set of a high-throughput glycoside hydrolase activity screen comprising 384 samples arrayed onto a NIMS surface at a 450 μm spacing, decreasing analysis time >100-fold while maintaining robust spot-finding. The utility of OMAAT was demonstrated for screening metabolic activities of different sized soil particles, including hydrolysis of sugars, revealing a pattern of size dependent activities. Finally, these results introduce OMAAT as an effective toolkit for analyzing spatially defined samples in MSI. OMAAT runs on all major operating systems, and the source code can be obtained from the following GitHub repository: https://github.com/biorack/omaat.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Predicting Elastic Properties of Materials from Electronic Charge Density Using 3D Deep Convolutional Neural Networks

Materials representation plays a key role in machine learning-based prediction of materials properties and new materials discovery. Currently both graph and three-dimensional (3D) voxel representation methods are based on the heterogeneous elements of the crystal structures. Here, we propose to use electronic charge density (ECD) as a generic unified 3D descriptor for materials property prediction with the advantage of possessing close relation with the physical and chemical properties of materials. We developed an ECD-based 3D convolutional neural networks (CNNs) for predicting the elastic properties of materials, in which CNNs can learn effective hierarchical features with multiple convolving and pooling operations. Extensive benchmark experiments over 2170 $Fm\bar3m$ face-centered-cubic materials show that our ECD-based CNNs can achieve good performance for elasticity prediction. Especially, our CNN models based on the fusion of elemental Materials-Agnostic Platform for Informatics and Exploration features and ECD descriptors achieved the best fivefold cross-validation performance. More importantly, we showed that our ECD-based CNN models can achieve significantly better extrapolation performance when evaluated over nonredundant data sets, where there are few neighbor-training samples around test samples. As an additional validation, we evaluated the predictive performance of our models on 329 materials of space group $Fm\bar3m$ by comparing to density functional theory calculated values, which shows a better prediction power of our model for bulk modulus than shear modulus. Because of the unified representation power of ECD, it is expected that our ECD-based CNN approach can also be applied to predict other physical and chemical properties of crystalline materials.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Toward machine-learning-assisted PW-class high-repetition-rate experiments with solid targets

We present progress in utilizing a machine learning (ML) assisted optimization framework to study the trends in a parameter space defined by spectrally shaped, high-intensity, petawatt-class (8 J, 45 fs) laser pulses interacting with solid targets and give the first simulation-based overview of predicted trends. A neural network (NN) incorporating uncertainty quantification is trained to predict the number of hot electrons generated by the laser–target interaction as a function of pulse shaping parameters. The predictions of this NN serve as the basis function for a Bayesian optimization framework to navigate this space. For post-experimental evaluation, we compare two separate neural network (NN) models. One is based solely on data from experiments, and the other is trained only on ensemble particle-in-cell simulations. Reviewing the predicted and observed trends across the experiment-capable laser parameter search space, we find that both ML models predict a maximal increase in hot electron generation at a level of approximately 12%–18%; however, no statistically significant enhancement was observed in experiments. On direct comparison of the NN models, the average discrepancy is 8.5%, with a maximum of 30%. Since shot-to-shot fluctuations in experiments affect the observations, we evaluate the behavior of our optimization framework by performing virtual experiments that vary the number of repeated observations and the noise levels. Here, we discuss the implications of such a framework for future autonomous exploration platforms in high-repetition-rate experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2016

SU-G-JeP4-01: An Assessment of a Microsoft Kinect V2 Sensor for Voluntary Breath-Hold Monitoring in Radiotherapy

Purpose: To determine whether the Microsoft Kinect Version 2 (Kinect v2), a commercial off-the-shelf (COTS) depth sensors designed for entertainment purposes, were robust to the radiotherapy treatment environment and could be suitable for monitoring of voluntary breath-hold compliance. This could complement current visual monitoring techniques, and be useful for heart sparing left breast radiotherapy. Methods: In-house software to control Kinect v2 sensors, and capture output information, was developed using the free Microsoft software development kit, and the Cinder creative coding C++ library. Each sensor was used with a 12m USB 3.0 active cable. A solid water block was used as the object. The depth accuracy and precision of the sensors was evaluated by comparing Kinect reported distance to the object with a precision laser measurement across a distance range of 0.6m to 2.0 m. The object was positioned on a high-precision programmable motion platform and moved in two programmed motion patterns and Kinect reported distance logged. Robustness to the radiation environment was tested by repeating all measurements with a linear accelerator operating over a range of pulse repetition frequencies (6Hz to 400Hz) and dose rates 50 to 1500 monitor units (MU) per minute. Results: The complex, consistent relationship between true and measured distance was unaffected by the radiation environment, as was the ability to detect motion. Sensor precision was < 1 mm and the accuracy between 1.3 mm and 1.8 mm when a distance correction was applied. Both motion patterns were tracked successfully with a root mean squared error (RMSE) of 1.4 and 1.1 mm respectively. Conclusion: Kinect v2 sensors are capable of tracking pre-programmed motion patterns with an accuracy <2 mm and appear robust to the radiotherapy treatment environment. A clinical trial using Kinect v2 sensor for monitoring voluntary breath hold has ethical approval and is open to recruitment. The authors are supported by a National Institute of Health Research (NIHR) Career Development Fellowship (CDF-2013-06-005). Microsoft Corporation donated three sensors. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Advancement of Certification Methods and Applications for Industrial Deployments of Components Derived from Advanced Manufacturing Technologies

One goal of the Advanced Materials and Manufacturing Technologies subprogram, within the Department of Energy’s (DOE) crosscutting technology development program, is to advance the qualification and certification of parts and components created via additive manufacturing (AM). AM offers a new paradigm for the design and optimization of new nuclear components, and for observing and tracking manufacturing performance and potential defects in a way that is not possible with traditional approaches. Tracking and evaluating these in situ data can lead to the estimation of local material properties and, with the use of engineering analysis tools, the estimation of component performance during operation. To achieve these objectives, a digital platform certification approach was developed and is summarized in this report.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Flexible AI Models for Grid Resilience

The rapid growth in size and complexity of artificial intelligence (AI) and machine learning (ML) models has led to increased energy demands, posing a threat to the reliability of the existing power grid. This project addresses the challenge of highly intermittent and energy-intensive inference workloads by (1) developing fidelity-adaptive neural networks capable of dynamic response to grid conditions and (2) integrating these networks with power flow simulations to assess their impact on power grid reliability. We will explore both top-down and bottom-up approaches to create hierarchies of submodels that provide a controlled trade-off between power draw and prediction accuracy. The top-down method utilizes NN pruning to reduce a flagship model into progressively smaller, energy-efficient variants. The bottom-up approach employs geometrically principled weight setting strategies to construct depth-efficient models from the ground up. A real-time hardware-in-the-loop (HIL) platform will be developed to simulate a scaled AC power grid, integrating live AI workload power draw and enabling dynamic model switching in response to grid feedback. This work will provide a novel framework for evaluating the impact of flexible AI/ML workloads on grid performance and establish new methodologies for energy-aware computing in data centers. The outcomes will demonstrate that adaptive AI/ML can play a critical role in improving grid stability while advancing NREL's leadership in energy-efficient computing research.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1977

Experimental program for the operational study of data collection platforms in Bolivia

The system developed for the SMS/GOES satellite while learning the limitations possessed by this system with regard to the LANDSAT 1 and 2 satellites with respect to the transmission distance and horizon angle is investigated. The advantages possessed by this system in comparison with conventional methods are evaluated so as to permit studying the feasibility of introducing it into this country in the near future.

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