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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Automatic detection of low surface brightness galaxies from Sloan Digital Sky Survey images

ABSTRACT Low surface brightness (LSB) galaxies are galaxies with central surface brightness fainter than the night sky. Due to the faint nature of LSB galaxies and the comparable sky background, it is difficult to search LSB galaxies automatically and efficiently from large sky survey. In this study, we established the low surface brightness galaxies autodetect (LSBG-AD) model, which is a data-driven model for end-to-end detection of LSB galaxies from Sloan Digital Sky Survey (SDSS) images. Object-detection techniques based on deep learning are applied to the SDSS field images to identify LSB galaxies and estimate their coordinates at the same time. Applying LSBG-AD to 1120 SDSS images, we detected 1197 LSB galaxy candidates, of which 1081 samples are already known and 116 samples are newly found candidates. The B-band central surface brightness of the candidates searched by the model ranges from 22 to 24 mag arcsec−2, quite consistent with the surface brightness distribution of the standard sample. A total of 96.46 per cent of LSB galaxy candidates have an axial ratio (b/a) greater than 0.3, and 92.04 per cent of them have $fracDev\_r$ < 0.4, which is also consistent with the standard sample. The results show that the LSBG-AD model learns the features of LSB galaxies of the training samples well, and can be used to search LSB galaxies without using photometric parameters. Next, this method will be used to develop efficient algorithms to detect LSB galaxies from massive images of the next-generation observatories.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Comparison of maximal Rubidium-82 activities for myocardial blood flow quantification between digital and conventional PET systems

Background: PET-based myocardial blood flow (MBF) quantification can be inaccurate when using high tracer activities. Our aim was to derive the maximal Rubidium-82 activity for MBF assessment using a new digital PET system and compare the results with conventional analog systems. Methods: 1.8 GBq Rubidium-82 was injected into the cardiac insert of an anthropomorphic torso phantom. Data were acquired for 10 min using an Ingenuity TF (Philips Healthcare), Discovery 690 (D690, GE Healthcare), and digital PET prototype system (Philips Healthcare). The dynamic ranges, defined as the maximal measured activity in the reconstructed images deviating < 10% from the true present activity, were determined in all scans. Results: The dynamic ranges were 312 MBq for Ingenuity TF, 650 MBq for D690, and 654 MBq for digital PET prototype. Conclusions: The maximal Rb-82 activity for MBF assessment using digital PET prototype is higher than that for its analog counterpart (Ingenuity TF), but seems comparable to the D690.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Analog-to-digital converter based on voltage-controlled superconducting devices

The increasing demand for cryogenic electronics in superconducting and quantum computing systems calls for ultra-energy-efficient data conversion architectures that remain functional at deep cryogenic temperatures. Here, in this work, we present the first design of a voltage-controlled superconducting flash analog-to-digital converter (ADC) based on a voltage-controlled quantum-enhanced Josephson junction field-effect transistor (JJFET). Exploiting its strong gate tunability and transistor-like behavior, the JJFET offers a scalable alternative to conventional current-controlled superconducting devices while aligning naturally with CMOS-style design methodologies. Building on our previously developed Verilog-A compact model calibrated to experimental data, we design and simulate a three-bit JJFET-based flash ADC targeted for integration within cryogenic control and readout circuitry in quantum computing. The core comparator block is realized through careful bias current selection and augmented with a three-terminal nanocryotron to precisely define reference voltages. Cascaded JJFET comparators ensure robust voltage gain, cascadability, and logic-level restoration across stages. Simulation results demonstrate accurate quantization behavior with ultra-low power dissipation, underscoring the feasibility of voltage-driven superconducting mixed-signal circuits. This work establishes a critical step toward unifying superconducting logic and data conversion, paving the way for scalable cryogenic architectures in quantum–classical co-processors, low-power artificial intelligence accelerators, and next-generation energy-constrained computing platforms.

Analog-to-digital converter↗
DOE OSTI2015

Mapping suitability areas for concentrated solar power plants using remote sensing data

The political push to increase power generation from renewable sources such as solar energy requires knowing the best places to site new solar power plants with respect to the applicable regulatory, operational, engineering, environmental, and socioeconomic criteria. Therefore, in this paper, we present applications of remote sensing data for mapping suitability areas for concentrated solar power plants. Our approach uses digital elevation model derived from NASA s Shuttle Radar Topographic Mission (SRTM) at a resolution of 3 arc second (approx. 90m resolution) for estimating global solar radiation for the study area. Then, we develop a computational model built on a Geographic Information System (GIS) platform that divides the study area into a grid of cells and estimates site suitability value for each cell by computing a list of metrics based on applicable siting requirements using GIS data. The computed metrics include population density, solar energy potential, federal lands, and hazardous facilities. Overall, some 30 GIS data are used to compute eight metrics. The site suitability value for each cell is computed as an algebraic sum of all metrics for the cell with the assumption that all metrics have equal weight. Finally, we color each cell according to its suitability value. Furthermore, we present results for concentrated solar power that drives a stream turbine and parabolic mirror connected to a Stirling Engine.

14 SOLAR ENERGY↗
DOE OSTI2023

Attack Surface Analysis of the Digital Twins interface with Advanced Sensor and Instrumentation Interfaces: Cyber Threat Assessment and Attack Demonstration for Digital Twins in Advanced Reactor Architectures

A digital twin is a virtual representation of a physical system or object using real-time data that can predict and analyze how the system or object performs. This relatively new technology can be applied to the field of nuclear power generation, to aid in the design and development of new nuclear power plants and reduce operation costs using predictive maintenance and other data analytical methods. While there are already companies utilizing simulation software to train operators and technicians in the nuclear industry, some are now transitioning to utilizing their existing technology, software, and methods to develop digital twin solutions for the next generation of nuclear power plants, offering their services to utilities and government organizations around the world.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Hardware-Based Randomized Encoding for Sensor Authentication in Power Grid SCADA Systems

Supervisory Control and Data Acquisition (SCADA) systems are utilized extensively in critical power grid infrastructures. Modern SCADA systems have been proven to be susceptible to cyber-security attacks and require improved security primitives in order to prevent unwanted influence from an adversarial party. One section of weakness in the SCADA system is the integrity of field level sensors providing essential data for control decisions at a master station. In this paper we propose a lightweight hardware scheme providing inferred authentication for SCADA sensors by combining an analog to digital converter and a permutation generator as a single integrated circuit. Through this method we encode critical sensor data at the time of sensing, so that unencoded data is never stored in memory, increasing the difficulty of software attacks. We show through experimentation how our design stops both software and hardware false data injection attacks occurring at the field level of SCADA systems.

42 ENGINEERING↗
DOE OSTI2022

Towards a machine-readable literature: finding relevant papers based on an uploaded powder diffraction pattern

A prototype application for machine-readable literature is investigated. The program is called pyDataRecognition and serves as an example of a data-driven literature search, where the literature search query is an experimental data set provided by the user. The user uploads a powder pattern together with the radiation wavelength. The program compares the user data to a database of existing powder patterns associated with published papers and produces a rank ordered according to their similarity score. The program returns the digital object identifier and full reference of top-ranked papers together with a stack plot of the user data alongside the top-five database entries. The paper describes the approach and explores successes and challenges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Post-composing ontology terms for efficient phenotyping in plant breeding

Abstract Ontologies are widely used in databases to standardize data, improving data quality, integration, and ease of comparison. Within ontologies tailored to diverse use cases, post-composing user-defined terms reconciles the demands for standardization on the one hand and flexibility on the other. In many instances of Breedbase, a digital ecosystem for plant breeding designed for genomic selection, the goal is to capture phenotypic data using highly curated and rigorous crop ontologies, while adapting to the specific requirements of plant breeders to record data quickly and efficiently. For example, post-composing enables users to tailor ontology terms to suit specific and granular use cases such as repeated measurements on different plant parts and special sample preparation techniques. To achieve this, we have implemented a post-composing tool based on orthogonal ontologies providing users with the ability to introduce additional levels of phenotyping granularity tailored to unique experimental designs. Post-composed terms are designed to be reused by all breeding programs within a Breedbase instance but are not exported to the crop reference ontologies. Breedbase users can post-compose terms across various categories, such as plant anatomy, treatments, temporal events, and breeding cycles, and, as a result, generate highly specific terms for more accurate phenotyping.

Mathematical & Computational Biology↗
DOE OSTI2021

Characterizing the Effect of Capillary Heterogeneity on Multiphase Flow Pulsation in an Intermediate–Scale Beadpack Experiment using Time Series Clustering and Frequency Analysis

An intermediate-scale beadpack drainage experiment was conducted to investigate how simple layered lamination heterogeneity affects CO 2 flow. Two simple layers of capillary barriers are manually packed in the tank and slow drainage was carried out using analog fluids to mimic the capillary- and gravity-dominated CO 2 upward migration process in deep saline aquifers. Nonwetting phase saturation time series clustering analysis and frequency analysis have been conducted on the experimental data. Additionally, modified invasion percolation numerical simulations were done on a digital model of the beadpack to compare to experimental results. Results show that capillary barriers can lead to strong pulsation behavior, which in turn can cause unexpected early breaching through other barriers. The inlet pressure is found to be able to respond to saturation changes in far regions of the domain, indicating that the wetting phase can transmit pressure changes from the other phase. Although static simulations were not able to capture all the dynamic behavior observed in the experiment, Monte Carlo composite simulation results combining many different realizations can better illustrate how the nonwetting phase will behave in the heterogeneous domain. Furthermore, our results suggest the need for CO 2 storage site selection with preference given to aquifers with more capillary barriers with finer grain sizes to avoid flow pulsation and to retard plume upward migration.

58 GEOSCIENCES↗
DOE OSTI2013

Development of neutron tomography and phase contrast imaging technique

This paper presents design and development of a state of art neutron imaging technique at CIRUS reactor with special reference for techniques adopted for tomography and phase contrast imaging applications. Different components of the beamline such as collimator, shielding, sample manipulator, digital imaging system were designed keeping in mind the requirements of data acquisition time and resolution. The collimator was designed in such a way that conventional and phase contrast imaging can be done using same collimator housing. We have done characterization of fuel pins, study of hydride blisters in pressure tubes hydrogen based cells, two phase flow visualization, and online study of locomotive parts etc. using neutron tomography and radiography technique. We have also done some studies using neutron phase contrast imaging technique on this beamline.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2011

Near-IR laser-based spectrophotometer for comparative analysis of isotope content of CO{sub 2} in exhale air samples

We present a laser spectrophotometer aimed at high-accuracy comparative analysis of content of {sup 12}CO{sub 2} and {sup 13}CO{sub 2} isotope modifications in the exhale air samples and based on a tunable near-IR diode laser (2.05 {mu}m). The two-channel optical scheme of the spectrophotometer and the special digital system for its control are described. An algorithm of spectral data processing aimed at determining the difference in the isotope composition of gas mixtures is proposed. A few spectral regions (near 4880 cm{sup -1}) are determined to be optimal for analysis of relative content of {sup 12}CO{sub 2} and {sup 13}CO{sub 2} in the exhale air. The use of the proposed spectrophotometer scheme and the developed algorithm makes the results of the analysis less susceptible to the influence of the interference in optical elements, to the absorption in the open atmosphere, to the slow drift of the laser pulse envelope, and to the offset of optical channels. The sensitivity of the comparative analysis of the isotope content of CO{sub 2} in exhale air samples, achieved using the proposed scheme, is estimated to be nearly 0.1 Per-Mille-Sign .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

THE X-RAY VARIABILITY OF A LARGE, SERENDIPITOUS SAMPLE OF SPECTROSCOPIC QUASARS

We analyze the X-ray variability of 264 Sloan Digital Sky Survey spectroscopic quasars using the Chandra public archive. This data set consists of quasars with spectroscopic redshifts out to z Almost-Equal-To 5 and covers rest-frame timescales up to {Delta}t{sub sys} Almost-Equal-To 2000 days, with three or more X-ray observations available for 82 quasars. It therefore samples longer timescales and higher luminosities than previous large-scale analyses of active galactic nucleus (AGN) variability. We find significant ({approx}>3{sigma}) variation in Almost-Equal-To 30% of the quasars overall; the fraction of sources with detected variability increases strongly with the number of available source counts up to Almost-Equal-To 70% for sources with {>=}1000 counts per epoch. Assuming that the distribution of fractional variation is Gaussian, its standard deviation is Almost-Equal-To 16% on {approx}>1 week timescales, which is not enough to explain the observed scatter in quasar X-ray-to-optical flux ratios as being due to variability alone. We find no evidence in our sample that quasars are more variable at higher redshifts (z > 2), as has been suggested in previous studies. Quasar X-ray spectra vary similarly to some local Seyfert AGNs in that they steepen as they brighten, with evidence for a constant, hard spectral component that is more prominent in fainter stages. We identify one highly variable Narrow Line Seyfert 1-type spectroscopic quasar in the Chandra Deep Field-North. We constrain the rate of kilosecond-timescale flares in the quasar population using Almost-Equal-To 8 months of total exposure and also constrain the distribution of variation amplitudes between exposures; extreme changes (>100%) are quite rare, while variation at the 25% level occurs in <25% of observations. [O III] {lambda}5007 A emission may be stronger in sources with lower levels of X-ray variability; if confirmed, this would represent an additional link between small-scale (corona) and large-scale (narrow-line region) AGN properties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The SparkPix-S ASIC for the sparsified readout of 1 MHz frame-rate X-ray cameras at LCLS-II: pixel design and simulation results

Exploiting the “sparse” nature of the information in XPCS (X-ray Photon Correlation Spectroscopy) and XSVS (Speckle Visibility Spectroscopy) experiments, we present the SparkPix-S, a 3-sides buttable Application Specific Integrated Circuit (ASIC) based on a sparsified readout strategy for large-format hybrid detectors. The SparkPix-S architecture, based on the successful ePix family, will be composed as follows: a front-end 2-D matrix of 384×352 square pixels with 50 µm pitch is arranged to match the dimensions of a PIN Si-sensor matrix; charge readout, signal shaping and amplitude discrimination is performed at pixel-level, by means of a low-power (<18 µW) analog processor, which, in case of an event, negotiates access to an analog bus placed every other column; on the chip periphery (balcony), the information on each bus is digitized by an array of successive approximation analog-to-digital converters (SAR-ADCs) running at 10 Msps; on the digital back-end the global logic will generate the output data stream using low-voltage differential signalling (LVDS). A first prototype of the SparkPix-S, with a reduced matrix size of 96×96 pixels, is currently under production on a 130 nm CMOS technology. Simulated performance results show an equivalent noise charge <60 el. r.m.s. at 1 MHz repetition rate, with a maximum input energy of 60 keV and capability to discriminate charge signals with equivalent energy as low as 900 eV.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: a tomographic measurement of structure growth and expansion rate from anisotropic galaxy clustering in Fourier space

In this study, we perform a tomographic structure growth and expansion rate analysis using the monopole, quadrupole and hexadecapole of the redshift-space galaxy power spectrum derived from the Sloan Digital Sky Survey (SDSS-III) Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12 combined sample, which covers the redshift range of 0.20 < $z$ < 0.75. By allowing for overlap between neighbouring redshift slices in order to extract information on the light-cone, we successfully obtain joint BAO and RSD constraints with a precision of 2-3 per cent for D A , 3-10 per cent for H and 9-12 per cent for fσ 8 with a redshift resolution of $Δz$ ~ 0.04. Our measurement is consistent with that presented in Wang et al., where the analysis is performed in configuration space. Finally, we apply our measurement to constrain the Em>f(R) gravity model, and find that the 95 per cent CL upper limit of log 10 B 0 can be reduced by 11 per cent by our tomographic BAO and RSD measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Generative Thermodynamic Computing

Here, we introduce a generative modeling framework for thermodynamic computing, in which structured data are synthesized from noise by the natural time evolution of a physical system governed by Langevin dynamics. While conventional diffusion models use neural networks to perform denoising, here the information needed to generate structure from noise is encoded by the dynamics of a thermodynamic system. Training proceeds by maximizing the probability with which the computer generates the reverse of a noising trajectory, which ensures that the computer generates data with minimal heat emission. We demonstrate this framework within a digital simulation of a thermodynamic computer. If realized in analog hardware, such a system would function as a generative model that produces structured samples without the need for artificially injected noise or active control of denoising.

Whitelam, Stephen [Lawrence Berkeley National Labo↗
DOE OSTI2022

Estimating Channel Width for the Middle Green River Using Remote Sensing

Channel geometry can affect the abundance and quality of fish habitats along rivers in the Colorado River basin. However, previous analyses of sediment transport and channel narrowing in the middle Green River have focused on very limited reaches of the river and have used techniques with varying degrees of resolution, leading to potential problems with interpretation and generalization to the overall reach. The goal of this study is to develop comprehensive baseline information for channel width estimation along the Green River by combining a high-resolution digital elevation model (DEM) derived from Light Detection and Ranging (LiDAR) data and Sentinel-2 multispectral satellite imagery. The objectives are to (1) estimate channel width using Sentinel-2 satellite imagery alone, (2) estimate channel width using the high-resolution DEM with ancillary information extracted from the multispectral imagery, and (3) examine the agreement in channel width estimates between the products derived from the two methods to gain insights for cost effective channel-width monitoring.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Considerations regarding the Use of Computer Vision Machine Learning in Safety-Related or Risk-Significant Applications in Nuclear Power Plants

With the advancements made to date in the field of artificial intelligence (AI), significant potential exists to utilize AI capabilities for nuclear power plant (NPP) applications. AI can replicate human decision making and it is usually faster and more accurate than humans. For implementations that impact critical NPP applications (e.g., safety-related or non-safety systems that potentially affect overall plant risk), a deeper safety analysis of the AI methods is necessary. AI applied to NPP operations could resemble the use of digital I&C (DI&C) because such applications involve digital computer hardware and custom-designed software that input plant data, execute complex software algorithms, and output the results to a system or licensed human operator to potentially provoke an action. For AI methods to be compliant with current safety requirements for DI&C, AI compatibility must be evaluated, and AI-related gaps may exist that prevent the prompt deployment of AI in NPPs. This effort aims to evaluate how example AI technologies align with the DI&C safety framework, and discusses how they could be analyzed, modeled, tested, and validated in a manner similar to typical DI&C technologies. Because AI is a broad field that encompasses areas such as machine learning (ML), natural language processing, and computer vision, this research focused on a subset of methods categorized as the computer vision ML (CVML) methods. This report explores two CVML use cases, gauge reading and fire watch, considered relevant to the DI&C standards, as they could play a safety-critical role. For the gauge reading use case, a CVML-enabled technology that can read gauges at oblique angles is utilized. For the fire watch use case, a CVML-enabled technology is utilized that migrates fire watch from a manual (human) approach to automated fire detection. These use cases are mainly intended to give context to the CVML system discussion. This effort assumes the worst-case scenario, with the CVML system being used to replace a safety-related or risk-significant system, thus requiring evaluation. Evaluating CVML against most of the relevant safety requirements for DI&C yielded several CVML-specific considerations due to the uniqueness of its characteristics in comparison with typical DI&C systems. For example, CVML models often employ commonly used (open-source) datasets, and it is not always possible to determine the level of overlap among open-source datasets. Therefore, the independence of the developed CVML models when demonstrating diversity is questionable, therefore creating vulnerability to common cause failure (CCF). The design verification process is also impacted since the data overlap could result in overestimation of the software validation and verification (V&V) performance results. Section 2 of this report evaluates a list of the identified CVML-specific characteristics and discusses the resulting considerations and potential solutions in the context of each referenced requirement. A summation is provided in Section 3. This report is not to be used as a guideline. It was developed to identify and consider issues in the implementation of ML technologies used to augment activities that may have a bearing on plant operation. The report draws parallels to the use of DI&C technologies, for which many standards are available to guide their use in nuclear plant operation. It considers the technologies and some of the potential implications of their use in safety-related applications but is not intended to address regulatory or licensing related issues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

The Color and Stellar Mass Dependence of Small-scale Galaxy Clustering in SDSS-III BOSS

We measure the color and stellar mass dependence of clustering in spectroscopic galaxies at 0.6 < z < 0.65 using data from the Baryon Oscillation Spectroscopic Survey component of the Sloan Digital Sky Survey. We greatly increase the statistical precision of our clustering measurements by using the cross-correlation of 66,657 spectroscopic galaxies to a sample of 6.6 million fainter photometric galaxies. The clustering amplitude w(R) is measured as the ratio of the mean excess number of photometric galaxies found within a specified radius annulus around a spectroscopic galaxy to that from a random photometric galaxy distribution. We recover many of the familiar trends at high signal-to-noise ratio. We find the ratio of the clustering amplitudes of red and blue massive galaxies to be w{sub red}/w{sub blue}=1.92±0.11 in our smallest annulus of 75–125 kpc. At our largest radii (2–4 Mpc), we find w{sub red}/w{sub blue}=1.24±0.05. Red galaxies therefore have denser environments than their blue counterparts at z ∼ 0.625, and this effect increases with decreasing radius. Irrespective of color, we find that w(R) does not obey a simple power-law relation with radius, showing a dip around 1 Mpc. Holding stellar mass fixed, we find a clear differentiation between clustering in red and blue galaxies, showing that clustering is not solely determined by stellar mass. Holding color fixed, we find that clustering increases with stellar mass, especially for red galaxies at small scales (more than a factor of 2 effect over 0.75 dex in stellar mass).

79 ASTRONOMY AND ASTROPHYSICS↗