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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 OSTI2016

Implementation of data citations and persistent identifiers at the ORNL DAAC

A requirement of data archives is that data holdings can be easily discovered, accessed, and used. One approach to improving data discovery and access is through data citations coupled with Digital Object Identifiers (DOI). The Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) since 1998 has issued data citations that have been accepted and used in peer-reviewed journals. Citation elements established by the ORNL DAAC are similar to those used for journal articles (authors, year, product title, and information to locate), and beginning in 2007 included a DOI that is persistent, actionable, specific, and complete. The approach used at the ORNL DAAC also allows for referring to subsets of the data, by including within the citation the temporal and spatial extent, and parameters used. Data citations allow readers to find data and reproduce the results of the research article, and also use those data to test new hypotheses, design new sample collections, or construct or evaluate models. The ORNL DAAC uses a manual method to compile data citations and has developed a database that links research articles and their use of specific ORNL DAAC data products. Automation of the data citation compilation process, as is the case for articles, will enable data citations to become a more common practice. In addition to enhancing discovery and access of the data used in a research article, the citation gives credit to data generators, data centers and their funders, and, through citation indices, determine the scientific impact of a data set.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

Scalability analysis of heavy-duty gas turbines using data-driven machine learning

With the increasing integration of variable renewable energy sources into power systems, the role of flexible power generation technologies like gas turbines (GT) in rapid grid balancing remains crucial. This sustained importance underscores the need for scaled and precise modeling of GT to ensure effective integration within evolving energy frameworks. While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). The model is developed to capture complex system interaction and to adapt to changing operational scenarios at different capacities, providing valuable insights of power system dynamics. In this study, the real-time digital simulator platform was employed to generate training data for the ML model and assess its dynamic characteristics. The ultimate objective was to develop a detailed modeling framework based on governing equations and data-driven ML capable of predicting key performance indicators, in thermal systems such as GTs, including power output, speed, fuel consumption, and exhaust temperature under diverse operating conditions at different scales. The developed ML framework demonstrated high accuracy, with mean relative errors for GT power prediction, reference speed, exhaust temperature, and compressor pressure ratio (CPR) parameters consistently below 0.1% across typical load fluctuation scenarios. Maximum deviations were limited to approximately 0.5 K for exhaust temperature and 0.009 for CPR, underscoring the model’s ability to replicating dynamic GT behavior with high precision. The adaptability of the ML model enables its application across diverse operational conditions and its extension to other thermal systems. By leveraging advanced ML techniques, this study presents a robust and scalable modeling framework that enhances GT simulation precision, facilitating improved integration into evolving power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Development of Application Function Blocks for Power-Hardware-in-the-Loop Testing of Grid-Connected Inverters: Preprint

Stability and accuracy of the PHIL platform has been a common problem and challenging issue for a long time, thus continuous efforts and research have been devoted to developing interface algorithms to improve upon this. Some of existing works exhibit promising solutions to compensate the errors in the PHIL platform. However, there is a need to harmonize various solutions into a standard framework that provides a general solution for various PHIL test beds and that can be reused with minimum modifications to avoid extra effort. A good way to do this is by using application function blocks (AFBs), which are model-based and can be developed as a standard library component, thus achieving satisfactory reusability and reconfigurability for various platforms. Since PHIL simulation has the flexibility of the software simulation, proper functions can be easily implemented in the digital real-time simulator (DRTS) to preprocess the reference signal before sending it to the power amplifier. Therefore, this paper aims to develop standard AFBs in DRTS for the PHIL interface to test grid-connected inverters. The PHIL interface algorithm is separated into five AFBs that will be presented in detail in this paper.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

A catalogue of Locus Algorithm pointings for optimal differential photometry for 23 779 quasars

ABSTRACT This paper presents a catalogue of optimized pointings for differential photometry of 23 779 quasars extracted from the Sloan Digital Sky Survey (SDSS) Catalogue and a Score for each indicating the quality of the Field of View (FoV) associated with that pointing. Observation of millimagnitude variability on a time-scale of minutes typically requires differential observations with reference to an ensemble of reference stars. For optimal performance, these reference stars should have similar colour and magnitude to the target quasar. In addition, the greatest quantity and quality of suitable reference stars may be found by using a telescope pointing which offsets the target object from the centre of the FoV. By comparing each quasar with the stars which appear close to it on the sky in the SDSS Catalogue, an optimum pointing can be calculated, and a figure of merit, referred to as the ‘Score’ is calculated for that pointing. Highly flexible software has been developed to enable this process to be automated and implemented in a distributed computing paradigm, which enables the creation of catalogues of pointings given a set of input targets. Applying this technique to a sample of 40 000 targets from the fourth SDSS quasar catalogue resulted in the production of pointings and Scores for 23 779 quasars based on their magnitudes in the SDSS r-band. This catalogue is a useful resource for observers planning differential photometry studies and surveys of quasars to select those which have many suitable celestial neighbours for differential photometry.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

WE-AB-209-05: Development of an Ultra-Fast High Quality Whole Breast Radiotherapy Treatment Planning System

Purpose: To enable near-real-time (<20sec) and interactive planning without compromising quality for whole breast RT treatment planning using tangential fields. Methods: Whole breast RT plans from 20 patients treated with single energy (SE, 6MV, 10 patients) or mixed energy (ME, 6/15MV, 10 patients) were randomly selected for model training. Additional 20 cases were used as validation cohort. The planning process for a new case consists of three fully automated steps:1. Energy Selection. A classification model automatically selects energy level. To build the energy selection model, principle component analysis (PCA) was applied to the digital reconstructed radiographs (DRRs) of training cases to extract anatomy-energy relationship.2. Fluence Estimation. Once energy is selected, a random forest (RF) model generates the initial fluence. This model summarizes the relationship between patient anatomy’s shape based features and the output fluence. 3. Fluence Fine-tuning. This step balances the overall dose contribution throughout the whole breast tissue by automatically selecting reference points and applying centrality correction. Fine-tuning works at beamlet-level until the dose distribution meets clinical objectives. Prior to finalization, physicians can also make patient-specific trade-offs between target coverage and high-dose volumes.The proposed method was validated by comparing auto-plans with manually generated clinical-plans using Wilcoxon Signed-Rank test. Results: In 19/20 cases the model suggested the same energy combination as clinical-plans. The target volume coverage V100% was 78.1±4.7% for auto-plans, and 79.3±4.8% for clinical-plans (p=0.12). Volumes receiving 105% Rx were 69.2±78.0cc for auto-plans compared to 83.9±87.2cc for clinical-plans (p=0.13). The mean V10Gy, V20Gy of the ipsilateral lung was 24.4±6.7%, 18.6±6.0% for auto plans and 24.6±6.7%, 18.9±6.1% for clinical-plans (p=0.04, <0.001). Total computational time for auto-plans was < 20s. Conclusion: We developed an automated method that generates breast radiotherapy plans with accurate energy selection, similar target volume coverage, reduced hotspot volumes, and significant reduction in planning time, allowing for near-real-time planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-FG-207B-05: Iterative Reconstruction Via Prior Image Constrained Total Generalized Variation for Spectral CT

Purpose: To investigate iterative reconstruction via prior image constrained total generalized variation (PICTGV) for spectral computed tomography (CT) using fewer projections while achieving greater image quality. Methods: The proposed PICTGV method is formulated as an optimization problem, which balances the data fidelity and prior image constrained total generalized variation of reconstructed images in one framework. The PICTGV method is based on structure correlations among images in the energy domain and high-quality images to guide the reconstruction of energy-specific images. In PICTGV method, the high-quality image is reconstructed from all detector-collected X-ray signals and is referred as the broad-spectrum image. Distinct from the existing reconstruction methods applied on the images with first order derivative, the higher order derivative of the images is incorporated into the PICTGV method. An alternating optimization algorithm is used to minimize the PICTGV objective function. We evaluate the performance of PICTGV on noise and artifacts suppressing using phantom studies and compare the method with the conventional filtered back-projection method as well as TGV based method without prior image. Results: On the digital phantom, the proposed method outperforms the existing TGV method in terms of the noise reduction, artifacts suppression, and edge detail preservation. Compared to that obtained by the TGV based method without prior image, the relative root mean square error in the images reconstructed by the proposed method is reduced by over 20%. Conclusion: The authors propose an iterative reconstruction via prior image constrained total generalize variation for spectral CT. Also, we have developed an alternating optimization algorithm and numerically demonstrated the merits of our approach. Results show that the proposed PICTGV method outperforms the TGV method for spectral CT.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1991

Advanced Photovoltaic Experiment, S0014: Preliminary Flight Results and Post-Flight Findings

The Advanced Photovoltaic Experiment (APEX) is an LDEF experiment designed to provide reference solar cell standards for laboratory measurements as well as to investigate the solar spectrum and the effects of long term exposure of solar cells to the LEO environment. Silicon and gallium arsenide solar cells were flown with the appropriate instrumentation to periodically measure cell performance and temperature. The experimental objectives, the design employed to realize these objectives and the solar cells and instrumentation selected for the flight are presented. A discussion of the flight data returned are included. Preliminary results from the post flight analysis of the absolute cavity radiometer, the digital solar angle sensor, and the Barr Associates narrow bandpass optical filters are also presented. The initial findings of work to determine the chemical nature of contamination layers on APEX are also presented.

Brinker, David J.↗
DOE OSTI2015

DC Microgrids&#x2013;Part I: A Review of Control Strategies and Stabilization Techniques

This paper presents a review of control strategies, stability analysis, and stabilization techniques for dc microgrids (MGs). Overall control is systematically classified into local and coordinated control levels according to respective functionalities in each level. As opposed to local control, which relies only on local measurements, some line of communication between units needs to be made available in order to achieve the coordinated control. Depending on the communication method, three basic coordinated control strategies can be distinguished, i.e., decentralized, centralized, and distributed control. Decentralized control can be regarded as an extension of the local control since it is also based exclusively on local measurements. In contrast, centralized and distributed control strategies rely on digital communication technologies. A number of approaches using these three coordinated control strategies to achieve various control objectives are reviewed in this paper. Moreover, properties of dc MG dynamics and stability are discussed. This paper illustrates that tightly regulated point-of-load converters tend to reduce the stability margins of the system since they introduce negative impedances, which can potentially oscillate with lightly damped power supply input filters. It is also demonstrated that how the stability of the whole system is defined by the relationship of the source and load impedances, referred to as the minor loop gain. Several prominent specifications for the minor loop gain are reviewed. Finally, a number of active stabilization techniques are presented.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2017

The phase-space structure of nearby dark matter as constrained by the SDSS

Previous studies using numerical simulations have demonstrated that the shape of the cosmic web can be described by studying the Lagrangian displacement field. We extend these analyses, showing that it is now possible to perform a Lagrangian description of cosmic structure in the nearby Universe based on large-scale structure observations. Building upon recent Bayesian large-scale inference of initial conditions, we present a cosmographic analysis of the dark matter distribution and its evolution, referred to as the dark matter phase-space sheet, in the nearby universe as probed by the Sloan Digital Sky Survey main galaxy sample. We consider its stretchings and foldings using a tetrahedral tessellation of the Lagrangian lattice. The method provides extremely accurate estimates of nearby density and velocity fields, even in regions of low galaxy density. It also measures the number of matter streams, and the deformation and parity reversals of fluid elements, which were previously thought inaccessible using observations. We illustrate the approach by showing the phase-space structure of known objects of the nearby Universe such as the Sloan Great Wall, the Coma cluster and the Boötes void. We dissect cosmic structures into four distinct components (voids, sheets, filaments, and clusters), using the Lagrangian classifiers DIVA, ORIGAMI, and a new scheme which we introduce and call LICH. Because these classifiers use information other than the sheer local density, identified structures explicitly carry physical information about their formation history. Accessing the phase-space structure of dark matter in galaxy surveys opens the way for new confrontations of observational data and theoretical models. We have made our data products publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1981

SEM analysis of ionizing radiation effects in an analog to digital converter /AD571/

The considered investigation is concerned with the study of the total-dose degradation mechanisms in an IIL analog to digital (A/D) converter. The A/D converter is a 10 digit device having nine separate functional units on the chip which encompass several hundred transistors and circuit elements. It was the objective of the described research to find the radiation sensitive elements by a systematic search of the devices on the LSI chip. The employed technique using a scanning electron microscope to determine the functional blocks of an integrated circuit which are sensitive to ionizing radiation and then progressively zeroing in on the soft components within those blocks, proved extremely successful on the AD571. Four functional blocks were found to be sensitive to radiation, including the Voltage Reference, DAC, IIL Clock, and IIL SAR.

Gauthier, M. K.↗
NASA NTRS1975

The 4D area navigation system description and flight test results

A 4D area navigation system was designed to guide aircraft along a prespecified flight path (reference path) such that the aircraft would arrive at the approach gate at a time specified by the ATC controller. Key components to achieve this requirement were: (1) stored reference trajectories; (2) a continuously recomputed capture trajectory to a selected waypoint on the reference trajectory so as to achieve the desired time of arrival; (3) electronic situation displays; and (4) a control system to follow the overall trajectory in space and time. The system was implemented in a digital integrated avionics system (STOLAND) installed on a CV-340 airplane. Although the 4D system was designed primarily for automatic operation, it was flight tested in a flight director mode (the pilot follows the flight director commands), because the CV-340 autopilot servos were not tied to the avionics system. The flight test showed that, even in the flight director mode, the pilot did achieve the objectives of path tracking and time of arrival control with only moderate workload. The system also permitted controlled delay of the time of arrival by path stretching, which takes advantage of the continuously changing capture trajectory to predict the time of arrival. Simulations in the automatic and manual modes were used to complement the flight data.

Lee, H. Q.↗
NASA NTRS1989

CSM research: Methods and application studies

Computational mechanics is that discipline of applied science and engineering devoted to the study of physical phenomena by means of computational methods based on mathematical modeling and simulation, utilizing digital computers. The discipline combines theoretical and applied mechanics, approximation theory, numerical analysis, and computer science. Computational mechanics has had a major impact on engineering analysis and design. When applied to structural mechanics, the discipline is referred to herein as computational structural mechanics. Complex structures being considered by NASA for the 1990's include composite primary aircraft structures and the space station. These structures will be much more difficult to analyze than today's structures and necessitate a major upgrade in computerized structural analysis technology. NASA has initiated a research activity in structural analysis called Computational Structural Mechanics (CSM). The broad objective of the CSM activity is to develop advanced structural analysis technology that will exploit modern and emerging computers, such as those with vector and/or parallel processing capabilities. Here, the current research directions for the Methods and Application Studies Team of the Langley CSM activity are described.

Knight, Norman F., Jr.↗
DOE OSTI2013

OPTICAL SPECTRA OF CANDIDATE INTERNATIONAL CELESTIAL REFERENCE FRAME (ICRF) FLAT-SPECTRUM RADIO SOURCES

Continuing our program of spectroscopic observations of International Celestial Reference Frame (ICRF) sources, we present redshifts for 120 quasars and radio galaxies. Data were obtained with five telescopes: the 3.58 m European Southern Observatory New Technology Telescope, the two 8.2 m Gemini telescopes, the 2.5 m Nordic Optical Telescope (NOT), and the 6.0 m Big Azimuthal Telescope of the Special Astrophysical Observatory in Russia. The targets were selected from the International VLBI Service for Geodesy and Astrometry candidate International Celestial Reference Catalog which forms part of an observational very long baseline interferometry (VLBI) program to strengthen the celestial reference frame. We obtained spectra of the potential optical counterparts of more than 150 compact flat-spectrum radio sources, and measured redshifts of 120 emission-line objects, together with 19 BL Lac objects. These identifications add significantly to the precise radio-optical frame tie to be undertaken by Gaia, due to be launched in 2013, and to the existing data available for analyzing source proper motions over the celestial sphere. We show that the distribution of redshifts for ICRF sources is consistent with the much larger sample drawn from Faint Images of the Radio Sky at Twenty cm (FIRST) and Sloan Digital Sky Survey, implying that the ultra-compact VLBI sources are not distinguished from the overall radio-loud quasar population. In addition, we obtained NOT spectra for five radio sources from the FIRST and NRAO VLA Sky Survey catalogs, selected on the basis of their red colors, which yielded three quasars with z > 4.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Real World Applications of AI/ML in Optimizing Airspace Operations

As National Airspace System (NAS) is going through the Digital Transformation journey, data science and analytics methods can significantly contribute to improving the traditional physics-based decision-making tools. The adoption of AI/ML methods will not only help accelerate Federal Aviation Administration (FAA)’s vision of Info-centric NAS but also contribute to the overall objective of sustainable aviation. AI/ML can improve the ground and airspace operations by enhancing the accuracy of current decision-making tools used by the airlines and the FAA to manage traffic on the ground and in the air. Huge amount of data that gets collected during a flight. AI/ML methods can extract information from this data and provide valuable insights to make better operational decisions. NASA has partnered with the FAA and commercial airlines such as American and Southwest Airlines on this effort and has successfully demonstrated the benefits of using ML in real world environment by reducing delays and optimizing ground operations at the US airports. In 2022 itself, NASA demonstrated real-world benefits (over 24K lbs. of fuel savings, over 76.6K lbs. CO2 emission savings, and several hours of delay savings) by deploying ML based prediction models to optimize ground operations at Dallas/Fort Worth International and Dallas Love Field Airports in Texas. These tools are being deployed on the cloud for broader deployment, adaptability, and scalability. NASA is developed a reference implementation of the cloud-based platform to significantly lower the bar to development and distribution of these digital services for aviation. In this talk, I will share information about the Digital Information Platform project, the novel AI/ML based approaches used for optimizing ground operations and the opportunities to partner with NASA on these demonstrations.

air traffic management↗
NASA NTRS1979

New techniques in television to provide research in three-dimensional real-time or near real-time imagery and reduced cost systems for teleconferencing and educational uses, part 1

The results are presented of a continuing research and development program the objective of which is to develop a reduced bandwidth television system and a technique for television transmission of holograms. The result of the former is a variable frame rate television system, the operation of which was demonstrated for both black-and-white and color signals. This system employs a novel combination of the inexpensive mass storage capacity of a magnetic disc with the reliability of a digital system for time expansion and compression. Also reported are the results of a theoretical analysis and preliminary feasibility experiment of an innovative system for television transmission of holograms using relatively conventional TV equipment along with a phase modulated reference wave for production of the original interference pattern.

Pao, Y. H.↗
DOE OSTI2016

Digital Architecture Planning Model

As part of the U.S. Department of Energy’s Light Water Reactor Sustainability Program, the Digital Architecture (DA) Project focuses on providing a model that nuclear utilities can refer to when planning deployment of advanced technologies. The digital architecture planning model (DAPM) is the methodology for mapping power plant operational and support activities into a DA that unifies all data sources needed by the utilities to operate their plants. The DA is defined as a collection of information technology capabilities needed to support and integrate a wide spectrum of real-time digital capabilities for performance improvements of nuclear power plants. DA can be thought of as integration of the separate instrumentation and control and information systems already in place in nuclear power plants, which are brought together for the purpose of creating new levels of automation in plant work activities. A major objective in DAPM development was to survey all key areas that needed to be reviewed in order for a utility to make knowledgeable decisions regarding needs and plans to implement a DA at the plant. The development was done in two steps. First, researchers surveyed the nuclear industry in order to learn their near-term plans for adopting new advanced capabilities and implementing a network (i.e., wireless and wire) infrastructure throughout the plant, including the power block. Secondly, a literature review covering regulatory documents, industry standards, and technical research reports and articles was conducted. The objective of the review was to identify key areas to be covered by the DAPM, which included the following: 1. The need for a DA and its benefits to the plant 2. Resources required to implement the DA 3. Challenges that need to be addressed and resolved to implement the DA 4. Roles and responsibilities of the DA implementation plan. The DAPM was developed based on results from the survey and the literature review. Model development, including the survey results and conclusions made about the key areas during the literature review, are described in this report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Status Report on Regulatory Criteria Applicable to the Use of Artificial Intelligence (AI) and Machine Learning (ML)

Although the interest in the use of artificial intelligence (AI) and machine learning (ML) in nuclear energy is increasing rapidly, at present their implementation is limited. This rapid increase in interest is not surprising considering that implementing AI and ML technology would allow for continuous monitoring, facilitate the implementation of predictive maintenance with optimized staffing plans, enable automation and autonomy opportunities that could drastically reduce fixed operation and maintenance costs, and provide training for operations and maintenance. Other industries are using AI for construction, and in the nuclear arena AI could provide great benefit in decommissioning activities. The ability of AI and ML to operate in real time vastly increases their potential impact. Before AI can be used in design, operations, or as a regulatory tool, the specifics on the regulations applicable to the use of AI for nuclear power applications need to be established. The difficulty is that the specific use cases will dictate the applicability of regulations. For example, even within the application domain associated with operations, the regulations might vary if the AI is used to create a virtual reference for plant operations or is used for training, optimization of maintenance intervals, prioritization of maintenance activities, etc. Different still is if the AI is to be used for design or setting technical specifications, which will introduce additional requirements. US Nuclear Regulatory Commission (NRC) licensing reviews are based on an applicant’s design meeting its performance assessment based on (1) safety goals and objectives, (2) deterministic and/or probabilistic analysis of accident scenarios, and (3) quantitative assessment of design alternatives against the safety goals and objectives using accepted engineering tools, methodologies, and performance criteria. The current regulatory framework does not explicitly address AI or autonomous control. However, as implementing AI technology will require the use of a digital platform, it must meet the requirements of an instrumentation and control (I&C) system. The regulatory requirements for AI, which will be incorporated into the I&C system, will be very dependent on how it is used (i.e., its functionality, safety classification, etc.). The licensing process is primarily risk-based with the identification of components and systems as nonsafety, important to safety, or safety related. A risk-informed approach allows further gradation of components and systems based on risk metrics such as core damage frequency or large early release fractions. Thus, the use cases and the risk categorization of impacted systems and components will determine the regulatory requirements. Regardless of how AI is used it presents new opportunities for risk-informing operating, maintenance, and regulatory decisions. Trustworthiness, transparency, and the ability to validate and verify the results will be paramount in showing that the systems and plant still meet their performance requirements. This report describes the results of research to identify regulatory implications of AI technologies and their uses. Specifically, this report reviews current regulatory guidance relevant to the application of AI for design (including design changes or new designs including advanced reactors), construction, operations, training, maintenance, research, testing, and as a regulatory tool. AI can be automated at different levels from purely informative purposes to autonomous controls. The focus of this review included determination of constraints on the application of AI technology, identification of any regulatory gaps or uncertainties, and clarification of anticipated technical basis information likely to be important for regulatory acceptance of these technologies. Currently, any use of AI at nuclear power plants is focused on nonsafety-related applications. The NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than create new regulations to address the use of AI and ML. This approach seems to be the best to encourage AI development without adding regulatory uncertainty.

97 MATHEMATICS AND COMPUTING↗