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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Characterization and identification of HPC applications at leadership computing facility

High Performance Computing (HPC) is an important method for scientific discovery via large-scale simulation, data analysis, or artificial intelligence. Leadership-class supercomputers are expensive, but essential to run large HPC applications. The Petascale era of supercomputers began in 2008, with the first machines achieving performance in excess of one petaflops, and with the advent of new supercomputers in 2021 (e.g., Aurora, Frontier), the Exascale era will soon begin. However, the high theoretical computing capability (i.e., peak FLOPS) of a machine is not the only meaningful target when designing a supercomputer, as the resources demand of applications varies. A deep understanding of the characterization of applications that run on a leadership supercomputer is one of the most important ways for planning its design, development and operation. In order to improve our understanding of HPC applications, user demands and resource usage characteristics, we perform correlative analysis of various logs for different subsystems of a leadership supercomputer. This analysis reveals surprising, sometimes counter-intuitive patterns, which, in some cases, conflicts with existing assumptions, and have important implications for future system designs as well as supercomputer operations. For example, our analysis shows that while the applications spend significant time on MPI, most applications spend very little time on file I/O. Combined analysis of hardware event logs and task failure logs show that the probability of a hardware FATAL event causing task failure is low. Combined analysis of control system logs and file I/O logs reveals that pure POSIX I/O is used more widely than higher level parallel I/O. Based on holistic insights of the application gained through combined and co-analysis of multiple logs from different perspectives and general intuition, we engineer features to "fingerprint" HPC applications. We use t-SNE (a machine learning technique for dimensionality reduction) to validate the explainability of our features and finally train machine learning models to identify HPC applications or group those with similar characteristic. To the best of our knowledge, this is the first work that combines logs on file I/O, computing, and inter-node communication for insightful analysis of HPC applications in production.

Liu, Zhengchun↗
DOE OSTI2021

Long-duration Energy Storage Technology Analysis and Development

This project develops a new low-cost and flexible long-duration energy storage (LDES) technology based on simultaneous regeneration technology. In lieu of the technology development, the project team also conducts a complete cost analysis for LDES based on various currently available technologies, as well as grid economic and environmental benefits analysis for LDES. There are three tasks in this project: Task 1. Fe-H2 flow cell fabrication, testing, demonstration; Task 2. Dynamic modeling, simulation and control architecture of power system; Task 3. Cost and grid analysis.

25 ENERGY STORAGE↗
DOE OSTI2022

ASDFL: An adaptive super‐pixel discriminative feature‐selective learning for vehicle matching

Abstract There are a large number of cameras in modern transportation system that capture numerous vehicle images continuously. Therefore, automatic analysis of these vehicle images is helpful for traffic flow management, criminal investigations and vehicle inspections. Vehicle matching, which aims to determine whether two input images depict an identical vehicle, is one of the core tasks in vehicle analysis. Recent relevant studies have focused on local feature extraction instead of global extraction, since local details can provide crucial cues to distinguish between cars. However, these methods do not select local features; that is, they do not assign weights to local features. Therefore, in this research, we systematically study the vehicle matching task, and present a novel annotation‐free local‐based deep learning method called Adaptive super‐pixel discriminative feature‐selective learning (ASDFL) to address this issue. In ASDFL, vehicle images are segmented into clusters of super‐pixels of similar size by considering the location and colour similarities of pixels without using any component‐level annotation. These super‐pixels are deemed to be the virtual components of vehicles. Moreover, a convolutional neural network is used to extract the deep features of these virtual components. Thereafter, an instance‐specific mask generation module driven by the extracted global features is enhanced to produce a mask to select the most distinctive virtual components of each vehicle image pair in the feature space. Finally, the vehicle matching task is accomplished by classifying the selected virtual component features of each imaged vehicle pair. Extensive experiments on two popular vehicle identification benchmarks demonstrate that our method is 1.57% and 0.8% more accurate than the previous baselines in a vehicle matching task on the VeRi and VehicleID datasets, respectively, which demonstrates the effectiveness of our method.

Qin, Rong↗
DOE OSTI2024

DLSIA: Deep Learning for Scientific Image Analysis

DLSIA (Deep Learning for Scientific Image Analysis) is a Python-based machine learning library that empowers scientists and researchers across diverse scientific domains with a range of customizable convolutional neural network (CNN) architectures for a wide variety of tasks in image analysis to be used in downstream data processing. DLSIA features easy-to-use architectures, such as autoencoders, tunable U-Nets and parameter-lean mixed-scale dense networks (MSDNets). Additionally, this article introduces sparse mixed-scale networks (SMSNets), generated using random graphs, sparse connections and dilated convolutions connecting different length scales. For verification, several DLSIA-instantiated networks and training scripts are employed in multiple applications, including inpainting for X-ray scattering data using U-Nets and MSDNets, segmenting 3D fibers in X-ray tomographic reconstructions of concrete using an ensemble of SMSNets, and leveraging autoencoder latent spaces for data compression and clustering. As experimental data continue to grow in scale and complexity, DLSIA provides accessible CNN construction and abstracts CNN complexities, allowing scientists to tailor their machine learning approaches, accelerate discoveries, foster interdisciplinary collaboration and advance research in scientific image analysis.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Identification and interpretation of patterns in rocket engine data

A prototype software system was constructed to detect anomalous Space Shuttle Main Engine (SSME) behavior in the early stages of fault development significantly earlier than the indication provided by either redline detection mechanism or human expert analysis. The major task of the research project is to analyze ground test data, to identify patterns associated with the anomalous engine behavior, and to develop a pattern identification and detection system on the basis of this analysis. A prototype expert system which was developed on both PC and Symbolics 3670 lisp machine for detecting anomalies in turbopump vibration data was checked with data from ground tests 902-473, 902-501, 902-519, and 904-097 of the Space Shuttle Main Engine. The neural networks method was also applied to supplement the statistical method utilized in the prototype system to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. In most cases the anomalies detected by the expert system agree with those reported by NASA. On the neural networks approach, the results are given the successful detection rate higher than 95 percent to identify either normal or abnormal running condition based on the experimental data as well as numerical simulation.

Lo, C. F.↗
NASA NTRS1978

Collection, processing and dissemination of data for the national solar demonstration program

A national solar data system developed for the DOE by IBM provides for automatic gathering, conversion, transfer, and analysis of demonstration site data. NASA requirements for this system include providing solar site hardware, engineering, data collection, and analysis. The specific tasks include: (1) solar energy system design/integration; (2) developing a site data acquisition subsystem; (3) developing a central data processing system; (4) operating the test facility at Marshall Space Flight Center; (5) collecting and analyzing data. The systematic analysis and evaluation of the data from the National Solar Data System is reflected in a monthly performance report and a solar energy system performance evaluation report.

Day, R. E.↗
DOE OSTI2023

Semi-Annual Report for Horizontal Compact High Temperature Gas Reactor (HC-HTGR) Development during Performance Period April 2023 – September 2023

Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multi-disciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed HC-HTGR in 3 years and support its commercialization as a safe, low-cost HTGR. Argonne National Laboratory (Argonne) is responsible for the design and analysis of the reactor cavity cooling system (RCCS) as a safety system for passive decay heat removal of the reactor concept. Additionally, Argonne is providing analysis of the primary coolant system to ensure temperatures within the core remain below safety margins during steady-state and potential accident scenarios. This fourth semi-annual report summarized the progress made at Argonne on the two tasks during the second half of FY23. As a part of the RCCS design task, recent efforts have been made to complete a conceptual design of the RCCS for the HC-HTGR, including the design update of the water panel and system configuration favorable in point of view of fabrication and system operation. Design calculations were conducted under various heat load conditions to validate the system design. Transient simulations using RELAP5-3D were conducted to investigate system dynamics under transients of interest and to evaluate the system performance in the design condition. The results demonstrated the overall system feasibility that the RCCS design maintains structures temperatures lower than maximum allowable temperature with sufficient system inventory without any active heat sink. In the primary system thermal hydraulics task, the preliminary analysis was performed for a long term pressurized conduction cooldown (PCC) transient. This analysis used a combination of a fully resolved and coarse homogenized mesh to predict the temperature distribution for the steady-state initial condition and the PCC transient. The steady-state initial condition was determined using a fully resolved full core model with 3D solid to 1D fluid coupling. The fully resolved mesh was also used to model the first 20 seconds of the PCC. The temperature difference between fuel pins and the graphite matrix becomes minimal and the dominant heat transfer shifts to a larger scale radially towards the RCCS. After 20 seconds, a homogenized coarse mesh is used, greatly reducing the computational costs of the model. These results demonstrate that the core is designed to passively remove enough decay heat in a protected loss of primary coolant flow to prevent an unsafe rise of core temperatures.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Electromagnetic control of spin ordered Mn 3 qubits: a density functional study

[Mn 3 O(O 2 CMe)(dpd 3/2 )] 2 is composed of two monomers each of which contain three Mn atoms at the vertices of an equilateral triangle. A full analysis of the electronic and magnetic structure of the dimer shows that each Mn atom carries a local spin of S = 2 while other spin states are energetically much higher. This result suggests application for conventional as well as quantum tasks. A detailed analysis of the electronic and magnetic structure of the monomer, on the other hand, suggests that there are three spin states of S = 1, S = 3/2 and S = 2 per monomer which are energetically competitive. Additionally, we found that while monomer–monomer interactions are very weak, the coupling of monomers via covalent linkers affects both the magnetization and electronic energy levels of monomers. In particular, the isolated monomers prefer a ground state with local spin of S = 1 on Mn atoms and an antiferromagnetically ordered structure while the dimers possess a ground state with local spin of S = 2 on Mn atoms and a ferromagnetically ordered structure. The investigation of the polarizability of both monomer and dimer is examined for antiferromagnetically ordered structures which induces a high dipole moment of 0.08 (a.u.) and 0.16 (a.u.) for monomer and dimer, respectively. The energy of the antiferromagnetic structure is also high compared to other spin-electric molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1991

Technology needs for high speed rotorcraft (3)

The spectrum of vertical takeoff and landing (VTOL) type aircraft is examined to determine which aircraft are most likely to achieve high subsonic cruise speeds and have hover qualities similar to a helicopter. Two civil mission profiles are considered: a 600-n.mi. mission for a 15- and a 30-passenger payload. Applying current technology, only the 15- and 30-passenger tiltfold aircraft are capable of attaining the 450-knot design goal. The two tiltfold aircraft at 450 knots and a 30-passenger tiltrotor at 375 knots were further developed for the Task II technology analysis. A program called High-Speed Total Envelope Proprotor (HI-STEP) is recommended to meet several of these issues based on the tiltrotor concept. A program called Tiltfold System (TFS) is recommended based on the tiltrotor concept. A task is identified to resolve the best design speed from productivity and demand considerations based on the technology that emerges from the recommended programs. HI-STEP's goals are to investigate propulsive efficiency, maneuver loads, and aeroelastic stability. Programs currently in progress that may meet the other technology needs include the Integrated High Performance Turbine Engine Technology (IHPTET) (NASA Lewis) and the Advanced Structural Concepts Program funded through NASA Langley.

Detore, Jack↗
DOE OSTI2022

Opportunities for Recovering Resources from Municipal Wastewater

Municipal wastewater contains valuable resources including water, energy, and nutrients that often enter and leave wastewater treatment plants (WWTPs) without being captured. Currently, plants are increasingly seeking to recover resources and reuse them in a sustainable way. Therefore, the purpose of this project was to assess the potential for recovery and reuse of water and products from municipal wastewater treatment plants across the United States and to examine how this potential varies by region. To accomplish this, three main tasks were set: first, to characterize wastewater treatment plants; second, to characterize technologies and pathways used to recover energy, nutrients, and water from treatment plants; third, to assess the demand for reclaimed resources and products at a regional level by performing spatial analysis. These three tasks were then synthesized to present key findings in this report and a geospatial dataset with the hope of guiding the increased use of resource recovery technologies in the U.S.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

Apollo experience report: Engineering and analysis mission support

The tasks performed by the team of specialists that evaluated hardware performance during prelaunch checkout and in-flight operation are discussed. The organizational structure, operational procedures, and interfaces as well as the facilities and software required to perform these tasks are discussed. The scope of the service performed by the team and the evaluation philosophy are described. Summaries of problems and their resolution are included as appendixes.

Fricke, R. W., Jr.↗
NASA NTRS1982

Environmental isolation task

The failure-analysis process was organized into a more specific set of long-term degradation steps so that material property change can be differentiated from module damage and module failure. Increasing module performance and life are discussed. A polymeric aging computer model is discussed. Early detection of polymer surface reactions due to aging is reported.

Coulbert, C. D.↗
NASA NTRS1987

Model-based analysis of control/display interaction in the hover task

The effect of Control/Display interaction in the hover task is analyzed using an optimal control approach to modeling pilot control behavior. The control/display configurations considered are those previously evaluated in a flight research program. The experimental data-base is reviewed and the procedure for modeling the task and the displayed information is presented in detail. All model-based results, time-domain as well as frequency-domain, are found to correlate extremely well with the subjective pilot ratings and comments. Time-domain measures consist of root mean-square errors and control inputs, attention allocation to displayed quantities, and magnitudes of task objective function. Frequency-domain measures include bandwidth, stability margins, and pilot phase compensation. Results are also shown to agree with previous findings on task interference in multi-axis tasks.

Schmidt, David K.↗
NASA NTRS1992

CRRES experiments, data collection, analysis and publication

The tasks undertaken to be performed under this contract included the continued coordination and documentation of the CRRES program and the development of an archive that details the experimental results obtained by the CRRES Program. Details of the work undertaken and results achieved are summarized in the following sections.

Miller, George P.↗
NASA NTRS1996

Task 7: Endwall treatment inlet flow distortion analysis

The overall objective of this study was to develop a 3-D numerical analysis for compressor casing treatment flowfields, and to perform a series of detailed numerical predictions to assess the effectiveness of various endwall treatments for enhancing the efficiency and stall margin of modern high speed fan rotors. Particular attention was given to examining the effectiveness of endwall treatments to counter the undesirable effects of inflow distortion. Calculations were performed using three different gridding techniques based on the type of casing treatment being tested and the level of complexity desired in the analysis. In each case, the casing treatment itself is modeled as a discrete object in the overall analysis, and the flow through the casing treatment is determined as part of the solution. A series of calculations were performed for both treated and untreated modern fan rotors both with and without inflow distortion. The effectiveness of the various treatments were quantified, and several physical mechanisms by which the effectiveness of endwall treatments is achieved are discussed.

Hall, E. J.↗