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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Visual Computing Environment

The Visual Computing Environment (VCE) is a NASA Lewis Research Center project to develop a framework for intercomponent and multidisciplinary computational simulations. Many current engineering analysis codes simulate various aspects of aircraft engine operation. For example, existing computational fluid dynamics (CFD) codes can model the airflow through individual engine components such as the inlet, compressor, combustor, turbine, or nozzle. Currently, these codes are run in isolation, making intercomponent and complete system simulations very difficult to perform. In addition, management and utilization of these engineering codes for coupled component simulations is a complex, laborious task, requiring substantial experience and effort. To facilitate multicomponent aircraft engine analysis, the CFD Research Corporation (CFDRC) is developing the VCE system. This system, which is part of NASA's Numerical Propulsion Simulation System (NPSS) program, can couple various engineering disciplines, such as CFD, structural analysis, and thermal analysis. The objectives of VCE are to (1) develop a visual computing environment for controlling the execution of individual simulation codes that are running in parallel and are distributed on heterogeneous host machines in a networked environment, (2) develop numerical coupling algorithms for interchanging boundary conditions between codes with arbitrary grid matching and different levels of dimensionality, (3) provide a graphical interface for simulation setup and control, and (4) provide tools for online visualization and plotting. VCE was designed to provide a distributed, object-oriented environment. Mechanisms are provided for creating and manipulating objects, such as grids, boundary conditions, and solution data. This environment includes parallel virtual machine (PVM) for distributed processing. Users can interactively select and couple any set of codes that have been modified to run in a parallel distributed fashion on a cluster of heterogeneous workstations. A scripting facility allows users to dictate the sequence of events that make up the particular simulation.

Lawrence, Charles↗
NASA NTRS1985

User interface enhancement report

The existing user interfaces to TEMPUS, Plaid, and other systems in the OSDS are fundamentally based on only two modes of communication: alphanumeric commands or data input and grapical interaction. The latter are especially suited to the types of interaction necessary for creating workstation objects with BUILD and with performing body positioning in TEMPUS. Looking toward the future application of TEMPUS, however, the long-term goals of OSDS will include the analysis of extensive tasks in space involving one or more individuals working in concert over a period of time. In this context, the TEMPUS body positioning capability, though extremely useful in creating and validating a small number of particular body positions, will become somewhat tedious to use. The macro facility helps somewhat, since frequently used positions may be easily applied by executing a stored macro. The difference between body positioning and task execution, though subtle, is important. In the case of task execution, the important information at the user's level is what actions are to be performed rather than how the actions are performed. Viewed slightly differently, the what is constant over a set of individuals though the how may vary.

Badler, N. I.↗
DOE OSTI2024

Visual feedback and guided balance training in an immersive virtual reality environment for lower extremity rehabilitation

Balance training is essential for physical rehabilitation procedures, as it can improve functional mobility and enhance cognitive coordination. However, conventional balance training methods may have limitations in terms of motivation, real-time objective feedback, and personalization, which a virtual reality (VR) setup may provide a better alternative. In this work, we present an immersive VR training environment for lower extremity balance rehabilitation with real-time guidance and feedback. The VR training environment immerses the user in a 3D ice rink model where a virtual coach (agent) leads them through a series of balance poses, and the user controls a trainee avatar with their own movements. Here we developed two coaching styles: positive-reinforcement and autonomous-supportive, and two viewpoints of the trainee avatar: first-person and third-person. The proposed environment was evaluated in a user study with healthy, non-clinical participants (n = 16, 24.4 ± 5.7 years old, 9 females). Our results show that participants showed stronger performance in the positive-reinforcement style compared to the autonomous-supportive style. Additionally, in the third-person viewpoint, the participants exhibited more stability in the positive-reinforcement style compared to the autonomous-supportive style. For viewpoint, participants exhibited stronger performance in the first-person viewpoint compared to third-person in the autonomous-supportive style, while they were comparable in the positive-reinforcement style. We observed no significant effects on the foot height and number of mistakes. Furthermore, we report the analysis of user performance with balance training poses and subjective measures based on questionnaires to assess the user experience, usability, and task load. The proposed VR balance training could offer an interactive, adaptive, and engaging environment and open new potential research directions for lower extremity rehabilitation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

S AP F LOWER : an automated tool for sap flow data preprocessing, gap-filling, and analysis using deep learning

Sap flow, a critical process in plant water use and ecosystem water cycles, is often measured using thermal dissipation probes (TDP) due to their ease of installation and continuous data collection. However, sap flow data frequently include noise, outliers, and gaps, creating challenges for analysis and requiring substantial manual processing. We developed S AP F LOWER , a tool that automates data preprocessing, model training, gap-filling, sapwood area scaling and modeling, and water use analysis. It integrates autocleaning, machine learning and deep learning models (e.g. random forest, Gaussian process regression, long short-term memory (LSTM), bidirectional LSTM (BiLSTM)), and efficient workflows to process sap flow data. S AP F LOWER can remove over 90% of noisy data while preserving legitimate variations and achieve high accuracy in gap-filling based on user-determined parameters. Random forest, LSTM, and BiLSTM models reduced root mean square error to 10% or less for long-term gaps. Model training and prediction can be performed efficiently within seconds. S AP F LOWER significantly enhances the efficiency and accessibility of TDP data analysis by automating complex tasks, enabling researchers without programming expertise to employ advanced techniques. Future improvements will focus on species-specific corrections for TDP and support for additional measurement methods. S AP F LOWER is openly available on GitHub (https://github.com/JiaxinWang123/SapFlower) and Zenodo (doi: 10.5281/zenodo.13665919).

ecosystem water balance↗
DOE OSTI2014

SU-F-18C-01: Minimum Detectability Analysis for Comprehensive Sized Based Optimization of Image Quality and Radiation Dose Across CT Protocols

Purpose: This work involved a comprehensive modeling of task-based performance of CT across a wide range of protocols. The approach was used for optimization and consistency of dose and image quality within a large multi-vendor clinical facility. Methods: 150 adult protocols from the Duke University Medical Center were grouped into sub-protocols with similar acquisition characteristics. A size based image quality phantom (Duke Mercury Phantom) was imaged using these sub-protocols for a range of clinically relevant doses on two CT manufacturer platforms (Siemens, GE). The images were analyzed to extract task-based image quality metrics such as the Task Transfer Function (TTF), Noise Power Spectrum, and Az based on designer nodule task functions. The data were analyzed in terms of the detectability of a lesion size/contrast as a function of dose, patient size, and protocol. A graphical user interface (GUI) was developed to predict image quality and dose to achieve a minimum level of detectability. Results: Image quality trends with variations in dose, patient size, and lesion contrast/size were evaluated and calculated data behaved as predicted. The GUI proved effective to predict the Az values representing radiologist confidence for a targeted lesion, patient size, and dose. As an example, an abdomen pelvis exam for the GE scanner, with a task size/contrast of 5-mm/50-HU, and an Az of 0.9 requires a dose of 4.0, 8.9, and 16.9 mGy for patient diameters of 25, 30, and 35 cm, respectively. For a constant patient diameter of 30 cm, the minimum detected lesion size at those dose levels would be 8.4, 5, and 3.9 mm, respectively. Conclusion: The designed CT protocol optimization platform can be used to evaluate minimum detectability across dose levels and patient diameters. The method can be used to improve individual protocols as well as to improve protocol consistency across CT scanners.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Modeling Large-Scale Slim Fly Networks Using Parallel Discrete-Event Simulation

As supercomputers approach exascale performance, the increased number of processors translates to an increased demand on the underlying network interconnect. We present that the slim fly network topology, a new low-diameter, low-latency, and low-cost interconnection network, is gaining interest as one possible solution for next-generation supercomputing interconnect systems. In this article, we present a high-fidelity slim fly packet-level model leveraging the Rensselaer Optimistic Simulation System (ROSS) and Co-Design of Exascale Storage (CODES) frameworks. We validate the model with published work before scaling the network size up to an unprecedented 1 million compute nodes and confirming that the slim fly observes peak network throughput at extreme scale. In addition to synthetic workloads, we evaluate large-scale slim fly models with real communication workloads from applications in the Design Forward program with over 110,000 MPI processes. We show strong scaling of the slim fly model on an Intel cluster achieving a peak network packet transfer rate of 2.3 million packets per second and processing over 7 billion discrete events using 128 MPI tasks. Enabled by the strong performance capabilities of the model, we perform a detailed application trace and routing protocol performance study. Lastly, through analysis of metrics such as packet latency, hop count, and congestion, we find that the slim fly network is able to leverage simple minimal routing and achieve the same performance as more complex adaptive routing for tested DOE benchmark applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Next Generation Electromagnetic Pump Analysis Tools (PLM DOC-0005-2188). Final Report

This report provides the broad historical review of EM Pump development and details of MATRIX development under this project. This report summarizes the efforts made to modernize the legacy performance models used in previous EM Pump designs and the improvements made to the analysis tools. This report provides information on Tasks 1, 3, and 4 of the entire project. The research for Task 4 builds upon Task 1: Update EM Pump Databank and Task 3: Modernize the Existing EM Pump Analysis Model, which are summarized within this report. Where research for Task 2: Insulation Materials Development and Evaluation identified parameters applicable to the analysis model with Task 4, the analysis code was updated, and analyses were made for additional materials. The important design variables for the manufacture and operation of an EM Pump that the model improvement can evaluate are: space constraints; voltage capability of insulation system; maximum flux density through iron; flow rate and outlet pressure; efficiency and manufacturability. The development of the next-generation EM Pump analysis tools during this two-year program provides information in three broad areas: Status of analysis model development; Improvements made to older simulations; and Comparison to experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

The Effect of Process History on Grain Boundaries and Dislocation Substructures on Functional Properties of Nb for SRF Cavities: Plastic Formability and Microstructural Evolution. Final report

While much progress has been made in improving the performance of cavities in the past decade, reproducible performance remains elusive. This renewal of “The cost of grain boundaries on the performance of superconducting cavities” examines in further depth the interactions between forming and annealing processes and functional performance at the scale of dislocation substructure and grain boundaries. There are five tasks identified in the renewal, which are: Characterization / analysis of current cavity technology: Effect of deformation, heat treatment, surface treatments, and residual damage on cavity function (Lee and Bieler) Characterization of dislocation mechanisms in single and bicrystals (Bieler) Quantifying effects of impurities and deformation mechanisms in Nb using density functional theory calculations (Solanki) Crystal plasticity constitutive model development (Pourboghrat and Eisenlohr) Modeling and measuring thermal conductivity in thin layers (Wright)

36 MATERIALS SCIENCE↗
DOE OSTI2024

Data Visualization: Augmented Reality

In recent years, there has been an increasing interest in developing new technologies for automated characterization and visualization of condition monitoring data. Augmented Reality (AR) is a technology that is being developed to improve such data visualization. Augmented reality has been defined as a technology that merges virtual and physical components in real-time, and in three dimensions. Wearable, commercially-available AR devices allow onsite engineers and technicians to perform inspection tasks with significantly more available information such as comparisons of past and present sensor and imager data, onsite data analysis and result displays, and various forms of metadata including technical drawings, previous inspection reports and maintenance histories, operation manuals, codes and standards, and holograms representing data analysis results superimposed onto the in situ monitored system.

42 ENGINEERING↗
NASA NTRS1972

Earth resources data analysis system

The Earth Resources Laboratory Data Analysis System provides a valuable research tool in the evaluation of multispectral, radiometric, photographic, and passive microwave imagery data. The system has been in operational use for several months and has performed quite well. Emphasis on versatility of both the hardware and software design facilitates system expansion to many specialized data analysis tasks. The many independent software handlers provide building blocks for major processing programs.

Source record↗
NASA NTRS1978

Design of impact-resistant boron/aluminum large fan blade

The technical program was comprised of two technical tasks. Task 1 encompassed the preliminary boron/aluminum fan blade design effort. Two preliminary designs were evolved. An initial design consisted of 32 blades per stage and was based on material properties extracted from manufactured blades. A final design of 36 blades per stage was based on rule-of-mixture material properties. In Task 2, the selected preliminary blade design was refined via more sophisticated analytical tools. Detailed finite element stress analysis and aero performance analysis were carried out to determine blade material frequencies and directional stresses.

Salemme, C. T.↗
NASA NTRS1982

Multilevel semantic analysis and problem-solving in the flight-domain

The use of knowledge-base architecture and planning control; mechanisms to perform an intelligent monitoring task in the flight domain is addressed. The route level, the trajectory level, and parts of the aerodynamics level are demonstrated. Hierarchical planning and monitoring conceptual levels, functional-directed mechanism rationalization, and using deep-level mechanism models for diagnoses of dependent failures are discussed.

Chien, R. T.↗
NASA NTRS1984

NASA: Model development for human factors interfacing

The results of an intensive literature review in the general topics of human error analysis, stress and job performance, and accident and safety analysis revealed no usable techniques or approaches for analyzing human error in ground or space operations tasks. A task review model is described and proposed to be developed in order to reduce the degree of labor intensiveness in ground and space operations tasks. An extensive number of annotated references are provided.

Smith, L. L.↗
NASA NTRS2003

Comparison of two weighted integration models for the cueing task: linear and likelihood

In a task in which the observer must detect a signal at two locations, presenting a precue that predicts the location of a signal leads to improved performance with a valid cue (signal location matches the cue), compared to an invalid cue (signal location does not match the cue). The cue validity effect has often been explained with a limited capacity attentional mechanism improving the perceptual quality at the cued location. Alternatively, the cueing effect can also be explained by unlimited capacity models that assume a weighted combination of noisy responses across the two locations. We compare two weighted integration models, a linear model and a sum of weighted likelihoods model based on a Bayesian observer. While qualitatively these models are similar, quantitatively they predict different cue validity effects as the signal-to-noise ratios (SNR) increase. To test these models, 3 observers performed in a cued discrimination task of Gaussian targets with an 80% valid precue across a broad range of SNR's. Analysis of a limited capacity attentional switching model was also included and rejected. The sum of weighted likelihoods model best described the psychophysical results, suggesting that human observers approximate a weighted combination of likelihoods, and not a weighted linear combination.

NASA Program Biomedical Research and Countermeasur↗
NASA NTRS2004

Compact Microscope Imaging System With Intelligent Controls Improved

The Compact Microscope Imaging System (CMIS) with intelligent controls is a diagnostic microscope analysis tool with intelligent controls for use in space, industrial, medical, and security applications. This compact miniature microscope, which can perform tasks usually reserved for conventional microscopes, has unique advantages in the fields of microscopy, biomedical research, inline process inspection, and space science. Its unique approach integrates a machine vision technique with an instrumentation and control technique that provides intelligence via the use of adaptive neural networks. The CMIS system was developed at the NASA Glenn Research Center specifically for interface detection used for colloid hard spheres experiments; biological cell detection for patch clamping, cell movement, and tracking; and detection of anode and cathode defects for laboratory samples using microscope technology.

McDowell, Mark↗
NASA NTRS2013

Pilot Workload and Speech Analysis: A Preliminary Investigation

Prior research has questioned the effectiveness of speech analysis to measure the stress, workload, truthfulness, or emotional state of a talker. The question remains regarding the utility of speech analysis for restricted vocabularies such as those used in aviation communications. A part-task experiment was conducted in which participants performed Air Traffic Control read-backs in different workload environments. Participant's subjective workload and the speech qualities of fundamental frequency (F0) and articulation rate were evaluated. A significant increase in subjective workload rating was found for high workload segments. F0 was found to be significantly higher during high workload while articulation rates were found to be significantly slower. No correlation was found to exist between subjective workload and F0 or articulation rate.

Bittner, Rachel M.↗
NASA NTRS1964

The Effect of Information Feedback Upon Psychophysical Judgments

An analysis was made of the role of presentation schedules and information feedback on performance in a forced-choice signal detection task. The experimental results indicate that information feedback facilitates performance, but only for certain presentation schedules. The present study was designed to assess performance in a signal detection task under two conditions of information feedback. In the I-condition, S was told on each trial whether his detection response was correct or incorrect; in the !-condition S was given no feedback regarding the correctness of his response. The task involved a 2-response, forced-choice auditory detection problem. On each trial 2 temporal intervals were defined and S was required to report which interval he believed contained the signal; i. e., in one interval a tone burst in a background of white noise was presented, while the other interval contained only white noise. A trial will be denoted as s1 or s2, depending on whether the signal was embedded in the 1st or 2nd interval; the S's response will be denoted A1 or A2 to indicate which interval he reported contained the signal. The probability of an s1 trial will be denoted as y. In this study two values of y were used (.50 and.75) and, as indicated above, two conditions of information feedback. Thus there were 4 experimental conditions (501, · 50I, 751, 75I); each S was run under all 4 conditions. Method Gaussian noise was presented binaurally in S's headphones throughout a test session and the signal was a 1000-cps sinusoid tone; the tone was presented for 100 msec. including equal fall and rise times of 20 msec. The ratio of signal energy to noise power in a unit bandwidth was 2.9, and was constant throughout the study. The. S was seated before a stimulus display board. On each trial a red warning light was flashed for 100 msec. Two amber lights then came on successively each for 1 sec.; these lights defined the 2 observation intervals. The onset of the signal occurred 500 msec. after the onset of one of the observation intervals. After the second amber light went off, S indicated his response by pressing 1 of 2 wand switches under cards reading "1st interval" and "2nd interval." For the !-condition a green light flashed on above the correct response key after S's response; the green light was omitted in the !-condition. Each trial lasted 6 sec. The S's were 12 male college students with normal hearing. They were run for two practice sessions followed by 20 test sessions. Test sessions were run on consecutive days, 350 trials/day. Each day S ran on 1 of the 4 experimental conditions; in successive 4-day blocks S ran one day on each of the 4 experimental conditions in a random order. Thus, over 20 days each of the experimental conditions was repeated 5 times.

Atkinson, Richard C.↗
DOE OSTI2016

Exploring the Performance of Spark for a Scientific Use Case

We present an evaluation of the performance of a Spark implementation of a classification algorithm in the domain of High Energy Physics (HEP). Spark is a general engine for in-memory, large-scale data processing, and is designed for applications where similar repeated analysis is performed on the same large data sets. Classification problems are one of the most common and critical data processing tasks across many domains. Many of these data processing tasks are both computation- and data-intensive, involving complex numerical computations employing extremely large data sets. We evaluated the performance of the Spark implementation on Cori, a NERSC resource, and compared the results to an untuned MPI implementation of the same algorithm. While the Spark implementation scaled well, it is not competitive in speed to our MPI implementation, even when using significantly greater computational resources.

Sehrish, Saba↗