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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Training to Facilitate Adaptation to Novel Sensory Environments

After spaceflight, the process of readapting to Earth s gravity causes locomotor dysfunction. We are developing a gait training countermeasure to facilitate adaptive responses in locomotor function. Our training system is comprised of a treadmill placed on a motion-base facing a virtual visual scene that provides an unstable walking surface combined with incongruent visual flow designed to train subjects to rapidly adapt their gait patterns to changes in the sensory environment. The goal of our present study was to determine if training improved both the locomotor and dual-tasking ability responses to a novel sensory environment and to quantify the retention of training. Subjects completed three, 30-minute training sessions during which they walked on the treadmill while receiving discordant support surface and visual input. Control subjects walked on the treadmill without any support surface or visual alterations. To determine the efficacy of training, all subjects were then tested using a novel visual flow and support surface movement not previously experienced during training. This test was performed 20 minutes, 1 week, and 1, 3, and 6 months after the final training session. Stride frequency and auditory reaction time were collected as measures of postural stability and cognitive effort, respectively. Subjects who received training showed less alteration in stride frequency and auditory reaction time compared to controls. Trained subjects maintained their level of performance over 6 months. We conclude that, with training, individuals became more proficient at walking in novel discordant sensorimotor conditions and were able to devote more attention to competing tasks.

Bloomberg, J. J.↗
NASA NTRS1991

Human visual performance model for crewstation design

An account is given of a Visibility Modeling Tool (VMT) which furnishes a crew-station designer with the means to assess configurational tradeoffs, with a view to the impact of various options on the unambiguous access of information to the pilot. The interactive interface of the VMT allows the manipulation of cockpit geometry, ambient lighting, pilot ergonomics, and the displayed symbology. Performance data can be displayed in the form of 3D contours into the crewstation graphic model, thereby yielding an indication of the operator's visual capabilities.

Larimer, James↗
DOE OSTI2015

Design Concepts for an Outage Control Center Information Dashboard

The nuclear industry, and the business world in general, is facing a rapidly increasing amount of data to be dealt with on a daily basis. In the last two decades, the steady improvement of data storage devices and means to create and collect data along the way influenced the manner in which we deal with information. Most data is still stored without filtering and refinement for later use. Many functions at a nuclear power plant generate vast amounts of data, with scheduled and unscheduled outages being a prime example of a source of some of the most complex data sets at the plant. To make matters worse, modern information and communications technology is making it possible to collect and store data faster than our ability to use it for making decisions. However, in most applications, especially outages, raw data has no value in itself; instead, managers, engineers and other specialists want to extract the information contained in it. The complexity and sheer volume of data could lead to information overload, resulting in getting lost in data that may be irrelevant to the task at hand, processed in an inappropriate way, or presented in an ineffective way. To prevent information overload, many data sources are ignored so production opportunities are lost because utilities lack the ability to deal with the enormous data volumes properly. Decision-makers are often confronted with large amounts of disparate, conflicting and dynamic information, which are available from multiple heterogeneous sources. Information and communication technologies alone will not solve this problem. Utilities need effective methods to exploit and use the hidden opportunities and knowledge residing in unexplored data resources. Superior performance before, during and after outages depends upon the right information being available at the right time to the right people. Acquisition of raw data is the easy part; instead, it is the ability to use advanced analytical, data processing and data visualization methods to turn the data into reliable information and comprehensible, actionable information. Techniques like data mining, filtering and analysis only work reliably for well-defined and well-understood problems. The path from data to decision is more complex. The ability to communicate knowledge during outages and emergent issues is crucial. This paper presents an approach to turn the unused data into an opportunity: applying principles from semiotics, human factors and visual analytics to transform the traditional way of processing outage data into media that will improve the collective situation awareness, knowledge, decisions, actions and overall performance of the entire outage team, and also support the reliability, quality and overall effectiveness of maintenance work. The application of the proposed visualization methods will become the medium of a semi-automated analytical process where humans and machines cooperate using their respective, distinct capabilities for the most effective results.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

LatticeAnalytics: Strut-Level Visualization and Inspection of Additively Manufactured Lattice Structures

Additive manufacturing (AM) is revolutionizing the production of custom components with complex internal geometries, essential for high-performance applications in diverse fields such as medicine and defense. These AM parts optimize strength while minimizing weight by utilizing internal lattice structures consisting of large quantities of small interconnected struts. However, the complexity of these structures, combined with the challenges of using X-ray Computed Tomography (XCT) data, makes validation of part reliability difficult. This ultimately inhibits the development of novel parts for our collaborating material scientists. Here, we introduce LatticeAnalytics, a novel framework specifically designed for visual inspection of defects in these lattice structures. Our framework offers an end-to-end solution that includes the data management of XCT scans, enables remote access for geographically dispersed teams through a web-based dashboard, and incorporates novel visualizations. Our analysis is facilitated by a coarse alignment between the lattice’s nominal model, a spatial graph, and the XCT data. We employ a simple VR-based approach for fast and rough alignment, followed by an offline registration and identification of the struts. With the nodes and struts aligned and identified in the volume, our framework allows querying of subvolumes containing a single strut at multiple resolutions. This avoids computation over the entire lattice and also allow for easy parallelization of down-stream computations, such as strut-specific metrics. To depict a fast overview of the strut quality, we introduce two innovative visual encodings, crucial for our collaborators’ research in creating novel AM parts: the Contour View and the Roughness Map, which depict critical geometrical and surface features of individual struts in standardized two 2D views. We evaluated the integrated system through expert interviews. The feedback confirms the framework’s practicality and its effectiveness in enhancing current inspection workflows. It solves major bottlenecks for our collaborators, ultimately helping them create novel parts with advanced properties.

Miao, Haichao [Lawrence Livermore National Laborat↗
NASA NTRS2004

Advanced Manufacturing Techniques Demonstrated for Fabricating Developmental Hardware

NASA Glenn Research Center's Engineering Development Division has been working in support of innovative gas turbine engine systems under development by Glenn's Combustion Branch. These one-of-a-kind components require operation under extreme conditions. High-temperature ceramics were chosen for fabrication was because of the hostile operating environment. During the designing process, it became apparent that traditional machining techniques would not be adequate to produce the small, intricate features for the conceptual design, which was to be produced by stacking over a dozen thin layers with many small features that would then be aligned and bonded together into a one-piece unit. Instead of using traditional machining, we produced computer models in Pro/ENGINEER (Parametric Technology Corporation (PTC), Needham, MA) to the specifications of the research engineer. The computer models were exported in stereolithography standard (STL) format and used to produce full-size rapid prototype polymer models. These semi-opaque plastic models were used for visualization and design verification. The computer models also were exported in International Graphics Exchange Specification (IGES) format and sent to Glenn's Thermal/Fluids Design & Analysis Branch and Applied Structural Mechanics Branch for profiling heat transfer and mechanical strength analysis.

Redding, Chip↗
DOE OSTI2014

Application of the Combined Judgmental and Randomly Placed Sampling Method

In the wake of the 2001 anthrax incidents in the United States, there has been considerable discussion about the role of judgmental and probabilistic sampling strategies, particularly in the context of clearance sampling. The Combined Judgmental and Random (CJR) methodology provides a statistical methodology that allows practitioners to leverage information from both judgmental and randomly selected sample locations and then quantify the confidence in negative results. The objective of the CJR sampling design is to demonstrate, with high probability, that a high percentage of the decision area (or population) is acceptable, given that none of the samples are unacceptable. The purpose of this document is to assist practitioners to appropriately use the CJR methodology and to implement this sampling design in Visual Sample Plan (VSP). We begin by defining some fundamental terms. A decision area is the geographical or spatial area (indoor or outdoor) about which practitioners wish to draw a conclusion on the basis of sampling and other relevant information. Decision areas typically include all or part of a building, but they may be any contaminated (or potentially contaminated) area for which characterization or clearance is required. In this report, a statistical sampling approach refers to any sampling approach based on a mathematical or statistical model that provides confidence or probability statements about the decision area. Statistical sampling approaches typically involve taking samples at random locations, or at the nodes of a randomly located grid or lattice that is superimposed on the decision area. The term probabilistic sampling is often used to describe statistical sampling designs that exclusively use randomly located samples. This terminology implies that probabilistic statements can only be made based upon the results of randomly placed samples. However, the CJR method utilizes a Bayesian model that gives rise to a formal probabilistic statement regarding the acceptability of the decision area based upon the information obtained from both judgmental and random samples. Judgmental samples play a vital role in the characterization and clearance process because they include the informed prior belief and expert knowledge of personnel involved in the sampling process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Can You Verifi This? Studying Uncertainty and Decision-Making About Misinformation using Visual Analytics

We describe a novel study of decision-making processes around misinformation on social media. Using a custom-built visual analytic system, we presented users with news content from social media accounts from a variety of news outlets, including outlets engaged in distributing misinformation. We conducted controlled experiments to study decision-making regarding the veracity of these news outlets and tested the role of confirmation bias (the tendency to ignore contradicting information) and uncertainty of information on human decision-making processes. Our findings reveal that the presence of conflicting information, presented to users in the form of cues, impacts the ability to judge the veracity of news in systematic ways. We also find that instructing participants even to explicitly disconfirm given hypotheses does not significantly impact their decision-making regarding misinformation when compared to a control condition. Our findings have the potential to inform the design of visual analytics systems so that they may be used to mitigate the effects of cognitive biases and stymie the spread of misinformation on social media.

misinformation, decision making, social media, vis↗
DOE OSTI2020

Deep Learning for Intelligent Bubble Size Detection in the Spallation Neutron Source Visual Target

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) will undergo proton power upgrade (PPU), increasing the proton beam power from 1.4 MW to 2.8 MW. From 2.8 MW, 2.0 MW will go to the current First Target Station and the rest will go to the future Second Target Station (STS). The First Target Station uses a liquid mercury target that is contained in a 316L stainless steel vessel. The proton beam is pulsed at 60 Hz, with a pulse of about 0.7μs. When the proton beam hits the target, the intense energy deposition leads to a rapid rise in temperature in the mercury. This temperature rise creates pressure waves that propagate through the mercury and cause cavitation erosion. The power upgrade will cause stronger pressure waves that will further increase damage because of cavitation. Injecting small helium bubbles in the mercury has been an efficient method of mitigating the pressure wave at 1.4 MW. However, at higher power, additional mitigation is necessary. Therefore, the 2 MW target vessel will be equipped with swirl bubblers and an additional gas injection port near the nose to inject more gas in the target. To develop a gas injection strategy and design, flow visualization in water with a transparent prototypical target (“visual target”) was performed. Bubble sizes and their spatial distribution in the flow loop are crucial to understanding the effectiveness of the bubbles in mitigating pressure waves. Bubbles were generated in the visual target under varied conditions of input pressures with helium and air. Images were captured using a high-speed camera at varied frame rates at different positions away from the swirl bubbler and different depths in the flow loop under varying lighting conditions. Initially, methods such as circular Hough transforms were applied after a series of images processing to obtain a general distribution of bubble sizes. Bubbles smaller than 500 μm are preferred to effectively mitigate the effect of pressure waves, which demands an accurate bubble detection and sizing system. Intelligent detection and identification of bubble sizes alleviate misdetection and improves accuracies. Employing neural networks, intelligent detection of bubble sizes and their distribution was developed and provides a robust alternative to traditional techniques. Human intervention was employed to label in-focus and out-of-focus bubbles in the set of training images. An object detection network using a pretrained convolutional neural network was created that extracted the features from the training images. Data augmentation was used to improve network accuracy through a random transformation of the original data.

Rasheed, Fayaz↗
DOE OSTI2014

Interface design of VSOP'94 computer code for safety analysis

Today, most software applications, also in the nuclear field, come with a graphical user interface. VSOP'94 (Very Superior Old Program), was designed to simplify the process of performing reactor simulation. VSOP is a integrated code system to simulate the life history of a nuclear reactor that is devoted in education and research. One advantage of VSOP program is its ability to calculate the neutron spectrum estimation, fuel cycle, 2-D diffusion, resonance integral, estimation of reactors fuel costs, and integrated thermal hydraulics. VSOP also can be used to comparative studies and simulation of reactor safety. However, existing VSOP is a conventional program, which was developed using Fortran 65 and have several problems in using it, for example, it is only operated on Dec Alpha mainframe platforms and provide text-based output, difficult to use, especially in data preparation and interpretation of results. We develop a GUI-VSOP, which is an interface program to facilitate the preparation of data, run the VSOP code and read the results in a more user friendly way and useable on the Personal 'Computer (PC). Modifications include the development of interfaces on preprocessing, processing and postprocessing. GUI-based interface for preprocessing aims to provide a convenience way in preparing data. Processing interface is intended to provide convenience in configuring input files and libraries and do compiling VSOP code. Postprocessing interface designed to visualized the VSOP output in table and graphic forms. GUI-VSOP expected to be useful to simplify and speed up the process and analysis of safety aspects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Linear oscillation of gas bubbles in a viscoelastic material under ultrasound irradiation

Acoustically forced oscillation of spherical gas bubbles in a viscoelastic material is studied through comparisons between experiments and linear theory. An experimental setup has been designed to visualize bubble dynamics in gelatin gels using a high-speed camera. A spherical gas bubble is created by focusing an infrared laser pulse into (gas-supersaturated) gelatin gels. The bubble radius (up to 150 μm) under mechanical equilibrium is controlled by gradual mass transfer of gases across the bubble interface. The linearized bubble dynamics are studied from the observation of spherical bubble oscillation driven by low-intensity, planar ultrasound driven at 28 kHz. It follows from the experiment for an isolated bubble that the frequency response in its volumetric oscillation was shifted to the high frequency side and its peak was suppressed as the gelatin concentration increases. The measurement is fitted to the linearized Rayleigh–Plesset equation coupled with the Voigt constitutive equation that models the behavior of linear viscoelastic solids; the fitting yields good agreement by tuning unknown values of the viscosity and rigidity, indicating that more complex phenomena including shear thinning, stress relaxation, and retardation do not play an important role for the small-amplitude oscillations. Moreover, the cases for bubble-bubble and bubble-wall systems are studied. The observed interaction effect on the linearized dynamics can be explained as well by a set of the Rayleigh–Plesset equations coupled through acoustic radiation among these systems. This suggests that this experimental setup can be applied to validate the model of bubble dynamics with more complex configuration such as a cloud of bubbles in viscoelastic materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

SeekAView: An Intelligent Dimensionality Reduction Strategy for Navigating High-Dimensional Data Spaces

Dealing with the curse of dimensionality is a key challenge in high-dimensional data visualization. We present SeekAView to address three main gaps in the existing research literature. First, automated methods like dimensionality reduction or clustering suffer from a lack of transparency in letting analysts interact with their outputs in real-time to suit their exploration strategies. The results often suffer from a lack of interpretability, especially for domain experts not trained in statistics and machine learning. Second, exploratory visualization techniques like scatter plots or parallel coordinates suffer from a lack of visual scalability: it is difficult to present a coherent overview of interesting combinations of dimensions. Third, the existing techniques do not provide a flexible workflow that allows for multiple perspectives into the analysis process by automatically detecting and suggesting potentially interesting subspaces. In SeekAView we address these issues using suggestion based visual exploration of interesting patterns for building and refining multidimensional subspaces. Compared to the state-of-the-art in subspace search and visualization methods, we achieve higher transparency in showing not only the results of the algorithms, but also interesting dimensions calibrated against different metrics. We integrate a visually scalable design space with an iterative workflow guiding the analysts by choosing the starting points and letting them slice and dice through the data to find interesting subspaces and detect correlations, clusters, and outliers. We present two usage scenarios for demonstrating how SeekAView can be applied in real-world data analysis scenarios.

Krause, Josua↗
DOE OSTI2016

Clinical evaluation of a medical high dynamic range display

Purpose: Recent new medical displays do have higher contrast and higher luminance but do not have a High Dynamic Range (HDR). HDR implies a minimum luminance value close to zero. A medical HDR display prototype based on two Liquid Crystal layers has been developed. The goal of this study is to evaluate the potential clinical benefit of such display in comparison with a low dynamic range (LDR) display. Methods: The study evaluated the clinical performance of the displays in a search and detection task. Eight radiologists read chest x-ray images some of which contained simulated lung nodules. The study used a JAFROC (Jacknife Free Receiver Operating Characteristic) approach for analyzing FROC data. The calculated figure of merit (FoM) is the probability that a lesion is rated higher than all rated nonlesions on all images. Time per case and accuracy for locating the center of the nodules were also compared. The nodules were simulated using Samei’s model. 214 CR and DR images [half were “healthy images” (chest nodule-free) and half “diseased images”] were used resulting in a total number of nodules equal to 199 with 25 images with 1 nodule, 51 images with 2 nodules, and 24 images with 3 nodules. A dedicated software interface was designed for visualizing the images for each session. For the JAFROC1 statistical analysis, the study is done per nodule category: all nodules, difficult nodules, and very difficult nodules. Results: For all nodules, the averaged FoM{sub HDR} is slightly higher than FoM{sub LDR} with 0.09% of difference. For the difficult nodules, the averaged FoM{sub HDR} is slightly higher than FoM{sub LDR} with 1.38% of difference. The averaged FoM{sub HDR} is slightly higher than FoM{sub LDR} with 0.71% of difference. For the true positive fraction (TPF), both displays (the HDR and the LDR ones) have similar TPF for all nodules, but looking at difficult and very difficult nodules, there are more TP for the HDR display. The true positive fraction has been also computed in function of the local average luminance around the nodules. For the lowest luminance range, there is more than 30% in favor of the HDR display. For the highest luminance range, there is less than 6% in favor of the LDR display. Conclusions: This study shows the potential benefit of using a HDR display in radiology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

QuickView PRO, QVPRO

QuickView PRO (QVPRO) is similar to QuickView but designed to focus on analysis. QuickView was designed for visualization only, adding analysis capabilities later. This made QuickView complicated when using it as an analysis tool. QVPRO uses the same analysis algorithms in a more streamlined workflow and has a user friendly GUI. QVPRO provides the unique capability of analyzing Photonic Doppler Velocimetry (PDV) data records from different PDV systems and still allows for processing hundreds of PDV data records in a practical manner.

Diaz, AbelB↗
DOE OSTI2026

pnnl/HADREC (33077-E)

This HADREC GUI is designed to visualize power system emergency control time-series data and facilitate the comparison of the newly developed meta strategy optimization algorithm-based emergency control with existing out-of-step-based emergency control approach, and a no-action case for reference.

Wang, Heng [Pacific Northwest National Laboratory ↗
DOE OSTI2016

A novel analysis method for paired-sample microbial ecology experiments

Many microbial ecology experiments use sequencing data to measure a community s response to an experimental treatment. In a common experimental design, two units, one control and one experimental, are sampled before and after the treatment is applied to the experimental unit. The four resulting samples contain information about the dynamics of organisms that respond to the treatment, but there are no analytical methods designed to extract exactly this type of information from this configuration of samples. Here we present an analytical method specifically designed to visualize and generate hypotheses about microbial community dynamics in experiments that have paired samples and few or no replicates. The method is based on the Poisson lognormal distribution, long studied in macroecology, which we found accurately models the abundance distribution of taxa counts from 16S rRNA surveys. To demonstrate the method s validity and potential, we analyzed an experiment that measured the effect of crude oil on ocean microbial communities in microcosm. Our method identified known oil degraders as well as two clades, Maricurvus and Rhodobacteraceae, that responded to amendment with oil but do not include known oil degraders. Furthermore, our approach is sensitive to organisms that increased in abundance only in the experimental unit but less sensitive to organisms that increased in both control and experimental units, thus mitigating the role of bottle effects .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

A Pervasive Parallel Processing Framework for Data Visualization and Analysis at Extreme Scale

The evolution of the computing world from teraflop to petaflop has been relatively effortless, with several of the existing programming models scaling effectively to the petascale. The migration to exascale, however, poses considerable challenges. All industry trends infer that the exascale machine will be built using processors containing hundreds to thousands of cores per chip. It can be inferred that efficient concurrency on exascale machines requires a massive amount of concurrent threads, each performing many operations on a localized piece of data. Currently, visualization libraries and applications are based off what is known as the visualization pipeline. In the pipeline model, algorithms are encapsulated as filters with inputs and outputs. These filters are connected by setting the output of one component to the input of another. Parallelism in the visualization pipeline is achieved by replicating the pipeline for each processing thread. This works well for today’s distributed memory parallel computers but cannot be sustained when operating on processors with thousands of cores. Our project investigates a new visualization framework designed to exhibit the pervasive parallelism necessary for extreme scale machines. Our framework achieves this by defining algorithms in terms of worklets, which are localized stateless operations. Worklets are atomic operations that execute when invoked unlike filters, which execute when a pipeline request occurs. The worklet design allows execution on a massive amount of lightweight threads with minimal overhead. Only with such fine-grained parallelism can we hope to fill the billions of threads we expect will be necessary for efficient computation on an exascale machine.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Verification of RESRAD-RDD. (Version 2.01)

In this report, the results generated by RESRAD-RDD version 2.01 are compared with those produced by RESRAD-RDD version 1.7 for different scenarios with different sets of input parameters. RESRAD-RDD version 1.7 is spreadsheet-driven, performing calculations with Microsoft Excel spreadsheets. RESRAD-RDD version 2.01 revamped version 1.7 by using command-driven programs designed with Visual Basic.NET to direct calculations with data saved in Microsoft Access database, and re-facing the graphical user interface (GUI) to provide more flexibility and choices in guideline derivation. Because version 1.7 and version 2.01 perform the same calculations, the comparison of their results serves as verification of both versions. The verification covered calculation results for 11 radionuclides included in both versions: Am-241, Cf-252, Cm-244, Co-60, Cs-137, Ir-192, Po-210, Pu-238, Pu-239, Ra-226, and Sr-90. At first, all nuclide-specific data used in both versions were compared to ensure that they are identical. Then generic operational guidelines and measurement-based radiation doses or stay times associated with a specific operational guideline group were calculated with both versions using different sets of input parameters, and the results obtained with the same set of input parameters were compared. A total of 12 sets of input parameters were used for the verification, and the comparison was performed for each operational guideline group, from A to G, sequentially. The verification shows that RESRAD-RDD version 1.7 and RESRAD-RDD version 2.01 generate almost identical results; the slight differences could be attributed to differences in numerical precision with Microsoft Excel and Visual Basic.NET. RESRAD-RDD version 2.01 allows the selection of different units for use in reporting calculation results. The results of SI units were obtained and compared with the base results (in traditional units) used for comparison with version 1.7. The comparison shows that RESRAD-RDD version 2.01 correctly reports calculation results in the unit specified in the GUI.

54 ENVIRONMENTAL SCIENCES↗