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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Comparing capacity coefficient and dual task assessment of visual multitasking workload

Capacity coefficient analysis could offer a theoretically grounded alternative approach to subjective measures and dual task assessment of cognitive workload. Workload capacity or workload efficiency is a human information processing modeling construct defined as the amount of information that can be processed by the visual cognitive system given a specified of amount of time. In this paper, I explore the relationship between capacity coefficient analysis of workload efficiency and dual task response time measures. To capture multitasking performance, I examine how the relatively simple assumptions underlying the capacity construct generalize beyond the single visual decision making tasks. The fundamental tools for measuring workload efficiency are the integrated hazard and reverse hazard functions of response times, which are defined by log transforms of the response time distribution. These functions are used in the capacity coefficient analysis to provide a functional assessment of the amount of work completed by the cognitive system over the entire range of response times. For the study of visual multitasking, capacity coefficient analysis enables a comparison of visual information throughput as the number of tasks increases from one to two to any number of simultaneous tasks. I illustrate the use of capacity coefficients for visual multitasking on sample data from dynamic multitasking in the modified Multi-attribute Task Battery.

capacity coefficient↗
DOE OSTI2014

Uveal Melanoma Treated With Iodine-125 Episcleral Plaque: An Analysis of Dose on Disease Control and Visual Outcomes

Purpose: To investigate, in the treatment of uveal melanomas, how tumor control, radiation toxicity, and visual outcomes are affected by the radiation dose at the tumor apex. Methods and Materials: A retrospective review was performed to evaluate patients treated for uveal melanoma with {sup 125}I plaques between 1988 and 2010. Radiation dose is reported as dose to tumor apex and dose to 5 mm. Primary endpoints included time to local failure, distant failure, and death. Secondary endpoints included eye preservation, visual acuity, and radiation-related complications. Univariate and multivariate analyses were performed to determine associations between radiation dose and the endpoint variables. Results: One hundred ninety patients with sufficient data to evaluate the endpoints were included. The 5-year local control rate was 91%. The 5-year distant metastases rate was 10%. The 5-year overall survival rate was 84%. There were no differences in outcome (local control, distant metastases, overall survival) when dose was stratified by apex dose quartile (<69 Gy, 69-81 Gy, 81-89 Gy, >89 Gy). However, increasing apex dose and dose to 5-mm depth were correlated with greater visual acuity loss (P=.02, P=.0006), worse final visual acuity (P=.02, P<.0001), and radiation complications (P<.0001, P=.0009). In addition, enucleation rates were worse with increasing quartiles of dose to 5 mm (P=.0001). Conclusions: Doses at least as low as 69 Gy prescribed to the tumor apex achieve rates of local control, distant metastasis–free survival, and overall survival that are similar to radiation doses of 85 Gy to the tumor apex, but with improved visual outcomes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Multiscale modeling and cinematic visualization of photosynthetic energy conversion processes from electronic to cell scales

We report conversion of sunlight into chemical energy, namely photosynthesis, is the primary energy source of life on Earth. A visualization depicting this process, based on multiscale computational models from electronic to cell scales, is presented in the form of an excerpt from the fulldome show Birth of Planet Earth. This accessible visual narrative shows a lay audience, including children, how the energy of sunlight is captured, converted, and stored through a chain of proteins to power living cells. The visualization is the result of a multi-year collaboration among biophysicists, visualization scientists, and artists, which, in turn, is based on a decade-long experimental-computational collaboration on structural and functional modeling that produced an atomic detail description of a bacterial bioenergetic organelle, the chromatophore. Software advancements necessitated by this project have led to significant performance and feature advances, including hardware-accelerated cinematic ray tracing and instanced visualizations for efficient cell-scale modeling. The energy conversion steps depicted feature an integration of function from electronic to cell levels, spanning nearly 12 orders of magnitude in time scales. This atomic detail description uniquely enables a modern retelling of one of humanity’s earliest stories—the interplay between light and life.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

A novel immunofluorescence method to visualize microtubules in the antiparallel overlaps of microtubule-plus ends in the anaphase and telophase midzone

Cell division, in which duplicated chromosomes are separated into two daughter cells, is the most dynamic event during cell proliferation. Chromosome movement is powered mainly by microtubules, which vary in morphology and are organized into characteristic structures according to mitotic progression. During the later stages of mitosis, antiparallel microtubules form the spindle midzone, and the irregular formation of the midzone often leads to failure of cytokinesis, giving rise to the unequal segregation of chromosomes. However, it is difficult to analyze the morphology of these microtubules because microtubules in the antiparallel overlaps of microtubule-plus ends in the midzone are embedded in highly electron-dense matrices, impeding the access of anti-tubulin antibodies to their epitopes during immunofluorescence staining. Here, we developed a novel method to visualize selectively antiparallel microtubule overlaps in the midzone. When cells are air-dried before fixation, aligned α-tubulin staining is observed and colocalized with PRC1 in the center of the midzone of anaphase and telophase cells, suggesting that antiparallel microtubule overlaps can be visualized by this method. In air-dried cells, mCherry-α-tubulin fluorescence and β-tubulin staining show almost the same pattern as α-tubulin staining in the midzone, suggesting that the selective visualization of antiparallel microtubule overlaps in air-dried cells is not attributed to an alteration of the antigenicity of α-tubulin. Taxol treatment extends the microtubule filaments of the midzone in air-dried cells, and nocodazole treatment conversely decreases the number of microtubules, suggesting that unstable microtubules are depolymerized during the air-drying method. It is of note that the air-drying method enables the detection of the disruption of the midzone and premature midzone formation upon Aurora B and Plk1 inhibition, respectively. These results suggest that the air-drying method is suitable for visualizing microtubules in the antiparallel overlaps of microtubule-plus ends of the midzone and for detecting their effects on midzone formation. - Highlights: • A novel method to visualize antiparallel microtubule overlaps is developed. • Unstable microtubules are depolymerized during an air-drying method. • This method can detect the effect of compounds on antiparallel microtubule overlaps.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

PSpecteR: A User-Friendly and Interactive Application for Visualizing Top-Down and Bottom-Up Proteomics Data in R

Visual examination of mass spectrometry data is necessary to assess data quality and to facilitate data exploration. Graphics provide the means to evaluate spectral properties, test alternative peptide/protein sequence matches, prepare annotated spectra for publication, and fine-tune parameters during wet lab procedures. Visual inspection of MS data is hindered by proprietary proteomics visualization software designed for particular workflows and academic software that lack visualization tools. We built PSpecteR, an open-source and interactive R Shiny web application to address these issues, with support for several steps of proteomics data processing, including: reading various mass spectrometry files, running open-source database search tools, labelling spectra with fragmentation patterns, testing post-translational modifications, plotting where identified fragments map to reference sequences, and visualizing algorithmic output and metadata. All figures, tables, and spectra are exportable within one easy-to-use graphical user interface. Our current software provides a flexible and modern R framework to support fast implementation of additional features. The open source code is readily available (https://github.com/EMSL-Computing/PSpecteR), and a PSpecteR Docker container (https://hub.docker.com/r/emslcomputing) is available for easy local installation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2017

Integrating Visualization Applications, such as ParaView, into HEP Software Frameworks for In-situ Event Displays

ParaView is a high performance visualization application not widely used in High Energy Physics (HEP). It is a long standing open source project led by Kitware and involves several Department of Energy (DOE) and Department of Defense (DOD) laboratories. Futhermore, it has been adopted by many DOE supercomputing centers and other sites. ParaView is unique in speed and efficiency by using state-of-the-art techniques developed by the academic visualization community that are often not found in applications written by the HEP community. In-situ visualization of events, where event details are visualized during processing/analysis, is a common task for experiment software frameworks. Kitware supplies Catalyst, a library that enables scientific software to serve visualization objects to client ParaView viewers yielding a real-time event display. Connecting ParaView to the Fermilab art framework will be described and the capabilities it brings discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

PanViz: interactive visualization of the structure of functionally annotated pangenomes

Summary: PanViz is a novel, interactive, visualization tool for pangenome analysis. PanViz allows visualization of changes in gene group (groups of similar genes across genomes) classification as different subsets of pangenomes are selected, as well as comparisons of individual genomes to pangenomes with gene ontology based navigation of gene groups. Furthermore it allows for rich and complex visual querying of gene groups in the pangenome. PanViz visualizations require no external programs and are easily sharable, allowing for rapid pangenome analyses. Availability and Implementation: PanViz is written entirely in JavaScript and is available on https:// github.com/thomasp85/PanViz. A companion R package that facilitates the creation of PanViz visualizations from a range of data formats is released through Bioconductor and is available at https:// bioconductor.org/packages/PanViz Generator.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Visualization System for Evolutionary Neural Networks for Deep Learning

Deep learning is actively used in a wide range of fields for scientific discovery. To effectively apply deep learning to a particular problem, it is important to select an appropriate network architecture and other hyper-parameters (at each layer). Evolving architectures and hyper-parameters using a genetic algorithm is one current approach to search the huge space of all possible configurations to find those more optimal for the problem. However, examining an evolutionary process and tuning the genetic algorithm are challenging, pushing most users to treat the process as a black box. To address this challenge, we propose a visualization system for evolutionary neural networks for deep learning. The key feature of our visualization system is to provide a visual analytics environment for evaluating a genetic algorithm in order to improve the underlying operations to reduce time to find good solutions. Our system is able to not only visualize how a genetic algorithm traverses its search space but also allows users to examine evolving networks in-depth to get insights to improve performance through interactive visualization components.

Chae, Junghoon↗
DOE OSTI2019

Low-Overhead In Situ Visualization Using Halo Replay

In situ visualization and analysis is of increasing importance as the compute and I/O gap further widens with the advance to exascale capable computing. Yet, in situ methods impose resource constraints leading to the difficult task of balancing simulation code performance and the quality of analysis. Applications with tightly-coupled in situ visualization often achieve performance through spatial and temporal downsampling, a tradeoff which risks not capturing transient phenomena at sufficient fidelity. Determining a priori visualization parameters such as sampling rate is difficult without time and resource intensive experimentation. We present a method for reducing resource contention between in situ visualization and stencil codes on heterogeneous systems. This method permits full resolution replay through recording halos and the communication-free reconstruction of interior values uncoupled from the main simulation. We apply this method in the computational fluid dynamics (CFD) code HARVEY [1] on the Summit supercomputer. We demonstrate minimal-overhead, in situ visualization relative to simulation alone, and compare the Halo Replay performance to tightly-coupled in situ approaches.

Ames, Jeff↗
DOE OSTI2024

LossLens: Diagnostics for Machine Learning Through Loss Landscape Visual Analytics

Modern machine learning often relies on optimizing a neural network's parameters using a loss function to learn complex features. Beyond training, examining the loss function with respect to a network's parameters (i.e., as a loss landscape) can reveal insights into the architecture and learning process. While the local structure of the loss landscape surrounding an individual solution can be characterized using a variety of approaches, the global structure of a loss landscape, which includes potentially many local minima corresponding to different solutions, remains far more difficult to conceptualize and visualize. To address this difficulty, we introduce LossLens, a visual analytics framework that explores loss landscapes at multiple scales. LossLens integrates metrics from global and local scales into a comprehensive visual representation, enhancing model diagnostics. Here we demonstrate LossLens through two case studies: visualizing how residual connections influence a ResNet-20, and visualizing how physical parameters influence a physics-informed neural network (PINN) solving a simple convection problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Efficient Probabilistic Visualization of Local Divergence of 2D Vector Fields with Independent Gaussian Uncertainty

This work focuses on visualizing uncertainty of local divergence of two-dimensional vector fields. Divergence is one of the fundamental attributes of fluid flows, as it can help domain scientists analyze potential positions of sources (positive divergence) and sinks (negative divergence) in the flow. However, uncertainty inherent in vector field data can lead to erroneous divergence computations, adversely impacting downstream analysis. While Monte Carlo (MC) sampling is a classical approach for estimating divergence uncertainty, it suffers from slow convergence and poor scalability with increasing data size and sample counts. Thus, we present a two-fold contribution that tackles the challenges of slow convergence and limited scalability of the MC approach. (1) We derive a closed-form approach for highly efficient and accurate uncertainty visualization of local divergence, assuming independently Gaussian-distributed vector uncertainties. (2) We further integrate our approach into Viskores, a platform-portable parallel library, to accelerate uncertainty visualization. In our results, we demonstrate significantly enhanced efficiency and accuracy of our serial analytical (speed-up up to 1946×) and parallel Viskores (speed-up up to 19698×) algorithms over the classical serial MC approach. We also demonstrate qualitative improvements of our probabilistic divergence visualizations over traditional mean-field visualization, which disregards uncertainty. We validate the accuracy and efficiency of our methods on wind forecast and ocean simulation datasets.

Ouermi, Timbwaoga [University of Utah]↗
DOE OSTI2014

SU-E-J-196: New Visualization Methods for Longitudinal MRI Registrations and Segmentations

Purpose: To develop visualization techniques to facilitate easy assessment of (a) registration and (b) tracking volumetric changes in structures during radiation therapy from MRI. Method: The frequently used method for visualizing registrations between scans is a multi-color overlay technique or deformation vector fields. However, the overlay technique is unintuitive and does not help to appreciate the quality of registration particularly when the registration mismatches are not very large. Similarly, the deformation fields give an indication of extent of deformation but do not help to assess the differences in registration. We present a mirroring and edge-augmented mirroring technique that places the fixed and moving image next to each other and allows the user to quickly assess the small differences in registration. Next, we present a volumetric intersection based 3D model to visualize the changes in diseased lymph node volumes in head and neck cancer. 3D model-based visualization provides more information about the location-specific changes in volume rather than the simplistic one dimensional information obtained from 2D plot of nodal volume changes. Result: We show results comparing our approach with the standard colorbased overlay method for comparing registrations of intra-patient registrations using T2-MRI. Upon comparing the mirroring technique with the color-overlay, one can more easily appreciate the differences in registration. Adding edge-based mirroring seems to further assist in evaluating the registration. Our approach for viewing registrations seems to be more intuitive and easy to use in order to help assess the quality of registration compared to color-based overlays. Similarly, the change volumetric model together with a 2D plot reveals more information including the locations undergoing changes and responding to treatment. Conclusions: Better approaches are necessary for assessing the quality of registrations and changes in diseased structures over time. Our approach presents some novel visualization solutions for registration and segmentation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Web-based, GPU-accelerated, Monte Carlo simulation and visualization of indirect radiation imaging detector performance

Purpose: Monte Carlo simulations play a vital role in the understanding of the fundamental limitations, design, and optimization of existing and emerging medical imaging systems. Efforts in this area have resulted in the development of a wide variety of open-source software packages. One such package, hybridMANTIS, uses a novel hybrid concept to model indirect scintillator detectors by balancing the computational load using dual CPU and graphics processing unit (GPU) processors, obtaining computational efficiency with reasonable accuracy. In this work, the authors describe two open-source visualization interfaces, webMANTIS and visualMANTIS to facilitate the setup of computational experiments via hybridMANTIS. Methods: The visualization tools visualMANTIS and webMANTIS enable the user to control simulation properties through a user interface. In the case of webMANTIS, control via a web browser allows access through mobile devices such as smartphones or tablets. webMANTIS acts as a server back-end and communicates with an NVIDIA GPU computing cluster that can support multiuser environments where users can execute different experiments in parallel. Results: The output consists of point response and pulse-height spectrum, and optical transport statistics generated by hybridMANTIS. The users can download the output images and statistics through a zip file for future reference. In addition, webMANTIS provides a visualization window that displays a few selected optical photon path as they get transported through the detector columns and allows the user to trace the history of the optical photons. Conclusions: The visualization tools visualMANTIS and webMANTIS provide features such as on the fly generation of pulse-height spectra and response functions for microcolumnar x-ray imagers while allowing users to save simulation parameters and results from prior experiments. The graphical interfaces simplify the simulation setup and allow the user to go directly from specifying input parameters to receiving visual feedback for the model predictions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

SU-E-J-214: MR Protocol Development to Visualize Sirius MRI Markers in Prostate Brachytherapy Patients for MR-Based Post-Implant Dosimetry

Purpose: The current CT-based post-implant dosimetry allows precise seed localization but limited anatomical delineation. Switching to MR-based post-implant dosimetry is confounded by imprecise seed localization. One approach is to place positive-contrast markers (Sirius) adjacent to the negative-contrast seeds. This patient study aims to assess the utility of a 3D fast spoiled gradient-recalled echo (FSPGR) sequence to visualize Sirius markers for post-implant dosimetry. Methods: MRI images were acquired in prostate implant patients (n=10) on Day 0 (day-of-implant) and Day 30. The post-implant MR protocol consisted of 3D T2-weighted fast-spin-echo (FSE), T2-weighted 2D-FSE (axial) and T1-weighted 2D-FSE (axial/sagittal/coronal). We incorporated a 3D-FSPGR sequence into the post-implant MR protocol to visualize the Sirius markers. Patients were scanned with different number-of-excitations (6, 8, 10), field-of-view (10cm, 14cm, 18cm), slice thickness (1mm, 0.8mm), flip angle (14 degrees, 20 degrees), bandwidth (122.070 Hz/pixel, 325.508 Hz/pixel, 390.625 Hz/pixel), phase encoding steps (160, 192, 224, 256), frequency-encoding direction (right/left, anterior/posterior), echo-time type (minimum-full, out-of-phase), field strength (1.5T, 3T), contrast (with, without), scanner vendor (Siemens, GE), coil (endorectal-coil only, endorectal-and-torso-coil, torsocoil only), endorectal-coil filling (30cc, 50cc) and endorectal-coil filling type (air, perfluorocarbon [PFC]). For post-implant dosimetric evaluation with greater anatomical detail, 3D-FSE images were fused with 3D-FSPGR images. For comparison with CT-based post-implant dosimetry, CT images were fused with 3D-FSPGR images. Results: The 3D-FSPGR sequence facilitated visualization of markers in patients. Marker visualization helped distinguish signal voids as seeds versus needle tracks for more definitive MR-based post-implant dosimetry. On the CT-MR fused images, the distance between the seed on CT to MR images was 3.2±1.6mm in patients with no endorectal coil, 2.3±0.8mm in patients with 30cc-PFC-filled endorectal-coil and 5.0±1.8mm in patients with 50cc-PFC-filled endorectal-coil. Conclusion: An MR protocol to visualize positive-contrast Sirius markers to assist in the identification of negative-contrast seeds was demonstrated. S Frank is a co-founder of C4 Imaging LLC, the manufacturer of the MRI markers.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

ParaView Catalyst: Enabling In Situ Data Analysis and Visualization

Computer simulations are growing in sophistication and producing results of ever greater fidelity. This trend has been enabled by advances in numerical methods and increasing computing power. However these advances come with several costs including massive increases in data size, difficulties examining output data, challenges in configuring simulation runs, and difficulty debugging running codes. Interactive visualization tools, like ParaView, have been used for post-processing of simulation results. However, the increasing data sizes, and limited storage and bandwidth make high fidelity post-processing impractical. In situ analysis is recognized as one of the ways to address these challenges. In situ analysis moves some of the post-processing tasks in line with the simulation code thus short circuiting the need to communicate the data between the simulation and analysis via storage. ParaView Catalyst is a data processing and visualization library that enables in situ analysis and visualization. Built on and designed to interoperate with the standard visualization toolkit VTK and the ParaView application, Catalyst enables simulations to intelligently perform analysis, generate relevant output data, and visualize results concurrent with a running simulation. Here, we provide an overview of the Catalyst framework and some of the success stories.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

In Situ Visualization of Radiation Transport Geometry

The ultimate goal for radiation transport is to perform full-core reactor modelling and simulation. Advances in computational simulation bring this goal close to reality and the newest Monte Carlo transport codes have begun to shift to using accelerators that have become a stalwart in the supercomputing and HPC space. Within the reactor modelling and simulation community, Monte Carlo transport simulations are considered the gold standard for simulation. Through the use of "combinatorial geometry" (constructive solid geomtry), complex models can be used with fewer approximation compromises while at the same time scale to run on some of the largest supercomputers in the world.Unfortunately, the state-of-the-art for "combinatorial geometry" visualization is to decompose the geometry into a mesh. This approach could require a significant amount of memory which is antithetical to in situ visualization. To address this issue, we introduce a ray caster for visualizing combinatorial geometry in radiation transport code. By only using the accelerators for the radiation transport code and leaving the CPU cores idle, there is an opportunity to conduct on node in situ visualization with the idle CPU cores, something domain experts have up to this point been unable to do. By utilizing VTK-m, the visualization can be run on the CPU as this particular application demands, but also run on any architecture that is supported by VTK-m, enabling future re-use across different platforms.

Kim, Mark B.↗
DOE OSTI2021

TangibleData: Interactive Data Visualization with Mid-Air Haptics

In this paper, we investigate the effects of mid-air haptics in interactive 3D data visualization. We build an interactive 3D data visualization tool that adapts hand gestures and mid-air haptics to provide tangible interaction in VR using ultrasound haptic feedback on 3D data visualization. We consider two types of 3D visualization datasets and provide different data encoding methods for haptic representations. Two user experiments are conducted to evaluate the effectiveness of our approach. The first experimental results show that adding a mid-air haptic modality can be beneficial regardless of noise conditions and useful for handling occlusion or discerning density and volume information. The second experiment results further show the strengths and weaknesses of direct touch and indirect touch modes. Our findings can shed light on designing and implementing a tangible interaction on 3D data visualization with mid-air haptic feedback.

Bhardwaj, Ayush↗
DOE OSTI2014

Parallel analysis tools and new visualization techniques for ultra-large climate data set

ParVis was a project funded under LAB 10-05: “Earth System Modeling: Advanced Scientific Visualization of Ultra-Large Climate Data Sets”. Argonne was the lead lab with partners at PNNL, SNL, NCAR and UC-Davis. This report covers progress from January 1st, 2013 through Dec 1st, 2014. Two previous reports covered the period from Summer, 2010, through September 2011 and October 2011 through December 2012, respectively. While the project was originally planned to end on April 30, 2013, personnel and priority changes allowed many of the institutions to continue work through FY14 using existing funds. A primary focus of ParVis was introducing parallelism to climate model analysis to greatly reduce the time-to-visualization for ultra-large climate data sets. Work in the first two years was conducted on two tracks with different time horizons: one track to provide immediate help to climate scientists already struggling to apply their analysis to existing large data sets and another focused on building a new data-parallel library and tool for climate analysis and visualization that will give the field a platform for performing analysis and visualization on ultra-large datasets for the foreseeable future. In the final 2 years of the project, we focused mostly on the new data-parallel library and associated tools for climate analysis and visualization.

54 ENVIRONMENTAL SCIENCES↗