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Results for “high performance visualization”

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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Design and evaluation of single and dual flow thrust vector nozzles with post exit vanes

This Thrust Vectored Research project required that a 1/24 scale model of the F/A-18 High Alpha Research Vehicle, (HARV), propulsion system be constructed on the university campus. This propulsion system was designed for cold flow testing on a multicomponent test rig. Forces and moments were measured to study nozzle performance parameters. The flow visualization technique of color Schlieren photography was performed to investigate the flow phenomena at the nozzle exit. The flow interactions that were identified consisted of vane nozzleing between the outer and lower vanes and vane tip interference. The thrust vectoring system consisted of three asymmetrically spaced vanes installed circumferentially on a maximum afterburner nozzle. The performance of the nozzle was investigated with the outer and lower vanes equally deflected, (-10 deg is less than delta(sub v) is less than 25 deg), and with the upper vane fully retracted, (delta(sub v) equals -10 deg). The nozzle pressure ratio ranged from 4 to 6. The results indicated that a vane nozzleing effect developed at nozzle pressure ratios of 4 and 6 when the outer and lower vanes were deflected far enough into the flow field such that the increase in vane area accelerated the flow past the vanes causing distorted shock waves. This accelerated flow was a result of a pressure differential existing between the inside surface of the vane and the ambient pressure. The stagnation pressure that developed along the inside surface of the vane accelerated the flow past the vanes causing it to equalize with ambient pressure, thus providing distorted shock waves. A tip interference was present at the trailing edge of the upper vane as a result of low nozzle pressure, NPR 4, with high vane deflection, delta(sub v) equals 25 degrees, and also with a high nozzle pressure, NPR 6, and low vane deflections, delta(sub v) equals 15 degrees.

Carpenter, Thomas W.↗
DOE OSTI2021

Stable, high-performance, dendrite-free, seawater-based aqueous batteries

Metal anode instability, including dendrite growth, metal corrosion, and hetero-ions interference, occurring at the electrolyte/electrode interface of aqueous batteries, are among the most critical issues hindering their widespread use in energy storage. Herein, a universal strategy is proposed to overcome the anode instability issues by rationally designing alloyed materials, using Zn-M alloys as model systems (M = Mn and other transition metals). An in-situ optical visualization coupled with finite element analysis is utilized to mimic actual electrochemical environments analogous to the actual aqueous batteries and analyze the complex electrochemical behaviors. The Zn-Mn alloy anodes achieved stability over thousands of cycles even under harsh electrochemical conditions, including testing in seawater-based aqueous electrolytes and using a high current density of 80 mA cm –2 . The proposed design strategy and the in-situ visualization protocol for the observation of dendrite growth set up a new milestone in developing durable electrodes for aqueous batteries and beyond.

25 ENERGY STORAGE↗
DOE OSTI2015

Mapping Metals Incorporation of a Whole Single Catalyst Particle Using Element Specific X-ray Nanotomography

Full-field transmission X-ray microscopy has been used to determine the 3D structure of a whole individual fluid catalytic cracking (FCC) particle at high spatial resolution and in a fast, noninvasive manner, maintaining the full integrity of the particle. Using X-ray absorption mosaic imaging to combine multiple fields of view, computed tomography was performed to visualize the macropore structure of the catalyst and its availability for mass transport. We mapped the relative spatial distributions of Ni and Fe using multiple-energy tomography at the respective X-ray absorption K-edges and correlated these distributions with porosity and permeability of an equilibrated catalyst (E-cat) particle. Both metals were found to accumulate in outer layers of the particle, effectively decreasing porosity by clogging of pores and eventually restricting access into the FCC particle.

02 PETROLEUM↗
DOE OSTI2022

Sim-Situ: A Framework for the Faithful Simulation of in situ Processing

The amount of data generated by numerical simulations in various scientific domains led to a fundamental redesign of how the analysis and visualization of simulation outputs are performed. The throughput and capacity of storage subsystems have not evolved as fast as the computing power in extreme-scale supercomputers, making the classical post-hoc approach highly inefficient. In situ processing has then emerged as a solution in which simulation and data analysis/visualization are intertwined for better performance and greater interactivity.Determining the best allocation, i.e., how many resources to allocate to simulation and analysis respectively, mapping, i.e., where and at which frequency to run the analysis/visualization, and data transfer mode is a complex task whose performance assessment is crucial to the efficient execution of in situ processing. However, such a performance evaluation of different strategies usually relies either on directly running them on the targeted execution environments, which can rapidly become extremely time- and resource-consuming, or on resorting to simplified models of the components of an in situ application, which can lack of realism. In both cases, the validity of the performance evaluation is limited.In this paper, we present Sim-Situ, a simulation-based framework for the faithful performance evaluation of in situ processing strategies. We designed Sim-Situ to reflect the typical features of in situ processing systems. Thanks to its modular design, Sim-situ has the necessary flexibility to easily and faithfully evaluate the behavior and performance of various allocation, mapping, and data transfer strategies. We illustrate the simulation capabilities of Sim-Situ on a Molecular Dynamics use case. We study the impact of different strategies on performance and show how users can leverage Sim-Situ to determine interesting tradeoffs when adding analysis/visualization components to their application.

Honoré, Valentin↗
NASA NTRS1974

Peripheral visual response time and visual display layout

Experiments were performed on a group of 42 subjects in a study of their peripheral visual response time to visual signals under positive acceleration, during prolonged bedrest, at passive 70 deg headup body lift, under exposures to high air temperatures and high luminance levels, and under normal stress-free laboratory conditions. Diagrams are plotted for mean response times to white, red, yellow, green, and blue stimuli under different conditions.

Haines, R. F.↗
NASA NTRS1989

Ice/frost/debris assessment for space shuttle mission STS-27R, December 2, 1988

An Ice/Frost/Debris assessment was conducted for Space Shuttle Mission STS-27R. Debris inspections of the flight elements and launch pad are performed before and after launch. Ice/frost conditions are assessed by the use of computer programs, nomographs, and infrared scanner data during cryogenic loading of the vehicle followed by an on-pad visual inspection. High speed photography is viewed after launch to identify ice/debris sources and evaluate potential vehicle damage. The Ice/Frost/Debris conditions of Mission STS-27R and their effect on the Space Shuttle Program are documented.

Katnik, Gregory N.↗
NASA NTRS1989

The role of flight planning in aircrew decision performance

The role of flight planning in increasing the safety and decision-making performance of the air transport crews was investigated in a study that involved 48 rated airline crewmembers on a B720 simulator with a model-board-based visual scene and motion cues with three degrees of freedom. The safety performance of the crews was evaluated using videotaped replays of the flight. Based on these evaluations, the crews could be divided into high- and low-safety groups. It was found that, while collecting information before flights, the high-safety crews were more concerned with information about alternative airports, especially the fuel required to get there, and were characterized by making rapid and appropriate decisions during the emergency part of the flight scenario, allowing these crews to make an early diversion to other airports. These results suggest that contingency planning that takes into account alternative courses of action enhances rapid and accurate decision-making under time pressure.

Pepitone, Dave↗
NASA NTRSDate not supplied

Overview of Plume-Surface Interaction Data from Subscale Inert Gas Testing at NASA MSFC Test Stand 300 Vacuum Facilities

Maturation and validation of predictive modeling capabilities for plume-surface interaction, and the effects caused by the impingement of rocket engine exhaust on surface regolith, require relevant, highly characterized ground test data. The multi-phase nature of this problem poses challenges to ground testing across physical scaling, test environments and techniques, and diagnostics. NASA has developed a Physics Focused Ground Test (PFGT) of plume-surface interaction to address this need. The PFGT is a subscale, inert-gas experiment at Mars- and Lunar-relevant ambient pressure conditions that will provide critical data for model validation of cratering, ejecta, and plume physics. In this test, the ambient pressure in a vacuum chamber will be varied, along with the height of a supersonic nozzle above a surface, and the mass flow rate through the nozzle. Testing will be performed on a range of regolith simulants of varying composition and will also include instrumented impingement plate tests in place of regolith simulant to characterize gas-only plume physics. Novel high-speed visual diagnostics will capture temporal data on crater formation and ejecta dynamics, and planar laser-induced fluorescence diagnostics will capture plume structure and behavior. This paper will present an overview of the data collected during this test – for both the cratering and ejecta testing and the gas-only plume physics testing. Emphasis will be placed on trends, effects, and interactions observed in the data across the test parameter space.

Chad J. Eberhart↗
NASA NTRS1987

An experimental low Reynolds number comparison of a Wortmann FX67-K170 airfoil, a NACA 0012 airfoil and a NACA 64-210 airfoil in simulated heavy rain

Wind tunnel experiments were conducted on Wortmann FX67-K170, NACA 0012, and NACA 64-210 airfoils at rain rates of 1000 mm/hr and Reynolds numbers of 310,000 to compare the aerodynamic performance degradation of the airfoils and to attempt to identify the various mechanisms which affect performance in heavy rain conditions. Lift and drag were measured in dry and wet conditions, a variety of flow visualization techniques were employed, and a computational code which predicted airfoil boundary layer behavior was used. At low angles of attack, the lift degradation in wet conditions varied significantly between the airfoils. The Wortmann section had the greatest overall lift degradation and the NACA 64-210 airfoil had the smallest. At high angles of attack, the NACA 64-210 and 0012 airfoils had improved aerodynamic performance in rain conditions due to an apparent reduction of the boundry layer separation. Performance degradation in heavy rain for all three airfoils at low angles of attack could be emulated by forced boundary layer transition near the leading edge. The secondary effect occurs at time scales consistent with top surface water runback times. The runback layer is thought to effectively alter the airfoil geometry. The severity of the performance degradation for the airfoils varied. The relative differences appeared to be related to the susceptibility of each airfoil to premature boundary layer transition.

Craig, Anthony P.↗
DOE OSTI2015

TU-CD-207-08: Intrinsic Image Quality Comparison of Synthesized 2-D and FFDM Images

Purpose: With the combined interest of managing patient dose, maintaining or improving image quality, and maintaining or improving the diagnostic utility of mammographic data, this study aims to compare the intrinsic image quality of Hologic’s synthesized 2-D (C-View) and 2-D FFDM images in terms of resolution, contrast, and noise. Methods: This study utilized a novel 3-D printed anthropomorphic breast phantom in addition to the American College of Radiology (ACR) mammography accreditation phantom. Analysis of the 3-D anthropomorphic phantom included visual assessment of resolution and analysis of the normalized noise power spectrum. Analysis of the ACR phantom included both visual inspection and objective automated analysis using in-house software. The software incorporates image- and object-specific CNR visibility thresholds which account for image characteristics such as noise texture which affect object visualization. T- test statistical analysis was also performed on ACR phantom scores. Results: The spatial resolution of C-View images is markedly lower (at least 50% worse) than that of FFDM. And while this is generally associated with the benefit of reduced relative noise magnitude, the noise in C-View images tends to have a more mottled (predominantly low-frequency) texture. In general, for high contrast objects, C-View provides superior visualization over FFDM; however this benefit diminishes for low contrast objects and is applicable only to objects that are sufficiently larger than the spatial resolution threshold. Based on both observer and automated ACR phantom analysis, between 50–70% of C-View images failed to meet ACR minimum accreditation requirements – primarily due to insufficient (unbroken) fiber visibility. Conclusion: Compared to FFDM, C-View offers better depiction of objects of certain size and contrast, but provides poorer overall resolution and noise properties. Based on these findings, the utilization of C-View images in the clinical setting requires careful consideration, especially if considering the discontinuation of FFDM imaging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Understanding failure in austenitic steels: Key considerations for molten salt storage in CSP applications

Owing to their excellent properties, austenitic stainless steels are extensively used in boilers, furnaces, molten salt tanks, and other applications that are subjected to extreme mechanical loads and high-temperature conditions. Their high corrosion and creep resistance make them suitable for high-temperature operating environments. Additionally, good fatigue resistance and favorable mechanical and visual properties are essential. However, the premature failure of several components at elevated temperatures has been previously reported. Although the failure analysis of components in service is complex, processes such as cold work and welding have been identified as contributing factors to the performance degradation of these steels. This study aims to analyze the various documented failure modes and mechanisms in austenitic steels, including creep, cracking, stress relaxation cracking, and fatigue, to better understand the multi-objective design requirements for these alloys as structural materials for high-temperature molten salt tanks in Concentrating Solar Power (CSP) plants. Stabilized austenitic grades, such as AISI 347H, demonstrate superior resistance to creep and corrosion-related degradation when compared to non-stabilized grades like AISI 316L at temperatures relevant to concentrated solar power (CSP) applications. In contrast, nickel-based alloys offer enhanced corrosion resistance, albeit at a higher cost. This review underscores that creep, stress relaxation cracking, and thermo-mechanical fatigue are the predominant long-term failure risks in CSP hot tanks.

14 SOLAR ENERGY↗
DOE OSTI2023

Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation

We evaluate AI-assisted generative capabilities on fundamental numerical kernels in high-performance computing (HPC), including AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG. We test the generated kernel codes for a variety of language-supported programming models, including (1) C++ (e.g., OpenMP [including offload], OpenACC, Kokkos, SyCL, CUDA, and HIP), (2) Fortran (e.g., OpenMP [including offload] and OpenACC), (3) Python (e.g., numpy, Numba, cuPy, and pyCUDA), and (4) Julia (e.g., Threads, CUDA.jl, AMDGPU.jl, and KernelAbstractions.jl). We use the GitHub Copilot capabilities powered by the GPT-based OpenAI Codex available in Visual Studio Code as of April 2023 to generate a vast amount of implementations given simple + + prompt variants. To quantify and compare the results, we propose a proficiency metric around the initial 10 suggestions given for each prompt. Results suggest that the OpenAI Codex outputs for C++ correlate with the adoption and maturity of programming models. For example, OpenMP and CUDA score really high, whereas HIP is still lacking. We found that prompts from either a targeted language such as Fortran or the more general purpose Python can benefit from adding code keywords, while Julia prompts perform acceptably well for its mature programming models (e.g., Threads and CUDA.jl). We expect for these benchmarks to provide a point of reference for each programming model's community. Overall, understanding the convergence of large language models, AI, and HPC is crucial due to its rapidly evolving nature and how it is redefining human-computer interactions.

Godoy, William↗
DOE OSTI2014

Dynamic functional imaging of brain glucose utilization using fPET-FDG

We report that glucose is the principal source of energy for the brain and yet the dynamic response of glucose utilization to changes in brain activity is still not fully understood. Positron emission tomography (PET) allows quantitative measurement of glucose metabolism using 2-[18F]-fluorodeoxyglucose (FDG). However, FDG PET in its current form provides an integral (or average) of glucose consumption over tens of minutes and lacks the temporal information to capture physiological alterations associated with changes in brain activity induced by tasks or drug challenges. Traditionally, changes in glucose utilization are inferred by comparing two separate scans, which significantly limits the utility of the method. We report a novel method to track changes in FDG metabolism dynamically, with higher temporal resolution than exists to date and within a single session. Using a constant infusion of FDG, we demonstrate that our technique (termed fPET-FDG) can be used in an analysis pipeline similar to fMRI to define within-session differential metabolic responses. We use visual stimulation to demonstrate the feasibility of this method. Ultimately, this new method has a great potential to be used in research protocols and clinical settings since fPET-FDG imaging can be performed with most PET scanners and data acquisition and analysis are straightforward. fPET-FDG is a highly complementary technique to MRI and provides a rich new way to observe functional changes in brain metabolism.

2-[18F]-fluorodeoxyglucose (FDG)↗
DOE OSTI2019

Galaxy morphological classification in deep-wide surveys via unsupervised machine learning

ABSTRACT Galaxy morphology is a fundamental quantity, which is essential not only for the full spectrum of galaxy-evolution studies, but also for a plethora of science in observational cosmology (e.g. as a prior for photometric-redshift measurements and as contextual data for transient light-curve classifications). While a rich literature exists on morphological-classification techniques, the unprecedented data volumes, coupled, in some cases, with the short cadences of forthcoming ‘Big-Data’ surveys (e.g. from the LSST), present novel challenges for this field. Large data volumes make such data sets intractable for visual inspection (even via massively distributed platforms like Galaxy Zoo), while short cadences make it difficult to employ techniques like supervised machine learning, since it may be impractical to repeatedly produce training sets on short time-scales. Unsupervised machine learning, which does not require training sets, is ideally suited to the morphological analysis of new and forthcoming surveys. Here, we employ an algorithm that performs clustering of graph representations, in order to group image patches with similar visual properties and objects constructed from those patches, like galaxies. We implement the algorithm on the Hyper-Suprime-Cam Subaru-Strategic-Program Ultra-Deep survey, to autonomously reduce the galaxy population to a small number (160) of ‘morphological clusters’, populated by galaxies with similar morphologies, which are then benchmarked using visual inspection. The morphological classifications (which we release publicly) exhibit a high level of purity, and reproduce known trends in key galaxy properties as a function of morphological type at z < 1 (e.g. stellar-mass functions, rest-frame colours, and the position of galaxies on the star-formation main sequence). Our study demonstrates the power of unsupervised machine learning in performing accurate morphological analysis, which will become indispensable in this new era of deep-wide surveys.

Martin, G.↗
NASA NTRS1999

Experimental and Computational Investigation of a Translating-Throat Single-Expansion-Ramp Nozzle

An experimental and computational study was conducted on a high-speed, single-expansion-ramp nozzle (SERN) concept designed for efficient off-design performance. The translating-throat SERN concept adjusts the axial location of the throat to provide a variable expansion ratio and allow a more optimum jet exhaust expansion at various flight conditions in an effort to maximize nozzle performance. Three design points (throat locations) were investigated to simulate the operation of this concept at subsonic-transonic, low supersonic, and high supersonic flight conditions. The experimental study was conducted in the jet exit test facility at the Langley Research Center. Internal nozzle performance was obtained at nozzle pressure ratios (NPR's) up to 13 for six nozzles with design nozzle pressure ratios near 9, 42, and 102. Two expansion-ramp surfaces, one concave and one convex, were tested for each design point. Paint-oil flow and focusing schlieren flow visualization techniques were utilized to acquire additional flow data at selected NPR'S. The Navier-Stokes code, PAB3D, was used with a two-equation k-e turbulence model for the computational study. Nozzle performance characteristics were predicted at nozzle pressure ratios of 5, 9, and 13 for the concave ramp, low Mach number nozzle and at 10, 13, and 102 for the concave ramp, high Mach number nozzle.

Deere, Karen A.↗
DOE OSTI2021

Machine learning elastic constants of multi-component alloys

The present manuscript explores application of machine learning methods for determining elastic constants and other derived mechanical properties of multi-component alloys. Here, a number of machine learning models, including linear regression, neural network and random forest based models, are trained and tested on a dataset of binary alloys generated using density functional theory (DFT) calculations and spanning over a large number of elemental species in the periodic table. Starting with a wide range of simple and easily accessible compositionally-averaged elemental features, a correlation-based feature selection strategy was used to systematically down-select a set of most relevant features towards the prediction of the elasticity tensor components. The true predictive performance and the associated uncertainties of the models were established by testing on unseen data and bootstrapping, respectively. A single and pair-wise feature partial dependence analysis was performed to visualize the average property trends in the multi-dimensional feature space in order to further understand the achieved predictive performance. The utility of the trained model is further demonstrated by obtaining sufficiently accurate yet highly efficient approximations for bulk modulus, Young’s modulus, shear modulus and Poisson’s ratio for alloys beyond the binary space (i.e., two-component alloys) on which the model was originally trained. More importantly, we test and validate the predictive performance of the developed model directly against the experimentally measured elastic constants of technologically relevant multi-component alloys (such as, Ni- and Ti-based alloys). Finally, utility of such a data-enabled route is demonstrated by predicting the possible range of various elastic properties for vast composition space available within the five component Ni-Cr-Fe-Mo-W alloy system in a high-throughput manner.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Probing ternary solvent effect in high V oc polymer solar cells using advanced AFM techniques

This work describes a simple method to develop a high V oc low band gap PSCs. In addition, two new atomic force microscopy (AFM)-based nanoscale characterization techniques to study the surface morphology and physical properties of the structured active layer are introduced. With the help of ternary solvent processing of the active layer and C 60 buffer layer, a bulk heterojunction PSC with V oc more than 0.9 V and conversion efficiency 7.5% is developed. In order to understand the fundamental properties of the materials ruling the performance of the PSCs tested, AFM-based nanoscale characterization techniques including Pulsed-Force-Mode AFM (PFM-AFM) and Mode-Synthesizing AFM (MSAFM) are introduced. Interestingly, MSAFM exhibits high sensitivity for direct visualization of the donor–acceptor phases in the active layer of the PSCs. Lastly, conductive-AFM (cAFM) studies reveal local variations in conductivity in the donor and acceptor phases as well as a significant increase in photocurrent in the PTB7:ICBA sample obtained with the ternary solvent processing.

25 ENERGY STORAGE↗