Results for “visualization application” — Page 77

NASA NTRS1994

A wind tunnel investigation of the effects of micro-vortex generators and Gurney flaps on the high-lift characteristics of a business jet wing

A study of a full-scale, semi-span business jet wing has been conducted to investigate the potential of two types of high-lift devices for improving aircraft high-lift performance. The research effort involved low-speed wind-tunnel tests of micro-vortex generators and Gurney flaps applied to the flap system of the business jet wing and included force and moment measurements, surface pressure surveys and flow visualization on the wing and flap. Results showed that the micro-vortex generators tested had no beneficial effects on the longitudinal force characteristics in this particular application, while the Gurney flaps were an effective means of increasing lift. However, the Gurney flaps also caused an increase in drag in most circumstances.

Martuccio, Michelle Therese↗

NASA NTRS2001

Use of Pressure Sensitive Paint for Diagnostics in Turbomachinery Flows With Shocks

The technology of pressure sensitive paint (PSP) is well established in external aerodynamics. In internal flows in narrow channels and in turbomachinery cascades, however, there are still unresolved problems. In particular, the internal flows with complex shock structures inside highly curved channels present a challenge. It is not always easy and straightforward to distinguish between true signals and "ghost" images due to multiple internal reflections in narrow channels. To address some of the problems, investigations were first carried out in a narrow supersonic channel of Mach number 2.5. A single wedge or a combination of two wedges were used to generate a complex shock wave structure in the flow. The experience gained in a small supersonic channel was used for surface pressure measurements on the stator vane of a supersonic throughflow fan. The experimental results for several fan operating conditions are shown in a concise form, including performance map points, midspan static tap pressure distributions, and vane suction side pressure fields. Finally, the PSP technique was used in the NASA transonic flutter cascade to compliment flow visualization data and to acquire backwall pressure fields to assess the cascade flow periodicity. A summary of shortcomings of the pressure sensitive paint technology for internal flow application and lessons learned are presented in the conclusion of the paper.

Lepicovsky, Jan↗

NASA NTRS2004

An Infrared Telescope for Planet Detection and General Astrophysics

NASA plans to launch a Terrestrial Planet Finder (TPF) mission in 2014 to detect and characterize Earth-like planets around nearby stars, perform comparative planetology studies, and obtain general astrophysics observations. During our recently completed a TPF Mission Architecture study for NASA/JPL we developed the conceptual design for a 28-meter telescope with an IR Coronagraph that meets these mission objectives. This telescope and the technology it embodies are directly applicable to future Far-IR and Submillimeter space missions. The detection of a 30th magnitude planet located within 50 milli-arc-seconds of a 5th (Visual) magnitude star is an exceptionally challenging objective. Observations in the thermal infrared (7-17 microns) are somewhat easier since the planet is "only" 15(sup m) fainter than the star at these wavelengths, but many severe challenges must still be overcome. These challenges include: 1. Designing a coronagraph for star:planet separations less than or equal to lambda/D. 2. Developing the deployment scheme for a 28m space telescope that can fit in an existing launch vehicle payload fairing. 3. Generating configuration layouts for the IR telescope, coronagraph, spacecraft bus, sunshade, solar array, and high-gain antenna. 4. Providing: Structural stability to within 10 microns to support the optics. Thermal control to achieve the necessary structural stability, as well as providing a stable (approx. 30K) thermal environment for the optics. Dynamics isolation from potential jitter sources. 5. Minimizing launch mass to provide the maximum payload for the science mission Interfacing to an EELV Heavy launch vehicle, including acoustic and stress loads for the launch environment. 6. Identifying the key technologies (which can be developed by 2009) that will enable TPF mission to be performed. 7. Generating a manufacturing plan that will permit TPF to be developed at a reasonable cost and schedule. Many of these design challenges result in inherently conflicting requirements on the design of TPF. Drawing on our experience with large space telescopes such as the Chandra X-ray Observatory and the Next Generation Space Telescope, we have created a conceptual design for TPF that successfully meets these challenging requirements. This paper describes our solution to these challenges.

Lillie, C. F.↗

NASA NTRS2009

Human-System Integration Scorecard Update to VB.Net

The purpose of this project was to create Human-System Integration (HSI) scorecard software, which could be utilized to validate that human factors have been considered early in hardware/system specifications and design. The HSI scorecard is partially based upon the revised Human Rating Requirements (HRR) intended for NASA's Constellation program. This software scorecard will allow for quick appraisal of HSI factors, by using visual aids to highlight low and rapidly changing scores. This project consisted of creating a user-friendly Visual Basic program that could be easily distributed and updated, to and by fellow colleagues. Updating the Microsoft Word version of the HSI scorecard to a computer application will allow for the addition of useful features, improved easy of use, and decreased completion time for user. One significant addition is the ability to create Microsoft Excel graphs automatically from scorecard data, to allow for clear presentation of problematic areas. The purpose of this paper is to describe the rational and benefits of creating the HSI scorecard software, the problems and goals of project, and future work that could be done.

Sanders, Blaze D.↗

NASA NTRS2014

Satellite Data of Atmospheric Pollution for U.S. Air Quality Applications: Examples of Applications, Summary of Data End-user Resources, Answers to Faqs, and Common Mistakes to Avoid

Satellite data of atmospheric pollutants are becoming more widely used in the decision-making and environmental management activities of public, private sector and non-profit organizations. They are employed for estimating emissions, tracking pollutant plumes, supporting air quality forecasting activities, providing evidence for "exceptional event" declarations, monitoring regional long-term trends, and evaluating air quality model output. However, many air quality managers are not taking full advantage of the data for these applications nor has the full potential of satellite data for air quality applications been realized. A key barrier is the inherent difficulties associated with accessing, processing, and properly interpreting observational data. A degree of technical skill is required on the part of the data end-user, which is often problematic for air quality agencies with limited resources. Therefore, we 1) review the primary uses of satellite data for air quality applications, 2) provide some background information on satellite capabilities for measuring pollutants, 3) discuss the many resources available to the end-user for accessing, processing, and visualizing the data, and 4) provide answers to common questions in plain language.

remote sensing↗

NASA NTRS2014

Satellite Data of Atmospheric Pollution for U.S. Air Quality Applications: Examples of Applications, Summary of Data End-User Resources, Answers to FAQs, and Common Mistakes to Avoid

Satellite data of atmospheric pollutants are becoming more widely used in the decision-making and environmental management activities of public, private sector and non-profit organizations. They are employed for estimating emissions, tracking pollutant plumes, supporting air quality forecasting activities, providing evidence for "exceptional event" declarations, monitoring regional long-term trends, and evaluating air quality model output. However, many air quality managers are not taking full advantage of the data for these applications nor has the full potential of satellite data for air quality applications been realized. A key barrier is the inherent difficulties associated with accessing, processing, and properly interpreting observational data. A degree of technical skill is required on the part of the data end-user, which is often problematic for air quality agencies with limited resources. Therefore, we 1) review the primary uses of satellite data for air quality applications, 2) provide some background information on satellite capabilities for measuring pollutants, 3) discuss the many resources available to the end-user for accessing, processing, and visualizing the data, and 4) provide answers to common questions in plain language.

Duncan, Bryan↗

NASA NTRS2017

Optical Flow for Flight and Wind Tunnel Background Oriented Schlieren Imaging

Background oriented Schlieren images have historically been generated by calculating the observed pixel displacement between a wind-on and wind-o image pair using normalized cross-correlation. This work uses optical flow to solve the displacement fields which generate the Schlieren images. A well established method used in the computer vision community, optical flow is the apparent motion in an image sequence due to brightness changes. The regularization method of Horn and Schunck is used to create Schlieren images using two data sets: a supersonic jet plume shock interaction from the NASA Ames Unitary Plan Wind Tunnel, and a transonic flight test of a T-38 aircraft using a naturally occurring background, performed in conjunction with NASA Ames and Armstrong Research Centers. Results are presented and contrasted with those using normalized cross-correlation. The optical flow Schlieren images are found to provided significantly more detail. We apply the method to historical data sets to demonstrate the broad applicability and limitations of the technique.

Image processing↗

NASA NTRS2018

Towards Design Principles for Visual Analytics in Operations Contexts

Operations engineering teams interact with complex data systems to make technical decisions that ensure the operational efﬁcacy of their missions. To support these decision-making tasks, which may require elastic prioritization of goals dependent on changing conditions, custom analytics tools are often developed. We were asked to develop such a tool by a team at the NASA Jet Propulsion Laboratory, where rover telecom operators make decisions based on models predicting how much data rovers can transfer from the surface of Mars. Through research, design, implementation, and informal evaluation of our new tool, we developed principles to inform the design of visual analytics systems in operations contexts. We offer these principles as a step towards understanding the complex task of designing these systems. The principles we present are applicable to designers and developers tasked with building analytics systems in domains that face complex operations challenges such as scheduling, routing, and logistics.

Lombeyda, Santiago↗

NASA NTRS2016

Reanalyzing Environmental Lidar Data for Archaeology: Mesoamerican Applications and Implications

This paper presents a preliminary archaeological assessment of extensive transects of lidar recently collected by environmental scientists over southern Mexico using the G-LiHT system of NASA's Goddard Space Flight Center. In particular, this article offers the results of a first phase of research, consisting of: 1) characterization and classification of the cultural and ecological context of the samples, and 2) bare earth processing and visual inspection of a sample of the flight paths for identification of probable anthropogenic Precolumbian features. These initial results demonstrate that significant contributions to understanding variations in Precolumbian land-use and settlement patterns and change is possible with truly multi-regional lidar surveys not originally captured for archaeological prospection. We point to future directions for the development of archaeological applications of this robust data set. Finally, we offer the potential for enriching archaeological research through tightly coupled collaborations with environmental science and monitoring. Archaeologists in the neotropics can acquire more data, better realize the full potential of lidar surveys, and better contribute to interdisciplinary studies of human-environmental dynamic systems through regionally focused and collaborative scientific research.

Golden, Charles↗

DOE OSTI2018

CPU Isosurface Ray Tracing of Adaptive Mesh Refinement Data

Adaptive mesh refinement (AMR) is a key technology for large-scale simulations that allows for adaptively changing the simulation mesh resolution, resulting in significant computational and storage savings. However, visualizing such AMR data poses a significant challenge due to the difficulties introduced by the hierarchical representation when reconstructing continuous field values. Here, we detail a comprehensive solution for interactive isosurface rendering of block-structured AMR data. We contribute a novel reconstruction strategy—the octant method—which is continuous, adaptive and simple to implement. Furthermore, we present a generally applicable hybrid implicit isosurface ray-tracing method, which provides better rendering quality and performance than the built-in sampling-based approach in OSPRay. Finally, we integrate our octant method and hybrid isosurface geometry into OSPRay as a module, providing the ability to create high-quality interactive visualizations combining volume and isosurface representations of BS-AMR data. Lastly, we evaluate the rendering performance, memory consumption and quality of our method on two gigascale block-structured AMR datasets.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1990

Workspace visualization and time-delay telerobotic operations

The paper examines the performance of telerobotic tasks where the operator and robot are physically separated, and a comunication time delay of up to several seconds between them exists. This situation is applicable to space robotic servicing-assembly-maintenance operations on low earth or geosynchronous orbits with a ground-based command station. Attention is given to two developments which address advanced time-delay teleoperations for unstructured tasks: (1) the 'phantom robot', a real-time predictive graphics simulator developed to allow teleoperator eye-to-hand coordination or robot free-space kinematics under a time delay of several seconds; and (2) shared compliance control, a modified form of automatic electromechanical impedance control employed in parallel with manual position control to permit soft contact and grasp compliance with workpiece geometry under a time delay of several seconds.

Schenker, P. S.↗

NASA NTRS1994

Performance Measurement, Visualization and Modeling of Parallel and Distributed Programs

This paper presents a methodology for debugging the performance of message-passing programs on both tightly coupled and loosely coupled distributed-memory machines. The AIMS (Automated Instrumentation and Monitoring System) toolkit, a suite of software tools for measurement and analysis of performance, is introduced and its application illustrated using several benchmark programs drawn from the field of computational fluid dynamics. AIMS includes (i) Xinstrument, a powerful source-code instrumentor, which supports both Fortran77 and C as well as a number of different message-passing libraries including Intel's NX Thinking Machines' CMMD, and PVM; (ii) Monitor, a library of timestamping and trace -collection routines that run on supercomputers (such as Intel's iPSC/860, Delta, and Paragon and Thinking Machines' CM5) as well as on networks of workstations (including Convex Cluster and SparcStations connected by a LAN); (iii) Visualization Kernel, a trace-animation facility that supports source-code clickback, simultaneous visualization of computation and communication patterns, as well as analysis of data movements; (iv) Statistics Kernel, an advanced profiling facility, that associates a variety of performance data with various syntactic components of a parallel program; (v) Index Kernel, a diagnostic tool that helps pinpoint performance bottlenecks through the use of abstract indices; (vi) Modeling Kernel, a facility for automated modeling of message-passing programs that supports both simulation -based and analytical approaches to performance prediction and scalability analysis; (vii) Intrusion Compensator, a utility for recovering true performance from observed performance by removing the overheads of monitoring and their effects on the communication pattern of the program; and (viii) Compatibility Tools, that convert AIMS-generated traces into formats used by other performance-visualization tools, such as ParaGraph, Pablo, and certain AVS/Explorer modules.

Yan, Jerry C.↗

DOE OSTI2023

Ensemble flow reconstruction in the atmospheric boundary layer from spatially limited measurements through latent diffusion models

Due to costs and practical constraints, field campaigns in the atmospheric boundary layer typically only measure a fraction of the atmospheric volume of interest. Machine learning techniques have previously successfully reconstructed unobserved regions of flow in canonical fluid mechanics problems and two-dimensional geophysical flows, but these techniques have not yet been demonstrated in the three-dimensional atmospheric boundary layer. Here, we conduct a numerical analogue of a field campaign with spatially limited measurements using large-eddy simulation. We pose flow reconstruction as an inpainting problem, and reconstruct realistic samples of turbulent, three-dimensional flow with the use of a latent diffusion model. The diffusion model generates physically plausible turbulent structures on larger spatial scales, even when input observations cover less than 1% of the volume. Through a combination of qualitative visualization and quantitative assessment, we demonstrate that the diffusion model generates meaningfully diverse samples when conditioned on just one observation. These samples successfully serve as initial conditions for a large-eddy simulation code. We find that diffusion models show promise and potential for other applications for other turbulent flow reconstruction problems.

17 WIND ENERGY↗

NASA NTRS2019

A Segmentation Algorithm for Characterizing Rise and Fall Segments in Seasonal Cycles: An Application to XCO2 to Estimate Benchmarks and Assess Model Bias

There is more useful information in the time series of satellite-derived column-averaged carbon dioxide (XCO2) than is typically characterized. Often, the entire time series is treated at once without considering detailed features at shorter timescales, such as nonstationary changes in signal characteristics – amplitude, period and phase. In many instances, signals are visually and analytically differentiable from other portions in a time series. Each rise (increasing) and fall (decreasing) segment in the seasonal cycle is visually discernable in a graph of the time series. The rise and fall segments largely result from seasonal differences in terrestrial ecosystem production, which means that the segment's signal characteristics can be used to establish observational benchmarks because the signal characteristics are driven by similar underlying processes. We developed an analytical segmentation algorithm to characterize the rise and fall segments in XCO2 seasonal cycles. We present the algorithm for general application of the segmentation analysis and emphasize here that the segmentation analysis is more generally applicable to cyclic time series. We demonstrate the utility of the algorithm with specific results related to the comparison between satellite- and model-derived XCO2 seasonal cycles (2009–2012) for large bioregions across the globe. We found a seasonal amplitude gradient of 0.74–0.77 ppm for every 10∘ of latitude in the satellite data, with similar gradients for rise and fall segments. This translates to a south–north seasonal amplitude gradient of 8 ppm for XCO2, about half the gradient in seasonal amplitude based on surface site in situ CO2 data (∼19 ppm). The latitudinal gradients in the period of the satellite-derived seasonal cycles were of opposing sign and magnitude (−9 d per 10∘ latitude for fall segments and 10 d per 10∘ latitude for rise segments) and suggest that a specific latitude (∼2∘ N) exists that defines an inversion point for the period asymmetry. Before (after) the point of asymmetry inversion, the periods of rise segments are lesser (greater) than the periods of fall segments; only a single model could reproduce this emergent pattern. The asymmetry in amplitude and the period between rise and fall segments introduces a novel pattern in seasonal cycle analyses, but, while we show these emergent patterns exist in the data, we are still breaking ground in applying the information for science applications. Maybe the most useful application is that the segmentation analysis allowed us to decompose the model biases into their correlated parts of biases in amplitude, period and phase independently for rise and fall segments. We offer an extended discussion on how such information about model biases and the emergent patterns in satellite-derived seasonal cycles can be used to guide future inquiry and model development.

Calle, Leonardo↗

NASA NTRS2019

A Segmentation Algorithm for Characterizing Rise and Fall Segments in Seasonal Cycles: an Application to Xco2 to Estimate Benchmarks and Assess Model Bias

There is more useful information in the time series of satellite-derived column-averaged carbon dioxide (XCO2) than is typically characterized. Often, the entire time series is treated at once without considering detailed features at shorter timescales, such as nonstationary changes in signal characteristics – amplitude, period and phase. In many instances, signals are visually and analytically differentiable from other portions in a time series. Each rise (increasing) and fall (decreasing) segment in the seasonal cycle is visually discernable in a graph of the time series. The rise and fall segments largely result from seasonal differences in terrestrial ecosystem production, which means that the segment's signal characteristics can be used to establish observational benchmarks because the signal characteristics are driven by similar underlying processes. We developed an analytical segmentation algorithm to characterize the rise and fall segments in XCO2 seasonal cycles. We present the algorithm for general application of the segmentation analysis and emphasize here that the segmentation analysis is more generally applicable to cyclic time series. We demonstrate the utility of the algorithm with specific results related to the comparison between satellite- and model-derived XCO2 seasonal cycles (2009–2012) for large bioregions across the globe. We found a seasonal amplitude gradient of 0.74–0.77 ppm for every 10∘ of latitude in the satellite data, with similar gradients for rise and fall segments. This translates to a south–north seasonal amplitude gradient of 8 ppm for XCO2, about half the gradient in seasonal amplitude based on surface site in situ CO2 data (∼19 ppm). The latitudinal gradients in the period of the satellite-derived seasonal cycles were of opposing sign and magnitude (−9 d per 10∘ latitude for fall segments and 10 d per 10∘ latitude for rise segments) and suggest that a specific latitude (∼2∘ N) exists that defines an inversion point for the period asymmetry. Before (after) the point of asymmetry inversion, the periods of rise segments are lesser (greater) than the periods of fall segments; only a single model could reproduce this emergent pattern. The asymmetry in amplitude and the period between rise and fall segments introduces a novel pattern in seasonal cycle analyses, but, while we show these emergent patterns exist in the data, we are still breaking ground in applying the information for science applications. Maybe the most useful application is that the segmentation analysis allowed us to decompose the model biases into their correlated parts of biases in amplitude, period and phase independently for rise and fall segments. We offer an extended discussion on how such information about model biases and the emergent patterns in satellite-derived seasonal cycles can be used to guide future inquiry and model development.

segmentation algorithm↗

DOE OSTI2019

Microscopy of Electrostatic Field Effect in Novel Quantum Materials (Final Report)

In this DOE Early Career project “Microscopy of Electrostatic Field Effect in Novel Quantum Materials”, the PI’s group explored the nanoscale electronic properties when charge carriers are electrostatically modulated in functional materials. Using a microwave impedance microscope (MIM), the team probed the spatial evolution of local conductivity in various field-effect transistors (FETs) ranging from traditional metal-oxide-semiconductor FETs, sketched oxide-interface FETs, to ferroelectric FETs and electric double-layer transistors (EDLTs). Specifically, the work has led to a deep understanding on the electrical inhomogeneity and conductive edge channels in atomically thin transition metal dichalcogenides and their heterostructures, which is of fundamental importance for their applications in electronics and photonics. The unique sub-surface imaging capability also enables the first-time report of ferroelectric field effect on Ge substrates due to the polarization switching of an epitaxial BaTiO 3 layer, as well as the visualization of sketched nanostructures in the LaAlO 3 /SrTiO 3 interface. Using a cryogenic MIM, the local channel conductance in ion-gel-gated oxide EDLTs has been successfully imaged, resolving a major challenge in the EDLT research to study electronic fluctuations in the devices. Finally, a new tuning-fork-based MIM has been developed to perform quantitative conductivity imaging on back-gated FETs. The research supported by this DOE grant is significant for understanding the nanoscale uniformity in technologically important materials towards energy applications.

2D materials↗

DOE OSTI2023

Probing the edge states of Chern insulators using microwave impedance microscopy

Microwave impedance microscopy (MIM) has been utilized to directly visualize topological edge states in many quantum materials. While the microwave response for conventional metals and insulators can be accurately quantified using simple lumped-element circuits, whose applicability to more exotic quantum systems remain limited. In this work, we present a general theoretical framework of the MIM response of arbitrary quantum materials. Applying it to topological edge states in a Chern insulator predicts an enhanced MIM response at the crystal boundaries due to collective edge magnetoplasmon (EMP) excitations. The unique resonance frequency of these plasmonic modes allows one to disentangle the signatures of topological versus trivial edge states. To benchmark our analytical predictions, we experimentally probe the MIM response of quantum anomalous Hall edge states in a Cr-doped (Bi,Sb) 2 Te 3 topological insulator and perform numerical simulations using a classical formulation of the EMP modes based on this realistic tip-sample geometry, both of which yield results consistent with our theoretical picture. Here we also show how the technique of MIM can be used to quantitatively extract the topological invariant of a Chern insulator and shed light on the microscopic nature of dissipation along the crystal boundaries.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Topology Inference of Unknown Networks Based on Robust Virtual Coordinate Systems

Learning and exploring the connectivity of unknown networks represent an important problem in practical applications of communication networks and social-media networks. Modeling large-scale networks as connected graphs is highly desirable to extract their connectivity information among nodes to visualize network topology, disseminate data, and improve routing efficiency. This paper investigates a simple measurement model in which a small subset of source nodes collect hop distance information from networked nodes in order to generate a virtual coordinate system (VCS) for networks of unknown topology. We establish the VCS to define logical distance among nodes based on principal component analysis and to determine connectivity relationship and effective routing methods. More importantly, we present a robust analytical algorithm to derive the VCS against practical issues of missing and corrupted measurements. We also develop a connectivity inference method which classifies nodes into layers based on the hop distances and derives partial information on network connectivity.

97 MATHEMATICS AND COMPUTING↗