Engineering topics

Kao, David

Publications and source records attributed to Kao, David.

15 records

NASA NTRS2017

VESsel GENeration Analysis (VESGEN): Innovative Vascular Mappings for Astronaut Exploration Health Risks and Human Terrestrial Medicine

Currently, astronauts face significant health risks in future long-duration exploration missions such as colonizing the Moon and traveling to Mars. Numerous risks include greatly increased radiation exposures beyond the low earth orbit (LEO) of the ISS, and visual and ocular impairments in response to microgravity environments. The cardiovascular system is a key mediator in human physiological responses to radiation and microgravity. Moreover, blood vessels are necessarily involved in the progression and treatment of vascular-dependent terrestrial diseases such as cancer, coronary vessel disease, wound-healing, reproductive disorders, and diabetes. NASA developed an innovative, globally requested beta-level software, VESsel GENeration Analysis (VESGEN) to map and quantify vascular remodeling for application to astronaut and terrestrial health challenges. VESGEN mappings of branching vascular trees and networks are based on a weighted multi-parametric analysis derived from vascular physiological branching rules. Complex vascular branching patterns are determined by biological signaling mechanisms together with the fluid mechanics of multi-phase laminar blood flow.

astronaut↗

NASA NTRS2012

Performance of Conformable Phenolic Impregnated Carbon Ablator in Aerothermal Environments

Conformable Phenolic Impregnated Carbon Ablator, a cousin of Phenolic Impregnated Carbon Ablator (PICA), was developed at NASA Ames Research Center as a lightweight thermal protection system under the Fundamental Aeronautics Program. PICA is made using a brittle carbon substrate, which has a very low strain to failure. Conformable PICA is made using a flexible carbon substrate, a felt in this case. The flexible felt significantly increases the strain to failure of the ablator. PICA is limited by its thermal mechanical properties. Future NASA missions will require heatshields that are more fracture resistant than PICA and, as a result, NASA Ames is working to improve PICA's performance by developing conformable PICA to meet these needs. Research efforts include tailoring the chemistry of conformable PICA with varying amounts of additives to enhance mechanical properties and testing them in aerothermal environments. This poster shows the performance of conformable PICA variants in arc jets tests. Some mechanical and thermal properties will also be presented.

ablative materials↗

NASA NTRS2010

Introduction to Vector Field Visualization

Vector field visualization techniques are essential to help us understand the complex dynamics of flow fields. These can be found in a wide range of applications such as study of flows around an aircraft, the blood flow in our heart chambers, ocean circulation models, and severe weather predictions. The vector fields from these various applications can be visually depicted using a number of techniques such as particle traces and advecting textures. In this tutorial, we present several fundamental algorithms in flow visualization including particle integration, particle tracking in time-dependent flows, and seeding strategies. For flows near surfaces, a wide variety of synthetic texture-based algorithms have been developed to depict near-body flow features. The most common approach is based on the Line Integral Convolution (LIC) algorithm. There also exist extensions of LIC to support more flexible texture generations for 3D flow data. This tutorial reviews these algorithms. Tensor fields are found in several real-world applications and also require the aid of visualization to help users understand their data sets. Examples where one can find tensor fields include mechanics to see how material respond to external forces, civil engineering and geomechanics of roads and bridges, and the study of neural pathway via diffusion tensor imaging. This tutorial will provide an overview of the different tensor field visualization techniques, discuss basic tensor decompositions, and go into detail on glyph based methods, deformation based methods, and streamline based methods. Practical examples will be used when presenting the methods; and applications from some case studies will be used as part of the motivation.

Kao, David↗

NASA NTRS2007

Displaying Properties of PDFs

PDFVis is a computer program that assists in visualization of uncertainty as represented by a probability density function (PDF) located at each grid cell in a spatial domain. The functions that PDFV performs are listed.

Kao, David↗

NASA NTRS2005

Modeling and Visualizing Flow of Chemical Agents Across Complex Terrain

Release of chemical agents across complex terrain presents a real threat to homeland security. Modeling and visualization tools are being developed that capture flow fluid terrain interaction as well as point dispersal downstream flow paths. These analytic tools when coupled with UAV atmospheric observations provide predictive capabilities to allow for rapid emergency response as well as developing a comprehensive preemptive counter-threat evacuation plan. The visualization tools involve high-end computing and massive parallel processing combined with texture mapping. We demonstrate our approach across a mountainous portion of North California under two contrasting meteorological conditions. Animations depicting flow over this geographical location provide immediate assistance in decision support and crisis management.

Kao, David↗

NASA NTRS2004

Picturing Data With Uncertainty

NASA is in the business of creating maps for scientific purposes to represent important biophysical or geophysical quantities over space and time. For example, maps of surface temperature over the globe tell scientists where and when the Earth is heating up; regional maps of the greenness of vegetation tell scientists where and when plants are photosynthesizing. There is always uncertainty associated with each value in any such map due to various factors. When uncertainty is fully modeled, instead of a single value at each map location, there is a distribution expressing a set of possible outcomes at each location. We consider such distribution data as multi-valued data since it consists of a collection of values about a single variable. Thus, a multi-valued data represents both the map and its uncertainty. We have been working on ways to visualize spatial multi-valued data sets effectively for fields with regularly spaced units or grid cells such as those in NASA's Earth science applications. A new way to display distributions at multiple grid locations is to project the distributions from an individual row, column or other user-selectable straight transect from the 2D domain. First at each grid cell in a given slice (row, column or transect), we compute a smooth density estimate from the underlying data. Such a density estimate for the probability density function (PDF) is generally more useful than a histogram, which is a classic density estimate. Then, the collection of PDFs along a given slice are presented vertically above the slice and form a wall. To minimize occlusion of intersecting slices, the corresponding walls are positioned at the far edges of the boundary. The PDF wall depicts the shapes of the distributions very dearly since peaks represent the modes (or bumps) in the PDFs. We've defined roughness as the number of peaks in the distribution. Roughness is another useful summary information for multimodal distributions. The uncertainty of the multi-valued data can also be interpreted by the number of peaks and the widths of the peaks as shown by the PDF walls.

Kao, David↗

NASA NTRS2003

Software Aids Visualization of Computed Unsteady Flow

Unsteady Flow Analysis Toolkit (UFAT) is a computer program that synthesizes motions of time-dependent flows represented by very large sets of data generated in computational fluid dynamics simulations. Prior to the development of UFAT, it was necessary to rely on static, single-snapshot depictions of time-dependent flows generated by flow-visualization software designed for steady flows. Whereas it typically takes weeks to analyze the results of a largescale unsteady-flow simulation by use of steady-flow visualization software, the analysis time is reduced to hours when UFAT is used. UFAT can be used to generate graphical objects of flow visualization results using multi-block curvilinear grids in the format of a previously developed NASA data-visualization program, PLOT3D. These graphical objects can be rendered using FAST, another popular flow visualization software developed at NASA. Flow-visualization techniques that can be exploited by use of UFAT include time-dependent tracking of particles, detection of vortex cores, extractions of stream ribbons and surfaces, and tetrahedral decomposition for optimal particle tracking. Unique computational features of UFAT include capabilities for automatic (batch) processing, restart, memory mapping, and parallel processing. These capabilities significantly reduce analysis time and storage requirements, relative to those of prior flow-visualization software. UFAT can be executed on a variety of supercomputers.

Kao, David↗

NASA NTRS2002

Visualizing 2D Probability Distributions from Satellite Image-Derived Data

Creating maps of biophysical and geophysical variables using Earth Observing System (EOS) satellite image data is an important component of Earth science. These 2D maps have a single value at every location and standard techniques are used to visualize them. Current tools fall short, however, when it is necessary to describe a distribution of values at each location. Distributions may represent a frequency of occurrence over time, frequency of occurrence from multiple runs of an ensemble forecast or possible values from an uncertainty model. 'Distribution data sets' are described, then a case study is presented to visualize such 2D distributions. Distribution data sets are different from multivariate data sets in the sense that the values are for a single variable instead of multiple variables. Our case study data consists of multiple realizations of percent forest cover, generated using a geostatistical technique that combines ground measurements and satellite imagery to model uncertainty about forest cover. We present several approaches for analyzing and visualizing such data sets. The first is a pixel-wise analysis of the probability density functions for the 2D image while the second is an analysis of features identified within the image. Such pixel-wise and feature-wise views will give Earth scientists a more complete understanding of distribution data sets.

Kao, David↗

NASA NTRS2002

Visualizing Spatially Varying Distribution Data

Box plot is a compact representation that encodes the minimum, maximum, mean, median, and quarters information of a distribution. In practice, a single box plot is drawn for each variable of interest. With the advent of more accessible computing power, we are now facing the problem of visual icing data where there is a distribution at each 2D spatial location. Simply extending the box plot technique to distributions over 2D domain is not straightforward. One challenge is reducing the visual clutter if a box plot is drawn over each grid location in the 2D domain. This paper presents and discusses two general approaches, using parametric statistics and shape descriptors, to present 2D distribution data sets. Both approaches provide additional insights compared to the traditional box plot technique

Kao, David↗

NASA NTRS2001

On Animating 2D Velocity Fields

A velocity field, even one that represents a steady state flow, implies a dynamical system. Animated velocity fields is an important tool in understanding such complex phenomena. This paper looks at a number of techniques that animate velocity fields and propose two new alternatives. These are texture advection and streamline cycling. The common theme among these techniques is the use of advection on some texture to generate a realistic animation of the velocity field. Texture synthesis and selection for these methods are presented. Strengths and weaknesses of the techniques are also discussed in conjunctions with several examples.

Kao, David↗

NASA NTRS2001

3D Flow Visualization Using Texture Advection

Texture advection is an effective tool for animating and investigating 2D flows. In this paper, we discuss how this technique can be extended to 3D flows. In particular, we examine the use of 3D and 4D textures on 3D synthetic and computational fluid dynamics flow fields.

Kao, David↗

NASA NTRS2001

Advecting Procedural Textures for 2D Flow Animation

This paper proposes the use of specially generated 3D procedural textures for visualizing steady state 2D flow fields. We use the flow field to advect and animate the texture over time. However, using standard texture advection techniques and arbitrary textures will introduce some undesirable effects such as: (a) expanding texture from a critical source point, (b) streaking pattern from the boundary of the flowfield, (c) crowding of advected textures near an attracting spiral or sink, and (d) absent or lack of textures in some regions of the flow. This paper proposes a number of strategies to solve these problems. We demonstrate how the technique works using both synthetic data and computational fluid dynamics data.

Kao, David↗

NASA NTRS2000

On Animating 2D Velocity Fields

A velocity field. even one that represents a steady state flow implies a dynamical system. Animated velocity fields is an important tool in understanding such complex phenomena. This paper looks at a number of techniques that animate velocity fields and propose two new alternatives, These are texture advection and streamline cycling. The common theme among these techniques is the use of advection on some texture to generate a realistic animation of the velocity field. Texture synthesis and selection for these methods are presented. Strengths and weaknesses of the techniques are also discussed in conjunction with several examples.

Kao, David↗

NASA NTRS1999

Which Way Is the Flow?

The line integral convolution (LIC) technique has been known to be an effective tool for depicting flow patterns in a given vector field. There have been many extensions to make it run faster and reveal useful flow information such as velocity magnitude, motion, and direction. There are also extensions to unsteady flows and 3D vector fields. Surprisingly, none of these extensions automatically highlight flow features, which often represent the most important and interesting physical flow phenomena. In this sketch, a method for highlighting flow direction in LIC images is presented. The method gives an intuitive impression of flow direction in the given vector field and automatically reveals saddle points in the flow.

Kao, David↗

NASA NTRS1998

Demonstrations at Supercomputing 1998

Contents of the papers include: Visualization techniques- The next generation, Small-machine visualizing very big data sets, Public display of Lunar Prospector data, Steering molecules via Feel, High-dimensional data browser, Multi-source visualization, Interactive surface flow visualization, and the Virtual Windtunnel.

Bryson, Steve↗