The Quarterly Publication of the Numerical 

Aerospace Simulation Systems Division

Researchers at Stanford University, supported

by NASA and the NAS Systems Division, are

studying muscle control to determine how it

produces dexterity and its implications for

future NASA missions. Page 6

New NAS Applications Branch Formed — 4

IPG Team Meets Large Scale Computing Milestone — 10

ILab: New Tool For IPG Parameter Studies — 12

New Version of Chimera Grid Tools Released — 18

Computers For Future Space Missions — 15

Spring 2001
Vol. 2, No. 1 • Spring 2001

Executive Editors: Bill Feiereisen

John Ziebarth

Editor: Nicholas A. Veronico

Writers: Holly A. Amundson

William M. Chan

Jill A. Dunbar

Stuart E. Rogers

Graphic Designer: Sue Kim

Illustrator: Gail Felchle

Contact the Editor:

Nicholas A. Veronico

Gridpoints

M/S 258-6

Moffett Field, CA 94035-1000

Tel. (650) 604-3046

Fax (650) 604-4377

nveronico@mail.arc.nasa.gov

Gridpoints is a quarterly publication of the NAS

Systems Division at NASA Ames Research Center.

The division’s staff includes government employees and contractors from Advanced Management

Technology Inc., Computer Sciences Corp., Cray

Inc., Eloret, Raytheon Company, and SGI.

Gridpoints acknowledges that some words, model

names and designations mentioned herein are the

property of the trademark holder. Gridpoints uses

them for identification purposes only.

The staff of Gridpoints would like to

thank the following people for their

assistance in preparing this publication: 

Michael Aigner, Dick Anderson, Michael

Boswell, Dan Cooke, Christine Cortez,

Glenn Deardorff, M. Jahed Djomehri,

Chris Gong, Ana Grady, T.R. Govindan,

Jean H. Heegaard, Bill Johnston, Chris

Kleiber, Karen McCann, Nagi N. Mansour,

Shelley Marshall, Meyya Meyappan, Gina

Morello, Paul Munoz, Todd Novak, Marcia

Redmond, Frank Sabadin, Ryan Spaulding,

Valerie Steele, Ron Sykora, Leigh Ann

Tanner, Bill Thigpen, Arsi Vaziri, Cliff

Williams, Maurice Yarrow, Steve Zornetzer

On The Cover:

Subscribe to Gridpoints

Subscriptions to Gridpoints are complementary.

Please send e-mail with your name, company

name, title, address, and zip code to:

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Note: Subscribers outside the continental United

States can access Gridpoints on the web in PDF

format at: http://www.nas.nasa.gov/gridpoints

The Quarterly Publication of the Numerical

6 Aerospace Simulation Systems Division

10

12

18

Features

Muscle Modeling: The Quest

For Dexterity

Researchers at Stanford University, supported by NASA and the NAS Systems Division,

are studying muscle control to determine

how it produces dexterity, and its implications for future NASA missions.

Nicholas A. Veronico

ILab: New IPG Tool Improves

Parameter Study Implementation

NAS researchers have designed a tool to fully 

automate parameter study creation and launching

within the IPG.

Holly A. Amundson

IPG Team Meets Large Scale

Computing Milestone

To meet its latest milestone, the Information Power

Grid team incorporated the updated 512-processor

Origin 2000, and ran a 14-million point computation across three remotely located computers.

Holly A. Amundson

Space Computing – The

Present Frontier

Computer modernization and miniaturization

hold the key to longer-duration space missions to

the outer reaches of the solar system.

Holly A. Amundson

Chimera Grid Tools Software

A new, updated version of the comprehensive

Chimera Grid Tools software package for overset grid generation has recently been released.

William M. Chan and Stuart E. Rogers

Researchers are studying muscles as a distributed control system. As a person lifts an object in their

hand, the biceps muscle flexes to produce a resultant movement around the elbow. See page 6 for

the full story. (G.J. Totora’s Principles of Anatomy and Physiology, Sixth Edition, used with permission of John Wiley & Sons, Inc.)

15
Gridpoints 1

NAS Mission

To lead the country in the research

and development of high-performance

computing for NASA Programs and

Missions by being the first to develop,

implement, and integrate new highperformance computing technologies

into useful production systems.

To provide NASA and its customers

with the most powerful, reliable, and

usable production high-performance

computing systems in the country.

Almost three years ago, the NAS Division began NASA’s Information

Power Grid (IPG) project at a time when the concept of Distributed

High Performance Computing was in its infancy. The division joined

an international community that had come together out of mutual interest to

develop a common compute and data infrastructure for science and engineering. The grid community evolved from a vision of shared access to resources,

and defined a research agenda to achieve this vision. At that time, there was no

running infrastructure that could be provided to scientists and engineers; however, there was a shared view of the research areas that needed to be addressed in

order to build the grid.

The grid project has come a long way in three short years. The once casual grid

community has evolved into a formal organization known as the Grid Forum.

This group has fostered world-wide interest and participation in defining the

grid. Various national and international grid projects have begun. I’m pleased

that NASA and NAS – along with our National Science Foundation (NSF)/

Partnership for Advanced Computational Infrastructure (PACI) and Department of Energy colleagues – are on the leading edge of

this revolution in the U.S., and are actively becoming

engaged with our overseas colleagues.

I’m writing this while participating in the first Global

Grid Forum (http://www.ggf1.nl), a working meeting

where technical experts are defining the standards upon

which all the international grid projects will interoperate.

The first Grid Forum, held two years ago, was hosted by

NAS. (We were worried that we could not accommodate

the 110 participants in our auditorium.) The Global

Grid Forum has advanced far beyond our humble beginnings. Attendance this

year had to be capped at 325 participants — remember, this is a working meeting, and we had to turn people away. To have such interest in the creation of our

own computing future is quite gratifying.

One of NASA’s great strengths is to carry research tasks through to working systems. This has been the IPG team’s focus for the last three years – to put in place

an infrastructure to provide researchers and engineers the computing power to

advance science. A working grid now exists that includes high-performance systems at three NASA research centers. In addition, we are about to link IPG with

the grids that our colleagues are building at the NSF/PACI centers. Uniform

access to many disparate resources has been touted as IPG’s advantage, but ease of

use has lagged. Portals have sprung up in order to make this access easier and more

uniform, and I invite you to visit the Information Power Grid portal, the IPG

Launch Pad at http://www.ipg.nasa.gov and see what this is all about. All of this

grid work remains focused on supporting the science and engineering of NASA’s

missions. I hope you enjoy the articles in this issue, which feature some of the

exciting work that will increasingly be done by using the grid as a tool.

As always, I welcome your feedback.

Bill Feiereisen 

wfeiereisen@mail.arc.nasa.gov

From The Division Chief

Continued on Page 2

New NAS Research

Branch Chief Appointed

NAS Systems Division Chief Bill

Feiereisen announced recently

that Bryan Biegel has been appointed

chief of the division's Research Branch.

The branch consists of some 40 programmers and scientists whose work

encompasses computer science research and development for aerospace

applications, NASA’s Information

Power Grid (IPG), and nanotechnology, among other areas.

“The challenges and possibilities of the

Research Branch Chief position are

compelling to me,” Biegel said. His first

order of business is to ensure that the

branch technical staff can work with

minimal bureaucratic “red tape,” and

that the staff’s talents and expertise are

fully utilized and acknowledged. “I’m

very excited about helping everyone in

the branch to work happily and efficiently, so that we will in turn help

NAS continue to do great things in

high-performance computing.” 

Biegel has worked in the NAS organization for more than three years as a

researcher in the semiconductor device

modeling group. Before accepting the

News

From

NAS
2 Gridpoints

News From NAS

branch chief position, he was employed by Computer Sciences Corp. under a NASA contract. His most recent

research projects have focused on quantum effects in ultrasmall conventional electronic devices, thermal and radiation

effects in space electronics, and electronic device modeling in

the IPG environment. 

Prior to joining the NAS division in

1997, Biegel was a research assistant at

Stanford University, where he developed

SQUADS, the Stanford Quantum

Device Simulator, an automated, extensible software package for accurately

modeling one-dimensional quantum

electronic devices. Biegel holds both a bachelor of science

degree and master’s degree in electrical engineering from the

University of Oklahoma, and earned his Ph.D. in electrical

engineering from Stanford.

High Dependability Computing

Workshop a Success

The first High Dependability Computing Consortium

(HDCC) workshop was held at the NAS Facility

January 10-12 to gather parties interested in making computer software more reliable for the future. Partnering to

form the HDCC, Carnegie Mellon University and NASA

Ames Research Center had the same goal in mind – to eliminate computer failures.

“This is an extremely important event for NASA – future

missions depend on the long-term success of software reliability and dependability,” says Steve Zornetzer, director of

Information Sciences and Technology at Ames. “This consortium represents a very unique and bold approach to tackling one of the most vexing problems, and potentially one of

the most important problems for the advancement of information technology in the 21st century,” he says.

When a computer fails, any number of things can go wrong

– downtime results in hundreds of thousands of e-commerce

dollars lost every hour, computer failures in space endanger

NASA mission success, and computer software failures at the

bank translate to no money at the ATM. All these problems

can be avoided by funneling time and effort into ensuring

dependability of the software used to run computers. 

During the three-day event, participants from industry, government, and academia reviewed case studies and participated in technology discussions to start the wheels turning on

the journey to software reliability. Speakers at the workshop

based their presentations on past software failures, present

capabilities, and requirements for future computing to

emphasize the importance of software dependability.

Participants included specialists from the University of

Southern California, Hewlett-Packard, NASA Goddard

Space Flight Center, Bell Laboratories, the Department of

Defense, and Canada’s McMaster University, among others. 

“I’m hoping that this will be the beginning of a continuous

process by which we put together a long-term effort (20 to

50 years) to build not just the industry, but the field of computer science,” says Jim Morris, dean of the School of Computer Science at Carnegie Mellon University. The workshop

planning committee will schedule more events in the coming months.

New Web Features for NAS Users

Anew, secure tool for scientists using the NAS Facility’s

supercomputing resources debuted January 23 on the

division’s website. The System Status page allows users to view

important information on the operational status and utilization of computing and storage resources. Users can also

check scheduled maintenance periods and get other useful systems data, which is updated automatically every 10 minutes.

From one page, users can: get the message of the day

(MOTD) for each user type; see the schedule for upcoming

system outages – and review previous outages; find out if any

systems are “down;” check system status history; view network router status; as well as view and print a histogram

showing system and storage utilization. 

Local NAS Facility users can also get status on printer queues.

The System Status page was developed by Ernst Kimler in

the NAS Engineering Branch.

Also new to the User Services section: a User FAQ page, with

answers to basic questions about using NAS computing

resources, and an easy-to-access user help form to request

assistance with a problem. 

For user-related assistance, contact NAS User Services at

nashelp@nas.nasa.gov or call (800) 331-8737.

NAS Scientist Named to Editorial Post

NAS Systems Division senior scientist Cun-Zheng Ning

has been named associate editor of the Journal of

Quantum Electronics (JQE), the monthly journal of the

IEEE-LEOS (Lasers and Electro-Optics Society). Ning’s

appointment was unanimously approved by the IEEE-LEOS

Board of Governors.

During his three-year tenure, which began in January 2001,

Ning’s duties will include identifying reviewers and making

decisions regarding acceptance of submitted papers. He has

published extensively in the fields of optoelectronics, lasers,

and nonlinear physics, and has served as conference chair or

member of technical committees in the field of optoelecBryan Biegel
www.nas.nasa.gov/gridpoints Gridpoints 3

tronics at many international conferences. Ning is task lead

for device modeling projects within the NAS division. He

obtained his Ph.D. in theoretical physics

at the University of Stuttgart, Germany.

He was a research assistant professor at

the University of Arizona before joining

NAS. Ning is employed by Computer

Sciences Corp.

IEEE-LEOS is considered to be the one of

the most influential organizations worldwide in the fields of lasers, optoelectronics, and optics sciences and engineering. Since inception in the early 1960s,

JQE has consistently received one of the highest citation ratings of any IEEE journal.

New Version of PEGASUS 

Code Released

Apublic beta release of the PEGASUS code (version 5.1)

is now available. PEGASUS is a key component in a

series of tool used in computational fluid dynamics (CFD)

analysis. Version 5.1 significantly reduces user effort and

allows for easier operation of the code.

The PEGASUS code is responsible for connecting overset

volume grids and preparing them for the OVERFLOW flow

solver. The new version dramatically reduces the time

required to perform the overset connection. The result is a

process which is automatic for many flow analysis problems.

The PEGASUS code, developed at NASA Ames Research

Center in collaboration with Microcraft Corp., is used by

both government and industry users. The code is used in

conjunction with the Chimera Grid Tools (used for grid generation) and OVERFLOW. A parallel version of PEGASUS

is in the works.

Interested readers can contact NAS researcher Stuart Rogers

at rogers@nas.nasa.gov for additional details. To obtain additional information on PEGASUS, including a software

request form and user’s manual, visit:

http://www.nas.nasa.gov/%7Erogers/pegasus/intro.html

Mars Landing Site Archive

Now Online

An extensive archive of Mars data is now available online

to assist in the selection of landing sites for the Mars

Explorer Rover (MER) twin rover missions scheduled for

launch in 2003. This interactive website, called the

Marsoweb (http://marsoweb.nas.nasa.gov/landingsites/) is a

collaboration between the Center for Mars Exploration

(CMEX) and the NAS Systems division. CMEX principal

investigator Virginia Gulick provides general guidance and

serves as contact to the Mars research community for data

content, and NAS senior research engineer Glenn Deardorff

is responsible for technical development. The pages contain

data from both the current Mars Global Surveyor (MGS)

and previous Viking Missions. 

The landing site section of the Marsoweb for the 2003 missions was developed, in part, for a Mars landing site workshop held at NASA Ames, January 24-26. Graphics from the

Mars site were used frequently in workshop participants’

talks, according to Deardorff. “The website was well received

and is being very actively used,” he says. 

The new landing site section enables researchers to navigate

landing sites within the equatorial landing zone of Mars

using Java-based image maps generated from geology maps,

elevation data, high-resolution MGS images, and a number

of other datasets. Much of the data available on the site was

presented to the Mars research community for the first time

at the January workshop. Deardorff has plans to incorporate

datasets for the entire surface of Mars in the future.

Cun-Zheng Ning

On February 26 2001, Nirav Kapadia was the guest

speaker at a NAS Information Power Grid Seminar

where he presented the talk, “Integrating Grid services

and Web Technologies to Power Application Portals: The

PUNCH Approach.” PUNCH (the Purdue University

Network Computing Hubs) is a prototype system that

allows users to run unmodified software via standard web

browsers. Kapadia’s focus was on Purdue’s approach to

key issues in the design of such a system, including: the

interface to the external world; internal system design;

support for legacy applications; and resource management

across administrative domains.

On March 3, 2001, Robert Horst from 3ware, Inc. discussed several different approaches for building Storage

Area Networks (SANs) using standard Ethernet switches

and interfaces in his NAS New Technology Seminar

“Ethernet Storage Area Networks.” A taxonomy for the

various types of network-attached storage was suggested,

with the focus of the talk on the hardware and software

technology of the native E-SAN implementation recently introduced in the 3ware Network Storage Unit.

These highlights are just two of the NAS technical seminars held recently. For a complete listing of NAS seminars, see the NAS technical training event Website :

http://www.nas.nasa.gov/User/Training/training.html

Videotapes of most seminars can be borrowed by sending

your request to: doc-center@nas.nasa.gov. For questions,

contact Marcia Redmond at: mredmond@mail.arc.nasa.gov

NAS Technical Seminars Span Range of Topics
4 Gridpoints

Believing in the power of individuals, and in harnessing

that power to accomplish important goals for NASA,

scientist Dochan Kwak is bringing researchers from

diverse disciplines together in a new organizational branch.

The branch is chartered to develop high-performance computing applications in space science, Earth and biological sciences, and the aerosciences applications that have always

been a cornerstone of the NAS organization. 

Complementing NAS’s existing Engineering and Research

branches, the Applications Branch completes the integration

plan envisioned by Division Chief Bill Feiereisen. “If you

think in terms of the various layers of technology, you start

with hardware support, and above that is systems software,

with tools above that, and applications at the top,” says

Feiereisen. (See chart below.) “Because NAS has always been

dependent on people from other organizations to develop

the applications, the idea was to bring in scientists from

Code A (the Aerospace Directorate at Ames Research

Center) to fill in the top of the ‘vertical integration stack.’”

Because applications work can’t be completely self-contained

within one organization, adds Feiereisen, the new branch is

additionally chartered to become a “conduit to other application areas,” such as Earth sciences.

The former Code A scientists, who joined NAS in May

2000, have extensive experience in aerospace applications,

and have close associations with NASA programs involved in

space transportation development and aerospace vehicles.

“We are in contact with the aerospace vehicle developers and

designers,” says Kwak, who was previously a Code A branch

chief. “So, while NAS’s high-end computing has been designed to address some of the large-scale computational issues,

now we (at NAS) can go a step further and demonstrate that

these application tools and procedures are useful to NASA

enterprises and industry customers.”

Focus on Advanced Technology Applications

Since May 2000, the group has been working together to create the branch organization, charter, and goals. Up to now,

and continuing through fiscal year 2001, Kwak explains,

most branch members have been engaged in work on

NASA’s Advanced Technology Applications (http://cas.arc.

nasa.gov/ grand.html). ATA focuses on areas critical to the

entire lifecycle of aerospace vehicles – from concept to operation – in order to reduce design cycle time and improve the

safety and efficiency of future aerospace vehicles and systems.

One important NASA project, for example, is to develop

tools and procedures applicable to second- and third-generation reusable launch vehicle activities, which require sophisticated computational tools and vast amounts of computing

power. One of Kwak’s teams is working with engineers at

NASA’s Marshall Space Flight Center on rocket subsystem

simulations in order to develop engines for future reusable

launch vehicles.

Another team is working on “powered lift vehicle simulation”

associated with such high-performance aircraft as the vertical

take-off Harrier jet in “ground effect” (when the vehicle is

close to the ground, such as during landing). The team is

demonstrating the use of high-fidelity computational fluid

dynamics (CFD) and neural networks to generate a stability

and control database using the Information Power Grid. 

Beyond aerospace applications, branch members have

expertise in developing computational methods and algorithms that can be applied to other sciences. “We can contribute to other areas such as biocomputing, for example in

the area of hemodynamics (the movement of blood and the

forces involved in blood circulation) and electromagnetic

wave propagation in the human body,” explains Kwak.

The group’s work in hemodynamics includes manufactured

devices such as the DeBakey Ventricular Assist Device, a

New Applications Branch

Tackles Diverse Challenges

Current

Practice

Future

Direction

AApppplliiccaattiioonnss

Applications

Branch

Engineering

Branch Research

Branch

Tools and Environments

System Software

Supercomputers/Networks/Storage

Tools and Environments

System Software

Supercomputers/Networks/Storage

The NAS ‘vertical integration stack’ shows the types of technologies encompassed in the NAS mission, and where each branch

in the division meshes with the others. The new Applications

Branch spans both current and future technologies.
www.nas.nasa.gov/gridpoints Gridpoints 5

miniature heart pump. Kwak and NAS

colleague Cetin Kiris employed computational fluid dynamics techniques and

the division’s high-performance computers to improve the blood flow

through the life-saving device. (See below, The Kind of Scientist We Need.)

Creating Applications for the Grid

Another important aspect of the applications work is NASA’s Information

Power Grid (IPG) testbed, the distributed high-speed computing infrastructure being developed collaboratively by

government, university, and industry

partners. Feiereisen explains that the intent is to make the grid a platform for

applications and tools’ developers to work

on. “I frequently say that the IPG is the

focus of the division. So, I expect that

everyone in the new branch – applications people, those doing CFD, biology

people – will write (tools) for the IPG

structure. The underlying series of platforms will be IPG-like, and they have to

think in terms of developing their science and engineering

for the future based on those platforms.”

Kwak would like to use the technology developed under the

ATA to demonstrate applications on the IPG in the not-toodistant future. “The IPG project team has made great

progress to date. The next step is to make an actual impact

on some significant NASA project. This group will add that

element into the IPG work.” — Jill A. Dunbar

Advanced Technology Applications are funded by the Computational Aerospace Sciences portion of NASA’s High Performance

Computing and Communications (HPCC) Program.

Dochan Kwak, newly appointed chief of the NAS applications branch, is a perfect fit for his new role. “He

has broad experience in computational fluid dynamics

(CFD), and by extrapolation, computational physics,” says

NAS Division Chief Bill Feiereisen. “Dochan has the

expertise, experience, and management talent – he is just

the kind of scientist we need.”

In Kwak’s 22-year career at Ames Research Center, he has

served as chief of both the Advanced Computational

Methods and the Computational Physics and Simulations

branches. Previously, he was a staff scientist at Los Alamos

National Laboratory. He holds a bachelor of science degree

in mechanical engineering from Seoul National University,

and a Ph.D. in aeronautics and astronautics from Stanford.

“I believe that the individual contributor is the most valuable asset to a research organization,” Kwak says. “And I like

to foster an environment where people can be productive

and excel.” To that end, he has been working with counterparts Bryan Beigel and Bill Thigpen, who lead NAS’s

Research and Engineering branches, respectively. “Communication has increased quite a

bit, and we’ve encouraged our

groups to work closely together.”

Kwak has received numerous

honors, including the First

NASA Software of the Year

award, for developing INS3D, a

CFD code used for solving

steady-state and time varying

flow problems. He was inducted

into the Space Technology Hall

of Fame in April 1999. Among Kwak’s many achievements are

a patent (shared with several inventors) for the DeBakey

Ventricular Assist Device (see www.nas.nasa.gov/Main/

Features/2000/Winter/debakey.html), a miniature heart

pump that prolongs the life of patients awaiting heart transplants. In addition, he has authored more than 80 papers,

is a favorite on the international science lecture circuit, and

has served on many scientific committees. 

‘The Kind of Scientist We Need’

Dochan Kwak

NAS’s top-level ‘org’ chart shows the division’s three branches: Applications,

Engineering, and Research, as well as the Physics Simulation and Modeling Office. An

underlying matrix organization dovetails with the three branches. This organizational

structure fosters synergy and innovation, and provides flexibility for sharing people

resources among the working groups. Bulleted items denote key areas or personnel for

each branch.
6 Gridpoints

Muscle Modeling:

The Quest For Dexterity 

Researchers at Stanford University, supported by NASA and the NAS

Systems Division, are studying muscle control to determine how it

produces dexterity, and its implications for future NASA missions.

Walking from the desk to the printer to retrieve a

printed e-mail, or picking up a pot of coffee to

pour the morning’s first cup are two luxuries

most people take for granted. The loss of one’s mobility

never enters a person’s mind until a high-profile celebrity

such as Christopher Reeve becomes paralyzed. In the year

2001, humankind is capable of sending space probes to distant planets, but making a muscle move smoothly through

artificial stimulation has eluded the world’s finest physicians

and scientists. 

Muscles are essentially a distributed control system where

one tool (the brain) manages the input of information from

sensors (nerves) and instructs actuators (the neurons inside

the muscle) to contract or relax, thus producing movement.

In an effort to advance the theory and science of distributed

control systems, NASA’s Center for Turbulence Research,

supported in part by the NAS Systems Division, is conducting a muscle modeling study by Stanford University

doctoral student Michael Aigner and assistant professor of

biomechanical engineering Jean Heegaard. To better understand the mechanics of a distributed control system, the

researchers sought an existing example on which to base

their modeling efforts. Muscles are natural examples of a

distributed control system and, although how they work is

now well understood, how they are controlled to produce

dexterity has yet to be determined. 

“The musculoskeletal system is an actual physical system

that we can see and test in the lab,” says Aigner. “Over the

years, researchers have observed various actuation, or movement patterns and how these patterns change inside the

muscle. For example, a weight lifter would like to have the

muscle’s action synchronized because synchronized actuation produces maximum force; however, a pianist wants his

or her finger muscle actuation unsynchronized, which delivers maximum dexterity. This shows our inspiration for

studying not just one or two control variables, but rather a

distribution of them across the entire muscle.”

Artificial Muscle Movement Today

Today’s state of the art in the electrostimulation of muscles

is represented by the “Stand Up and Walk” project at the

University of Montpellier, France. Six patients recently

received microcomputer implants (located in the abdomen),

and electrode implants in the leg muscles. An external transmitter sends a signal to the implanted computer, which

stimulates the leg muscles to expand and contract. Using

this method, a paraplegic can lean on a walker and signal the

computer to move the leg muscles to produce movement. 

While Stand Up and Walk is an incredible accomplishment,

the drawback is that through artificial stimulation, patients

can only take about 10 steps before they are physically exhausted. “I’ve seen videos of paraplegic people using today’s

technology to walk in a lab for 10 yards, and then they’re

The Center for Turbulence Research (CTR) is a joint

NASA/Stanford center that sponsors the work of postdoctoral fellows on turbulence research. This includes

studies of turbulence modeling, combustion modeling, turbulence control, aero-acoustics and, in general,

research on flows where turbulence plays a dominant

role. The center has a facility at Stanford and one at

Ames Research Center (ARC). Co-located in the same

building at ARC are civil service scientists from the

Physics Simulation and Modeling Office of the NAS

Systems Division who collaborate with CTR postdoctoral fellows and visitors. The distributed control work described in this article was motivated by

CTR’s work on distributed control for aerodynamic

drag reduction.

Center for Turbulence Research
www.nas.nasa.gov/gridpoints Gridpoints 7

totally exhausted because there is no dexterity in what they

do,” says Heegaard. “They are walking like crazy, but its

crazy that they’re walking at all! There is still so little understanding of what produces smooth motion. 

“We must find out how muscles move using so little energy

when controlled by the brain, versus why muscles require so

much energy to perform the same task when artificially

stimulated. So far it’s a brute-force method that is still very

experimental. If we can understand the central nervous system pattern generator, one can start encoding it in small

computers and have paraplegic people walk again. It’s far

fetched, but conceptually it’s there.” 

Computational Modeling

For muscle studies to advance, researchers must progress

past today’s single-input parameter studies that assume there

is only one activation variable per muscle. Using singleinput parameters, the contractile behavior of the entire muscle is controlled by a single neural signal. By contrast, distributed control muscle models will enable researchers to

explore the dynamics that produce dexterity. 

Aigner and Heegaard spent the early computational phase of

their research (1999 to 2000) developing an understanding

As a person lifts an object in their hand (above), the biceps muscle flexes to produce a resultant movement around the elbow.

Zooming in on a microscopic level (right) distinguishes the structure of the myosin fibers and the attached neural network.

(These figures are from G.J. Totora’s Principles of Anatomy and

Physiology, Sixth Edition [ISBN 0-471-367885], and are

used with permission of John Wiley & Sons, Inc.)
8 Gridpoints

of how the muscle system behaved. Then the pair began

examining the basic geometries of a two-dimensional muscle model and the physics involved in its movement. Aigner

began the computational study using the computer program

Matlab, and is now using “Tact,” a custom finite element

code written in part by Heegaard, to model more complex

muscle systems. Tact is run on Linux-based PCs using dual

Intel Pentium processors. 

“We’re typically dealing with problems that have anywhere

from 1,000 to 50,000 degrees of freedom (or unknowns),

and CPU times ranging from a few minutes to a few hours,”

says Heegaard. “We’re not interested in having problems

that are so large that it will take us weeks to run. From a

research point of view, we want quick results to find out if

what we’re doing is working or not.”

In the early 1990s, supercomputers at the NAS Facility were

used by Clay Anderson, now at Stanford, to model the

movement of the musculo-skeletal system. Anderson used

the Intel Paragon supercomputer to predict the activation

patterns on a series of 30 to 40 muscles. In Anderson’s study,

each muscle had only one control parameter, which was

used to make a 3-D multi-body computer model of a skeleton walk. At that time, it took nearly four months to run the

computation on an SGI workstation, and about a month on

the Intel Paragon supercomputer. With advancements in

computer speed and technology over the past decade –

depending upon the parameters, Aigner and Heegaard’s

computations can be run in a few hours – if not minutes –

on their desktop computers. 

Aerodynamic and Robotics Implications

NASA is interested in the development of distributed control systems that have hundreds or thousands of actuators

controlling the flow around a wing. The challenge is to

develop a control system capable of managing the actuators

and sensors while remaining light enough for flight. The

fields of fluid dynamics and aero-elasticity have developed

theories that revolve around the idea that hundreds or thousands of small flaps or spoilers on a wing could improve air

flow over its surface. Aerodynamic drag is reduced by opening or closing the spoilers, depending on the aircraft’s “nose

up” angle in relation to its direction of flight.

“There is a parallel between a muscle and a wing system in

the sense that the muscle is also made up of a large number

of sensors and actuators,” explains Heegaard. “The big question is, how do we deal numerically and computationally with

the problem? How could one find the best configuration of

flaps up or down? The physics of the problem is so complex

that even if you had just a few parameters, calculating the

movements of the control system would be difficult.”

This computational visualization depicts the bending of the elbow joint and lifting of the forearm through the contraction of the

biceps muscle. An increasing load is applied at the wrist (black arrow) and the biceps muscle has to progressively contract to raise the

forearm. The plots above represent the amount of hydrostatic pressure in the body of the muscle as a result of the force exerted on the

tendons and the muscle’s contraction. The blue shades represent tensile stress while the yellow depicts compressive stress. Notice the

inhomogeneity of the stress distribution, with tensile stress at the periphery of the muscle and compressive stress in the bulk of the muscle belly as the forearm is raised. (Heegaard, Aigner; visualization by Eric Girod)
www.nas.nasa.gov/gridpoints Gridpoints 9

Studying distributed control systems also crosses over into

the field of robotics. To give a robot the dexterity of a

human hand, researchers must understand how the hand is

controlled in order to mimic its actions. Describing the

challenges of bringing dexterity to a robot, Heegaard says

that while a simple robot may have five movement parameters, a muscle has a nearly endless amount of control inputs.

Each input adjusts the muscle’s movement slightly, thereby

producing dexterity.

Future Simulations

Aigner and Heegaard’s next step is to study a distributed

muscle control system in action. As the project progresses,

the researchers foresee modeling simulations of multiple

muscles with distributed controls in a realistic musculoskeletal model of a hand. “For that we will need very powerful computers and computational facilities, and that’s

where the NAS Systems Division comes in,” Aigner said. “It

will involve a whole new area of research and an entirely new

set of computational challenges.”

—Nicholas A. Veronico

For more information on the Stand Up and Walk program:

http://europa.eu.int/comm/research/success/en/med/0077e.html

Ematrix

Ethick CE Ethin

Above left: Rheological model for one-dimensional muscle

contraction. The passive elasticity of the thick myosin (Ethick)

and thin actin (Ethin) fibers plus that of the surrounding fibrous

matrix (Ematrix) combine with the active behavior of the contractile element to generate muscle force.

Below left: The contractile element is a black box which represents the activation triggered ratcheting process of the crossbridges between the myosin and actin. As more cross-bridges

become attached, the greater the muscle’s ability to voluntarily

contract.

Matrix (Ematrix)

Actin (Ethin) Cross

Bridges

(CE)

Myosin (Ethick)

Michael Aigner is working on his Ph.D. in mechanical

engineering at Stanford University.

His interests include developing and

analyzing mathematical models of complex real-world dynamic control systems,

such as human skeletal muscle. He

received his undergraduate degrees in

mechanical engineering and mathematics from the University of California at

Davis and a masters in mechanical engineering from

Stanford.

Jean H. Heegaard is an Assistant Professor of Mechanical

Engineering at Stanford University. He conducts research

in the area of computer modeling of the

human body with special focus on the

musculo-skeletal system. Studies include

the use of finite element, multibody

dynamics and optimal control approaches to analyze joint biomechanics;

evaluation of surgical procedures; and

simulation of growth phenomena. He is

a member of the Orthopedic Research Society and the

American Society of Mechanical Engineering. In 1998, he

was awarded a Whitaker Foundation Research Grant to

study human knee joint biomechanics during pedaling

using advanced computer simulations. He has authored or

co-authored more than 20 papers, about 60 conference

papers, and holds editorial positions for several journals.

About The Researchers
10 Gridpoints

NASA’s Information Power Grid (IPG) team

achieved another milestone at the end of December

2000, successfully integrating the updated SGI

Origin 2000, Lomax, into the grid’s infrastructure. Lomax,

with 512 processors running at 400 megahertz each, is the

second large-scale machine to be incorporated into NASA’s

IPG. After integrating Lomax into the IPG production environment, the team demonstrated the grid’s capabilities by

solving a multi-part aerospace research problem using two

additional distributed IPG resources (one each at NASA’s

Langley and Glenn Research Centers, see Figure 1). 

IPG resources Sharp, a 24-processor SGI Origin 2000 at

Glenn Research Center in Ohio, and Whitcomb, an eightprocessor SGI Origin 2000 at

Langley Research Center in Virginia, were used in concert with

Lomax to solve complex aerospace

geometries using the computer

code OVERFLOW, version D,

(see sidebar: OVERFLOW IPG

Applications). This particular version of OVERFLOW is designed

specifically to take advantage of

parallel and distributed computing resources by limiting the number of processors that can

be used at any one time. “This will enable us to calculate a

complex aerospace problem much faster by using all three of

the machines,” explains Arsi Vaziri, IPG deputy project

manager. Using a small number of processors on three distributed machines will reduce turnaround time and create a

distributed, collaborative problem solving environment –

this approach to computing is also more cost-effective. 

The Importance of Data Transfer

In addition to demonstrating integration of a large supercomputer into the IPG structure, the December milestone

illustrates the importance of data transfer between remote

resources. “Our approach to the IPG is geared towards an

IPG Team Meets Large-Scale

Computing Milestone

To meet its latest milestone, the Information Power Grid team incorporated the

updated 512-processor Origin 2000, and ran a 14-million point computation

across three remotely located computers. 

Figure 1: IPG provides aggregated

computing in a parallel and distributed fashion. The grid can

effectively use underutilized resources, decrease computational

turnaround time, support a collaborative problem-solving environment, and provide more cost-effective computing solutions.
www.nas.nasa.gov/gridpoints Gridpoints 11

equal emphasis on data transmission and computational

speed,” explains Vaziri. Many of NASA’s newer research programs rely heavily on cross-center collaboration, and IPG

provides an economical method for sharing data between

colleagues at remote locations. 

“Agency-wide programs like ISE (Intelligent Synthesis

Environment) are essentially advanced design, or computer

design projects for NASA’s aerospace enterprise, and that’s

what we’re targeting – a computing environment that enables application domains to work with a large collection of

machines, including supercomputers,” explains IPG Project

Manager Bill Johnston.

The Globus middleware package, designed to enable different types of IPG resources to interface with each other, was

installed on Lomax with very few software changes. “Globus

enables the IPG team to easily run any computational code

and transfer data between Lomax, Sharp, and Whitcomb,”

explains Johnston.

In addition to having the ability to transfer code and data

easily, IPG users now have a collection of distributed

resources, located at the three NASA centers, to reduce endto-end turnaround time for aerospace design and simulation

problems. The next milestone, scheduled to be met in

September 2001, will incorporate an electron microscope

located at the University of California at San Diego into the

grid’s infrastructure to facilitate experiments requiring high

data-transfer rates using the IPG’s high-performance computing systems.

— Holly A. Amundson

One of the large-scale OVERFLOW applications the IPG team used to demonstrate the successful completion of

the December milestone was a Navier-Stokes

computational fluid dynamics (CFD) simulation of flow about a generic reusable launch

vehicle. The simulation was run using a distributed version of OVERFLOW, version D, which

required 215 grids, or computational meshes,

and approximately 14 million grid points (see

figure at right). Without OVERFLOW-D, this

application could not have been run on multiple machines. Running this aerospace configuration with the recently integrated 512-processor Origin 2000 verifies that the IPG is capable

of supporting aerospace calculations in a production environment. 

The team also used a wind tunnel flow simulation of a high-lift wing configuration, which required 32 computational grids and nearly nine

million grid points. This type of high-fidelity

CFD code provides significant gains for the aerospace industry by reducing design-cycle time.

OVERFLOW IPG Applications

IPG large-scale application results using OVERFLOW version D. Above: Visualization of a generic reusable launch vehicle X-38 flow simulation –

215 zones and 14 million points. (Maurice Yarrow)

Below: Wind tunnel flow simulation of a wingbody model encompassing 32 zones and 9 million

grid points. (M. Jahed Djomehri)
12 Gridpoints

Building large parameter studies may result in a pounding headache – editing hundreds of files, creating shell

scripts to run jobs, saving data entered, and shipping

the studies off for distributed processing is a recipe for errors.

Depending on the number of variables, a parameter study

(see sidebar: Creating Parameter Studies) can grow very large,

very quickly. There is, however, a new software package that

can solve this problem. NAS Research Scientist Maurice

Yarrow and NAS Software Engineer Karen McCann have

been working since early November 1999 to develop ILab,

“The Information Power Grid Virtual Laboratory,” a scriptgenerating program. ILab fully automates the process of creating and submitting parameter studies to IPG resources, as

well as monitoring them – all within a matter of minutes.

Designed to serve as an IPG research testbed, “ILab is modular and flexible enough so that you can use it to perform

IPG parameter study experiments within the context of the

tool’s capabilities,” Yarrow says. ILab has been used to test

features of Globus, a middleware package designed to enable

different applications to interface between IPG resources.

ILab enables IPG users to launch parameter studies and is

compatible with many resources connected to the grid. “ILab

is very generic, it gives users access to the grid without really

having to be a part of the grid. ILab is compatible with

Globus although it doesn’t require that researchers have a

Globus certificate to use it,” explains Yarrow. “ILab is, in a

way, like a gateway to the grid,” adds McCann. The tool will

run on any Unix operating system on the network supporting the required level of Perl (Perl 5.005) and Perl/Tk (Tk

8.0). “One of the problems we may face is that not all users

will have Perl and Perl/Tk on their systems. We’re trying to

work out an installation package to help solve this problem,”

explains McCann.

The Ins-and-Outs of ILab

The architecture of ILab can be broken up into a front half

and a back half. The front half makes use of a series of graphical user interface (GUI) wizards to collect information about

a user’s parameter study, such as resources used to run the job

and additional files necessary to complete the study. The

ILab: New IPG Tool

Improves Parameter

Study Implementation

NAS researchers have designed a tool to fully automate

parameter study creation and launching within the IPG.

Aparameter study is a collection of computer jobs

involving exactly the same computer program,

solver, or engineering tool, but each new job is run with

slightly different input. For example, aerospace parameter studies typically involve the velocity of the vehicle

(Mach number) and angle of attack (in still air, the angle

that the nose of the aircraft makes with the direction of

travel). Each input file for this aerospace study will have

a different Mach number and angle of attack. If there

are 10 values for each of the two variables in the study,

100 combinations of Mach number and angle of attack

exist, making it a 10-by-10 parameter study. The more

combinations, the more complicated a parameter study. 

The initial part of the task that ILab automates is the

process of creating input files for any number of combinations. Researchers can include any number of varying

parameters, creating an n-dimensional parameter study.

“I don’t know anybody who wants to use an editor 100

times to create 100 different variations of the same file.

It’s time-consuming and prone to error,” says Yarrow.

Creating Parameter Studies
www.nas.nasa.gov/gridpoints Gridpoints 13

back half of ILab is the code

generator – using the information collected by the front half,

it generates script files to run the

actual parameter study. 

Because the scripts are generated

automatically by ILab, users

have only to answer some very

specific questions, prompted by

the program. No programming

is necessary to run parameter

studies using the tool, although

users can include their own

scripts as ILab “processes.”

Currently, there are about 20

screens in the program – all were

written using a total of 23,000

lines of Perl and Perl/Tk code.

Had the program been written

in Java or C++, McCann estimates it would have taken

50,000 to 60,000 lines of code to complete, because she says,

these are very “wordy” programming languages.

ILab uses three different methods for sending parameter

studies to IPG resources: the local, Globus, and distributed

job models. The local job model is the most simplistic, limited to launching small computational jobs in sequential

order on a local workstation. The Globus job model (for users

with a Globus certificate) sends jobs to remote resources

using the Globus middleware package. The distributed job

model enables researchers to launch jobs onto remote systems without the requirement of a Globus certificate.

In addition, ILab has the ability to handle

a number of other middleware packages

commonly found on IPG resources

including Message Passing Interface (MPI)

and Portable Batch System (PBS) software.

“We have designed ILab to be modular in

a way that will permit us to easily add new

capabilities and make changes to existing

capabilities with relative ease,” explains

Yarrow. “To make the tool user friendly,

we added the ability to enter an arbitrary

command, which is necessary because

there is always something the user wants to

do that we are not going to be able to

anticipate,” explains Yarrow. “This way,

the user ultimately has flexibility in the

event that there is some variety of operation that is not supported by ILab.” 

The tool also has a load-balancing algorithm, which interrogates designated

machine resources, determines availability,

and sends jobs to those machines that are ready for immediate processing. In addition, ILab also has built-in job monitoring capabilities – each job is represented by a set of colorcoded icons to help the user determine a job’s progress.

McCann and Adrian DeVivo have designed an extensive

help package for the tool, complete with a searchable index.

“The index is in the form of a hierarchical list. From anywhere in the program users can pop up the help screen – it’s

a real user convenience,” explains McCann. ILab also furnishes a list of IPG resources available to researchers for running parameter studies, including detailed information about

each machine. In the near future, the team would like to

X-38 Crew Return Vehicle with finite-difference mesh system. ILab created and launched a 16-

by-12 parametric study in Mach number and angle-of-attack utilizing OVERFLOW-D2 to

calculate the flow field around the X-38.

Coefficients of lift-over-drag for the X-38 at the 192 values of Mach number and

angle-of-attack in the ILab parameter study.
14 Gridpoints

automate this resource list, running automatic resource

updates when the ILab application is opened.

Eliminating the Bugs

“There are a lot of possible error conditions; this is why we

need to have users test out ILab. Until it has been tested on

a significant number of ‘real world’ problems, you don’t really know what error conditions you’re going to run into,”

explains McCann. Users provide Yarrow and McCann with

helpful feedback to address errors and inadequacies as they

are discovered. Features such as plug-in capabilities, enabling

the use of a graphics post-processor of choice, will give users

more freedom when setting up parameter studies. 

Expanding ILab’s Capabilities

Parameter study software is just now starting to surface in the

research community. Currently, the size of the user community performing parameter studies is small, but growing.

Researchers are beginning to realize that they can find out a

lot about their problems by creating multi-variable parameter studies. “ILab is superior to other similar products currently on the market. It has a much more sophisticated user

interface, it simplifies the parameterization creation

sequence, and it’s easy to use because it doesn’t require any

hand editing of input files,” says Yarrow.

Although ILab is still in the pre-alpha testing phase, a great

deal of progress has been made on the development of the

tool over the past year. Yarrow and McCann plan to continue work on the tool, testing its capabilities with the assistance

of NAS users. Currently, the capability to automatically

restart jobs is being added, a feature required by many NAS

users performing computational fluid dynamics parameter

studies. Improvements like the restart option will be made

until the tool is mature enough to handle nearly all parameter studies imaginable.

— Holly A. Amundson

Left: ILab’s edit parameters

screen displays an input file:

The user will highlight fields

to be parameterized, and then

enter a list to create multiple

parameterized copies of the

input file. 

Below: During experiment

execution, ILab's job monitor

screen shows job status by colorcoded icons.
www.nas.nasa.gov/gridpoints Gridpoints 15

Anew generation of computers is on the horizon.

Unlike the massive, egomaniacal computer who

threatened to take control of the space ship in

Stanley Kubrick’s 2001: A Space Odyssey, future space computers will be made of atomic-scale components combined

with new methods of computing. Researchers are examining

how to design computers with low power requirements that

can withstand the extreme conditions in space. While results

of this research could be 15 to 20 years away, planning must

begin now.

Computers are essential to NASA’s exploration of our solar

system. Mission success depends on the reliability and survivability of space computers. While operating on a limited

Space Computing —

The Present Frontier

Computer modernization and miniaturization hold the key to longerduration space missions to the outer reaches of the solar system.

Figure 1: This image represents temperature and radiation levels in the solar system. Earth has one of the mildest environments while

the moons of Jupiter (Io, and Europa) represent some of the most extreme conditions of radiation and temperature in the solar system.

These moons also generate great scientific interest and are prime targets for exploration. The green shaded region represents the intense

burst of radiation from sun spots and is known to damage electronic systems in satellites. (NASA-Jet Propulsion Laboratory).
16 Gridpoints

supply of power, space computers may be exposed to high

levels of radiation and extreme temperatures. Computers

have performed reasonably well on many NASA missions,

despite having less than one-tenth the computing capability

of their counterparts on Earth. 

While Earth-based computers double in performance every

18 to 24 months, systems used in space have simply been

adaptations of terrestrial computer technology. This adaptation to the space environment results in a substantial loss of

performance, and does not provide the optimal technology

for NASA missions. 

To meet the demands placed on computer capabilities for

future NASA space missions to Mars, the moons of Jupiter,

and other distant planets, new and innovative approaches are

necessary. NASA researchers are currently combining new

computing models, nanotechnology, and biologically

inspired models to address the needs of space computing.

Facets of this research will be conducted by the

Revolutionary Computing project of NASA’s Intelligent

Systems (IS) Program.

“The Revolutionary Computing project will look at how

space systems are different from Earth-based computing.

Space computing has different requirements than Earth

computing, such as the need to operate in an extreme thermal and radiation environment, which creates an extra set of

challenges,” explains NAS Senior Scientist T.R. Govindan.

The project’s goal is to increase computer capacity by pursuing new ways of computing that will allow low-power

consumption, robust operation under exposure to high levels of radiation and extreme temperatures (see Figure 1, page

15). The IS Program is funded by NASA headquarters and

was inaugurated at the beginning of October 2000, merging

four areas of computer science research:

automated reasoning; human-centered

computing; intelligent data understanding;

and revolutionary computing.

From Earth to Space

The current trend in ground-based computing is miniaturization – making computer processors as small and as dense as

possible. This may not be the best approach

for designing space computers because

these small, dense processors are less tolerant to radiation and extreme temperatures

found in space. A current solution to this

problem is radiation hardening, which

involves redesigning and repackaging computer chips to negate the effects of radiation. Unfortunately, radiation hardening

decreases overall performance, making space-based computers much less capable than their terrestrial counterparts.

When an electronic device is exposed to the high levels of

radiation found in space, the entire system can be damaged,

rendering it useless (see Figure 2). Much progress has been

made in silicon-on-insulator (SOI) technology devices – most recently with the creation

of an insulating layer to prevent radiation

from reaching active regions of an electronic device and destroying it. Unfortunately,

SOI devices tend to have self-heating effects

and do not protect well against all types of

radiation in space.

“Recent results in physics and biology may

lead to revolutionary approaches to computer hardware,” says Dan Cooke, IS program manager. “These revolutionary technologies may address the extreme thermal

and radiation environment of space, as well

as the limited power and weight requirements for space-based systems. The

Revolutionary Computing Program is

designed to position NASA so that it can better exploit these

new technologies should they come to full fruition.”

Figure 2: Freeze frame from an Alpha radiation video demonstrating the effects of radiation on a semiconductor in space. The

video begins by showing the radiation strike in a confined area

on the surface of the electronic device, which eventually spreads

throughout the entire semiconductor. Exposure to high levels of

radiation can potentially interrupt the operation of a device,

threatening the safety of space missions. The use of silicon-oninsulator (SOI) technology is expected to minimize the effect

radiation has on electronic devices by keeping a majority of

the generated electric charge away from active systems in space.

(Bryan Biegel)

“...Revolutionary

technologies may

address the extreme

thermal and radiation environment of

space, as well as the

limited power and

weight requirements for spacebased systems.”

–Dan Cooke, program manager

NASA Intelligent Systems
www.nas.nasa.gov/gridpoints Gridpoints 17

“We are focusing on the computational models and languages implied by

these new approaches, and the development of certain massively parallel

algorithms that will be of benefit to

NASA in the future. Results from the

program may also be beneficial to the

development of problem solutions that

exploit more conventional approaches

to computing,” Cooke says.

Innovative Approaches

One innovative approach to improving

space computers is to mimic the design

of biological systems. “In general, biological processes are more fault-tolerant and they degrade gracefully – if

some part of the device is damaged, it

doesn’t sabotage the entire system,”

explains Govindan. 

With traditional computing, if some

part of the processor is damaged, the

whole computer fails. Neural computing, for example, may potentially provide a superior model for complex

information processing and problem solving. Neural networks contain a large number of simple interconnected and

interacting neurons – a helpful model for designing space

systems capable of exploring a massive amount of data in a

short period of time. Current work with neural computing

deals with instantaneous recognition of patterns; an example

is face recognition in a static image. Future research will deal

with dynamic, or moving environments.

Another approach to solving computationally complex problems rooted in biology is to use genetic and evolutionary

algorithms (See Gridpoints, Winter 1999, page 4). Genetic

and evolutionary processes naturally occurring in biological

structures such as DNA, cell functioning, and ecosystems are

excellent models for creating programs designed to manage

vast amounts of data and arrive at an optimal solution (see

Figure 3). Using biologically inspired models does, however,

create a challenge – data must be translated in a way suitable

for arriving at a reasonable solution. 

Nanotechnology, the manipulation of materials and devices

at the atomic- and nanoscales will also help improve space

computing. Nanotechnology devices consume less power,

and combined with architecture and new models of computation could be more robust in the extreme radiation and temperature environment of space. NAS researchers in the science and technology group are examining what new types of

devices can be made, and which ones would be suitable for

space computing applications.

New models of computation, combined with new materials

and devices could be the answer to current problems with

computers used to conduct missions to distant planets. Future

space missions include exploration of Io and Europa; however, planning must start now in order to make the journey

into deep space possible. 

—Holly A. Amundson

Evolvable

Hardware

Solution Algorithms

Evolution and Adaption

Reconfiguration

Adaption and Repair

Solution

Problem Class

Figure 3: This evolvable computing model uses genetic and evolutionary algorithms to

solve complex computing problems. Researchers working on the Revolutionary

Computing project are currently looking at ways to solve problems using biologically

inspired algorithms modeled after selective reproduction, mutation, and genome crossover

to search for an optimal solution. (Jason Lohn)

Artist’s rendering of a hydrobot exploring oceans beneath Europa’s

icecap. A mission of this type would present extreme environments for computing. (NASA/Jet Propulsion Laboratory)
18 Gridpoints

I

n computational simulations of flows about an object, a

computational grid is used to model the object’s geometry. For configurations involving complex geometry, viscous flow physics, and bodies in dynamic motion relative to

each other, the Chimera overset grid method is currently one

of the most computationally cost-effective options for

obtaining accurate aerodynamics results. Considerable success has been achieved in applying this method to a wide

variety of problems, as shown on page 19. 

Chimera Grid Tools (CGT) is a software package containing

a suite of tools for creating overset computational grids, and

performing geometry processing, grid diagnostics, solution

analysis, and flow solver input preparation. Scientists from

the Ames Army/NASA Rotorcraft Division and NAS

Systems Division released CGT version 1.4 in

October 2000. Since its inception at NASA four

years ago, CGT has been requested by and distributed to more than 200 domestic, commercial, and

U.S. government organizations under non-disclosure agreements. The software has been utilized in

aerospace, marine, automotive, environmental, and

sports applications. In addition to the authors, Steve

Nash (formerly with MCAT Inc. at NASA Ames)

and Pieter Buning (NASA Langley) collaborated on

the development of CGT. 

“Engineers in Aerodynamics Technology at the

Boeing Co. (Long Beach, Calif.), routinely use

CGT and the OVERGRID GUI (graphical user

interface) for overset grid generation on a wide variety of configurations,” says Jeff Slotnick, aerodynamics technology principal engineer. “Examples of

recent projects using Chimera Grid Tools and the

OVERGRID GUI include commercial and military transports, the Blended Wing Body, and Advanced

Theatre Transport configurations.”

“We use the Chimera Grid Tools on a daily basis to support

a wide range of Space Shuttle and International Space Station

analyses,” says Reynaldo Gomez, a senior engineer at NASA

Johnson Space Center. “CGT is rapidly becoming a comprehensive set of tools for generating and manipulating overset

grids. One of the main benefits of this set of tools is that it

collects utilities developed by the overset community into a

single package that runs on a wide range of platforms.”

The current procedure for performing computational flow

analysis on complex configurations typically involves the following four steps: Geometry processing to obtain a clean

By William M. Chan and Stuart E. Rogers

Chimera Grid Tools Software

A new, updated version of the comprehensive Chimera Grid Tools software

package for overset grid generation has recently been released.

Chimera Grid Tool’s hierarchical structure: low level library routines are

utilized by individual batch modules which themselves are called by the

configuration scripts and the graphical interface.
www.nas.nasa.gov/gridpoints Gridpoints 19

description of the configuration; grid

generation to obtain a set of overset composite grids around the configuration;

flow solution computation at given flow

conditions; and post-processing to

obtain integrated forces and moments, local pressure profiles, and various other

flow features data.

The Structure

of CGT

CGT consists of a

hierarchy of software modules together with documentation

and examples (see diagram, page 18). At the lowest level are

libraries containing commonly used functions such as

input/output routines for data files, stretching functions,

projection routines, and many others. This set of libraries is

gradually evolving into an applications programming interface (API) for grid-generation utilities. 

At one level above the libraries are about 30 independent

programs that can be used in batch mode. These programs

have been developed individually, are continuously updated,

and range from a few months old to about 12 years old.

Capabilities offered by these programs include editing, redistribution, smoothing and projection of grids, hyperbolic and algebraic surface and volume grid generation, and Cartesian grid generation. At the highest level,

two pieces of software communicate with the individual programs. The first is a graphical user interface and the second

is a collection of configuration automation scripts.

The OVERGRID Graphical User Interface

The primary function of OVERGRID is to provide a single

graphical interface environment for performing a wide range

of operations prior to running the flow solver.

(See: www.nas.nasa.gov/~rogers/cgt/doc/overgrid.

html). These operations typically include checking and processing the input geometry, generating the surface and volume grids, analyzing the

grid quality using various diagnostics, and creating input parameter files for the domain connectivity program and the flow solver.

Currently, OVERGRID can be used to create

structured grids from a geometry description composed of multiple panel networks or triangles. Users of OVERGRID have reported a reduction in grid generation

time by as much as a

factor of four.

A new module recently added to OVERGRID assists users in preparing inputs for the OVERFLOW

and OVERFLOW-D flow solvers. For dynamic simulations

involving bodies in relative motion, the OVERFLOW-D

input file may require up to 100 global parameters and about

70 to 90 parameters for each grid,

depending on the numerical scheme chosen.

Preparing such an

input file for a complex configuration

can be a formidable

task, especially for a

new user. The interface

offered in OVERGRID

provides a simplified set of

commonly used and self-explanatory options for the user to choose from. A fictitious example

using the Space Shuttle Launch Vehicle illustrates the type of

simulations that can be prepared using the new OVERFLOW-D interface in OVERGRID (see Figure 1, page 20). 

Configuration Automation Scripts

In a typical computational fluid dynamics (CFD) analysis,

many different CGT programs are used to proceed through

the grid generation phase. Most of these tools require similar

information about the grid system, including solid wall

information, boundary condition information, and information about which surfaces form separate components in the

configuration. 

A sample of recent simulations using grids created by Chimera

Grid Tools (clockwise from top left): Surface grids on a Navy

submarine (Applied Physics Laboratory, Johns Hopkins

University); Impeller section of the Space Shuttle Main Engine

(NAS Systems Division, NASA Ames Research Center); V-22

tiltrotor (Army Aeroflightdynamics Directorate); and the X-38

prior to release from the NASA B-52 airplane (NASA Johnson

Space Center).
20 Gridpoints

A Tcl (Tool command language) script system was recently

added to the CGT package that provides automation for

many of the steps performed during the grid generation

process. The scripts were developed in support of work in the

Advanced Subsonics Technology Program, where a group of

CFD specialists were tasked with computing the flow over a

Boeing 777 in a landing configuration in less than 50 working days. The geometry and surface grids for this configuration are shown in Figure 2. The group was able to exceed the

program’s milestone by computing the first solution of this

high-lift aircraft in only 32 working days.

User Input Improves Product

CGT is being continuously updated and improved. New features and capabilities are constantly added, usually as a result

of requests from the large user community. After the release

of version 1.4, input from users will be compiled and incorporated into a future release of CGT. Feedback from realworld users of CGT has enabled the software program to

evolve into the robust design tool that it is today. More information on CGT is available at: www.nas.nasa.gov/~rogers/

cgt/doc/man.html.

About the Authors

William M. Chan is currently a senior research scientist at

ELORET in the NAS Systems Division’s Applications Branch.

He is the primary author of OVERGRID and many of the modules in CGT. Since 1990, he has been a contractor at NASA

Ames working on algorithm and software development for overset grid technology in support of the Space Shuttle, Advanced

Subsonic Technology, and Rotorcraft programs. 

Stuart E. Rogers is an aerospace engineer also working in the

Applications Branch of the NAS Systems Division. He has been

working at NASA Ames since 1985 on the development and

application of CFD software. His work has included the codevelopment of the INS2D and INS3D flow solvers, Chimera

Grid Tools, and most recently, further development of the overset-grid software known as PEGASUS. His applications have

included problems in high-lift aerodynamics, bio-fluid flows,

and hydrodynamics.

Figure 1: An example of a fictitious Space Shuttle Launch

Vehicle separation procedure

showing the OVERGRIDOVERFLOW-D interface for

creating inputs for a simulation

involving four bodies in

dynamic relative motion. Each

body may contain multiple

grids where each grid is depicted in a different color. Simple

widgets allow the user to define

the different bodies and to specify their attributes such as mass,

moments of inertia, center of

gravity and applied loads.

Figure 2: Surface grids on a Boeing 777-200 transport aircraft

in landing configuration, which was analyzed using the CGT

script system.
www.nas.nasa.gov/gridpoints Gridpoints 21

Calendar of

Events

IEEE-NASA Symposium on 

Mass Storage Systems

San Diego, California • April 17-20

The 18th IEEE Symposium on Mass Storage Systems and

9th NASA Goddard Space Flight Center Conference on

Mass Storage will focus on the issues surrounding the storage of large data collections that are web accessible. Topics

for discussion include managing large volumes of data, longterm mass storage requirements, and experiences in fielding

solutions. Emphasis is on current and future practical solutions addressing issues in data management, storage systems

and media, data acquisition, long-term retention of data,

and data distribution. Conference information is available

at: www.storageconference.org/2001

International Parallel and Distributed

Processing Symposium (IPDPS 2001)

San Francisco, California • April 23-27

IPDPS is an international forum for engineers and scientists

from around the world to present their latest research findings in all aspects of parallel computation. In addition to

technical sessions of submitted paper presentations, the

meeting offers workshops, tutorials, an industrial track, and

commercial exhibits. Simultaneously, the Workshop on Parallel and Distributed Scientific and Engineering Computing

with Applications (PDSECA-01) will also be held at the

same venue. Visit www.ipdps.org for more information. 

The 2001 International Conference on 

Computational Science

San Francisco, California • May 28–30

The 2001 International Conference on Computational

Science is becoming a vital part of many scientific investigations, affecting researchers and practitioners in areas ranging

from aerospace and automotive, to chemistry, electronics,

geosciences, to mathematics, and physics. Attendance information is available at: www.ucalgary.ca/iccs 

or visit: www.hpcc.rdg.ac.uk/iccs

Mobile Terrestrial and Space Networking Workshop

NASA Ames Research Center • June 25-27

Hosted by NASA Research and Education Network

(NREN) and sponsored by NREN and the National

Science Foundation (NSF). The objective of this workshop

is to identify and explore various high-end wireless, mobile,

and satellite communications networking technologies, as

they can be used to support the scientific community. The

technical program will be divided into three themes: technologies and architectures, seamless integration of heterogeneous networks, and applications. Note that participation is

by invitation only. For more information, contact Marjory

Johnson at mjjohnson@arc.nasa.gov.

Sixth Annual Computational Aerospace Sciences

Workshop

NASA Ames Research Center • July 31—August 2

NASA’s High Performance Computing and Communications Program is hosting its sixth annual technology forum

on Computational Aerospace Sciences (CAS) at NASA Ames

Research Center, Silicon Valley, Calif. Researchers from

NASA, industry, academia, as well as other government

agencies will discuss the challenges and successes of their

work. For further details, visit:

www.cas.nasa.gov/cas2001.htm

10th IEEE International Symposium on High

Performance Distributed Computing

San Francisco, California • August 7–9

The 10th International Symposium on High Performance

Distributed Computing is a forum for presenting the latest

research findings on the use of networked systems for highperformance computing. Submissions are encouraged on all

aspects of high-performance distributed computing, visualization, and collaboration, including hardware technologies,

network protocols, the middleware that ties distributed

resources together into “computational, data, and collaboration Grids,” middleware that enables application use of

Grids, and tools and languages that support application

development. Detailed information is available at:

www-itg.lbl.gov/HPDC-10/

Visualization of a Harrier vertical take-off and landing fighter

jet with a 33-knot headwind, hovering 10 feet above the

ground. The engine inlet is ingesting a ground vortex. Computation by Jasim Ahmad, Neal Chaderjian, Scott Murman, and

Shishir Pandya. Visualization by Tim Sandstrom of the NAS

data analysis group.
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Chimera Grid Tools Software

A new, updated version of the comprehensive Chimera

Grid Tools software package for overset grid generation has

recently been released. See page 18.

Space Computing – The Present Frontier

Computer modernization and miniaturization holds the

key to longer-duration space missions to the outer reaches of the solar system. See page 15.