MY SPACE INDUSTRY EXPERIENCE
Kamara Brown
The George Washington University
School of Engineering and Applied Science
Department of Electrical Engineering
An Assessment of System Engineering Conceptual Design Laboratory
The John Hopkins University/Applied Physics Laboratory (JHU/APL)
Space Department, Space Systems Applications, Mission and Space Systems Engineering
Kamara Brown 1, James Leary 2, Richard Anderson
1
Research Associate, George Washington University
2
Principal Investigator, Section Supervisor Space System Engineer , JHU/APL 3 Co-Principal Investigator, Space System Engineer, JHU/APL
Research Problem Statement
As APL moves towards planning deep space
missions, there is a need for improving their
practices for conceptual spacecraft design. The
SE Lab is being developed to better position APL
in collaborating more effectively with NASA
centers as well as other potential partners who
have created similar design centers as an
standard approach to conducting business.
Defining the System Engineering Laboratory

3
What is the SE Lab?
Collaboration conceptual tool
Enhance existing system engineering and system
Architecture processes
 Characteristics / Intent of the SE Laboratory
Tool to assist and increase quality of proposals
Mission Concept Studies, System Test Planning
 Key Spacecraft Mission Question:
How do the different Spacecraft Subsystems interact to perform one or more missions?
Background
The SE Lab is being developed to better position
APL in collaborating more effectively with NASA
centers as well as other potential partners who have
created similar design centers as an standard
approach to conducting business.
Data Analysis
Phoenix Model Power Sheet Flow Chart
TAB: TxPWR vs DR
Tx_RF-PWR
Range (30 – 250)
A:2
[INPUT]
POWER DATA
EXCEL WORKBOOK
(B:2 = 2 X A:2)
Tx DC
POWER
B:2
[OUTPUT]
H:52
MEDIUM / HIGH
POWER
[INPUT]
TAB: Detailed Power Budget
Solar Sentinels
Power
WORKBOOK
H:52
ARRAY AREA
[OUTPUT]
CALCULATE ARRAY AREA WORKBOOK
PWR TOTAL = (0.23)(.77)(1358) (1/ R2) (A)
TOTAL POWER
[INPUT]
H:71
TOTAL CBE + 30% MARGIN
(BUS POWER)
[ OUTPUT]
Developed Flow Chart for
Subsystem to model in
Phoenix Integration
Relationship Models
In PWR’s World,
FAULT
PROTECTION is
considered
RELIABILITY
S/A Pointing
Requirements
G&C
FAULT PROTECTION
COMMUNICATIONS
Load PWR
SERVICES
Load PWR
SERVICES
SUN POINTING ERROR
MASS
RELIABILITY
LIFETIME /
DURATION
BATTERY
CYCLE
S/A ARTICULATION AXES
C&DH
CONTROL
CELLS
ARRAY
RADIATION
Load PWR
SERVICES
SUN DISTANCE
S/C MISSION SYSTEM
Load PWR
SERVICES
POWER
Load PWR
SERVICES
PROP
POWER
VOLTAGE RANGE
BATTERY
CYCLE
PWR
DISTRIBUTION
∑ PWR LOAD
PRIMARY PWR
SOURCE TYPES
SUN / ECLIPSE
CONDITIONS
PWR ELECTRONICS
PARAMETERS
(Box [PSE, PDU, SAJB] quantities ,
PWR Consumption, PWR
Dissipation, Mass, Dimensions )
Bus Voltage Range
CONTROL
MODE(S)
Load PWR
SERVICES
THERMAL
S/A OPERATING
TEMP
Load PWR
SERVICES
MECH
PAYLOAD
S/A PACKAGING
DEPLOYMENT
MISSION
POWER SUBSYSTEM
SUBSYSTEM
Developed Subsystem
Relationship Models to
identify Top Level Mission
Needs
Software Analysis
Spearhead a study on
Phoenix Integration to
identify whether it will
serve the SE Lab in
developing Deep Space
missions studies and
prototypes.
An Assessment of System Engineering Conceptual Design Laboratory
Results / Recommendations
Phoenix Integration
Need standardized forms from spacecraft
subsystem leads in order to have a super
decision-making system
File Wrapping Tools present more reusability
for the scripts between Different system models
Future Phases
 Further investigation on defining requirements
and constraints
 Validate against additional software toolsets
that develop comprehensive models
 Research cost trends and estimating
relationships
 Developing cost estimating methods and
models
Acknowledgments
The John Hopkins University
Applied Physics Laboratory
James Leary, Richard Anderson
Dr. Ralph McNutt
Grant Tregre, Patrick Hill
Andre Smith, Donna Williams
David Artis, Richard Conde
Special Thanks to:
Dave Rosage
Joseph Dolan
Linda Butler
Dipak Srinivasan
Karen Kirby
SEA-3 Mission and Space System Engineering Group
2006 NASA / APL Research Associates
An Assessment of Artificial Intelligence Technologies for Vehicle Management Systems
Spacecraft and Vehicles Systems Department, Advanced Sensors & Health Management Systems, Code EV23
1
2
3
Kamara Brown , Dr. Mike Watson , Dr. Luis Trevino
1
Research Associate, George Washington University
2
Principal Investigator, Branch Chief, NASA MSFC
Research Problem Statement
3
Principal Investigator, Artificial Intelligence Scientist, NASA MSFC
Results
Data Analysis
As NASA moves towards planning deep space missions, there
is a need for examining applications utilizing autonomous
systems and AI technologies. This will allow space vehicle
systems that can make decisions on its on. The intelligent
system must dynamically select the “optimum” configurations
for supporting such critical subsystems like crew environment,
electrical power systems, propulsion systems.
Research Objective
• To spearhead a study on how AI Techniques can create
intelligent (decision-making) space vehicle systems
• To analyze and determine the most prominent techniques
Recommendations
Bayesian Belief Network
• Appears to be the most prominent for space applications
Why?
• Allows flexible
• Does not need any previous knowledge (very user friendly)
• Graphical representation with strong mathematical foundation
Acknowledgments
NASA Marshall Space Flight Center
Dr. Mike Watson, Dr. Luis Trevino, Dr. Deidre Paris
Dr. Katherine Chavis
John Wiley, Amanda Duffell, Valentin Korman
Linda Brewster, Ricky Howard
Special Thanks to:
Dr. Frank Six
Dr. Gerry Karr
Dr. Ruth Jones
Jessica Culler, Omar Mireles
NASA Academy Staff
2005 NASA Academy Research Associates
NAAA, NASA, Committees
Quality Assurance
Collaborations
Giving Back
Visiting NASA Academies
Newsletters
Strategic Planning Meetings
Projects