MY SPACE INDUSTRY EXPERIENCEMY 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) The John Hopkins University/Applied Physics Laboratory (JHU/APL)

Space Department, Space Systems Applications, Mission and Space Systems EngineeringSpace Department, Space Systems Applications, Mission and Space Systems EngineeringKamara Brown Kamara Brown 11, James Leary , James Leary 22, Richard Anderson , Richard Anderson 33

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

The SE Lab is being developed to better The SE Lab is being developed to better position APL in collaborating more position APL in collaborating more effectively with NASA centers as well as effectively with NASA centers as well as other potential partners who have created other potential partners who have created similar design centers as an standard similar design centers as an standard approach to conducting business.approach to conducting business.

As APL moves towards planning deep As APL moves towards planning deep space missions, there is a need for space missions, there is a need for improving their practices for conceptual improving their practices for conceptual spacecraft design. The SE Lab is being spacecraft design. The SE Lab is being developed to better position APL in developed to better position APL in collaborating more effectively with collaborating more effectively with NASA centers as well as other potential NASA centers as well as other potential partners who have created similar partners who have created similar design centers as an standard approach design centers as an standard approach to conducting business. to conducting business.

Research Problem Statement Background

Defining the System Engineering Laboratory

What is the SE Lab? Collaboration conceptual toolEnhance existing system engineering and system Architecture processes

Characteristics / Intent of the SE LaboratoryTool to assist and increase quality of proposalsMission Concept Studies, System Test Planning

Key Spacecraft Mission Question: How do the different Spacecraft Subsystems interact to perform one or more missions?

Data Analysis

POWER DATA EXCEL WORKBOOK

(B:2 = 2 X A:2)

Tx DC POWER

TAB: TxPWR vs DR

Tx_RF-PWRRange (30 – 250)

H:52MEDIUM / HIGH

POWER[INPUT]

Phoenix Model Power Sheet Flow Chart

A:2[INPUT]

B:2[OUTPUT]

Solar Sentinels Power

WORKBOOK

TAB: Detailed Power Budget H:71 TOTAL CBE + 30% MARGIN

(BUS POWER)[ OUTPUT]

H:52

TOTAL POWER[INPUT]

CALCULATE ARRAY AREA WORKBOOK

PWR TOTAL = (0.23)(.77)(1358) (1/ R2) (A)

ARRAY AREA[OUTPUT]

Developed Flow Chart for Developed Flow Chart for Subsystem to model in Subsystem to model in Phoenix IntegrationPhoenix Integration

Relationship Models

Developed Subsystem Developed Subsystem Relationship Models to Relationship Models to identify Top Level Mission identify Top Level Mission NeedsNeeds

POWER

S/C MISSION SYSTEM

FAULT PROTECTION COMMUNICATIONS

THERMAL

MECH

G&C

BATTERY CYCLE

SUN DISTANCE

S/A OPERATING TEMP

In PWR’s World, FAULT

PROTECTION is considered

Load PWR SERVICES

S/A Pointing Requirements

∑ PWR LOAD

S/A PACKAGING DEPLOYMENT

LIFETIME / DURATION

PROPLoad PWR SERVICES

RELIABILITY

RELIABILITY

PAYLOAD

C&DH

Load PWR SERVICES

ARRAY

PRIMARY PWR SOURCE TYPES

CELLS

PWR ELECTRONICS PARAMETERS

(Box [PSE, PDU, SAJB] quantities , PWR Consumption, PWR

Dissipation, Mass, Dimensions )

MISSION

POWER SUBSYSTEM

SUBSYSTEM

Load PWR SERVICES

Load PWR SERVICES

S/A ARTICULATION AXES

Load PWR SERVICES

SUN POINTING ERROR

PWR DISTRIBUTION

BATTERY CYCLE

Load PWR SERVICES

RADIATION

SUN / ECLIPSE CONDITIONS

Bus Voltage RangeCONTROL MODE(S)

POWER

MASS

CONTROL

VOLTAGE RANGE

Software Analysis

Spearhead a study on Spearhead a study on Phoenix Integration to Phoenix Integration to identify whether it will identify whether it will serve the SE Lab in serve the SE Lab in developing Deep Space developing Deep Space missions studies and missions studies and prototypes.prototypes.

An Assessment of System Engineering Conceptual Design Laboratory

Results / Recommendations

The John Hopkins UniversityThe John Hopkins UniversityApplied Physics LaboratoryApplied Physics Laboratory

James Leary, Richard AndersonJames Leary, Richard AndersonDr. Ralph McNuttDr. Ralph McNutt

Grant Tregre, Patrick HillGrant Tregre, Patrick HillAndre Smith, Donna WilliamsAndre Smith, Donna Williams

David Artis, Richard CondeDavid Artis, Richard Conde

Special Thanks to: Special Thanks to: Dave RosageDave RosageJoseph DolanJoseph DolanLinda ButlerLinda Butler

Dipak SrinivasanDipak SrinivasanKaren KirbyKaren KirbySEA-3 Mission and Space System Engineering SEA-3 Mission and Space System Engineering Group Group 2006 NASA / APL Research Associates2006 NASA / APL Research Associates

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

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

Future Phases

An Assessment of Artificial Intelligence Technologies for Vehicle Management Systems

Spacecraft and Vehicles Systems Department, Advanced Sensors & Health Management Systems, Code EV23

Kamara Brown Kamara Brown 11 , Dr. Mike Watson , Dr. Mike Watson 22 , Dr. Luis Trevino , Dr. Luis Trevino 33

1 Research Associate, George Washington University 2 Principal Investigator, Branch Chief, NASA MSFC 3 Principal Investigator, Artificial Intelligence Scientist, NASA MSFC

Data Analysis

As NASA moves towards planning deep space As NASA moves towards planning deep space missions, there is a need for examining applications missions, there is a need for examining applications utilizing autonomous systems and AI technologies. utilizing autonomous systems and AI technologies. This will allow space vehicle systems that can make This will allow space vehicle systems that can make decisions on its on. The intelligent system must decisions on its on. The intelligent system must dynamically select the “optimum” configurations dynamically select the “optimum” configurations for supporting such critical subsystems like crew for supporting such critical subsystems like crew environment, electrical power systems, propulsion environment, electrical power systems, propulsion systems.systems.

• To spearhead a study on how AI Techniques can To spearhead a study on how AI Techniques can create intelligent (decision-making) space vehicle create intelligent (decision-making) space vehicle systemssystems

• To analyze and determine the most prominent To analyze and determine the most prominent techniquestechniques

Acknowledgments

Research Objective

Research Problem Statement

NASA Marshall Space Flight CenterNASA Marshall Space Flight CenterDr. Mike Watson, Dr. Luis Trevino, Dr. Deidre ParisDr. Mike Watson, Dr. Luis Trevino, Dr. Deidre ParisDr. Katherine ChavisDr. Katherine ChavisJohn Wiley, Amanda Duffell, Valentin KormanJohn Wiley, Amanda Duffell, Valentin KormanLinda Brewster, Ricky HowardLinda Brewster, Ricky Howard

Special Thanks to:Special Thanks to:

Dr. Frank SixDr. Frank SixDr. Gerry KarrDr. Gerry KarrDr. Ruth JonesDr. Ruth JonesJessica Culler, Omar MirelesJessica Culler, Omar MirelesNASA Academy StaffNASA Academy Staff2005 NASA Academy Research Associates2005 NASA Academy Research Associates

Results

Bayesian Belief NetworkBayesian Belief Network

• Appears to be the most prominent for space applicationsAppears to be the most prominent for space applications

Why?Why?• Allows flexibleAllows flexible• Does not need any previous knowledge (very user friendly)Does not need any previous knowledge (very user friendly)• Graphical representation with strong mathematical foundationGraphical representation with strong mathematical foundation

Recommendations

NAAA, NASA, CommitteesNAAA, NASA, Committees

Quality AssuranceQuality Assurance

CollaborationsCollaborations

Giving BackGiving Back

Quality AssuranceQuality Assurance

CollaborationsCollaborations

Giving BackGiving Back

Visiting NASA AcademiesVisiting NASA Academies

NewslettersNewsletters

Strategic Planning MeetingsStrategic Planning Meetings

ProjectsProjects

Visiting NASA AcademiesVisiting NASA Academies

NewslettersNewsletters

Strategic Planning MeetingsStrategic Planning Meetings

ProjectsProjects

NASA Academy Alumni Association Future Leaders of the Aerospace Industry

NASA Academy Alumni AssociationNASA Academy Alumni Association

Young Leaders of the Space Industry TodayYoung Leaders of the Space Industry Today

NAAA