Using Architecture Models to
Understand Policy Impacts
Cost of US Launch Policy: B-TOS Case Study Using Min Cost Rule
1
Policy
C
increases
cost
Utility
0.995
D
100% of B-TOS architectures have
cost increase under restrictive launch
policy for a minimum cost decision
maker
B
0.99
Restrictive launch policy
Unrestrictive launch policy
B-TOS Case Study: Probability of Success Impact of 1994 U.S. Space Transportation Policy
for a Minimum Cost Decision Maker
1
0.985
A
0.995
0.98
0
100
200
300
400
500
Cost
600
700
800
Lifecycle Cost ($M)
98%
of B-TOS
architectures
• Swarm
of small
sats.
have
increased launch
doing
observation
probability
success under
• Utility forofmultiple
restrictive
launch
policy for a
missions
minimum cost decision
maker
Space Systems, Policy, and Architecture Research Consortium
0.99
Utility
B-TOS
0.985
0.98
0%
Policy increases
launch probability
of success
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
B-TOS Architecture Probability of Launch Success (Lifecycle total)
Probability of Success
From Weigel, 2002
©2002 Massachusetts Institute of Technology
29
Using Architecture Models to
Consider Uncertainty
TechSat
• Constellation of
satellites doing
observation
of
Performance
moving
objects
and Coston the
ground
movedriven
• Uncertainties
bydifferently
instrument for
performance/cost
different
architectures
under
uncertainty
[Martin, 2000]
Space Systems, Policy, and Architecture Research Consortium
From Walton, 2002
©2002 Massachusetts Institute of Technology
30
15
Changes in User Preferences Can be
Quickly Understood
Architecture
trade space
reevaluated
in less than
one hour
Original
User changed
preference
weighting for
lifespan
Revised
0.8
0.8
0.7
y
t
i
l
i
t
U
X-TOS
0.7
y
t
i
l
i
t
U
0.6
0.5
0.6
0.5
0.4
0.4
0.3
0.3
0.2
40
42
46
44
48
50
52
Lifecycle Cost ($M)
54
56
58
60
0.2
40
42
44
46
48
50
52
54
56
58
60
Lifecycle Cost ($M)
Space Systems, Policy, and Architecture Research Consortium
©2002 Massachusetts Institute of Technology
31
Assessing Robustness and Adaptability
• Pareto front shows trade-off of accuracy and cost
• Determined by number of satellites in swarm
• Could add satellites to increase capability
1
E
D
C
Utility
Utility
0.995
Most desirable
architectures
B
0.99
0.985
A
0.98
100
B-TOS
Cost
1000
Lifecycle Cost ($M)
Space Systems, Policy, and Architecture Research Consortium
©2002 Massachusetts Institute of Technology
32
16
Questioning User Desires
A-TOS
• Swarm of very
simple satellites
taking ionospheric
measurements
• Several different
missions
High Latitude Utility
• Best low-cost mission do only one job well
• More expensive, higher performance missions require
more vehicles
• Higher-cost systems can do multiple missions
• Is the multiple mission idea a good one?
Equatorial Utility
Space Systems, Policy, and Architecture Research Consortium
©2002 Massachusetts Institute of Technology
33
Understanding Limiting
Physical or Mission constraints
4000.00
SPACETUG
Low Biprop
3500.00
• General
Medium Biprop
High Biprop
purpose
orbit
Extreme Biprop
transfer
Low Cryo
vehicles
Medium Cryo
• Different
High Cryo
propulsion
Extreme Cryo
systems
and
Low Electric
grappling/obser
Medium Electric
High Electric
vation
Extreme Electric
capabilities
Low Nuclear
• Lines
show
Medium Nuclear
increasing fuel
High Nuclear
mass
fraction
Extreme Nuclear
Cost (M$)
3000.00
2500.00
2000.00
1500.00
1000.00
500.00
0.00
0.00
0.20
0.40
0.60
0.80
1.00
Utility (dimensionless)
Hits a “wall” of either physics (can’t change!) or utility (can)
Space Systems, Policy, and Architecture Research Consortium
©2002 Massachusetts Institute of Technology
34
17
Integrated Concurrent Engineering (ICE)
• ICE techniques from Caltech and JPL
• Linked analytical tools with human experts in
the loop
• Very rapid design iterations
• Result is conceptual design at more detailed
level than seen in architecture studies
• Allows understanding and exploration of design
alternatives
• A reality check on the architecture studies - can
the vehicles called for be built, on budget, with
available technologies?
Space Systems, Policy, and Architecture Research Consortium
©2002 Massachusetts Institute of Technology
35
ICE Process (CON with MATE)
ICE Process
Leader
“Chairs” consist of
computer tool AND
human expert
MATE
Mission
Cost
Power
Thermal
Key system
attributes passed to
MATE chair, helps to
drive design session
Systems
Propulsion
ICE-Maker
Server
Structures
Communication
Configuration
Command
and Data
Handling
Reliability
Electronic
communication
between tools and
server
Space Systems, Policy, and Architecture Research Consortium
Attitude
Determination
and Control
Verbal or online chat
between chairs
synchronizes actions
• Directed Design
Sessions allow very
fast production of
preliminary designs
• Traditionally, design
to requirements
• Integration with
MATE allows utility
of designs to be
assessed real time
©2002 Massachusetts Institute of Technology
36
18
ICE Result - XTOS Vehicle
• Early Designs had
excessively large fuel
tanks and bizarre
shapes
• Showed limits of
coarse modeling done
in architecture studies
• Vehicle optimized for
best utility - maximum
life at the lowest
practical altitude
Space Systems, Policy, and Architecture Research Consortium
©2002 Massachusetts Institute of Technology
37
SPACETUG Biprop One-Way GEO Tug
• 1312 kg dry mass, 11689 kg wet mass
• Quite big (and therefore expensive); not very
practical (?);
Scale for all
images: black
cylinder is 1 meter
long by 1 meter in
diameter
Space Systems, Policy, and Architecture Research Consortium
©2002 Massachusetts Institute of Technology
38
19
SPACETUG Tug Family
(designed in a day)
Bipropellant
Cryogenic
Wet Mass: 11689 kg
Wet Mass: 6238 kg
Electric – One way
Wet Mass: 997 kg
Electric – Return Trip
Wet Mass: 1112 kg
Space Systems, Policy, and Architecture Research Consortium
©2002 Massachusetts Institute of Technology
39
Learning from the ICE results:
Mass Distribution Comparison
C&DH
0%
ADACS (dry)
0%
Pressurant
0%
Link
1%
C&DH
0%
Link
0%
Pressurant
0%
ADACS (dry)
0%
Power
11%
Propulsion (dry)
6%
Structures &
Mechanisms
2%
Thermal
0%
Propulsion (dry)
2%
Propellant
37%
Power
1%
Mating System
3%
Structures &
Mechanisms
17%
Payload
0%
Thermal
5%
Payload
0%
Mating System
27%
Electric Cruiser
Propellant
88%
Biprop one-way
• Low ISP fuel requires very large mass fraction to do mission
• Other mass fractions reasonable, with manipulator system,
power system, and structures and mechanisms dominating
Space Systems, Policy, and Architecture Research Consortium
©2002 Massachusetts Institute of Technology
40
20
More Than Mass Fractions
LEO Tender 1
mass summary
Power System Mass Breakdown
Solar array
mass
66%
0%
1%
16%
5%
3%
2%
52%
21%
ADACS (dry)
C&DH
Link
Power
Propulsion (dry)
Structures & Mechanisms
Thermal
Mating System
Payload
Propellant
Pressurant
0%
Cabling mass
6%
Battery mass
19%
PMAD mass
9%
Select solar array material:
Detailed information can be
drawn from subsystem sheets,
including efficiencies, degradations
temperature tolerances, and areas
Space Systems, Policy, and Architecture Research Consortium
6 (InGaP/GaAs/Ge)
Triple Junction
Minimum efficiency
Maximum efficiency
Nominal temperature
Temperature loss
Performance degredation
Minimum temperature
Maximum temperature
Energy density
24.5
28.0
28.0
0.5
2.6
0.5
85.0
25.0
Solar array mass
Total solar array area
# of solar arrays
Individual solar array area
150.6685167
9.965098159
2
4.98254908
%
%
C
%/deg C
% / year
C
C
W / kg
kg
m^2
#
m^2
©2002 Massachusetts Institute of Technology
41
Trade Space Check
The GEO mission is near the “wall” for conventional propulsion
Space Systems, Policy, and Architecture Research Consortium
©2002 Massachusetts Institute of Technology
42
21
SPACETUG
LEO Tender Family
LEO 1 - 1404 kg wet
LEO 4 - 1782 kg wet
Space Systems, Policy, and Architecture Research Consortium
LEO 2 - 1242 kg wet
LEO 4A - 4107 kg wet
Tenders
• Orbit transfer
vehicles that
live in a
restricted,
highly
populated set
of orbits
• Do low Delta-V
transfers,
service,
observation
©2002 Massachusetts Institute of Technology
43
Tenders on the tradespace
The Tender missions are feasible with conventional propulsion
Space Systems, Policy, and Architecture Research Consortium
©2002 Massachusetts Institute of Technology
44
22
What you will learn
• Trade space evaluation allows efficient quantitative
assessment of system architectures given user needs
• State-of-the-art conceptual design processes refine
selected architectures to vehicle preliminary designs
• Goal is the right system, with major issues understood
(and major problems ironed out) entering detailed
design
Emerging capability to get from user needs to robust solutions
quickly, while considering full range of options, and maintaining
engineering excellence
Space Systems, Policy, and Architecture Research Consortium
©2002 Massachusetts Institute of Technology
45
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