multi-attribute tradespace exploration for survivability
TRANSCRIPT
Multi-Attribute Tradespace Exploration for Survivability: Application to Satellite Radar
Matthew G. Richards, Ph.D.Matthew G. Richards, Ph.D.Doctoral Research Assistant, Engineering Systems Division
Massachusetts Institute of Technology
David B. SteinDavid B. SteinUndergraduate Research Assistant, SEAri
Massachusetts Institute of Technology
AIAA Space 2009AIAA Space 2009
Adam M. Ross, Ph.D.Adam M. Ross, Ph.D.Research Scientist, Engineering Systems Division
Massachusetts Institute of Technology
Daniel E. Hastings, Ph.D.Daniel E. Hastings, Ph.D.Professor, Aeronautics and Astronautics & Engineering Systems
Massachusetts Institute of Technology
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Agenda
• Problem Statement• Research Questions• Methodology Overview• Case Application: Satellite Radar• Discussion• Future Work
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Temporal system properties known as “ilities” (e.g., flexibility) are a critical design challenge for engineering systems
– Survivability is a critical challenge for aerospace system architecture
Given limitations of survivability engineering for aerospace systems,* need design methodology that:
1. incorporates survivability as an active trade throughout design process2. reflects dynamics of operational environments over entire lifecycle3. captures path dependencies of system vulnerability and resilience4. extends in scope to architecture-level survivability assessments5. takes a value-centric perspective
Opportunity to build on recent research on dynamic tradespace exploration (Ross 2006)
Application of survivability methodology may address critical issue for military space
– Satellite radar architecture development
Problem Statement
*Richards, M., Hastings, D., Rhodes, D., and Weigel, A., “Systems Architecting for Survivability: Limitations of Existing Methods for Aerospace Systems,” 6th Conference on Systems Engineering Research, Los Angeles, CA, April 2008.
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Research Questions
1. What is a dynamic, operational, and value-centric definition of survivability for engineering systems?
2. What design principles enable survivability?
3. How can survivability be quantified and used as a decision metric in exploring tradespaces during conceptual design of aerospace systems?
4. For a given space mission, how to evaluate the survivability of alternative system architectures in dynamic disturbance environments?
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Definition of SurvivabilityAbility of a system to minimize the impact of finite-duration disturbances on value delivery
through (I) the reduction of the likelihood or magnitude of a disturbance, (II) the satisfaction of a minimally acceptable level of value delivery during and after a disturbance, and/or (III) a timely recovery
time
value
Epoch 1a Epoch 2
original state
disturbance
recov
ery
Epoch: Time period with a fixed context; characterized by static constraints, design concepts, available technologies, and articulated attributes (Ross 2006)
emergency value threshold
required value threshold
permitted recovery time
VxVe
Tr
Epoch 1b
V(t)
disturbance duration
Td
Type I
Type II
degradation
Epoch 3
Type III
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Survivability MetricsNeed to evaluate ability of system to (1) minimize utility losses and (2) meet critical value thresholds before, during, and after environmental disturbances
time-weighted utility loss• Difference between design utility,
Uo, and time-weighted average utility
• Internalizes lifecycle degradation• Inspired by Quality Adjusted Life
Years in health economics*
dttUT
UUdl
L )(10
threshold availability• Ratio of time above critical value
thresholds (Vx during baseline Epoch, Ve during disturbance and recovery Epochs) to design life
• Accommodates changing expectations across contexts
dlT T
TATA
desirable attributes: value-based, dynamic, continuous
*Pliskin, J., D. Shepard and M. Weinstein (1980). "Utility Functions for Life Years and Health Status." Operations Research, 28(1): 206-224.
TAT = time above thresholdsTdl = time of design life
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Legend
Multi-Attribute Tradespace Exploration (MATE) for Survivability
Define Mission
Enumerate Disturbances
Apply Design Principles
Elicit Attributes
Calculate Utility
Specify Design Vector
Explore Tradespace
Estimate Cost
Model Baseline Performance
Calculate Survivability
Model Lifecycle Performance
Monte Carlo analysis
Evolved
MATE
New
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Phases of MATE for Survivability
1. Elicit Value Proposition – Identify mission statement and quantify decision-maker needs during nominal and emergency states.
2. Generate Concepts – Formulate concepts that address decision-maker needs.
3. Characterize Disturbance Environment – Develop concept-neutral models of disturbances in operational environment of proposed systems.
4. Apply Survivability Principles – Incorporate susceptibility reduction, vulnerability reduction, and resilience enhancement strategies into design vector.
5. Model Baseline System Performance – Model and simulate cost and performance of design alternatives to gain an understanding of how decision-maker needs are met in a nominal operational environment.
6. Model Impact of Disturbances on Lifecycle Performance – Model and simulate performance of design alternatives across a representative sample of disturbance encounters to gain an understanding of how decision-maker needs are met in perturbed environments.
7. Apply Survivability Metrics – Compute time-weighted utility loss and threshold availability for each design alternative as summary statistics for system performance across representative operational lives.
8. Explore Tradespace – Perform integrated cost, utility, and survivability trades across design space to identify promising alternatives for more detailed analysis.
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Case Application: Satellite Radar
Critical issue in national security space– Unique all-weather surveillance capability– Opportunity for impact given ongoing studies– Rich multi-dimensional tradespace
Unit-of-analysis: SR architecture– Radar payload– Constellation of satellites– Communications network
Availability of data– Systems Engineering Advancement
Research Initiative (SEAri)
To assess potential satellite radar architectures for providing the United States Military a global, all-weather, on-demand capability to track moving ground targets; supporting tactical military operations; maximizing cost-
effectiveness; and surviving disturbances in the natural space environment.
Case Application Goal (CBO 2007)
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Phase 1: Elicit Value Proposition
0
0.2
0.4
0.6
0.8
1
0 2 4 6 8
number of target boxes
0
0.2
0.4
0.6
0.8
1
0 20 40 60
minimum detectable velocity (m/s)
0
0.2
0.4
0.6
0.8
1
0 500 1000 1500
minimum radar cross section (dB)
0
0.2
0.4
0.6
0.8
1
0 100 200 300 400
target acquisition time (min)
0
0.2
0.4
0.6
0.8
1
0 20 40 60 80
track life (min)
0
0.2
0.4
0.6
0.8
1
0 100 200 300
tracking latency (min)
ki=3/18
ki=1/18 ki=1/18
ki=1/18
ki=3/18
ki=9/18
Util
ity
1
Attribute value
0
Excluded Attribute Values
Excess Attribute Values (typically assigned Utility = 1)
single-attribute utility curve
Util
ity
1
Attribute value
0
Excluded Attribute Values
Excess Attribute Values (typically assigned Utility = 1)
single-attribute utility curveAttributes: concept-neutral evaluation criteria specified
by a decision maker
sate
llite
rada
r attr
ibut
es
number of target boxes minimum radar cross section (m2) minimum detectable velocity (m/s)
tracking latency (min)track life (min)target acquisition time (min)
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Phase 2: Generate Concepts
Peak Transmit Power 1.5 10 20 [KW] 9 9 9 3 1 1 9 9 9 0 1 9 9 9 9 96Radar Bandwidth .5 1 2 [GHz] 9 9 3 3 1 1 9 9 9 0 1 3 3 3 3 66Radar Frequency X UHF 9 9 3 3 1 1 9 9 9 0 1 3 3 3 3 66Physical Antenna Area 10 40 100 200 [m^2] 9 9 9 3 1 1 9 9 9 1 1 9 9 9 9 97Receiver Sats per Tx Sat 0 1 2 3 4 5 9 9 3 3 1 1 9 3 3 1 1 9 9 9 9 79Antenna Type Mechanical vs. AESA 9 9 9 3 3 1 9 9 9 1 1 9 9 9 9 99Satellite Altitude 800 1200 1500 [km] 9 9 3 9 9 3 9 9 9 9 3 1 1 1 1 85Constellation Type 8 Walker IDs 0 0 1 9 9 3 0 0 3 9 3 9 9 9 9 73Comm. Downlink Relay vs. Downlink 0 0 0 0 0 9 0 0 0 0 9 9 9 3 9 48Tactical Downlink Yes vs. No 0 0 0 0 3 9 0 0 0 0 9 9 9 3 9 51Processing Space vs. Ground 0 0 0 1 0 3 1 0 0 0 3 9 9 9 9 44Maneuver Package 1x, 2x, 4x 1 1 1 1 1 0 1 1 1 1 0 9 3 3 3 27Tugable Yes vs. No 1 1 1 1 1 0 1 1 1 1 0 9 9 9 9 45Constellation Option none, long-lead, spare 0 0 0 0 0 0 0 0 0 0 0 9 9 9 9 36Total 65 64 42 39 30 33 66 58 62 23 33 106 100 88 100
Bas
elin
e Cost
Act
ual
Cost
s (E
ra)
Imag
ing L
aten
cy
Res
olu
tion (
Pro
xy)
Tar
get
s per
Pas
s
Fiel
d o
f Reg
ard
Rev
isit F
requen
cy
Definition RangeVariable Name Min
imum
Tar
get
RC
S
DES
IGN
VA
RIA
BLES
MissionATTRIBUTES
ScheduleProgrammaticsCost
Bas
elin
e Sch
edule
Act
ual
Sch
edule
(Era
)
To
tal Im
pact
Tracking Imaging
Min
. D
etec
table
Vel
oci
ty
Num
ber
of
Tar
get
Box
es
Tar
get
Acq
uis
itio
n T
ime
Tar
get
Tra
ck L
ife
Tra
ckin
g L
aten
cy
Design Value Mapping Matrix establishes
traceability between value-space and design-space
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Phase 3: Characterize Disturbance Environment
Enumerate disturbances– Orbital debris– Signal attenuation
Gather data on disturbance magnitude and occurrence– NASA ORDEM2000 debris model
• Space Surveillance Network• Haystack and Haystack radar data• Goldstone radar data• Long-Duration Exposure Facility • Hubble Telescope array impact data• Space Shuttle impact data• Mir impact data
Develop system-independent models of disturbance environment
6.5
7
7.5
8
8.5
9
9.5
150 300 450 600 750 900 1050 1200 1350 1500 1650 1800 1950
km/s
Average Orbital Velocity
Spatial Density
10-3
10-2
10-1
100
101
102
10-10
10-8
10-6
10-4
10-2
100
102
debris size (cm)
spat
ial d
ensi
ty (
obje
cts/
km3 )
Debris Spatial Density (800 km circular, i=42.6º)
ORDEM2000 spatial density estimates
fit (piecewise cubic hermite interpolating polynomial)
>10um>100um>1mm>1cm >10cm>1m
altitude (km)
Phase 4: Apply Survivability Principles
design principles concept enhancements design variables (units) atm
osph
eric
dra
g flu
ctua
tions
arc
disc
harg
ing
high
-flux
radi
atio
n
mic
rom
eteo
rites
/ de
bris
sign
al a
ttenu
atio
n
chan
ge in
targ
et c
hara
cter
istic
s
failu
re o
f rel
ay b
ackb
one
loss
of t
actic
al g
roun
d no
de
prevention reduce exposed s/c area antenna area (m^2) 9 0 3 9 0 0 0 0mobilityconcealmentdeterrencepreemption
∆V (m/s) 9 0 3 1 0 0 0 0s/c servicing interface 9 0 1 1 0 0 0 0
ground receiver maneuverability mobile receiver 0 0 0 0 3 0 0 3radiation-hardened electronics hardening (cal/cm^2) 0 3 9 1 0 0 0 0bumper shielding shield thickness (mm) 0 0 0 9 0 0 0 0duplicate critical s/c functions bus redundancy 0 1 9 3 0 0 0 0on-orbit satellite spares extra s/c per orbital plan 0 1 3 3 0 3 0 0multiple ground receivers ground infrastructure level 0 0 0 0 3 0 0 9over-design power generation peak transmit power (kW) 0 0 0 3 9 9 0 0over-design link budget assumed signal loss (dB) 0 0 0 0 9 0 0 0over-design propulsion system ∆V (m/s) 3 0 3 0 3 9 0 0excess on-board data storage s/c data capacity (gbits) 0 0 0 0 0 0 3 3excess constellation capacity number of satellites 0 1 3 9 0 0 0 0interface with airborne assets tactical downlink 3 3 3 3 3 3 3 3
communications downlink 0 0 1 1 9 0 9 3tactical downlink 0 0 1 1 9 0 9 3
spatial separation of spacecraft orbital altitude (km) 1 1 3 3 0 9 0 0spatial separation of s/c orbits number of planes 0 0 3 9 0 1 0 1
failure mode reduction reduce s/c complexity bus redundancy 0 0 9 0 0 0 0 0fail-safe autonomous operations autonomous control 0 0 0 0 3 0 3 3
antenna type 0 0 0 0 3 9 0 0radar bandwidth (GHz) 0 0 0 0 9 3 0 0
retraction of s/c appendages reconfigurable 0 0 9 3 0 0 0 0containment s/c fault monitoring and response autonomous control 0 1 3 1 0 0 0 0replacement rapid reconstitution constellation spares 0 1 3 9 0 0 0 0repair on-orbit-servicing s/c servicing interface 9 1 3 3 0 3 0 0T
III
disturbances
Type
IITy
pe I
s/c maneuveringavoidance
hardness
margin
heterogeneity multiple communication paths
redundancy
flexible sensing operationsevolution
distribution
13
Survivability Variable Mapping Matrix establishes traceability between environment and design-space
Orbit Altitude (km)8001500
Peak Transmit Power (kW)1.51020
Walker ID5/5/19/3/227/3/166/6/5
Radar Bandwidth (MHz)50010002000
Antenna Area (m^2)1040100
Comm. ArchitectureDirect Downlink Only
Relay Backbone
Constellation Spares012
Shield Thickness (mm)1510
finalized design vector (n=3888)
surv
ivab
ility
varia
bles
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Phase 5: Model Baseline System Performance
desi
gn
0 20 40 60 80 100 1200
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
lifecycle cost ($B)
utili
ty (
dim
ensi
onle
ss)
p y p ( )
012
22 23 24 25 26 27
0.5
0.51
0.52
y(
Baseline tradespace only internalizes costs of survivability features
Satellite Radar Tradespace by Constellation Spares (n=2268)
number of spares
Phase 6: Model Impact of Disturbances on Lifecycle Performance
Tt AU ,
DesignVector
designs
Static SR Model
debris impactscross-sectional area
debris flux (>1mm)
utilityreplace
t
attenuationloss
loss
500 Monte Carlo runs per constellation
UtilityCost
Survivability
Tear Tradespace
1
7
6
5
4
3
2 shieldingdownlink(s)
signal attenuation
t t
Susceptibility
Vulnerability
spare satellites
Resilience
kinetic energy
Pk
0%
5
0%
1
00%
threshold availability (1stpercentile)
10 15 20 25 300.1
0.15
0.2
0.25
0.3
0.35
0.4
lifecycle cost ($B)
utili
ty (
dim
ensi
onle
ss)
Survivability Tradespace - No Filtering
0.9
0.91
0.92
0.93
0.94
0.95
0.96
0.97
0.98
0.99
1
time-weighted utility loss (99th percentile)threshold availability (1st percentile)
dttUT
UUdl
L )(10
dlT T
MTATA
15
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0 20 40 60 80 100 1200
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
lifecycle cost ($B)
desi
gn u
tility
(di
men
sion
less
)
Tear Tradespace - all designs (n=2268)
0.9
0.91
0.92
0.93
0.94
0.95
0.96
0.97
0.98
0.99
1
time-weighted utility loss (95th percentile)threshold availability (1st percentile)
Phase 7: Apply Survivability Metrics
threshold availability (1stpercentile)
0.35 0.36 0.37 0.38 0.39 0.4 0.410
50
100
150
200
250
300
350Time-Weighted Average Utility - Design 3109 (n=500)
num
ber
of r
uns
0.95 utility loss
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0 20 40 60 80 100 1200
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
lifecycle cost ($B)
desi
gn u
tility
(di
men
sion
less
)
Tear Tradespace - all designs (n=2268)
0.9
0.91
0.92
0.93
0.94
0.95
0.96
0.97
0.98
0.99
1
time-weighted utility loss (95th percentile)threshold availability (1st percentile)
Phase 8: Explore Tradespacethreshold availability (1
stpercentile)
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Magnify Tear Tradespacethreshold availability (1
stpercentile)
20 25 30 35 40 45 50 55 60 650.2
0.3
0.4
0.5
0.6
0.7
0.8
lifecycle cost ($B)
desi
gn u
tility
(di
men
sion
less
)
Tear Tradespace (magnified)
0.9
0.91
0.92
0.93
0.94
0.95
0.96
0.97
0.98
0.99
1
time-weighted utility loss (95th percentile)threshold availability (1st percentile)
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20 25 30 35 40 45 50 55 60 650.2
0.3
0.4
0.5
0.6
0.7
0.8
lifecycle cost ($B)
desi
gn u
tility
(di
men
sion
less
)
Pareto Efficient Set for Cost, Utility, Utility Loss, and Threshold Availability (magnified)
0.9
0.91
0.92
0.93
0.94
0.95
0.96
0.97
0.98
0.99
1
time-weighted utility loss (95th percentile)threshold availability (1st percentile)
Identify Pareto-Efficient Surface of Cost, Utility, and Survivability
2908 2901
3718 3711
threshold availability (1stpercentile)
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20 25 30 35 40 45 50 55 60 650.2
0.3
0.4
0.5
0.6
0.7
0.8
lifecycle cost ($B)
desi
gn u
tility
(di
men
sion
less
)
Pareto Efficient Set for Cost, Utility, Utility Loss, and Threshold Availability (magnified)
0.9
0.91
0.92
0.93
0.94
0.95
0.96
0.97
0.98
0.99
1
time-weighted utility loss (99th percentile)threshold availability (1st percentile)
Select Interesting Point Designs
3231
risk averse decision maker
2908 2901
3718 3711
threshold availability (1stpercentile)
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threshold availability (1stpercentile)
20 25 30 35 40 45 50 55 60 650.2
0.3
0.4
0.5
0.6
0.7
0.8
lifecycle cost ($B)
utili
ty (
dim
ensi
onle
ss)
Filtered by Cost, Utility, Utility Loss, and Threshold Availability
0.9
0.91
0.92
0.93
0.94
0.95
0.96
0.97
0.98
0.99
1
time-weighted utility loss (99th percentile)threshold availability (1st percentile)
desi
gn
2908
Extract Survivability Insights from Selected Point Designs
• Survivability insights from selected point designs– Relay backbone critical for achieving continuous threshold availability– Investing in spare satellite(s) minimizes utility losses– Satellite shielding has limited impact in nominal debris environment– Distributed constellation mitigates worst-case risks
Design Vector ID 2908 2901 3231 3718 3711 orbit altitude (km) Walker constellation 9/3/2 9/3/2 27/3/1 66/6/5 66/6/5 transmit frequency (GHz) antenna area (m^2) 100 100 40 antenna type radar bandwidth (MHz) peak transmit power (kW) tugable comm. architecture direct relay relay direct relay tactical link shield thickness (mm) 1 1 10satellite spares 0 2 2 0 2 lifecycle cost ($B) 22.3 25.8 31.2 54.8 57.4 utility 0.51 0.51 0.47 0.74 0.74 utility loss (95th) 0.09 0.01 0.00 0.06 0.00 utility loss (99th) 0.12 0.02 0.00 0.07 0.01threshold availability (1st) 0.95 1.00 1.00 0.95 1.00
1
20 20
yes yes
no no
40AESA AESA2000 2000
1500 1500
10 10
Design Vector ID 2908 2901 3231 3718 3711 orbit altitude (km) Walker constellation 9/3/2 9/3/2 27/3/1 66/6/5 66/6/5 transmit frequency (GHz) antenna area (m^2) 100 100 40 antenna type radar bandwidth (MHz) peak transmit power (kW) tugable comm. architecture direct relay relay direct relay tactical link shield thickness (mm) 1 1 10satellite spares 0 2 2 0 2 lifecycle cost ($B) 22.3 25.8 31.2 54.8 57.4 utility 0.51 0.51 0.47 0.74 0.74 utility loss (95th) 0.09 0.01 0.00 0.06 0.00 utility loss (99th) 0.12 0.02 0.00 0.07 0.01threshold availability (1st) 0.95 1.00 1.00 0.95 1.00
1500 1500
10 1040
AESA AESA2000 2000
1
20 20
yes yes
no no
Design Vector ID 2908 2901 3231 3718 3711 orbit altitude (km) Walker constellation 9/3/2 9/3/2 27/3/1 66/6/5 66/6/5 transmit frequency (GHz) antenna area (m^2) 100 100 40 antenna type radar bandwidth (MHz) peak transmit power (kW) tugable comm. architecture direct relay relay direct relay tactical link shield thickness (mm) 1 1 10satellite spares 0 2 2 0 2 lifecycle cost ($B) 22.3 25.8 31.2 54.8 57.4 utility 0.51 0.51 0.47 0.74 0.74 utility loss (95th) 0.09 0.01 0.00 0.06 0.00 utility loss (99th) 0.12 0.02 0.00 0.07 0.01threshold availability (1st) 0.95 1.00 1.00 0.95 1.00
1
no no20 20
yes yes
40AESA AESA2000 2000
1500 1500
10 10
2901
3231
3718 3711
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threshold availability (1stpercentile)
20 25 30 35 40 45 50 55 60 650.2
0.3
0.4
0.5
0.6
0.7
0.8
lifecycle cost ($B)
utili
ty (
dim
ensi
onle
ss)
Filtered by Cost, Utility, Utility Loss, and Threshold Availability
0.9
0.91
0.92
0.93
0.94
0.95
0.96
0.97
0.98
0.99
1
time-weighted utility loss (99th percentile)threshold availability (1st percentile)
desi
gn
2908
Extract Survivability Insights from Selected Point Designs
• Survivability insights from selected point designs– Relay backbone critical for achieving continuous threshold availability– Investing in spare satellite(s) minimizes utility losses– Satellite shielding has limited impact in nominal debris environment– Distributed constellation mitigates worst-case risks
Design Vector ID 2908 2901 3231 3718 3711 orbit altitude (km) Walker constellation 9/3/2 9/3/2 27/3/1 66/6/5 66/6/5 transmit frequency (GHz) antenna area (m^2) 100 100 40 antenna type radar bandwidth (MHz) peak transmit power (kW) tugable comm. architecture direct relay relay direct relay tactical link shield thickness (mm) 1 1 10satellite spares 0 2 2 0 2 lifecycle cost ($B) 22.3 25.8 31.2 54.8 57.4 utility 0.51 0.51 0.47 0.74 0.74 utility loss (95th) 0.09 0.01 0.00 0.06 0.00 utility loss (99th) 0.12 0.02 0.00 0.07 0.01threshold availability (1st) 0.95 1.00 1.00 0.95 1.00
1
20 20
yes yes
no no
40AESA AESA2000 2000
1500 1500
10 10
Design Vector ID 2908 2901 3231 3718 3711 orbit altitude (km) Walker constellation 9/3/2 9/3/2 27/3/1 66/6/5 66/6/5 transmit frequency (GHz) antenna area (m^2) 100 100 40 antenna type radar bandwidth (MHz) peak transmit power (kW) tugable comm. architecture direct relay relay direct relay tactical link shield thickness (mm) 1 1 10satellite spares 0 2 2 0 2 lifecycle cost ($B) 22.3 25.8 31.2 54.8 57.4 utility 0.51 0.51 0.47 0.74 0.74 utility loss (95th) 0.09 0.01 0.00 0.06 0.00 utility loss (99th) 0.12 0.02 0.00 0.07 0.01threshold availability (1st) 0.95 1.00 1.00 0.95 1.00
1500 1500
10 1040
AESA AESA2000 2000
1
20 20
yes yes
no no2901
3231
3718 3711
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threshold availability (1stpercentile)
20 25 30 35 40 45 50 55 60 650.2
0.3
0.4
0.5
0.6
0.7
0.8
lifecycle cost ($B)
utili
ty (
dim
ensi
onle
ss)
Filtered by Cost, Utility, Utility Loss, and Threshold Availability
0.9
0.91
0.92
0.93
0.94
0.95
0.96
0.97
0.98
0.99
1
time-weighted utility loss (99th percentile)threshold availability (1st percentile)
desi
gn
2908
Extract Survivability Insights from Selected Point Designs
• Survivability insights from selected point designs– Relay backbone critical for achieving continuous threshold availability– Investing in spare satellite(s) minimizes utility losses– Satellite shielding has limited impact in nominal debris environment– Distributed constellation mitigates worst-case risks
Design Vector ID 2908 2901 3231 3718 3711 orbit altitude (km) Walker constellation 9/3/2 9/3/2 27/3/1 66/6/5 66/6/5 transmit frequency (GHz) antenna area (m^2) 100 100 40 antenna type radar bandwidth (MHz) peak transmit power (kW) tugable comm. architecture direct relay relay direct relay tactical link shield thickness (mm) 1 1 10satellite spares 0 2 2 0 2 lifecycle cost ($B) 22.3 25.8 31.2 54.8 57.4 utility 0.51 0.51 0.47 0.74 0.74 utility loss (95th) 0.09 0.01 0.00 0.06 0.00 utility loss (99th) 0.12 0.02 0.00 0.07 0.01threshold availability (1st) 0.95 1.00 1.00 0.95 1.00
1
20 20
yes yes
no no
40AESA AESA2000 2000
1500 1500
10 10
2901
3231
3718 3711
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Methodological Insights
MATE for Survivability incorporates survivability as a decision metric into conceptual design – Design principles reveal latent survivability trades and inform selection
of survivability design variables– Survivability metrics enable discrimination among thousands of design
alternatives
Implementation considerations– Subject percentile reporting levels to sensitivity analysis– Balance broad exploration with selected of individual point designs
MATE for Survivability improves on existing tradespace approaches– Pareto front in traditional MATE study excludes most survivable designs– Evaluates survivability implications for selection of baseline architecture
seari.mit.edu © 2008 Massachusetts Institute of Technology 25
Future Work
• Methodological improvements– Parameterize concept-of-operations in design vector
– Extend scope for systems-of-systems (SoS) engineering
• Apply MATE for Survivability to additional systems for prescriptive insights
water distributionpower distribution transportation communications
Questions?
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Limitations of Existing Metrics
• Construct validity• Binary assessment criteria
Inherent Availability
• Survivability preferences confounded with availability and capability
Mission Effectiveness
• Construct validity• Binary assessment criteria• Time to failure assumed as exponential density function
Reliability Function
(aka Survival Function)
• Binary assessment criteria• Assumes independence among shot and mission outcomes
Campaign Survivability
• Binary assessment criteria fails to internalize graceful degradation
Engagement Survivability
MTBFtetFtR /)(1)(
HKHKS PPPP 11
(Ball 2003; Blanchard and Fabrycky 2006)
MTTRMTBFMTBFAi
NK
NS PPCS )1(
t = operating time
MTBF = mean time between failure
MTTR = mean time to repair
S = survive, K = kill, H = hit
N = number of engagements
CapabilityPAMoME Si
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Need Measures of Central Tendency Across Runs
0 2 4 6 8 100
0.05
0.1
0.15
0.2
0.25
time (years)
utili
ty (
dim
ensi
onle
ss)
DV(19) - Run(2/500)
V(t)
Threshold
0 2 4 6 8 100
0.05
0.1
0.15
0.2
0.25
time (years)
utili
ty (
dim
ensi
onle
ss)
DV(19) - Run(1/500)
V(t)
Threshold
0 2 4 6 8 100
0.05
0.1
0.15
0.2
0.25
time (years)
utili
ty (
dim
ensi
onle
ss)
DV(19) - Run(89/500)
V(t)
Threshold
0 2 4 6 8 100
0.05
0.1
0.15
0.2
0.25
time (years)
utili
ty (
dim
ensi
onle
ss)
DV(1137) - Run(3/500)
V(t)
Threshold
0 2 4 6 8 100
0.05
0.1
0.15
0.2
0.25
time (years)
utili
ty (
dim
ensi
onle
ss)
DV(1137) - Run(20/500)
V(t)
Threshold
0 2 4 6 8 100
0.05
0.1
0.15
0.2
0.25
time (years)ut
ility
(di
men
sion
less
)
DV(1137) - Run(426/500)
V(t)
Threshold
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General Conclusions
• Definition of baseline system architecture should include survivability considerations for efficient mitigation of disturbances
• Uniting tradespace exploration with survivability analysisgenerates knowledge that may ultimately lead to better design decisions
• Importance of survivability will grow as critical infrastructures become increasingly large-scale, long-lived, and interdependent
• Conceptualization of survivability for engineering systems is a solution-generating and decision-making framework, enabling discovery of systems robust to finite-duration disturbances