Space Systems, Policy, and Architecture Research Consortium 1 Hugh McManus Space Systems, Policy, and Architecture Research Consortium A joint venture of MIT, Stanford, Caltech & the Naval War College for the NRO ?2002 Massachusetts Institute of Technology Space Systems Architecture Lecture 3 Introduction to Tradespace Exploration Metis Design Space Systems, Policy, and Architecture Research Consortium 2 ? ? Concept Development System-Level Design Detail Design Testing and Refinement Production Ramp-Up Product Design and Development, 1995 Phases of Most relevant to processes in these phases ?2002 Massachusetts Institute of Technology Tradespace Exploration A process for understanding complex solutions to complex problems Allows informed “upfront” decisions and planning From Ulrich & Eppinger, Product Development 1 Space Systems, Policy, and Architecture Research Consortium 3 ? ? Ideally, many architectures assessed ? Avoids optimized point solutions that will not support evolution in environment or user needs ? Provides a basis to explore technical and policy uncertainties ? Provides a way to assess the value of potential capabilities A process for understanding complex solutions to complex problems ?2002 Massachusetts Institute of Technology Architecture Trade Space Exploration Model-based high-level assessment of system capability Allows informed “upfront” decisions and planning Space Systems, Policy, and Architecture Research Consortium 4 ? State-of-the-art rapid preliminary design method ? Design tools linked both electronically and by co-located humans ? Design sessions iterate/converge designs in hours ? Requires ready tools, well poised requirements A process creating preliminary designs very fast Allows rapid reality check on chosen architectures Aids transition to detailed design ?2002 Massachusetts Institute of Technology Integrated Concurrent Engineering 2 Number of Architectures Explored: 50488 Number of Architectures Explored: 50488 Space Systems, Policy, and Architecture Research Consortium 5 User Needs Robust Adaptable Concepts Months, not Years ICE Conceptual Design MATE Architecture Evaluation ? Linked method for progressing from vague user needs to conceptual/preliminary design very quickly ? MANY architectures, several/many designs considered ? adaptable concepts, consideration of policy, risk. ?2002 Massachusetts Institute of Technology Emerging Capability Understanding the trades allows selection of robust and Space Systems, Policy, and Architecture Research Consortium 6 km Km DESIGN VARIABLES: The architectural trade parameters ? Orbital Parameters – Apogee altitude (km) – Perigee altitude (km) – Orbit inclination 150-1100 150-1100 0, 30, 60, 90 ? Physical Spacecraft Parameters – Antenna gain – communication architecture – propulsion type – power type – delta_v Total Lifecycle Cost ($M2002) a specific architecture Assessment of the utility and cost of a large space of possible system architectures X-TOS ? Small low-altitude science mission ?2002 Massachusetts Institute of Technology What is an Architecture Trade Space? Each point is 3 Space Systems, Policy, and Architecture Research Consortium 7 ? Understand the Mission ? Create a list of ? Interview the Customer ? Create Utility Curves ? Develop the design model ? Evaluate the potential Architectures Mission Concept Attributes Calculate Utility Develop System Model Estimate Cost Architecture Define Design Vector ?2002 Massachusetts Institute of Technology “Attributes” vector and system Trade Space Developing A Trade Space Space Systems, Policy, and Architecture Research Consortium 8 Concept ? Small low-altitude science mission ? Known instruments Attributes ? Data Life Span ? Data Collection Altitude(s) ? Diversity of Latitude(s) ? Time Spent at Equator ? Data Latency ? Number of Vehicles and Mission Design ? Apogee Altitude ? Perigee Altitude ? Orbit Inclination ? Antenna Gain ? Communications Architecture ? Propulsion Type ? Power Type ? 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 150 350 550 750 950 Data Collection Altitude (km) Utility ?2002 Massachusetts Institute of Technology XTOS Tradespace Development Design Vector Manuever Delta-V Capability Define Utility 4 Space Systems, Policy, and Architecture Research Consortium 9 Continued Total Lifecycle Cost ($M2002) Each point is a specific architecture ? Orbit Calculations (STK) ? Spacecraft Estimations (SMAD) ? Launch Module 50488 Architectures Explored ? SMAD/NASA mode? Multi-Attribute Utility Theory architectures ?2002 Massachusetts Institute of Technology System Model Estimate Cost Calculate Utility Pareto front of “best” Space Systems, Policy, and Architecture Research Consortium 10 ? ? ? ? ) ? 2002 Massachusetts Institute of Technology Understanding What Systems Do Transmit Information Collect Information Move Mass (inc. People) Others (Space Station… [Beichman et al, 1999] 5 Martin 2000 Space Systems, Policy, and Architecture Research Consortium 11 Stakeholders ? ? ? Enterprise Employees Corporation End Users ConsumersCustomer Acquirers Shareholders UnionsSociety Partners Suppliers ?2002 Massachusetts Institute of Technology Understanding who cares - Many interested parties in a complex system Each “customer” has a set of needs They are different, and can be contradictory Space Systems, Policy, and Architecture Research Consortium 12 ATOS: Multi-vehicle Ionosphere Explorer In Situ Direct Scintillation Sensing Topside Sounding GPS Occultation GPS UV Sensing ?2002 Massachusetts Institute of Technology Concept Selection: Bounding 6 ?2002 Massachusetts Institute of Technology 14 Space Systems, Policy, and Architecture Research Consortium 13 Scoping Spacecraft Instrument Control Center Physics Model Instrument -> Local Ionosphere Current State Predict Future State User-Specific System Integration User Set User Set User Set User Set Ionospheric characteristics Database Other Data Sources (Various assets) A-TOS scope Ionosphere ?2002 Massachusetts Institute of Technology Global Ionospheric Model Global Ionospheric Model Hanscom Model Raw, commutated, uncalibrated data Decommutated, calibrated instrument data “Scientist” “Warfighter” “Space Weather” “Knowledgeable” Go/No-Go “green light” Space Systems, Policy, and Architecture Research Consortium Attributes ? “what the decision makers need to consider” ? ( and/or what the user truly cares about) ? Examples: Billable minutes = ? TPF Pictures = camera performance metrics ? Rescue/move satellites = mass moving, grappling capability, timeliness – Could have sub-cartoons for above GINA metrics [Beichman et al, 1999] 7 DATA Space Systems, Policy, and Architecture Research Consortium 15 (5)(4)(3) (2)(1) 1) Data Life Span 2) Data Altitude 3) Maximum Latitude 4) Time Spent at Equator 5) Data Latency km Km 2004 2005 ?2002 Massachusetts Institute of Technology XTOS Attributes Space Systems, Policy, and Architecture Research Consortium 16 Utilities ? ? ? Single Attribute Utility function 0 1 Good -> Attribute Multi-Attribute Utility analysis 0 1 Good -> Expense ?2002 Massachusetts Institute of Technology “What the attributes are WORTH to the decision makers” Single Attribute utility maps attribute to utility Multi-attribute utility maps an architecture (as expressed by its attributes) to utility 8 9 Space Systems, Policy, and Architecture Research Consortium ?2002 Massachusetts Institute of Technology 17 Single Attribute Utilities 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 150 350 550 750 950 Data Collection Altitude (km) Utility Space Systems, Policy, and Architecture Research Consortium ?2002 Massachusetts Institute of Technology 18 Multi-Attribute Utility Single Attribute Utility Curve for Data Point Altitude 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 150 350 550 750 950 Altitude (km) 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 Lifespan Latitude Latency Equator Time Altitude Weight Factors of each Attribute (k values) ( ) ’ = +=+ N i ii XUKkXKU 1 1)(1)( Total Lifecycle Cost ($M 2002) Utility XTOS Design Vector ? “Parameters of the Trade Space” Variable: First Order Effect: Orbital Parameters: ?Apogee altitude (200 to 2000 km) Lifetime, Altitude ?Perigee altitude (150 to 350 km) Lifetime, Altitude ?Orbit inclination (0 to 90 degrees) Lifetime, Altitude Latitude Range Time at Equator Physical Spacecraft Parameters: ?Antenna gain (low/high) Latency ?Comm Architechture (TDRSS/AFSCN) Latency ?Propulsion type (Hall / Chemical) Lifetime ?Power type (fuel / solar) Lifetime ?Total DV capability (200 to 1000 m/s) Lifetime Space Systems, Policy, and Architecture Research Consortium ?2002 Massachusetts Institute of Technology 19 Space Systems, Policy, and Architecture Research Consortium 20 ? mothership ?2002 Massachusetts Institute of Technology ATOS design Vector Geometry of the Multi-vehicle Swarm Swarm Orbit Parameters Mothership/ no Number of spacecraft in swarm Geometry of swarm 10 Space Systems, Policy, and Architecture Research Consortium 21 Identify key interactions for modeling that are likely to be (or not be) distinguishers Design Vars Perigee Apogee Delta-V Propulsion Inclination Comm System Ant. Gain Power system Mission Scenario Total Impact Attributes Data Lifespan 9 9 9 6 0 0 0 6 9 48 Sample Altitude 9 9 0 0 0 0 0 0 9 27 Diversity of Latitudes 0 0 0 0 9 0 0 0 9 18 Time at Equator 0 6 0 0 9 0 0 0 9 24 Latency 3 3 0 0 3 9 9 6 3 36 Total 21 27 9 6 21 9 9 12 39 Cost 9 9 3 6 6 3 6 6 9 Total w/Cost 30 36 12 12 27 12 15 18 48 ?2002 Massachusetts Institute of Technology Scoping-QFDs Sums identify attributes and Design Variables Space Systems, Policy, and Architecture Research Consortium 22 Scoping-Iteration/evolution After GINA exercise module progress 10/20/00 10/31/00 1/15/01 1/21/01 # sats/swarm # swarms Instrument type # instruments/sat Position control scheme Concept type # sats/swarm Mothership (yes/no) # sats/swarm # subplanes/swarm # suborbits/subplane # sats/swarm # subplanes/swarm # suborbits/subplane ?2002 Massachusetts Institute of Technology TABLE II. EVOLUTION OF DESIGN VECTOR First Cut After utility characterization and Schedule Crunch Swarm type Swarm orbit Intra-swarm orbit TT&C scheme Ground station Mission lifetime Processing scheme Latitude of interest # swarms per plane # orbital planes Swarm altitude Swarm orientation Swarm geometry Separation within swarm Swarm perigee altitude Swarm apogee altitude Yaw angle of subplanes Max sat separation Mothership (yes/no) Swarm perigee altitude Swarm apogee altitude Yaw angle of subplanes Max sat separation 11 Mapping Design Vector to Attributes and Utilities - Simulation Models XTOS Simulation Software Flow Chart All variations on design Orbits Spacecraft Launch Satellite vector database Mission Scenario Cost (lifecycle) Utility Mission scenarios with Output acceptable satellites Space Systems, Policy, and Architecture Research Consortium ?2002 Massachusetts Institute of Technology 23 Space Systems, Policy, and Architecture Research Consortium 24 Availability Probability of Detection # S/C per Cluster …. …. …. Constellation Altitude S/C Bus Launch & Operations RadarConstellation Payload System AnalysisAntenna Power 1 2 3 4 5 6 7 8 9 10 0 10 20 30 40 50 60 70 80 90 100 ?2002 Massachusetts Institute of Technology Techsat Models Inputs (Design Vector) Key Outputs Lifecycle Cost Revisit Rate Resolution & MDV # Clusters Aperture Diameter MATLAB Models 12 13 Space Systems, Policy, and Architecture Research Consortium ?2002 Massachusetts Institute of Technology 25 Exploring the Tradespace 2300 2400 2500 2600 2700 2800 2900 3000 1150 1200 1250 1300 1350 1400 Zoom in of the TPF System Trade Space Performance (total # of images) Lifecycle Cost ($millions) $0.55M/Image $0.5M/Image $0.45M/Image $0.4M/Image 0 500 1000 1500 2000 2500 3000 3500 4000 800 1000 1200 1400 1600 1800 2000 2200 2400 TPF System Trade Space Performance (total # of images) Lifecycle Cost ($millions) $2M/Image $1M/Image $0.5M/Image $0.25M/Image True Optimal Solution Taguchi Solution Many good architectures at c. $0.5M/Image Each point is an evaluated architecture Cadillac Chevy TPF: a science imaging system Space Systems, Policy, and Architecture Research Consortium ?2002 Massachusetts Institute of Technology 26 The Pareto Front ? Set of “best” solutions ? “Dominated” solutions are more expensive or less capable 0 500 1000 1500 2000 2500 3000 3500 4000 800 1000 1200 1400 1600 1800 2000 2200 Performance (total # of images) L i f e c y c l e C o s t ( $ M ) TPF System Trade Space Pareto-Optimal Front Dominated Solutions Non-Dominated Solutions $2M/Image $1M/Image $0.5M/Image $0.25M/Image Utility (images) Cost ($M) Multi-Objective SA Exploration of the TPF Trade Space Performance (total # images L i f e c y c l e C o s t ( $ m i l l i o n s ) $2M/Image $1M/Image $0.5M/Image $0.25M/Image Space Systems, Policy, and Architecture Research Consortium 27 ? 0 500 1000 1500 2000 2500 3000 700 800 900 1000 1100 1200 1300 1400 1500 1600 Pareto Front ?2002 Massachusetts Institute of Technology Optimization Can look for the Pareto front using advanced optimization techniques Current Solution Path Pareto-Optimal Set Space Systems, Policy, and Architecture Research Consortium 28 Designs from traditional process TPF ? Terrestrial Planet Finder - a large astronomy system ? Design space: Apertures separated or connected, 2-D/3- D, sizes, orbits ? ?2002 Massachusetts Institute of Technology Using the Trade Space to Evaluate Point Designs From Jilla, 2002 Images vs. cost [Beichman et al, 1999] 14