A Framework for Incorporating ilities in Tradespace Studies

Transcription

1 A Framework for Incorporating ilities in Tradespace Studies September 20, 2007 H. McManus, M. Richards, A. Ross, and D. Hastings Massachusetts Institute of Technology

2 Need for ilities Washington, DC in June 2004 According to Dr. Marvin Sambur, Systems Engineering for Robustness means developing systems that are Capable of adapting to changes in mission and requirements Expandable/scalable, and designed to accommodate growth in capability Able to reliably function given changes in threats and environment Effectively/affordably sustainable over their lifecycle Developed using products designed for use in various platforms and systems Easily modified to leverage new technologies Robustness scope expanded beyond classical robustness Experts questioned What does it mean? How can it be measured/analyzed? Who is going to pay for it? How can designers account for these operational ilities *Adapted from Ross, A., Rhodes, D., and Hastings, D., Defining System Changeability: Reconciling Flexibility, Adaptability, Scalability, and Robustness for Maintaining System Lifecycle Value, INCOSE Int l Symposium 2007, San Diego, CA, June 2007 seari.mit.edu 2007 Massachusetts Institute of Technology 2

3 The Ilities design challenge Incorporating operational ilities e.g. robustness, versatility, flexibility, adaptability, scalability, survivability a major challenge for designers/architects Not simple system attributes Not captured by static tradespace models Measure preserved/enhanced value delivery in the presence of change seari.mit.edu 2007 Massachusetts Institute of Technology 3

4 Outline A visual framework for categorizing and defining operational ilities Modification of framework for including ilities in tradespace studies Simple example: Survivability of an orbital transfer vehicle seari.mit.edu 2007 Massachusetts Institute of Technology 4

5 Ilities address the ability of a system to preserve value delivery under change Consider things that change: Needs/ (expectations/req.s, system performance) Visualizing Ilities The Ility Space Context (e.g. environment, peer systems, social context, etc.) Context System (form, boundaries, operational modes, etc.) A visualization: Ilities characterized by motion in these three dimensions A E B S Needs (performance, expectations) System seari.mit.edu 2007 Massachusetts Institute of Technology 5

6 Visualizing Ilities Survivability Context AB: Robust B Minimal Control Performance Operational Performance Needs (performance, expectations) A System seari.mit.edu 2007 Massachusetts Institute of Technology 6

7 Visualizing Ilities Survivability AB: Robust AC: Survivable AX: Failure Context C X B Minimal Control Performance Operational Performance Needs (performance, expectations) A System seari.mit.edu 2007 Massachusetts Institute of Technology 7

8 Visualizing Ilities Survivability AB: Robust AC: Survivable AX: Failure Context C X B D Minimal Control Performance Operational Performance Needs (performance, expectations) A E AD: Survival through adaptation DA: Full Recovery DE: Altered Recovery System seari.mit.edu 2007 Massachusetts Institute of Technology 8

9 Challenge of Incorporating Ilities in Tradespace Studies Temporal system properties that are difficult to represent in a static tradespace Ilities (currently) need to be disaggregated from attributes Attributes need to be independent, but Ilities defined by attribute performance over time So ilities cannot be incorporated into attribute set or aggregated into a multi-attribute utility Abstract view of ilities represented in ility space difficult to implement in tradespace models seari.mit.edu 2007 Massachusetts Institute of Technology 9

10 Alternate Ility Representation* Plot performance/expectations vs. time Context, system, expectations change in epochs * See Ross, A., Managing Unarticulated Value: Changeability in Multi-Attribute Tradespace Exploration, Ph.D. Dissertation, Engineering Systems Division, Massachusetts Institute of Technology, Cambridge, MA, seari.mit.edu 2007 Massachusetts Institute of Technology 10

11 Three-Epoch Model of Survivability Three epochs Initial operations Operation in a harsh environment for a finite duration Return to normal operation Simple Epoch representation allows trade-space modeling of each epoch Operational modeling of Epoch 1 and 3 In this case, simple debris impact model* in Epoch 2 * Lai, S., Murad, E., and McNeil, W., Hazards of Hypervelocity Impacts on Spacecraft, Journal of Spacecraft and Rockets, 39(1), January-February seari.mit.edu 2007 Massachusetts Institute of Technology 11

12 Baseline Study: Space Tug Existing MATE* study of space tug trade space Three attributes Delta-V Capability Response time Three design variables Design Space >Manipulator Mass Low (300kg) Medium (1000kg) High (3000 kg) Extreme (5000 kg) >Propulsion Type Storable bi-prop Cryogenic bi-prop Electric (NSTAR) Nuclear Thermal >Fuel Load - 8 levels >Simple performance model Delta-V calculated from rocket equation Binary response time (electric propulsion slow) Capability solely dependent on manipulator mass Cost calculated from vehicle wet and dry mass * MATE: Multi-Attribute Tradespace Exploration; see McManus, H., and Schuman, T., Understanding the Orbital Transfer Vehicle Tradespace, AIAA , Sept seari.mit.edu 2007 Massachusetts Institute of Technology 12

13 Incorporation of Debris Risk and Bumper Shielding in Tradespace For all Epochs: Add six levels of shielding to design vector For Epoch 2: Compute probability of debris collision 10 years of space tug operating at 800 km apogee Exposed satellite cross-sectional area Existing Debris flux model Given collision, compute probability of surviving impact Simple bumper shield model No active survivability strategies (in this model) seari.mit.edu 2007 Massachusetts Institute of Technology 13

14 Survivable Space Tug Tradespace (Epoch 1) Utility (dimensionless) Cost ($M) Survivability lowers initial utility Mass of shielding (~cost) Loss of Delta-V due to pushing extra mass around (~utility loss) seari.mit.edu 2007 Massachusetts Institute of Technology 14

15 Ility as Independent Decision Factor: Cost-Utility-Survivability Tradespace Survivability (prob. of 10 yr life in LEO) Cost ($M) Utility (dimensionless) Difficult to visualize and understand seari.mit.edu 2007 Massachusetts Institute of Technology 15

16 Exploring Trade Space Requires Creative Display Utility (dimensionless) Cost ($M) seari.mit.edu 2007 Massachusetts Institute of Technology 16

17 Discussion Technical results Small vehicles are intrinsically survivable, badly penalized by shield mass On larger vehicles, shielding may be worthwhile for risk-adverse decision makers Size mix of debris population makes shielding less effective than expected Some vehicles have delta-v headroom that allows shielding without utility penalty Modeling lessons learned Satellite survivability to an environmental disturbance can be parametrically modeled Extreme nonlinearities associated with costs and benefits of shielding in different regions of the tradespace Display of cost, utility, and survivability in tradespaces requires innovative visualizations seari.mit.edu 2007 Massachusetts Institute of Technology 17

18 Conclusions Framework Ility Space added clarity to, and illustration of, ility taxonomy Epoch representation better for planning analysis Lessons from Implementation Example Possible (though not easy) to present decision maker with ility information as part of a tradespace exploration Approach should generalize from our simple example Explicit results and emergent understandings can help improve up-front decision-making seari.mit.edu 2007 Massachusetts Institute of Technology 18

19 Backup Slides

20 Future Survivability Work Current Limitations Single decision maker Binary survivability model, Single survivability design variable considered System-level analysis does not address architectural, sociotechnical issues Next steps Incorporate dual decision makers for survivability performance trades Application of Lawson s decision analysis Improve model fidelity to allow for partially degraded satellite states Incorporate other survivability design variables Space situational awareness Collision avoidance Explore portfolio approach to risks management Contrast Operationally Responsive Space approach with existing monolithic architecture seari.mit.edu 2007 Massachusetts Institute of Technology 20

21 Validation of Space Tug Tradespace Tool Orbital Recovery Corp. Orbital tugboat to supply propulsion, navigation and guidance to maintain a satellite in its orbital slot for 10+ years Electric Cruiser (2002 study) CX-SLES (2009 launch) Wet Mass kg Dry Mass kg * Propellant kg * Equipment kg * DV m/s *** 15900** Utility Cost * seari.mit.edu 2007 Massachusetts Institute of Technology 21

22 NASA ORDEM2000 Model SSN catalog Haystack and Haystack Auxiliary radar data Goldstone radar data Impact measurements from the Long-Duration Exposure Facility (LDEF) Hubble Space Telescope Solar Array (HST-SA) impact data European Retrievable Carrier (EuReCa) impact data Space Shuttle window and radiator impact data Space Flyer Unit (SFU) data Mir impact data Characterizing LEO Debris Environment Debris per cubic kilometer 1.00E E E E E E E E E E E E-10 km/s Spatial Density LEO altitude (km) Average Orbital Velocity seari.mit.edu 2007 Massachusetts Institute of Technology 22 >10um >100um >1mm >1cm >10cm >1m

23 Debris Model cross section flux (collisions/m^2/year) 1.00E E E E E E E E E E-09 data source Remo 2005 tracked debris (NORAD catalog) Orbital Debris Flux in LEO object diameter (cm) cross section flux (collisions/m^2/year) LEO collisions/year result E degradation E damage E damage E severe damage E E-03 severe damage E E-03 severe damage E E-06 severe damage (assuming 10 m^2 LEO satellite cross-sectional area) Regression across heterogeneous data y = 4E-05x debris diameter (cm) seari.mit.edu 2007 Massachusetts Institute of Technology 23

24 Bumper shields are effective for passive protection against fragments smaller than 1 cm in diameter Works by fragmenting or vaporizing projectile in first layer, dispersing impulsive load into particle cloud which hits next layer over larger area Design parameters of bumper system Thickness and material of outer wall Spacing between shield and backup layers Thickness and material of backup layers Survivability Design Variable: Bumper Shielding t b = t b C m V S Cmv 2 S Backup sheet thickness in cm where backup sheet will not deflect, rupture, or spall Empirically-derived constant 41.5±14.0 cm 3 g -1 km -1 s Projective mass in g Projectile velocity in km/s Bumper spacing in cm Lai (2002) seari.mit.edu 2007 Massachusetts Institute of Technology 24

25 Survivability and Costs as Constraints - utility shown by shading Cost ($M) Survivability (prob. of 10 yr life in LEO) Pick the best from the box seari.mit.edu 2007 Massachusetts Institute of Technology 25