1. © The Aerospace Corporation 2011 Determining Risk from Fragmentation Events Roger C. Thompson The Aerospace corporation Systems Engineering Division The Aerospace Corporation 5 April 2011 UNCLASSIFIED

2. Roger.Thompson@aero.org Systems Analysis and Simulation Outline Background – space debris and risk modeling Debris environment The Aerospace Corporation’s experience in space debris and risk modeling –Launch collision avoidance –Debris Analysis Response Team (DART) The Aerospace Corporation’s research and development –Methodologies –Software UNCLASSIFIED

3. Roger.Thompson@aero.org Systems Analysis and Simulation 3 Space Debris and Collision Risk Modeling Space debris has been growing operational concern for years –ISS Conjunctions, Mar 09 –Iridium 33 / Cosmos 2251 collision, Feb 09 –USA 193, Feb 08 –Chinese ASAT test, Jan 07 –On-orbit collisions (e.g. US rocket body / Chinese launch debris, Jan 05) –Multiple recent breakup events (e.g. SL-12, Mar 09, Briz-M, Feb 07) –Launch vehicle debris shedding (e.g. Delta IV / DMSP-17, Nov 06) Aerospace models risk FROM –Cataloged objects –Background environment –Debris-producing events Aerospace models risk TO –New launches (LCOLA) –Resident, active spacecraft (DART) –Specific close approach scenarios as requested UNCLASSIFIED

4. Roger.Thompson@aero.org Systems Analysis and Simulation 4 Space Debris Analysis Debris Producing Event: Collisions ASATs On-orbit breakups Launch shedding Characterize Debris Event: Identify objects Generate modeled debris Determine breakup time and location Background models Resident Space Object Catalog Tracking Data: Aerospace Fusion Center AFRL, NROC, JSPOC, ESA, NASA, AFSPC, SSN Other space environment Other intelligence Determine Risk, Create Products: LCOLA DART products COLA Anomaly resolution Ops support Figure is UNCLASSIFIED UNCLASSIFIED

5. Roger.Thompson@aero.org Systems Analysis and Simulation 5 Debris Environment Space debris comes from multiple sources –Background debris (naturally occurring or manmade – too small to track) –Cataloged debris (launch and deployment related – trackable) –Debris producing events (explosions, collisions) Debris producing events generate a moderate number of large debris particles which will get cataloged and a huge number of smaller debris particles which will never be tracked or cataloged –Smaller particles will eventually dissipate and become part of a slightly enhanced background –Prior to dissipation, they pose an unseen, elevated risk to resident spacecraft Size ClassQuantityImpact 10 cm or larger Hundreds Tracked and cataloged by space surveillance network Catastrophic damage to spacecraft 1 cm to 10 cm Tens of thousands Most can’t be tracked Catastrophic damage to spacecraft 3 mm to 1 cm Millions Can’t be tracked Localized damage only Smaller than 3 mm Millions Can’t be tracked Minimal if any damage to spacecraft Table is UNCLASSIFIED UNCLASSIFIED

6. Roger.Thompson@aero.org Systems Analysis and Simulation 6 Background Models All active spacecraft implicitly accept risk from “background” of small, untrackable objects: micrometeoroids, man-made debris Two major background models –NASA ORDEM 2000 –ESA MASTER 05 Neither model includes recent major breakup events –ORDEM update being evaluated Aerospace applies both models to provide risk points of reference Average risk/day in LEO = 3x10 -6 Figure is UNCLASSIFIED UNCLASSIFIED

7. Roger.Thompson@aero.org Systems Analysis and Simulation 7 LCOLA Support Overview Aerospace provides Launch Collision Avoidance (LCOLA) analyses for NRO, SMC, and NASA (Goddard Spaceflight Center) launches –Support specifically required by Mission Directors for all NRO & SMC missions –NASA support coordinated through OSL –Support to both rehearsals and launch Software development began in 1996 –Probability of collision would open more launch opportunities –Protection would be consistent with distance-based blackouts Launch-on-Minute (LOM) or Launch-on-Second (LOS) Range Safety, Space Safety, and Mission Assurance COLA integrated into a single simple report UNCLASSIFIED

8. Roger.Thompson@aero.org Systems Analysis and Simulation 8 DART – Debris Event Quick Response CONOPS Trajectory reconstruction (Aerospace Fusion Center) Government customers Aerospace Process Generate reports Aerospace customer interface Asset list Iterate as new data becomes available Model database NASA Target determination Debris generation Collision risk assessment Mission Ground Sites Figure is UNCLASSIFIED UNCLASSIFIED External information tasking events

9. Roger.Thompson@aero.org Systems Analysis and Simulation 9 Debris Generation Typical ASAT event will produce over 4 million particles (discrete element sets) –Mass distribution Cumulative number of fragments of a given mass and larger –Spread velocity distribution Fragment velocities relative to center of mass of debris cloud Determines extent of and density variations within debris cloud –Area/mass distribution Function of constituent material densities Figures are UNCLASSIFIED UNCLASSIFIED

10. Roger.Thompson@aero.org Systems Analysis and Simulation Collision Risk Assessment Satellite with cross-section Expanding debris cloud Cumulative fluence (average no. impacts, summed over layers) Collision probability Path traversed by satellite through debris cloud Local debris density Local debris relative encounter velocity Probabilistic Continuum Model of Debris Cloud Figure is UNCLASSIFIED UNCLASSIFIED

11. Roger.Thompson@aero.org Systems Analysis and Simulation 11 Sample DART Report Iridium collision – Worst case 100% Fragmentation Decreasing Risk Table is UNCLASSIFIED IRIDIUM 33 collision with COSMOS 2251 10 Feb 2009 16:55:59.8 UTC Graphic is UNCLASSIFIED Each scatter dot represents a space asset UNCLASSIFIED Space Risk for 10-11 Feb

12. Roger.Thompson@aero.org Systems Analysis and Simulation 12 Risk Analyses Multiple reports are generated at various stages in timeline Many reports aim at providing an understanding of risk for individual or groups of spacecraft Reports vary with circumstances of breakup, issue being explored Graphic is UNCLASSIFIED Figures are UNCLASSIFIED UNCLASSIFIED

13. Roger.Thompson@aero.org Systems Analysis and Simulation 13 Debris Field Evolution Many reports, plots, animations address the evolution of the debris field SOAP displays shown real-time at NROC, JSpOC Figures are UNCLASSIFIED Debris not to scale UNCLASSIFIED

14. Roger.Thompson@aero.org Systems Analysis and Simulation 14 Chinese vs. US Impact Events January 2007 Chinese ASAT Event Intercept Altitude Only 10% of the particles have decayed in 60 days, and only 18% in one year. In 5 years, only 31% have decayed, and 69% are still in orbit. The colors represent the density of debris within an altitude band. Higher density means higher probability of encounter for satellites in that band. The density drops as debris is cleaned out by the atmosphere. Time is measured from the impact. 77% of particles decay in 1 day, 90% in 17 days, and over 99% in 97 days. Less than 0.01% remain in orbit after a year. February 2008 US Intercept Intercept Altitude Particles per 50 km altitude shell UNCLASSIFIED Figure is UNCLASSIFIED

15. Roger.Thompson@aero.org Systems Analysis and Simulation 15 Comparison to Tracked Debris Collision + 60 days Debris not to scale Tracking, cataloging of debris still underway –1949 objects cataloged (as of 14 March 2011) –COSMOS debris count is almost 3 times the Iridium count Models matched reasonably well 2 months after collision –Less than half of the current object count had been cataloged 60 days after event ~95% of debris is still in orbit Iridium Cosmos UNCLASSIFIED Figure is UNCLASSIFIED

16. Roger.Thompson@aero.org Systems Analysis and Simulation Ballistic Missile Intercept Simulations Characterize risk prior to actual events –Debris is short-lived, event will be over before DART can respond Analyses focus on the risk from intercept-generated debris to –Resident space objects –People and vehicles on the ground from the reentry of the debris into the atmosphere Debris risk will be dependent on altitude, latitude, and the geometry of the intercept(s) Four orbit classes defined to assess risk to RSOs –Sun-synchronous, ~98  inclination –Mid-inclination (45  ) –Critically-inclined (63  ) –Communications, ~85  inclination UNCLASSIFIED

17. Roger.Thompson@aero.org Systems Analysis and Simulation Methodology For each orbit class –Vary altitudes from 422 - 1122 km (6800 – 7500 km radius) –Eight different altitudes, 100 km increments Location of satellite in orbit will be important –Debris is short-lived, but density is relatively high –Satellites will be in the wrong place/wrong time or miss the event entirely Create a Walker constellation for each altitude –36 planes (every 10  in RAAN) –36 satellites in each plane (every 10  in Mean Anomaly) Total of 10,368 satellites in each orbit class –Provides an estimate of wrong place/wrong time risk in addition to collision risk from debris encounters UNCLASSIFIED

18. Roger.Thompson@aero.org Systems Analysis and Simulation Methodology (cont’d) Perform Collision Risk Assessment (slide 10) –For each debris particle Propagate all 10,368 satellites over the life of the debris objects Use an exaggerated cross-sectional area to obtain a statistically significant number of “hits” Particle flux is a function of the number of “hits” and the volume swept out by the sphere Probability is calculated from particle flux Fraction of satellites encountering any debris divided by total satellites represents risk (%) of being in the wrong place at the wrong time Probability of collision is the calculated risk if the satellite does encounter debris –Maximum and minimum probabilities reported to characterize the distribution/spread of the debris –Compare to background risk from untracked objects to determine elevated risk UNCLASSIFIED

19. Roger.Thompson@aero.org Systems Analysis and Simulation Sample Results – Probability of Collision Late Boost Intercept Mid-Course Intercept UNCLASSIFIED

20. Roger.Thompson@aero.org Systems Analysis and Simulation Sample Results – Relative Risk for 12 Cases Sun-Synchronous Orbits UNCLASSIFIED

21. Roger.Thompson@aero.org Systems Analysis and Simulation Other Related Activities Delta IV debris shedding analyses –Model development from on-board video –Risk assessment for DSP-23, L-49, L-26 Upper stage and satellite disposal analyses –Minimize collision risk for disposed GPS, HEO, and GEO objects for 100+ yrs Established the Center for Orbital Reentry and Debris Studies (CORDS) in 1997 NAVSTAR 29 disposal orbit evolution Debris cloud risk vs. satellite RAAN L26 debris lifetime vs. shedding time UNCLASSIFIED

22. Roger.Thompson@aero.org Systems Analysis and Simulation 22 Aerospace Debris and Risk Models Compared with MDA, NASA MDA, NASA, Aerospace conducted joint study in summer 2007 to compare modeling approaches and results –Motivated by FY-1C event –Each breakup model is based on empirical data from ground- and space- based tests, but not the same tests –Each model has been in use for a number of years for applications specific to the developing organization Each model uses a different set of input parameters Approach was to compare individual model results with data measured/collected from two real world events –Highlight areas for potential model improvements Study yielded good agreement, joint report briefing issued UNCLASSIFIED

23. Roger.Thompson@aero.org Systems Analysis and Simulation 23 Debris Cloud Risk Model Comparison Aerospace and STEPAL Risk Models Plot shows impact risk posed to ISS vs. intercept time for a hypothetical intercept scenario, ISS RAAN = 0, initial mean anomaly = 289.014° Results are based on KIDD breakup model (fragments with mass >= 3 mm Al sphere) Impact Risk Posed to ISS vs. Intercept Time (3mm debris data) STEPAL Model Aerospace Model Vulnerability Area = 30m 2 Cross Sectional Area Of ISS Figure is Unclassified UNCLASSIFIED

24. Roger.Thompson@aero.org Systems Analysis and Simulation Model Comparison Conclusions For a missile intercept case, MDA predictions were the most consistent of the three models with measurement data For a satellite intercept case, the NASA and Aerospace predictions were more consistent with measurement data (RCS) –NASA/Aerospace showed the best agreement in debris RCS for larger debris –MDA showed the best agreement in debris RCS for smaller debris –Aerospace showed the best agreement with debris tracks Risk analysis will be scenario dependent Overall, the best agreement between model-to-measured data is found when the intercept event matches the events comprising the empirical data upon which the model is based UNCLASSIFIED

25. Roger.Thompson@aero.org Systems Analysis and Simulation 25 DART Experience 2 satellite intercepts (FY-1C and USA-193) and 1 satellite collision (Iridium 33) 4 launch debris cloud risk assessments 14 real world close approaches 29 exercises Special analyses where processes applied to answer specific questions Model comparison with MDA and NASA –NASA: NASA Standard breakup model/SBRAM risk assessment tool –MDA: KIDD breakup model/REBLE risk assessment tool –Bottom line: satellite risk assessments agree within an order of magnitude Current usage has all been below 1000 km –Includes ballistic missile intercept simulations UNCLASSIFIED

26. Roger.Thompson@aero.org Systems Analysis and Simulation 26 Summary of Aerospace Debris Analysis Activities High profile of recent debris event have raised significant concerns about space debris –Govt support to Commercial and Foreign Enterprises (CFE) is of particular concern Aerospace has active research programs addressing multiple aspects of space debris and space situational awareness DART and LCOLA processes undergoing continuing evolution –Goal is to evolve initial laboratory capabilities into more operational, sustainable capability –Use prototype capabilities as guide to Govt acquisition, operations UNCLASSIFIED