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The Effectiveness of Space Debris Mitigation Measures
ISU’s 16th Annual International Symposium
21st February 2012
Adam E. White, Hugh G. Lewis, Hedley Stokes
Introduction• Considerable effort was made to identify mitigation measures
to constrain the growth of the debris population in LEO
• Resulting measures were published in
– the Inter-Agency Space Debris Coordination Committee (IADC) Space Debris Mitigation Guidelines in 2002
– UN Space Debris Mitigation Guidelines in 2007
• The capability to apply these measures is limited and some of these measures have a greater capacity to reduce debris creation than others
• The challenge of identifying, quantifying and addressing the constraints is the objective of the European Union Framework 7 project - Alignment of Capability and Capacity for the Objective of Reducing Debris (ACCORD)
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ACCORD project
• Three stage approach:
– Survey the capability of industry to implement debris mitigation measures and identifying existing and future challenges
– Review the capacity of mitigation measures to reduce debris creation
– Combine capability and capacity indicators within an environmental impact ratings system, which can easily communicate the effectiveness of mitigation practices and identify opportunities for strengthening capability and capacity
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Quantifying mitigation
• The University of Southampton’s evolutionary model, the Debris Analysis and Monitoring Architecture for the Geosynchronous Environment (DAMAGE) was used to quantify mitigation measures in LEO
• Mitigation measures were adopted from the IADC Space Debris Mitigation Guidelines and fully implemented. These are:
– Limit the release of mission-related objects
– Passivation of spacecraft and rocket bodies at end of mission life
– Collision avoidance manoeuvres on operational spacecraft
– Post-mission disposal of spacecraft and rocket bodies conforming to the 25-year rule
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DAMAGE model• DAMAGE is a three-dimensional evolutionary computational
model
• Uses a semi-analytical orbital propagator
• NASA standard breakup model
• Pair-wise collision prediction algorithm based on the ‘ Cube’ approach adopted in NASA’s LEGEND
• Uses a Monte Carlo (MC) approach to account for stochastic elements
• The initial debris population used was derived from the Meteoroid and Space Debris Terrestrial Environment Reference (MASTER) 2009 population of objects 10 cm
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DAMAGE study parameters
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• Objects: 10 cm, orbits intersecting LEO
• Initial population: MASTER 2009 (1st May 2009 epoch)
• Launch traffic: repeating cycle (2000-2009) from MASTER 2009
• Conservative solar flux projection
• Nominal time-step: 5 days
• NASA Standard Break-up model utilised
• ‘Cube’-like collision algorithm: 10 km cube-size
• Projection period: 2009 through 2209
• 100 Monte Carlo runs per scenario
Mitigation implementation
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• Collision avoidance (CA) – Operational spacecraft manoeuvred to avoid all collisions
within their 8 year operational lifetime
• Mission-related objects (MRO) – No mission-related objects were included
• Passivation (PASS) – No explosions occurred
• Post-mission disposal (PMD) – All spacecraft and rocket bodies launched after 1 May
2009 were manoeuvred to a 25-year decay orbit or to a graveyard orbit
Study scenarios
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Scenario number Mitigation measures implementedMRO PASS PMD CA
1 2 3 4 5 6 7 8 9
10 11 12 13 14 15 16
• Performance metrics:
– NERF (Normalised Effective Reduction Factor)
– Synergy Metric
NERF• The NERF (Δ) is a ranked number with compares a scenarios
capacity to reduce debris
• The NERF compares the value of a simulation output quantity, Q with the corresponding output quantity from the worst cast (non-mitigation scenario), Q1, and the ‘best-case’ scenario Q2:
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1
• A ranking of 1 indicates the greatest effect and a ranking of 0 indicates no effect
Synergy metric (S)• Synergy occurs when two or more mitigation scenarios
implemented together are greater than the sum of the individual mitigation measures implemented separately
is the NERF calculated for a scenario with multiple mitigation measures and ∑ Δi is the sum of the NERF values calculated for the same mitigation measures when implemented separately:
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i
iS
• A positive value identifies scenarios where an enhancement of the effectiveness of multiple mitigation measures occurs
• A negative value represents scenarios where multiple mitigation measures hinder one another
Results
• Without mitigation the LEO debris population will likely triple in size after 200 years
• In contrast full adoption of the four key mitigation measures, can limit the growth of the LEO debris population substantially 11
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Top 8 NERF scenarios
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Bottom 8 NERF scenarios
Positive Synergy scenarios
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Negative Synergy scenarios
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Conclusions
• Implementing fully all four mitigation measures significantly reduces the creation of new space debris in LEO
• Post-mission disposal is the most effective individual mitigation measure in LEO but it can lead to an increase in the number of collisions below 500 km
• Passivation and limiting the release of mission related objects have a lesser although still beneficial impact on the LEO debris population
• Collision avoidance manoeuvres appear only to have a limited effect on the LEO debris population however, they remain pivotal to the protection of individual space assets and work well with other mitigation measures to reduce the number of collisions
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Thank you
Adam E. White: [email protected]
Financial support for this work was provided by the EU Framework 7 Programme. The authors would like to thank Holger Krag and Heiner Klinkrad (ESA ESOC) for permission to use the MASTER
population data.
