The Fast Debris Evolution (FaDE) Model

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The Fast Debris Evolution (FaDE) Model

• H.G. Lewis, G.G. Swinerd, R.J. Newland A.
  Saunders

Astronautics Research Group School of Engineering
Sciences
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Outline

• Motivation Aims
• The FADE-? Model
• Comparison with Talents 1992 PIB Model
• Results
• Summary

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Motivation

• The future debris environment is traditionally
  characterised using a few key descriptors, e.g.
• Effective number of objects
• Number of collisions
• The impact of space operations on the debris
  environment can be addressed by answering broad
  questions, e.g.
• Has the number of objects increased or decreased?
• How has the number of objects increased or
  decreased?

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Motivation

• Evolutionary models typically use Monte Carlo
  simulation
• Many runs required for reliable distributions
• Mean and standard deviations usually reported

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Motivation

• Evolutionary models typically use Monte Carlo
  simulation
• Many runs required for reliable distributions
• Mean and standard deviations usually reported

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Aim

• Reduce the effort required to capture basic
  descriptors of the future environment
• Reduce/remove the need for many MC runs
• Maintain accuracy of forecasts
• Identify interesting cases quickly
• Use full, 3-D models to explore outliers
• Characterise runs by their differences from the
  average
• Improve accessibility to future projections
• Flexibility
• Explore different scenarios
• Explore sensitivity to intitial conditions
• Provide outreach possibilities

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FaDE Approach

• Describe debris evolution using an equation of
  motion/intitial value problem
• Estimate values of N for t gt 0 using Eulers
  method
• Include debris species
• Intacts
• Explosion fragments
• Collision fragments

( yr-1)
( yr-1)
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FaDE Approach

• Intacts
• Explosion fragments
• Collision fragments

( yr-1)
( yr-1)
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FaDE Approach Launches, Explosions Removals

• L represents the product of launch rate and
  number of intacts per launch (similar definition
  for E)
• Value of D is species-dependent
• Coefficients L, E, D define basic scenario

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FaDE Basic User Interface
Blurb
Graphical output
Control Panel
Graph options
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FaDE Approach Collisions

• Random collisions account for the biggest
  difference between MC runs in DAMAGE
• Number
• Timing
• Energy
• Need to capture the average collision and
  collision rate

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FaDE Approach Collisions

• Collision probability from DAMAGE

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FaDE Approach Collisions

• Collision probability from DAMAGE No new
  launches after 2000 (1957 2040)

R2 0.9677
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FaDE Approach Collisions

• Empirical model for insertion of collision
  fragments derived from DAMAGE
• A, B, C are coefficients defining collision
  frequency
• F is the average number of fragments produced by
  a collision

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FaDE Initial Conditions

• Defined using 60 MC DAMAGE runs of a No new
  launches after 2000 (1957 2040) scenario

Parameter Value
Projection period 1957 2040
No new launches after 2000
Time-step 5 days
Minimum object size 10 cm
Collision prediction cube size 10 km
Collision prediction active from 1957
Explosions Only confirmed explosions of objects launched prior to 2000 allowed
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FaDE Initial Conditions from DAMAGE

• No new launches after 2000 (1957 2040)
• Number of objects ? 10 cm

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FaDE Initial Conditions from DAMAGE

• No new launches after 2000 (1957 2040)
• Number of collisions

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FaDE Comparison With Talent (1992)

• FADE
• Talent (1992) Eqn. 1
• Roots of the equation (dN/dt 0)
• Determined by
• Identify source and sink terms
• Understand behaviour

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FaDE Testing Comparison with DAMAGE

• Two scenarios
• Business as usual (1957 2040)

Parameter Value
Projection period 1957 2040
Traffic model (2000 2040) Based on launch statistics for 1996-2001
Future explosions (2000 2040) Based on explosion statistics for 1996 - 2001
Time-step 5 days
Minimum object size 10 cm
Collision prediction cube size 10 km
Collision prediction active from 1957
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FaDE Testing Comparison with DAMAGE

• Two scenarios
• No new launches after 2000 (1957 2200)

Parameter Value
Projection period 1957 2200
No new launches after 2000
Time-step 5 days
Minimum object size 10 cm
Collision prediction cube size 10 km
Collision prediction active from 1957
Explosions Only confirmed explosions of objects launched prior to 2000 allowed
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FaDE Comparison with DAMAGE

• Business as usual (1957 2040)
• Number of objects ? 10 cm

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FaDE Comparison with DAMAGE

• Business as usual (1957 2040)
• Number of collisions

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FaDE Comparison with DAMAGE

• No new launches after 2000 (1957 2200)
• Number of objects ? 10 cm

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FaDE Comparison with DAMAGE

• No new launches after 2000 (1957 2200)
• Number of collisions

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Summary

• FaDE captures the evolution of basic environment
  characteristics
• Tuned using one or more MC runs
• Tuning is currently trial-and-error
• Automatic approach to be adopted
• Easy to access and use
• Allows quick forecasts
• Can identify important outliers in DAMAGE runs
• FaDE-? improves information output