The Fast Debris Evolution (FaDE) Model H.G. Lewis, G.G. Swinerd, R.J. Newland & A. Saunders Astronautics Research Group School of Engineering Sciences

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders2 Outline Motivation & Aims The FADE-  Model Comparison with Talent’s 1992 PIB Model Results Summary

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders3 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?

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders4 Motivation Evolutionary models typically use Monte Carlo simulation –Many runs required for reliable distributions –Mean and standard deviations usually reported

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders5 Motivation Evolutionary models typically use Monte Carlo simulation –Many runs required for reliable distributions –Mean and standard deviations usually reported

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders6 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

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders7 FaDE Approach Describe debris evolution using an equation of motion/intitial value problem: Estimate values of N for t > 0 using Euler’s method: –Include debris species: Intacts Explosion fragments Collision fragments (# yr -1 )

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders8 FaDE Approach Intacts: Explosion fragments: Collision fragments: (# yr -1 )

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders9 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’

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders10 FaDE: Basic User Interface Control Panel ‘Blurb’ Graphical output Graph options

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders11 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

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders12 FaDE Approach: Collisions Collision probability from DAMAGE

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders13 FaDE Approach: Collisions Collision probability from DAMAGE ‘No new launches after 2000’ (1957 – 2040) R 2 =

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders14 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

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders15 FaDE: Initial Conditions Defined using 60 MC DAMAGE runs of a ‘No new launches after 2000’ (1957 – 2040) scenario ParameterValue Projection period1957 – 2040 No new launches after2000 Time-step5 days Minimum object size10 cm Collision prediction: cube size10 km Collision prediction: active from1957 ExplosionsOnly confirmed explosions of objects launched prior to 2000 allowed

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders16 ‘No new launches after 2000’ (1957 – 2040) –Number of objects  10 cm FaDE: Initial Conditions from DAMAGE

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders17 ‘No new launches after 2000’ (1957 – 2040) –Number of collisions FaDE: Initial Conditions from DAMAGE

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders18 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

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders19 FaDE Testing: Comparison with DAMAGE Two scenarios –‘Business as usual’ (1957 – 2040) ParameterValue Projection period1957 – 2040 Traffic model (2000 – 2040)Based on launch statistics for Future explosions (2000 – 2040)Based on explosion statistics for Time-step5 days Minimum object size10 cm Collision prediction: cube size10 km Collision prediction: active from1957

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders20 FaDE Testing: Comparison with DAMAGE Two scenarios –‘No new launches after 2000’ (1957 – 2200) ParameterValue Projection period1957 – 2200 No new launches after2000 Time-step5 days Minimum object size10 cm Collision prediction: cube size10 km Collision prediction: active from1957 ExplosionsOnly confirmed explosions of objects launched prior to 2000 allowed

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders21 FaDE: Comparison with DAMAGE ‘Business as usual’ (1957 – 2040) –Number of objects  10 cm

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders22 FaDE: Comparison with DAMAGE ‘Business as usual’ (1957 – 2040) –Number of collisions

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders23 FaDE: Comparison with DAMAGE ‘No new launches after 2000’ (1957 – 2200) –Number of objects  10 cm

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders24 FaDE: Comparison with DAMAGE ‘No new launches after 2000’ (1957 – 2200) –Number of collisions

The Fast Debris Evolution (FaDE) Model – Lewis, Swinerd, Newland & Saunders25 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