DEBRIS REMOVAL DESIGN DRIVERS BASED ON TARGET SELECTION 2 nd European Workshop on Active Debris Removal CNES HQ, Paris, 18 th - 19 th July 2012 Adam White:

DEBRIS REMOVAL DESIGN DRIVERS BASED ON TARGET

SELECTION

2nd European Workshop on Active Debris Removal

CNES HQ, Paris, 18th- 19th July 2012

Adam White: [email protected] Lewis: [email protected]

University of Southampton

Hedley Stokes: [email protected] Space Ltd.

• It is probable that the space debris population will continue to grow even with a good compliance of commonly adopted mitigation measures

• This growth will be driven predominately by catastrophic collisions in Low Earth Orbit (LEO)

• Studies shave shown that Active Debris Removal (ADR) can potentially be an effective measure in reducing the population of space debris in the long-term

• An important challenge associated with ADR is the choice of targets to be removed

• The aim of this study is to investigate the effectiveness of ADR when targets are constrained to orbital regimes and object types

• The work presented is part of the Alignment of Capability and Capacity for the Objective of Reducing Debris (ACCORD) project

Introduction

ACCORD Project

• Survey the capability of industry to implement debris mitigation measures

• Review the capacity of mitigation measures to reduce debris creation

Investigate measures to reduce space debris including ADR scenarios

• Combine capability and capacity indicators within an environmental impact ratings system

Alignment of Capability and Capacity for the Objective of

Reducing Debris http://www.fp7-accord.eu/

Aim: To communicate the efficiency of current debris mitigation practices and to identify opportunities for strengthening European capability

European Commission FP7

ADR Target Selection

The top 567 ADR targets orbit parameters for one Monte Carlo (MC) simulation using the Debris Analysis and Monitoring Architecture to the Geosynchronous Environment (DAMAGE) model. Based on Equation (1)

Top ADR Targets (1)

The top 567 ADR targets orbit parameters for one Monte Carlo (MC) simulation using the Debris Analysis and Monitoring Architecture to the Geosynchronous Environment (DAMAGE) model. Based on Equation (1)

Top ADR Targets (1)

1

2

34 5

4

1

2

35

Top ADR Targets (2)

• DAMAGE was used to quantify the effect of removing target objects on a yearly basis from these clusters

• Spacecraft (S/C) and rocket bodies (R/B) debris were assigned to a cluster (1-5), c, based on their Euclidean distance from a user-defined location (in the inclination-altitude parameter space)

• A cluster selection value, Qc , is assigned to each cluster:

(2)

– where n is the number of objects in the cluster

• DAMAGE simulated removals from the cluster having the highest Qc value

Methodology

Study Scenarios

Scenario

Target selection criterion

Object type/s removed

1 No remediation -

2Removal from cluster

based on Eqn. (2) R/B

3Removal from cluster

based on Eqn. (2) S/C

4Removal from cluster

based on Eqn. (2) R/B + S/C

5Removal based on Eqn.

(1) R/B + S/C

Study Parameters

• Projection period: 2009 - 2209

• Initial population: Meteoroid and Space Debris Terrestrial Environment Reference (MASTER) 2009 (1st May 2009 epoch)

• Objects: 10 cm, orbits intersecting LEO

• Launch traffic: 8-year cycle (2001-2009) from MASTER 2009

• Mitigation: passivation (100%), post-mission disposal (90%) following IADC mitigation guidelines

• Remediation: three removals a year (2020-2209), perigee altitude < 1400 km and eccentricity < 0.5

• Time-step: 5 days

• Number of Monte Carlos (MC) per scenario: 100

Average LEO population

Summary of Results

Scenario 1 2 3 4 5

Number of objects ≥10 cm

20579 (3383)

16563 (3118)

17293 (2634)

16480 (2477)

16499 (2152)

% MC below initial population

15 61 48 63 62

Number of damaging collisions

24.8 (6.8)15.2 (4.5)

16.4 (4.7)

14.3 (4.2)

14.2 (4.4)

Number of catastrophic

collisions36.8 (7.7)

27.3 (6.9)

29.5 (6.5)

28.2 (5.7)

27.9 (5.8)

ERF Values

Scenario 1 2 3 4 5

Effective Reduction Factor (ERF)

- 7.08 5.79 7.23 7.20

ERF(Damaging collisions)

- 0.017 0.015 0.018 0.019

ERF(catastrophic

collisions)- 0.017 0.013 0.015 0.016

ratio - - - 1.21 1.07

Cluster Selection

57, 538 km

64, 804 km 72.5, 580

km

83, 720 km

99, 692 km

Conclusions & ADR Impacts• Constraining removals to particular orbital regimes does not

appear to compromise the effectiveness of ADR in LEO

– ADR vehicles designed to remove multiple objects from a particular orbital regime will have reduced transfer energy requirements

• Constraining removals to particular orbital regimes leads to the majority of removals from ~83 (mostly R/Bs) and ~99 (mostly S/C) inclination orbits

– ADR vehicle designs can be tailored to specific target types and orbital regimes

• Removing only R/Bs appears to be as effective as removals targeting both R/Bs and S/C

– ADR vehicles can be targeted at R/Bs, which have common geometrical properties, grappling points etc., resulting in simpler, repeatable designs

Thank you

Adam E. [email protected]

Financial support for this work was provided the EU Framework 7 Programme (ACCORD Project, No. 262824). The authors would like to thank Holger Krag and Heiner Klinkrad

(ESA ESOC) for permission to use the MASTER population data.