INTERCEPTION DEBRIS – FROM INITIALS TO FULL SIGNATURE

1. 1st Annual Israel Multinational BMD Conference & Exhibition INTERCEPTION DEBRIS – FROM INITIALS TO FULL SIGNATURE Presented By: Mr. J. Yifat WALES, Ltd., Israel

2. PRESENTATION TOPICS • Introduction • Debris Model Overview • Calculation of Debris Parameters Distributions • Example of Debris Model Result • Summary

3. INTRODUCTION • Pre and post intercept debris are becoming an issue of main concern since they might have severe impact on multiple aspects of BMD • Debris clouds are generated in various events

4. INTRODUCTION (Cont.) • In order to assess the impact of debris on BMD elements and analyze possible solutions, a thorough understanding of debris cloud characteristics is required: • Debris physical parameters distributions according to the specific debris generating event • Debris cloud dynamics • Sensor sky picture in presence of the debris • Debris physics is very complex with many uncertainties and is usually referred to as an “order of magnitude” problem

5. INTRODUCTION (Cont.) • The goal of this study was to develop an integrated debris model that simulates debris clouds for various debris generating events and scenarios • A new, comprehensive debris model was developed, based on data from open literature • The model provides order of magnitude estimations of debris cloud characteristics and distributions that fit open source empirical data and hydrocode simulations

6. DEBRIS MODEL OVERVIEW • The model currently incorporates the following sub-models (each of these models or combination of them is used in its relevant debris generating event): • NASA’s EVOLVE model: based on various empirical data of satellites breakups, interceptions, explosions and hypervelocity impact experiments (Solwind, SOCIT, etc.) • NASA’s FASTT model: based on physical conservation equations and empirical data of satellite breakups • Mott & Gurney equations for distributions of explosion debris • WALES Debris RCS Signature model • Physical Conservation Equations (mass & momentum)

7. DEBRIS MODEL OVERVIEW (Cont.) • The Integrated Debris Model: • Enables quick generation of random realizations of debris clouds for many debris generating events • Can be updated according to future empirical data (i.e. TBM interception tests) • Can be used in sensor and architecture studies in order to fully understand the impact of debris on the various BMD elements and come up with possible algorithms and solutions to the debris problem HE System Level Analysis Tools

8. DEBRIS MODEL OVERVIEW (Cont.) • The new debris model is relevant for most debris generating events • The model calculates the following physical properties for the entire debris cloud (later used in dynamic simulation): • Mass • Diameter (defined as fragment’s longest dimension) • Δ Velocity • Ballistic Coefficient • RCS Distribution

9. DEBRIS DISTRIBUTIONS CALCULATION Collision Explosion Diameter Distribution Area to Mass Distribution EVOLVE Model FASTT Model Mass Distribution Mott Equations Gurney Equations RCS Model Δ Velocity Distribution Ballistic Coefficient Distribution All distributions fit available empirical data RCS Signature

10. EXPLOSION DEBRIS MASS DISTRIBUTION CALCULATION • In case of debris caused by explosion (HE initiation), the fragments mass distribution is calibrated such that the number of small fragments (belongs mostly to the metal surrounding the HE) would agree with Mott equations, which are verified according to numerous HE terrestrial experiments: f (m) Mott EVOLVE EVOLVE - Calibrated m

11. Gurney EVOLVE DEBRIS Δ VELOCITY DISTRIBUTION CALCULATION • In the cases of explosions, the velocities of fragments from the areas surrounding the HE (most of the small fragments) are derived from the Gurney equations for explosion fragmentations: • NASA’s empirical model is used for the remaining fragments • A transition function is used to integrate both models HE

12. DEBRIS Δ VELOCITY DISTRIBUTION CALCULATION (Cont.) • Velocities created by the model (stochastic) are added to the center of mass velocity (target and interceptor) • On average, smaller fragments receive higher added velocities and show much wider spread than larger and heavier fragments • To guarantee conservation of momentum, a random unified distribution over a spherical surface (Isotropic) was used for velocities directions Center of Mass Velocity

13. RCS DISTRIBUTION CALCULATION • RCS assessment of debris was performed using a set of representative debris shapes and sizes • Swerling distribution fitted for each examined shape and size • Average projected area defines RCS distribution parameters for each fragment in integrated debris model Radar A Radar B

14. EXAMPLE OF MODEL RESULT – DEBRIS CLOUD SIMULATION BASED ON GENERIC TARGET AND INTERCEPTOR Generic HE RV, HTK Interception

15. INSIGHTS FROM MODEL RESULTS • Fragments Mass, Length and Velocity show spread up to an order of magnitude - fits empirical findings • A few large and heavy fragments are produced • Interceptions that involve HE explosions produce less debris, since part of RV mass is HE which is converted to energy and gas • Hypervelocity collisions (HTK) produce fragments with higher velocities than explosions (confirmed in ground experiments)

16. SUMMARY • Various debris models, based on numerous empirical findings and physical equations were updated, calibrated and gathered under one integrated debris model • The model can be used to produce reasonable realizations of debris clouds from various debris generating scenarios • Debris distributions produced by the model agree with empirical data, hydrocode simulations and classic fragmentation models • An example of debris cloud realization for a generic interception event was presented • Debris model shows great potential for contributing to BMD system level analyses