Intelligent fuzing for penetrating munitions: experiments and analysis of representative configurations 53 nd Annual Fuze Conference Lake Buena Vista, FL, USA, 19-21 May 2009 Centre d Etudes de Gramat BP 80200 F-46500 GRAMAT Jean-Marc Sibeaud
Area of activity CEG is Technical Center of the French MoD procurement Agency (DGA) Expert center for Terminal effectiveness of Conventional Air-to-Ground weapons and missiles Gives support to program managers for weapons or components development (SCALP/EG missile, AASM PGM, MdCN Navy cruise missile, FBM 21 fuze for air delivered munitions) Provide Armée de l air and Aéronavale (French Air Force and Navy Air Force) with means for determining effectiveness of strikes and perform mission planning Anticipate on threat evolution 19-21 May 2009 Slide N 2
Next generation fuzing will make use of embedded intelligence Hardened targets (Hard target defeat) and soft targets Objective: Improve warhead lethality while minimizing collateral damage Capability to control weapon s depth of burst and eventually full trajectory 19-21 May 2009 Slide N 3
Hard and soft targets defeat: optimal fuze delay depends on target and weapon parameters V Soil Desired depth of weapon detonation Concrete Void D HE D N HE loading CoG Subsoil maximum lethality if point of detonation located at the right place 19-21 May 2009 Slide N 4
Validated analytical and computational tools exist to help predict the fuze delay for a given mission CEG and the French targetting Center operate the CalPen3D analytical program that computes the curvilinear trajectory of the weapon within the target The fuze delay is therefore accessible to the mission planner Z (m) 2 1 0-1 -2-3 -4-5 -6-7 -8 Soil Concrete Concrete -9 Case#1-configuration#1: triaxial nose and tail sensing Case#2-configuration#1: triaxial nose and tail sensing -10-3 -2-1 0 1 2 3 4 5 X (m) 19-21 May 2009 Slide N 5
Hard target defeat: unexpected situations using a constant fuze delay Thicker Concrete slab than expected Reduced lethality 19-21 May 2009 Slide N 6
Smart fuzing The munition analyses its environnement and triggers the HE charge when conditions are met Void sensing Layer counting Trajectory calculation In this latter option, the warfighter specifies the point of detonation instead of a fuze delay High-G sensors, rugged electronics and complex algorithms must be developped and integrated 19-21 May 2009 Slide N 7
An illustration of the possibilities and challenges: perforating of spaced concrete plates with a model scale projectile Prior to testing Post testing T = 0 295 m/s AOI = 0 Finite element simulation T = 10 ms 19-21 May 2009 Slide N 8
Presentation of the EMHAC High-G G recorder and Experimental result Triaxial T2M-Junghans Shock datta recorder Range of data acquisition ± 20 kgs (Channel X1) ; ± 60 kgs (channels X2, Y, Z) Storage duration : unlimited (FLASH memory) Sensors : Endevco Accelerometers Sampling rate : up to 500kHz (4-channel) or 1MHz (2-channels) Memory size : 256 M samples Reusable 30000 EMAHC recovered data 20000 Accéleration (g) 10000 0-10000 -20000 CAPTEUR -30000 0 5 10 15 20 25 Time (ms) 19-21 May 2009 Slide N 9
Axial Velocity (m/s) Double integration of signal 300 290 280 270 260 250 240 230 220 210 200 190 3000 295 m/s 251 m/s 2µs sampling period 229 m/s 203 m/s provides continuous velocity and displacement time histories prior knowledge of initial conditions (velocity) is required Axial Displacement (mm) 2500 2000 1500 1000 500 0 2 µs sampling period Nose position 0 2 4 6 8 10 12 Time (ms) 2500 mm 10.8 ms Smart fuze development would require knowledge of initial conditions (velocity) 19-21 May 2009 Slide N 10 Must be transferred from weapon guidance system
Influence of sampling rate and filtering on velocity 320 300 280 Axial Velocity (m/s) 260 240 220 200 180 160 140 120 2 µs sampling period 2 µs sampling period - filtered 0.2 ms 2 µs sampling period - filtered 0.6 ms 0.01 ms sampling period 0.1 ms sampling period 100 0 2 4 6 8 10 12 Time (ms) Consistent velocity prediction requires minimum sampling rate (at least 100 khz or one sample every 0.01 ms) Filtering of acceleration signal has marginal effect on velocity determination 19-21 May 2009 Slide N 11
Influence of sampling rate and filtering on location 3000 2 µs sampling period Axial Displacement (mm) 2500 2000 1500 1000 500 2 µs sampling period filtered 0.2 ms 2 µs sampling period filtred 0.6 ms 0.01 ms sampling period 0.1 ms sampling period ~ 500 mm error in weapon location (at small scale) using lowest rate sampling 0 0 2 4 6 8 10 12 Time (ms) Prediction of displacement highly affected by sampling rate 19-21 May 2009 Slide N 12
Numerical simulation capabilities in order to better understand process Axial acceleration (1000 G's) 6 4 2 0-2 -4-6 -8-10 -12-14 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Time (ms) Experiment 8049 - SDR Filtered 0.2 ms Calculation - SDR filtered 0.2 ms FE calculation result match reasonnably well data (both filtered similarly) FE prediction need to be improved in order to reduce frequency mismatch (eigen modes of model must be monitored) 19-21 May 2009 Slide N 13
Analytical modeling (CalPen curvilinear calculation of projectile trajectory within the target) 300 Axial Velocity (m/s) 290 280 270 260 250 240 230 220 210 200 190 0 2 4 6 8 10 12 Time (ms) from acceleration filtered - 0.6 ms from acceleration filtered - 0.2 ms From original acceleration sampling Pléiades Axial acceleration (1000 G's) 6 4 2 0-2 -4-6 -8-10 -12-14 Experiment 8049 - SDR Filtered 0.2 ms Calculation - SDR filtered 0.2 ms Pléiades analytical calc. 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Time (ms) 19-21 May 2009 Slide N 14
Next step : analysis of a plane trajectory using experiments at scale 2/3 (see Fuze 52 paper) Pléiades T5-D Exp. T5-D t = 0 ms V = 349 m/s t = 15 ms V = 229 m/s t = 9.4 ms V = 230 m/s Assumption : plane trajectory 1 sensor 1 axis 1 sensor 2 axis (longitudinal (x) and transverse (y) of projectile) 2 sensors 2-axis per sensor 19-21 May 2009 Slide N 15
T5-D D configuration - 2 sensors 2-axis Accélération (1000 Gs) 6 4 2 0-2 -4-6 x-deceleration y-acceleration Y (m) 1 0.5 0-0.5-1 -1.5-2 CalPen Simulation Integrated from 1 point 2-axis sensor -8 0.000 0.005 0.010 0.015 0.020 0.025 Time (s) Single axis sensing performs well provided that initial direction of munition is given If this data is not available integration of x and y strapdown signals provide the expected trajectory and depth. Error appears important because of ricochet of munition on vertical wall cannot be interpreted by a single point sensor -2.5-3 -3.5-4 -4.5 From projectile x-axis only sensor 0 1 2 3 4 X (m) 19-21 May 2009 Slide N 16
6 T5-D D configuration - 1 sensor 1 and 2-axis2 1.0 Accélération (1000 Gs) 4 2 0-2 -4-6 x-deceleration y-acceleration Y (m) 0.5 0.0-0.5-1.0-1.5-2.0 CalPen Simulation 2-sensors 2-axis Angle ( ) -8-50 -55-60 -65-70 -75-80 -85-90 0.000 0.005 0.010 0.015 0.020 0.025 Time (s) CalPen 2-sensor 2-axis Deviation due to out plane excursion Accurate if trajectory is plane -2.5-3.0-3.5-4.0-4.5 0 1 2 3 4 X (m) Angle between projectile and inertial coordinate axis can be calculated and therefore inertial accelerations from which velocity and position are derived 19-21 May 2009 Slide N 17
General case : curvilinear trajectory To be developed and hopefuly presented at the 54 th annual Fuze Conference 19-21 May 2009 Slide N 18
Conclusion Shock data recorder provides invaluable information for penetrator trajectory analysis and identification of challenges posed by smart fuzing for Hard target Penetration applications Three channel Shock data recorder currently investigated Use of multiple miniature G-hardened sensors may allow inertial measurement to be done and therefore a precise determination of the detonation point in the target core 19-21 May 2009 Slide N 19