Modeling Fragmentation Performance of Insensitive Explosive Fragmentation Munitions

Transcription

1 2009 Insensitive Munitions and Energetic Materials Technology Symposium, Tucson, Arizona May 2009 Modeling Fragmentation Performance of Insensitive Explosive Fragmentation Munitions V. M. Gold and Y. Wu U.S. Army RDECOM-ARDEC Picatinny, New Jersey

2 Acknowledgments US Army ARDEC: Dr. E. L. Baker Mr. A. J. Mock Mr. W. J. Poulos Mr. W. Ramos Mr. P. J. Samuels Mr. L. Sotsky Mr. T. Wu Polytechnic Institute of New York: Professor L. I. Stiel

3 Outline Introduction: Overview of the PAFRAG (Picatinny Arsenal FRAGmentation) Modeling Methodology Modeling Fragmentation Performance of Insensitive Explosive Fragmentation Munitions Summary

4 PAFRAG Modeling Methodology Expensive Fragmentation Arena Testing Z-data CALE PAFRAG CASRED/ALGRID PAFRAG Modeling Lethality Modeling Inexpensive CALE Dynamic high-strain high strain rate continuum analyses PAFRAG Picatinny Arsenal Fragmentation code Fragmentation modeling CASRED/ALGRID Lethality Codes Model the effectiveness of the munition

5 Natural Fragmentation: PAFRAG-MOTT Model Based on Mott s s theory of break-up of cylindrical ring-bombs Stress Release Wave Fracture Average circumferential fragment length: B 1 A 1 A 1 B 1 Region Under Plastic Expansion x 0 2PF 1/ 2 r V Average fragment mass: Region Stress Relieved B 2 1 x A 2 A 2 B 2 is a statistical parameter and can be determined from fragmentation test data Fragment size distribution: N m N 0 e 1/ 2 m

6 PAFRAG Experimentation Fragment velocities Surface cracking N R =N R (m) Flash Radiography Orthogonal X-rays Celotex Rear Fragment Recovery High Speed Photography N=N(m) Sawdust Fragment Recovery gives Final munitions require arena testing PAFRAG experimentation is adjusted according to specific project/customer needs

7 V/V 0 vs Time and High Speed Photography Detonation products break through and appear on the surface 10 V/V Axial cracking starts V/V 0 =6.2 Average Fragmentation Time 3 V/V 0 = V/V 0 = Time, sec

8 PAFRAG Modeling Methodology for Lethality Assessments R Hardened steel shell Steel fragments R Explosive PAFRAG modeling and experimentation v z CALE Predicts mass and velocity flow field Z-data z 1500 PAFRAG Number of fragments, N Number of fragments Predicts Lethality Fragment mass m, grams , degrees Sawdust fragment recovery test data Predicts number of fragment distributions

9 CALE-PAFRAG Modeling Given: Fragmentation performance of Charge A Find: Fragmentation performance of Charge B Charge A Explosive Fuze R v z Charge A Fragmenting Shell Steel Fragments V/V 0 =3, t=49sec Charge B Booster Charge B Main Charge Fuze Nose Front Mount and Front Retainer V/V 0 =3, t=40sec

10 Cumulative number of fragments versus fragment mass, Charge A Number of fragments, N/N PAX % 9% COMP-B, Arena Test Data, Average COMP-B, Sawdust Test Data, 346 COMP-B, Sawdust Test Data, 347 COMP-B, PAFRAG Analyses fitted to test data, =54.4 HBU-88B, PAFRAG Analyses fitted to test data, =51.0 PAX-25, PAFRAG Analyses fitted to test data, =40.0 Comp-B decreases with brisance decreases HBU-88B Fragment mass m, grains

11 Parameter versus explosive detonation Chapman-Jouguet (CJ) pressure (P 45 CJ ) assumed 40 Charge A, PAFRAG Analyses fitted to data Charge A, =(P CJ ) Comp-B, =55.85 Charge B, PAFRAG Analyses fitted to data Charge B, assumed =(P CJ ) PBXN-9 Charge B, estimated PAX-3,=55.65 TNT, =44.88 Comp-B GUDN/TNT (45/55)=44.38 IMX-101, =44.03 PAX-25 from test data HBU P CJ, GPa

12 Cumulative number of fragments versus fragment mass, Charge B Cumulative number of fragments, N/N TNT PBXN-9, Arena Test Data, Average PBXN-9, PAFRAG Analyses fitted to test data, =56.0 Comp-B, PAFRAG Analyses, =55.85 PAX-3, PAFRAG Analyses, =55.65 TNT, PAFRAG Analyses, =44.88 GUDN/TNT (45/55), PAFRAG Analyses, =44.38 IMX-101, PAFRAG Analyses, =44.03 PBXN-9 IMX-101 Comp-B PAX-3 GUDN/TNT (45/55) Fragment mass m, grains P CJ decreases, decreases, fragmentation performance degrades

13 Fragment velocities versus theta for varying explosive compositions, Charge B PBXN-9, Arena Test Data PBXN-9, PAFRAG Analyses, Cell Data, t=40sec, V/V 0 =3 PBXN-9, PAFRAG Analyses, Momentum Average, t=40sec, V/V 0 =3 Comp-B, PAFRAG Analyses, Momentum Average, t=45sec, V/V 0 =3 PAX-3, PAFRAG Analyses, Momentum Average, t=48sec, V/V 0 =3 TNT, PAFRAG Analyses, Momentum Average, t=52sec, V/V =3 GUDN/TNT (45/55), PAFRAG Analyses, Momentum Average, t=49sec, V/V 0 =3 IMX-101, PAFRAG Analyses, Momentum Average, t=52sec, V/V 0 = Velocity, V, cm/sec Fragment velocities decrease, degrees

14 Summary New modeling methodology for assessing performance of IM munitions developed Employing IM explosives with low brisance properties and low Chapman-Jouguet (CJ) pressures leads to decreases in the fragment numbers and velocities Based on the experimental data available to-date, an approximately linear relationship between the -parameter and the Chapman-Jouguet (CJ) detonation pressures is observed To maintain lethality requirements, explosive fragmentation munitions with IM formulations requires employing high fragmentation steel alloys, or controlled/preformed fragmentation techniques, or a combination of thereof

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16 Back-up slides