IM Hazards Modeling & Simulation an International Collaboration - - PowerPoint PPT Presentation

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IM Hazards Modeling & Simulation an International Collaboration Abstract Number 22170 Co-author: Steven Collignon NSWC Dahlgren Division Co-author: Thomas Swierk (presenter) Hart Technologies, Inc., 2019 Insensitive Munitions &

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IM Hazards Modeling & Simulation – an International Collaboration

Abstract Number 22170 Co-author: Steven Collignon NSWC Dahlgren Division Co-author: Thomas Swierk (presenter) Hart Technologies, Inc.,

Distribution Statement A: Approved for Public Release unlimited. Distribution unlimited.

2019 Insensitive Munitions & Energetic Materials Technology Symposium Sevilla, Spain 21-24 October 2019

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Contents of Presentation

  • Background

What?

  • Goals and objectives

Why?

  • Focus on propellant types – HPP and

MSP

How?

  • Lab-scale Testing & Model Development
  • Pre-test Predictions for Analog RM Tests

What happened?

  • Conclusions summarized for both nations

What was accomplished?

  • Improved M&S capability applicable for

future weapon development

Who benefits?

  • Principal contributors from each nation

Who did it?

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Distribution Statement A: Approved for Public Release unlimited. Distribution unlimited.

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Background

  • The US DoD and UK MOD both have a requirement to

field weapons systems that are IM compliant.

  • Improved modelling and simulation (M&S) tools will

reduce risk in the acquisition process and help weapon systems meet the IM requirements.

  • An IM Project Arrangement was established.
  • For the US, participants included the Army, Navy and the

DOE/NNSA National Laboratories (LLNL, LANL and SNL), under the auspices of the Joint DoD/DOE Munitions Program.

  • In the UK, participants included Dstl, DOSG, AWE, QinetiQ,

several universities and other government contractors.

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Goals & objectives

The goal was to develop or modify M&S tools and apply them to a technically challenging IM problem useful for future weapon system development and assessment activities.

  • Rocket motors have historically been vulnerable to many of the IM

hazards with solid propellants being particularly vulnerable.

  • M&S tools have been successfully used to examine threats to

explosive-filled munitions, but that capability was seriously lacking when applied to rocket motor propellants.

The objectives of this work were to:

  • Develop M&S tools for system-level IM assessment.
  • Exercise these tools in a joint IM assessment of a weapon system

analog.

  • Demonstrate the ability to integrate validated M&S into system-level

design and quantification.

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Propellant Focus

  • The initial focus for the modeling capability development was a “generic”

high-performance propellant (HPP).

  • Modeling was aimed at determining the propellant response to a fragment

impact threat as described in STANAG 4496.

  • The technical challenge was to develop a predictive capability to determine

the propellant response from the impact of a threat fragment as it traveled through the motor sidewall and into the internal cavity (bore) of the rocket motor.

  • A “generic” minimum signature propellant (MSP) was identified as an

appropriate candidate for additional model improvement.

  • This candidate propellant and the modeling capability that was developed

were the main components of the system-level demonstration.

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Fragment Impact Response of Rocket Motors

Projectile Plexiglas Case Propellant Case Propellant

  • Motors need to pass IM fragment impact requirements
  • Better understanding of motor reaction needed to foster potential

IM improvements

  • Motors containing HD 1.1 propellant can detonate via
  • Shock to Detonation Transition (SDT)
  • Unknown Detonation Transition (XDT)

[More prevalent problem than previously thought]

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Lab-scale test configurations ABVR tests Cylindrical tests

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  • ABVR can replicate the detonative behavior of a full-scale motor
  • SDT threshold differs by <350 ft/s for the fragment velocity.
  • XDT reaction region is the same for thinner web thickness.
  • Thicker web causes some deviation.
  • Insufficient data available to compare non–detonative region.

Conclusions from Sub-scale Testing by AMRDEC *

[ To support Predictive Model Development]

  • Motors can detonate at lower

velocities than what is typically expected.

  • Non-detonative regions may

exist that are bounded by detonative regions at high and low fragment impact velocities.

* “Validation of the Army Burn to Violent Reaction (ABVR) Test as a Tool to Predict Full-Scale Motor Response to Fragment Impact” paper given by Dr. Jamie Neidert, 2018 IMEMTS. 7

UNCLASSIFIED

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Analog Rocket Motor & Test Setup

  • MSP-1 propellant (31.3 lbs.)
  • Web thickness of 2.41 in
  • Oriented vertically – nose down
  • Mirror allowed for internal

viewing of motor

  • Pressure gauges set in circular

patter or 45° offset from shotline

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Predicting XDT in Rocket Motors

Technical Challenge: Determine the role of the propellant debris cloud properties and second wall shock effects when modeling the delayed detonation of an MSP.

  • Problem: Rocket motors with MSP can undergo delayed XDT (detonation) modes at

unacceptably low projectile impact velocities.

  • Hypothesis: Based on the hypothesis that delayed XDT is essentially SDT in a porous

cloud, conduct a range of simulations on the shock compaction of MSP debris clouds.

  • Goals of Study: To examine (1) if initiation occurs in debris cloud and (2) if it

propagates to the rest of debris cloud and/or underlying bulk propellant. Consider a range of debris cloud parameters and projectile speeds.

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XDT Phenomenon

Penetration & Debris Cloud Formation

X X X X X X X X X X

Debris Cloud Compaction- Initiation?

XDT?

Does detonation Propagate in Cloud?

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Approach for Model Predictions

  • Problem: MSP rocket motors undergo XDT at unacceptably

low projectile impact velocities. Validated models don’t exist for predicting XDT & deflagration in projectile impact scenarios.

  • Objective: Develop and validate the LLNL HERMES*

model to predict the impact response of MSP rocket motors from SDT to XDT to deflagration.

  • Benefits: Munition designers can use the HERMES model in

ALE3D to develop new rocket motors and barriers that eliminate susceptibility to XDT.

  • Use the XDT model to aide the design of new sub-scale

experiments that screen new MSP formulations.

  • Develop methodology for XDT modeling that can be applied

to other energetic materials.

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* Reaugh, White, Curtis, Springer (2018), Journal of Propellants, Explosives and Pyrotechnics

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HERMES Model Mechanism

  • Validating modeling capabilities with sub-scale testing resulted in accurate predictions

when extrapolating hazard response to full-scale systems.

  • HERMES model was calibrated to demonstrate model behavior in slab ABVR geometry.

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XDT Reaction – when, where, how ?

It was hypothesized that XDT is essentially SDT in the debris cloud where two things need to happen

  • INITIATION needs to occur in the porous debris cloud that is shock

compacted by the projectile.

  • Most energetic materials show increased shock sensitivity with increasing

porosity and projectile impact velocity.

  • The main reason for suppressing XDT at small gaps was the higher density

debris clouds does not have sufficient porosity to initiate at lower fragment velocities.

  • Detonation needs to PROPAGATE into the rest of the debris cloud or bulk
  • propellant. There isn’t sufficient material in the debris cloud to continue to

propagate detonation.

  • XDT requires INITIATION + PROPAGATION to occur.

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Three parameters drive XDT conditions to create cloud density conditions: bore size, web/slab thickness and projectile velocity.

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Pre-test Model Used For Test Predictions

Setup for large-scale rocket motor analog design in ALE3D Pre-test modeling performed before live full-scale analog rocket motor tests.

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Experiments HERMES Model Deflagration-XDT threshold

Note: Pre-test simulations at nominal, not actual, fragment velocities.

XDT-SDT threshold

HERMES model pre-test simulations of analog rocket motor HERMES simulations demonstrate good agreement for XDT- SDT & XDT-deflagration thresholds.

2400 ft/s: Deflagration 3800 ft/s: XDT 4400 ft/s: SDT

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Accomplishments

MSP Model Development

  • Developed the HERMES model for XDT and implemented in ALE3D.
  • Conducted subscale testing (ABVR & cylindrical tests) to characterize and

collect necessary input data for the model development.

  • Parameterized the HERMES/XDT model for MSP based on material

characterization and subscale test data.

  • Designed and conducted the analog rocket motor tests to enable model validation.
  • 3-D simulations predicted the response of the analog rocket motor prior to the test.
  • Validated the accuracy of the HERMES model with the pre-test predictions of the

analog MSP rocket motor responses.

SDT & XDT reactions were successfully predicted by the US for its MSP variant (MSP-1). SDT reactions were successfully predicted by the UK for its MSP variant (propellant “A”).

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XDT is a prominent detonation mechanism in rocket motors and needs to be mitigated.

  • XDT can be controlled by influencing properties (such as

porosity, flame temperature and particle velocity) of the propellant debris cloud.

  • Potential mitigation strategies:
  • Eliminate cavity – insert material or fill with solid propellant grain.
  • Design cavity to negate hazards associated with a debris cloud.
  • Optimize web thickness or bore size/shape ratio to minimize XDT.

Future Design Considerations

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Rocket motor design improvements should be considered by the development community for new or improved design applications.

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Benefits for future studies

A generalized SDT/XDT experiment was created.

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Benefits for future studies

Conceptual framework describing the XDT phenomenon

(for each fragment/target combination)

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Acknowledgements

US Technical Team

  • Mr. Paul Butler, SNL (retired)
  • Dr. Eric Harstad, SNL
  • Dr. Lara Leininger, LLNL
  • Dr. Eric Mas, LANL
  • Dr. Thomas Mason, LANL
  • Dr. Jamie Neidert, AMRDEC, team lead
  • Dr. Mark Pfeil, AMRDEC
  • Mr. Jack Reaugh, LLNL
  • Dr. Keo Springer, LLNL
  • Ms. Jessica Stanfield, AMRDEC
  • Dr. Bradley White, LLNL

US DOE/JMP Tech Advisors

  • Dr. Dennis Baum
  • Mr. Paul Butler
  • Dr. Eric Brown
  • Dr. Steve DeTeresa
  • Ms. Kelly Rhodes
  • Dr. John Bingert
  • Dr. Chris Cross
  • Dr. Aaron Brundage

UK Technical Team

  • Mr. Philip Cheese, MOD/DOSG
  • Dr. Malcolm Cook, AWE
  • Dr. Ian Cullis, QinetiQ, UK technical

team lead, MOD contract (retired)

  • Dr. Peter Gould, QinetiQ
  • Dr. Alec Milne, Fluid Gravity
  • Dr. William Proud, Imperial College
  • Mr. Thomas Reeves, MOD/DOSG
  • Dr. Michael Sharp, MOD/DOSG
  • Mr. Nathan White, MOD/DOSG
  • Dr. David Williamson, Cambridge

University US Technical Project Officer

  • Mr. Robert Garrett, NSWCDD (retired), 2006-2007
  • Mr. Steven Collignon, NSWCDD, 2008-2018

UK Technical Project Officer Dr./Professor Adam Cumming (retired), MOD/Dstl, 2006-2013

  • Mr. Peter Collins (retired), MOD/Dstl, 2013-2016
  • Mr. Justin Fellows, MOD/Dstl, 2016-2018

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Distribution Statement A: Approved for Public Release unlimited. Distribution unlimited.