Fabrication of Functionally Graded Composite Energetic Materials Using Twin Screw Extrusion Processing Hugh A. Bruck Dept. of Mechanical Engineering University.

Fabrication of Functionally

Graded Composite Energetic

Materials Using Twin Screw Extrusion

ProcessingHugh A. BruckDept. of Mechanical EngineeringUniversity of Maryland

Mitch GallantNSWCIHDIV-Indian Head,MD& Dept. of Mechanical EngineeringUniversity of Maryland

Continuous Mixer & Extruder Users’ Group Meeting

Indian Head, MD

30 October 2002

This work was supported by the Office of Naval Research YIP: Dr. James Short, program manager

Motivation

• Composite Energetic Materials have been traditionally manufactured using batch processing

• New continuous manufacturing technology known as Twin Screw Extrusion (TSE) is being used to produce higher quality composite energetic materials with more flexibility and control

• Current manufacturing of composite energetic materials is focused on homogeneous formulations

• The continuous nature of the TSE process is ideally suited for the manufacture of functionally graded materials

Naval Grand Challenges

• NAVSEA– Missile Defense

• High & Controlled Lethality Warheads• Green Warheads• Long Range• Enhanced Maneuver

– Sixth Generation Energetic Systems• On-the-fly Dial-a-yield Energetics

– Assured Lethality/Effects & Scalable Combat Power• Extended Range guided Munitions• Green Energetics• Increased Range/Standoff

• ONR– Materials by Design

• First principles for the effects of gradient microstructures on material performance• Computational techniques for yielding the processing conditions to fabricate

gradient architectures that optimize system performance

Technical Objective

Tailor Burn Rate Performance in a Monolithic Rocket Motor Utilizing New Design and Control Schemes for Twin Screw Extrusion based on Functionally Graded Material (FGM) Architectures

Propellant Continuously Extruding from Die of TSE FGM Architecture

Research Objectives

1) How do dynamic variations in process conditions and composition during TSE affect the evolution of functionally graded architectures?

2) Can the architectures be predicted by newly-developed residence distribution (RD) models?

3) Can the gradient architectures produced by dynamic processing conditionsbe characterized?

Pelletizer

Twin Screw Extruder

PFT

Solid Ingredient Liquid Ingredient

Loss-in-WeightSolids Feeder

Triple PistonPump

LiquidsHolding Tank

Conveyor

WasteContainer

Twin Screw Extrusion Process

Research Objectives (cont’d)

4) Can the burn rate performance of the gradient architectures be predicted?

5) How can the process and performance models be integrated with optimization methods to determine the appropriate TSE processing conditions to manufacture FGCEMs?

Increasing Distance along Extrudate

Cross-section of Extrudate

Material Variation in TSE Extrudate

Functionally Graded Propellant Concept

Inverse DesignProcedure

Research Approach

Research is being con-ducted at UMD/College Park and NAVSEA-IH through a collaborative research agreement (Center for Energetic Concepts Development)

ComputationalComputationalToolsTools

ManufacturingManufacturingScienceScience

MaterialsCharacterization

Inverse Design Procedure – synergistic integration of component design with fabrication processes for optimizing performance using FGMs

Dynamic Characterization of TSE

Process

0

dt)t(c

)t(c)t(e

Residence Time Distribution:

)vv(a2d

3de)vv(

2

a)v(g

Ca

WHFcosD)1i2(

LA2B

VLAAN

QB

C

3Av

d

cf

pmf

d

v

o

dvvhvvg

vzf

')'()'(

)]([

RVD Model:

Can predict gradient architecture using RVD convolution!

RTD Measurements

Screw Design and Throughput Effects

Screw Design and Temperature Effects

218 C, less retention

177 C, greater retention

10 lb/hr, less retention

5 lb/hr, greater retention

Characterized Effects of Screw Design, Throughput, and Temperature on RTDs for 28 mm TSE

RTD Modeling

Ab

sorb

ance

Pro

be

Time (sec)

Reasonable Unconstrained Fit to Gao RTD Model

dttad ett

atf 2

3

2)(

Gao RTD Model

CQa

WHFcosD)1i2(

LA2B

VLAA

N

B

Q

At

a

3tt

d

cf

pmf

m

md

Td = 0 (a = 3.35 x 10-2/s)

Td = 15.2

Tm = 84.3 (a = 4.34 x 10-2/s)

RTD Modeling (cont’d)

2

)ln()tln(exp

2tP

2

2

Modified Weisstein Model

Ab

sorb

ance

Pro

be

Time (sec)

Better Unconstrained Fit to RTD Data!

= 47.5 s

Gradient Measurements

Graded Polymer

Composites

5 cm

Microstructural Characterization

• Average Individual Particle Size

• Average Particle Size for the Distribution of Particles

• Similar Treatment for Shape Factor Analysis

• Discrete Fast Fourier Transform Analysis of Frequency Variations in Particle Distribution

dd

ddav

2/

0

2/1

2

2sin2

2cos

minmax

2

avavav ddgd )(

max

min

d

ds f fff ssgs )(

1

0

1

0

)(221

21),(1

),(N

x

N

y

yxieyxIN

Discrete 2D FFT

Frequency variation in particle distribution

• Statistically-based combustion model

• Combines Beckstead, Derr, and Price (BDP) model with Glick’s statistical formalism

• Models composite propellant as a random arrangement of polydispersed pseudopropellants

oDd

dddvv

oDd

dddpp

oDd

dd

ood

DdFrR

rR

DdFrR

rR

DdFr

r

DDF

o

o

o

ln1

ln1

ln

ln

lnln

2

1exp

ln2

1

,

,

2

2/1

Polydispersed pseudopropellants

Petite Ensemble Model

Steady–state PEM calculations (w/o

fuel)

p

oignign

oxToxox

oignoxo

oxs

oxox

Tox

oo

Tox

pox

ppox

p

DC

mr

DrfD

h

RT

EAm

D

h

D

hmm

mr

D

1

,

2

/

),,(

exp

133

/

• Use COE to determine Ts,ox from adiabatic flame temperature calculations (PEP, NASA SP-273)

Gradient effects?

Burn rate variation w/ composition

3-D FEA Modeling of Rocket Motor Performance

Transfinite Interpolation Partial Differential Equation

SPP 02 (3-D Euler CFD code)

Graded elements?

Genetic Algorithms (GAs)

Differential Evolution GA

Optimization Methods

Robust Employs evolutionary

principles (mutation, crossover)

Optimal Material Distribution

Optimal Material Distribution

Comparison of Computational Time

Comparison of Computational Time

Inverse Design Procedure for FGCEMs

Conclusions

• A Twin Screw Extrusion (TSE) process is being used to manufacture Functionally Graded Composite Energetic Materials

• Using Residence Distribution (RD) Models, the transient effects of the TSE process on the evolution of functionally graded materials can be characterized by convolving the RD with the transient operating condition

• The modified Weisstein model provides a better fit to the RTD than the Gao model

• Gradient measurements correlated with RD convolution predictions

• A new inverse design procedure is being developed that integrates RD, PEM, and FEA models with GAs for TSE processing of functionally graded composite energetic materials using an inverse design procedure