fabrication of functionally graded composite energetic materials using twin screw extrusion...
TRANSCRIPT
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