characterization of raw material properties for optimum lcm processing chuck zhang florida advanced...
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Characterization of Raw Material Properties for Optimum LCM
Processing
Chuck Zhang
Florida Advanced Center for Composite Technologies (FAC2T)Florida A&M University-Florida State University
forNSF/DOE/APC Future of Modeling in Composites Molding Processes
June 9, 2004
Common Defects in Liquid Composite Molded Parts
• Dry spots • Dimension variations• Voids and poor wetting
Variations exist in these defectsdue to the variations in raw materials and processing parameters!
Modeling and Simulation Can Help Predict Flow and Dimension
Problems
Flow-induced dryspot Spring-in by residual stress
Effective process modeling and simulation requires accurate raw material properties!
Research Issues
• Statistical characterization of raw materials properties
• Stochastic modeling and analysis of process and defects
• Robust design to improve process reproducibility
Research Challenges
• Accurate estimation of permeability for complex part geometry (modeling)
• In-situ measurement of permeability (experimental)
• Statistical permeability characterization (modeling & experimental)
Gas-assisted, Real-time ASsessment of Permeability (GRASP)
upper mold
fiber preform
Lower mold andpressure sensor array
Inlet and flowmeter Outlet and flowmeter
N2
Resin
Gas
Whole-Field Permeability Estimation with GRASP
Finite element analysis
Fiber preformHigh permeability
Low permeability
Estimated permeabilityMeasured pressure
Computed pressure
Flow validation
Close Loop LCM Operation with Hardware-In-The-Loop Simulation
Preform and mold
N2
In-situ, whole-field permeability
measurement (GRASP)
Flow simulation
LCM process
Process optimization
Hardware-in-the-loop
GA
NN
0 0.2 0.4 0.6 0.8 10
0.2
0.4
0.6
0.8
1300290280270260250240230220210200190180170160
Statistical Characterization of Fiber Permeability with GRASP
Woven Carbon Fabrics
X
Y
0 0.2 0.4 0.6 0.8 10
0.2
0.4
0.6
0.8
1 23992292218520781972186517581651154414371331122411171010903796690583476369
0 0.2 0.4 0.6 0.8 10
0.2
0.4
0.6
0.8
1 9.18E-118.81E-118.45E-118.08E-117.71E-117.34E-116.98E-116.61E-116.24E-115.88E-115.51E-115.14E-114.78E-114.41E-114.04E-113.67E-113.31E-112.94E-11
0
2
4
6
8
10
12
14
3.0E-11 4.0E-11 5.0E-11 6.1E-11 7.1E-11 8.1E-11 6.0E-11
Bin
Freq
uenc
y
Frequency
Standard Dev. = 23.6% of Mean
Pressure Distribution
Estimated Permeability
GRASP may be used to validate permeability estimation model
Statistical Characterization of Permeability
.
.
.
. Racetracking permeability
.
.
.
.
SimulationExperiment
Kg1, Kr1
Kg2, Kr2
Kgn, Krn
Summary
• Variations exist in LCM raw materials and processing parameters and LCM process performance varies due to the variations
• Accurate estimation and statistical characterization of permeability are important to improve LCM part quality and process reproducibility