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