Induction Heating Assisted Permeation Enhancement for the VARTM Process Richard Johnson and Ranga Pitchumani University of Connecticut Composites Processing.

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Induction Heating Assisted Permeation Enhancement for the VARTM Process Richard Johnson and Ranga Pitchumani University of Connecticut Composites Processing Laboratory 191 Auditorium Road, Storrs, CT Sponsors: NSF(CTS ), AFOSR(f ) Presented at the International SAMPE Technical Conference. Nov. 5th Baltimore, MD

Composites Processing Laboratory, University of Connecticut Outline Introduction to VARTM –Process description –Controlling the mold filling stage Numerical Modeling –Nonisothermal mold filling with induction heating Experimental Setup Model Validation Results Questions

Composites Processing Laboratory, University of Connecticut Process Description Vacuum Assisted Resin Transfer Molding (VARTM) Preform permeation is a critical step –voids and dry spots = poor part quality

Composites Processing Laboratory, University of Connecticut Process Difficulties - Filling Variation in preform permeability from that predicted by theory leads to non-uniform fill –uncertainty in pore structure –heterogeneous preform layups –race tracking Need for flow control

Composites Processing Laboratory, University of Connecticut Control Boundary control methods show reduced controllability further from the controlled boundary Need for more localized control D. Nielsen, R. Pitchumani (COMPOS PART A-APPL S: 2001) (COMPOS SCI TECHNOL: 2002) (POLYM COMPOSITE: 2002)

Composites Processing Laboratory, University of Connecticut Line Vacuum Low Permeability Patch Line Source Mold Fill - Heterogeneous Preform Layup Heterogeneous layups can lead to dry spots Proposed control scheme: Active localized heating

Composites Processing Laboratory, University of Connecticut Mold Fill with Heating Low Permeability Patch Uniformly Heated to  60C Line Source Line Vacuum Addition of heat to the low permeability area –improved uniformity –elimination of voids and dry spots

Composites Processing Laboratory, University of Connecticut Heating Methods Resistive –contact required Ultrasonic –contact required –possibility of ultrasonic horn melting vacuum bags Induction –compact, mobile heating unit –requires susceptors Laser –requires fast scanning of intentionally defocused beam

Composites Processing Laboratory, University of Connecticut Numerical Modeling - Induction Heating Induction power calculation –current conservation at the nodes of the susceptor mesh –summation of voltages in a loop = emf Induction coil geometry emf i I1I1 I2I2 I3I3 I4I4

Composites Processing Laboratory, University of Connecticut Numerical Modeling - Flow Flow governed by Darcy’s law: Pressure distribution: –five-point Laplacian scheme –Darcy’s law used to find velocities –volume tracking method used to find the flow front locations BC’s –Walls impenetrable with no slip –vacuum line defined with negative pressure –inlet defined by atmospheric pressure at the surface of the source container Permeability –Carman-Kozeny relationship: –C z values from literature:

Composites Processing Laboratory, University of Connecticut Numerical Modeling - Heat Transfer Energy equation: 3-D control volume analysis and ADI method (Douglas and Gunn: 1964) BC’s –mold sides considered adiabatic –top surface of the vacuum bag and bottom surface of the mold considered convective –inlet and outlet at ambient temperature

Composites Processing Laboratory, University of Connecticut Numerical Modeling Coupled by viscosity –Arrhenius equation: –flow is dependent on temperature through viscosity –temperature is dependent on the flow Iterative solution –convergence based on temperature: Time step varied –mesh Courant number –mesh Fourier numbers

Composites Processing Laboratory, University of Connecticut Experimental Setup

Composites Processing Laboratory, University of Connecticut Model Validation P = -77 kPa No Heating Vacuum Level: 77kPa Coil Voltage: 125V Coil Position: 5.08cm Vacuum Level: 77kPa Coil Voltage: 140V Coil Position: 15.24cm

Composites Processing Laboratory, University of Connecticut Numerical Study Parametric study –varied parameters induction coil location –(stationary in each simulation) induction coil voltage vacuum level permeability ratio

Composites Processing Laboratory, University of Connecticut Results - Upper Bound Definition of maximum and quasi-steady-state temperature If the maximum allowed temperature is 100 o C then V max = 85V

Composites Processing Laboratory, University of Connecticut Results - Lower Bound Coil location: cm Vacuum level: -77 kPa Coil location: 5.08 cm Vacuum level: -77kPa

Composites Processing Laboratory, University of Connecticut Results - Central Patch  vacuum level  higher allowable voltages Coil locations closer to the inlet –upper bound  higher allowable voltages –lower bound increases sharply with permeability ratio 5.08 cm cm cm

Composites Processing Laboratory, University of Connecticut Results - Central Patch with Race Tracking Comparison to non-race tracking cases –similar upper bound –more restrictive lower bound lower permeability ratios requiring heating higher required voltages at the same permeability ratio 5.08 cm cm cm

Composites Processing Laboratory, University of Connecticut Numerical Study Parametric study varied parameters –permeability ratio –induction voltage –coil position Merit function

Composites Processing Laboratory, University of Connecticut Results - Side by Side Ideal coil location and RMS error Ideal coil location and quasi- steady state temperature

Composites Processing Laboratory, University of Connecticut Summary Description of the VARTM process Numerical model for non-isothermal flow in VARTM with induction heating Experimental setup Parametric studies –two preform layups –varied parameters: induction coil location vacuum level induction coil voltage permeability ratio –processing windows Current work: active control

Composites Processing Laboratory, University of Connecticut Questions ?