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Simulated Active Control in a VARTM Process Using Induction Heating Richard Johnson and Ranga Pitchumani University of Connecticut Composites Processing.

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Presentation on theme: "Simulated Active Control in a VARTM Process Using Induction Heating Richard Johnson and Ranga Pitchumani University of Connecticut Composites Processing."— Presentation transcript:

1 Simulated Active Control in a VARTM Process Using Induction Heating Richard Johnson and Ranga Pitchumani University of Connecticut Composites Processing Laboratory 191 Auditorium Road, Storrs, CT Presented at the 14 th International Conference on Composite Materials, July 18, 2003, San Diego, CA Sponsors: Office of Naval Research, National Science Foundation

2 Composites Processing Laboratory, University of Connecticut Outline Introduction Experimental setup Numerical modeling Active control –Temperature –Motion Numerical Study Ongoing work

3 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

4 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)

5 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

6 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

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

8 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

9 Composites Processing Laboratory, University of Connecticut Experimental Setup

10 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:

11 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

12 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 Fourier number –mesh Courant numbers

13 Composites Processing Laboratory, University of Connecticut Active Control Temperature Heat the resin to supply aid to flow permeation Fundamental challenge: Limit temperatures so as to not gel the resin during filling Motion The induction coil must be moved so as to heat the appropriate regions Only x and y direction motion are considered

14 Composites Processing Laboratory, University of Connecticut Temperature Control Maximize the coil voltage - achieving the fastest fill times Specified upper bound: 100°C Temperature measurement is difficult Lumped capacitance approach

15 Composites Processing Laboratory, University of Connecticut Motion control y - direction motion Maintain the coil above filled regions Keep the coil just behind the flow front Allows for control where the preform layup is not know a priori x - direction motion Keep the coil behind the location of maximum lag Use delays to avoid potential problems

16 Composites Processing Laboratory, University of Connecticut Numerical Study

17 Composites Processing Laboratory, University of Connecticut Preform Layup: Predetermined Random Coil path corresponds to the low permeability areas Improved uniformity over unheated case

18 Composites Processing Laboratory, University of Connecticut Preform Layup : Side Strip Coil location remains at the right side of the mold Notable improvement in uniformity

19 Composites Processing Laboratory, University of Connecticut Preform Layup: Center Patch Demonstrates a practical application Coil remains centered in the mold Can potentially avoid void entrapment

20 Composites Processing Laboratory, University of Connecticut Preform Layup: Computer Selected Random Shows improved uniformity Coil location follows the lag location

21 Composites Processing Laboratory, University of Connecticut Delay Times Minimum RMS error: 2–10 second delay Physical limitation: coil power up from standby to 200V: 7 sec Recommended delay: 7-10 Seconds

22 Composites Processing Laboratory, University of Connecticut Summary & Ongoing Work Summary –Numerical model of the VARTM process –Induction heating control Ongoing Work –Implement control logic on physical setup –Incorporate resin cure kinetics in the numerical model –Replace upper control bound with a function of the cure kinetics

23 Composites Processing Laboratory, University of Connecticut Questions?


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