Induction Heating of Carbon-Fiber Composites: Thermal Generation Model

Abstract

A theory of local and global mechanisms of heat generation and distribution in carbon-fiber-based composites subjected to an alternating magnetic field has been proposed. A model that predicts the strength and distribution of thermal generation through the thickness of carbon-fiber-based laminated composites has been developed. Earlier work has established the distribution of point voltages in the plane of the laminate that exist in the form of potential differences between fibers in adjacent plies in a cross-ply or angle-ply laminate system. In this work a capacitive-layer microstructure that models the actual fiber-reinforced-polymer microstructure from a square-packing assumption to a series of conductive parallel plates is formulated. An effective parameter of heating, gamma, that establishes the distribution of heating through the thickness is defined. Extreme gradients in this thermal source can exist with peaks occurring at the interfaces of ply-ply orientation changes. An optimization study establishes the effect of various microstructural and macrostructural parameters on the heating parameter, gamma. Several parametric studies are performed on the computer algorithm, which calculates gamma to further analyze these effects.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2000
Accession Number
ADA382423

Entities

People

  • Bruce K. Fink
  • John W. Gillespie Jr.
  • Roy L. Mccullough

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Advanced Electronics
  • Air Platforms
  • Energy and Power Technologies
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Artillery
  • Carbon Fibers
  • Composite Materials
  • Fiber Reinforced Polymers
  • Fibers
  • Geometry
  • Graphitic Materials
  • Induction Heating
  • Laminates
  • Magnetic Fields
  • Materials
  • Materials Laboratories
  • Materials Science
  • Military Research
  • Thickness
  • Three Dimensional
  • Two Dimensional

Readers

  • Computational Modeling and Simulation
  • Pulsed Power and Plasma Physics.
  • Reinforced Composite Materials

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms