The Finite Element Analysis Of Heat Transfer In Glass Blowing Forming Process Mold

Temperature is one of the most important study objection for numerical modelingin the glass blowing forming process. It is affect that not only the design of moldstructure, but also the performance and quality of products. With the technique ofnumerical simulation, such as least square method and finite elementmethod(FEM),this paper analyzed the heat conduction of the temperature field inglass forming process and made a computer programming for the inversion of theimportant heat transfer coefficient in the forming process. In this paper, the mainwork and conclusions as follows:1The analysis of foundation model and formula derication. Based on thecharacteristics of the glass, we convert three-dimensional temperature field toaxisymmetric problem, then formula the derivation of energy equation in cylindricalcoordinate. For the validity of the calculation, we choose iteration method to solve theproblem of the boundary conditions; We deduced the FEM fundamental equation inGalerkin method.2Determination of the initial temperature of model and time step. With theconstant time step of model, we can solve the problem that the grid are alwayschanging lead to the computing complexity; Based on the characteristics of melt flowin the cavity, we link a one-dimensional finite element structure in the interface nodeof melt and die wall.3Algorithm establishing. Based on the Taylor formula and differencemethod,we solved the problem that the coefficient of heat transfer can not bedescribed in explicit expression.With the method of least square, we solve thecontradictory linear equations and get the approximate solution.4Programming and result analysis. We programming the algorithm of heattransfer coefficient inversion in the platform of Visual C++. Then we run program tocalculate and reduce the error step by step. At last, we get the satisfactory conclusion.We analysis the influence of heat transfer coefficient to temperature in the method offorward modeling; we get the value of transfer coefficient with the actual measured value; at last, we discussed the influence of weighting and different difference count.