Application of stochastic method for solving inverse heat conduction problems

A Kalman filter method in conjunction with the control volume methodology is adopted as a numerical tool for solving two-dimensional inverse heat conduction problems. The noise of the measurement data and process is considered in this work. One of the main objectives of this work is to study the influence on the inverse solution of the initial values of the covariance matrices Numerical examples are given to illustrate the efficiency of the proposed method for solving inverse heat conduction problems. The state variable (nodal temperatures) and the errors of the estimate are calculated. The accuracy of the numerical solution for the inverse problem is examined by comparing the results with the direct solution of the problem.