APPLICATION OF IMPROVED GENETIC ALGORITHM TO SOLVING INVERSE HEAT CONDUCTION PROBLEMS

The inverse problem of estimating the heat transfer coefficient and surface temperature is formulated. An algorithm is proposed based on the minimization of the least-square errors between the measured temperatures and calculated temperatures by the finite element model. The solution is sought by genetic algorithm which is able to search for optimal solution. To speed up the convergence rate and enhance inversion precision, the real genetic algorithm is applied. Numerical results show that the strategy developed in the paper is capable of dealing with both unknown heat transfer coefficient and unknown surface temperature, and has the ability to suppress measurement noise.