A study of the thermal stress field based on SCNN (structure-controllable neural network)

Thermal stress constitutes a major parameter for monitoring the loss of steam turbine service life. To date, for the real-time calculation of thermal stresses employed in most eases is an analytical method. As the analytical method involves a simplification of the two-dimensional axial-symmetric heat conduction equation for a rotor, it will lead to some emirs in evaluating the thermal stress. In view of this, by way of the intermediate calculation results of a finite element analysis for thermal stress field the authors have utilized a SCNN (structure-controllable neural network) method to simulate the solution of an algebraic equation of integral rigidity matrix for the thermal stress field. By using the displacement of nodes thus obtained, one can identify the thermal stress field of a rotor.