Resumen
In this research, a two-stage deep convolutional neural network is proposed to predict the off-design performance of a S-CO2 turbine based on field reconstruction. Once the deep model is well-trained, the calculation with graphics processing unit (GPU)-acceleration can quickly predict the physical fields on the blade surface and turbine performance. In practical engineering applications, the proposed method can not only reduce the design cycle of components but also help to grasp the actual operating conditions in real time.