Reactor power shape synthesis using Group Method of Data Handling

This paper describes the Group Method of Data Handling (GMDH) algorithm to reconstruct 20-node axial core power shapes from five-level in-core detector power measurements. Conventional methods in this field are the parameter identification framework by adopting fixed basis functions and the determination of parameters weighted to each terms of known functions like Fourier series or spline forms. This study proposes GMDH, an evolutionary algorithm, to find the optimal functional form and parameters simultaneously those describe the power distribution accurately. A total of 1060 cases of axially 1-dimensional core power distributions of 20-nodes are generated by 3-dimensional core design code covering beginning-of-life to end-of-life core burnup histories to validate the method. Axially five-point box powers at in-core detector positions are considered as measured snapshots. The reconstructed axial power shapes using GMDH method are compared to the reference power shapes. The results show that the proposed method is very robust and accurate compared with the spline fitting method.