A reduced order model for investigating the dynamics of the Gen-IV LFR coolant pool


Applied Mathematical Modelling, 46, pp. 263-284




S. Lorenzi, A. Cammi, L. Luzzi, and G. Rozza

In the control field, the study of the system dynamics is usually carried out relying on lumped-parameter or one-dimensional modelling. Even if these approaches are well suited for control purposes since they provide fast-running simulations and are easy to linearize, they may not be sufficient to deeply assess the complexity of the systems, in particular where spatial phenomena have a significant impact on dynamics. Reduced Order Methods (ROM) can offer the proper trade-off between computational cost and solution accuracy. In this work, a reduced order model for the spatial description of the Gen-IV LFR coolant pool is developed for the purpose of being employed in a control-oriented plant simulator of the ALFRED reactor. The spatial modelling of the reactor pool is based on the POD-FV-ROM procedure, previously developed with the aim of extending the literature approach based on Finite Element to the Finite Volume approximation of the Navier–Stokes equations, and building a reduced order model capable of handling turbulent flows modelled through the RANS equations. The mentioned approach is employed to build a ROM-based component of the ALFRED simulator for the coolant pool. The possibility of varying the input variables of the model has been also undertaken. In particular, the lead velocity at the Steam Generator outlet has been considered as a parametrized boundary condition since it can be a possible control variable. The results have turned out to be very satisfactory in terms of both accuracy and computational time. As a major outcome of the ROM model, it has been proved that its behaviour is more accurate than a 0D-based model without requiring an excessive computational cost.

title = {A reduced order model for investigating the dynamics of the Gen-IV LFR coolant pool},
journal = {Applied Mathematical Modelling},
volume = {46},
year = {2017},
pages = {263-284},
doi = {10.1016/j.apm.2017.01.066},
author = {Lorenzi, S. and Cammi, A. and Luzzi, L. and Rozza, G.}

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