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See detailComparison of Several RANS Modelling for the Pavia TRIGA Mark II Research Reactor
Introini, Carolina; Cammi, Antonio; Lorenzi, Stefano et al

in Journal of Nuclear Engineering and Radiation Science (2018)

Aim of this work is the comparison of different turbulent models based on the Reynolds Averaged Navier-Stokes (RANS) equations in order to find out which model is the most suitable for the study of the ... [more ▼]

Aim of this work is the comparison of different turbulent models based on the Reynolds Averaged Navier-Stokes (RANS) equations in order to find out which model is the most suitable for the study of the channel thermal-hydraulics of the TRIGA Mark II reactor. Only the steady state behaviour (i.e. the full power stationary operational conditions) of the reactor has been considered. To this end, the RAS (Reynolds-Averaged Simulation) models available in the open source CFD software OpenFOAM have been applied to the most internal channel of the TRIGA and assessed against a Large Eddy Simulation (LES) model. The results of the latter approach, expressed in terms of axial velocity, turbulent viscosity, turbulent kinetic energy, and temperature have been compared with the results obtained by the RAS models available in OpenFOAM (k − ε, k − ω and Reynolds Stress Transport). Heat transfer is taken into account as well by means of the turbulent energy diffusivity parameter. The simulation results demonstrate how, amongst the RAS models, the k − ω SST is the one whose results are closer to the LES simulation. This model seems to be the best one for the treatment of turbulent flow within the TRIGA subchannel, offering a good compromise between accuracy and computational requirements. Since it is much less expensive than an LES model, it can be applied even to full core calculation, in order to obtain accurate results with less computational effort. [less ▲]

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See detailDevelopment of a Data-Driven Approach based on Kalman filtering for CFD Reactor Analysis
Introini, Carolina; Cammi, Antonio; Lorenzi, Stefano et al

in PHYSOR 2018 (2018)

In the last several years, computer-based simulation has become an important analysis and design tool in many engineering fields. The common practice involves the use of low-fidelity models, which in most ... [more ▼]

In the last several years, computer-based simulation has become an important analysis and design tool in many engineering fields. The common practice involves the use of low-fidelity models, which in most cases are able to provide fairly accurate results while maintaining a low computational cost. However, for complex systems such as nuclear reactors, more detailed models are required for the in-depth analysis of the problem at hand, due for example to the complex geometries of the physical domain. Nevertheless, such models are affected by potentially critical uncertainties and inaccuracies. In this context, the use of data assimilation methods such as the Kalman filter to integrate local experimental data witihin the numerical model looks very promising as a high-fidelity analysis tool. In this work, the focus is the application of such methods to the problem of fluid-dynamics analysis of the reactor. Indeed, in terms of nuclear reactor investigation, a detailed characterization of the coolant behaviour within the reactor core is of manda- tory importance in order to understand, among others, the operating conditions of the system, and the potential occurrence of accident scenarios. In this context, the use of data assimilation methods allows the extraction of information of the thermo-dynamics state of the system in a benchmarked transitory in order to increase the fidelity of the com- putational model. Conversely to the current application of control-oriented black-box in the nuclear energy community, in this work the integration of the data-driven paradigm into the numerical formulation of the CFD problem is proposed. In particular, the al- gorithm outlined embeds the Kalman filter into a segregated predictor-corrector formu- lation, commonly adopted for CFD analysis. Due to the construction of the developed method, one of the main challenges achieved is the preservation of mass-conservation for the thermo-dynamics state during each time instant. As a preliminary verification, the proposed methodology is validated on a benchmark of the lid-driven cavity. The obtained results highlight the efficiency of the proposed method with respect to the state-of-art low fidelity approach. [less ▲]

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See detailA Reduced Order Kalman Filter for Computational Fluid-Dynamics Applications
Introini, Carolina; Cammi, Antonio; Lorenzi, Stefano et al

Poster (2018)

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See detailComparison of Several RANS Modelling for the Pavia TRIGA Mark II Research Reactor
Introini, Carolina; Baroli, Davide UL; Peters, Bernhard UL

Poster (2017)

In this study, a detailed analysis of the turbulent regime within the core of the Pavia TRIGA Mark II reactor is perfomed by means of an in-depth comparison of the RAS (Reynolds-Averaged Simulation ... [more ▼]

In this study, a detailed analysis of the turbulent regime within the core of the Pavia TRIGA Mark II reactor is perfomed by means of an in-depth comparison of the RAS (Reynolds-Averaged Simulation) turbulence models implemented in OpenFOAM. Aim of this analysis is to give some important information with respect to the flow regime within the core. The performance of the various models is tested against a LES (Large Eddy Simulation) of the innermost channel. [less ▲]

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See detailA mass conservative Kalman filter algorithm for thermo-computational fluid dynamics
Introini, Carolina; Baroli, Davide UL; Lorenzi, Stefano et al

in Materials (n.d.)

Computational fluid-dynamics (CFD) is of wide relevance in engineering and science, due to its capability of simulating the three-dimensional flow at various scales. However, the suitability of a given ... [more ▼]

Computational fluid-dynamics (CFD) is of wide relevance in engineering and science, due to its capability of simulating the three-dimensional flow at various scales. However, the suitability of a given model depends on the actual scenarios which are encountered in practice. This challenge of model suitability and calibration could be overcome by a dynamic integration of measured data into the simulation. This paradigm is known as data-driven assimilation (DDA). In this paper, the study is devoted to Kalman filtering, a Bayesian approach, applied to Reynolds-Averaged Navier-Stokes (RANS) equations for turbulent flow. The integration of the Kalman estimator into the PISO segregated scheme was recently investigated by (1). In this work, this approach is extended to the PIMPLE segregated method and to the ther- modynamic analysis of turbulent flow, with the addition of a sub-stepping procedure that ensures mass conservation at each time step and the com- patibility among the unknowns involved. The accuracy of the algorithm is verified with respect to the heated lid-driven cavity benchmark, incorporat- ing also temperature observations, comparing the augmented prediction of the Kalman filter with the CFD solution obtained on a very fine grid. [less ▲]

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