References of "Cammi, Antonio"
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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 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 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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