Ingress of Coolant Event simulation with TRACE code with accuracy evaluation and coupled DAKOTA Uncertainty Analysis

Preliminary thermal-hydraulic deterministic safety analysis of an in-vessel LOCA for the DTT facility

“…Considering that the plant is currently under design, some data, necessary to develop the model and qualitatively evaluate the results, are not already present in the current collection of data, summarized in the Safety Data List (SADL) [7]. Therefore, in order to develop this preliminary analysis and test the TRACE model, some data have been extrapolated from the existing experimental Integrated ICE facility [4,8], where the in-vessel LOCA has been investigated. The Integrated ICE facility, built at the Japan Atomic Energy Research Institute (JAERI), is used for the characterization of two-phase flow during an Ingress of Coolant Event (ICE) in fusion reactors; in particular, it simulates a plasma facing component tube rupture.…”

“…ICE has a pressure suppression system (Suppression Tank, ST) connected with the VV through a Relief Pipe (RP). The suppression system is activated by a magnetic valve (MV), installed on the RP [8].The Integrated ICE facility is equipped with three injection nozzles, from a boiler to the Plasma Chamber (PC), to simulate the rupture of the coolant piping and the consequent water injection in the PC. The chosen ICE experiment, considered to test the DTT model, is case 4, in which 2 out of 3 nozzles are in function: the main thermal-hydraulic parameters of the test are summarized in Table 1 [8].…”

Cold Leg LBLOCA uncertainty analysis using TRACE/DAKOTA coupling

“…As shown in Figure 4, the RPV collapsed coolant level increases and reach the BAF (Bottom of Active Fuel) after about 50 s after the SOT in the reference calculation, with a time dispersion of around 10 s. During the refill phase the core is mainly uncovered, the heat is not removed from the fuel rod; the cladding temperature rises and reaches the second cladding temperature peak of about 1075 K at around As indicated in [17], for the Spearman coefficient, if the coefficient is higher than 0.5 (or lower than -0.5) the correlation is significant, if it is between 0.2 and 0.5 (or -0.2 and -0.5) the correlation is moderate, otherwise it is low. In this study the same threshold values have been adopted for the Pearson coefficient, as done in [24]. In relation to the hot rod cladding temperature, the peaking factor presents a significant monotonous correlation after the SOT and a moderate monotonous and linear correlation between 25 and 50 s after the SOT.…”

Towards application of uncertainty quantification procedure combined with experimental procedure for assessment of the accuracy of the DEM approach dedicated for granular flow modeling

“…Taking into account the above, the model uncertainty quantification was performed based on the calculated time average velocities of the granular phase in the defined cross-sections of the test rig. Open-source code Dakota [29] was used for the quantity of interest (QOI) analysis. Parameters for the QOI analysis are the previously mentioned material properties, the flow rates of gas particles, velocities, and the mesh resolution used in the CFD-DEM simulations.…”

“…The presented work deals with three aspects; experimental work, numerical model validation, and application of uncertainty quantification for determination of the influence of different uncertainties, which originate from the experimental data and selected mathematical models. The impact of these uncertainties was studied based on sampling points generated by applying the Latin hypercube technique in the Dakota code [29]. Sets of simulations were performed to determine various correlations between the input and output data.…”