Validation of the 4C Code on the AC Loss Tests of a Full-Scale ITER Coil

The AC loss tests on the first ITER Central Solenoid Module (CSM) have been modelled and compared to the test results. The model has been implemented in the 4C code, a thermal-hydraulic modelling tool which includes the CSM winding pack and the cryogenic circuit of the test facility. Two modes of operation of the circuit have been analyzed: the nominal and the “isolation” mode, i.e., when the cryogenic circuit valves are operated to isolate the coil during the current dumps. The computed mass flow rate, pressure and coil outlet temperature at different locations have been compared with the measurements, showing a very good agreement in both modes of operation of the circuit. The validated model helped in the interpretation of the experimental results, such as the backflow at the coil inlet -which cannot be measured- or the non-monotonic outlet temperature evolution following the current dump. Furthermore, the code was used to qualify the isochoric method for the quantification of the deposited energy due to AC losses, as it was the only method applicable in case of current dumps from high current

Analysis of the DC performance of the ITER CSI coil using the 4C code

The DC performance of the ITER Central Solenoid Insert (CSI) coil, a single layer solenoid wound using the same Nb3Sn conductor that will be adopted for the 3L module of ITER CS, was measured during the 2015 test campaign in different magnetic field and current operating conditions, before and after electromagnetic and thermal cycles, as well as before and after quench tests. The 4C thermal-hydraulic code is applied here to the analysis of the CSI performance: first, the free parameters of the model are calibrated; then, the model is validated against measurements not used for its calibration. The model is then used to compute the current sharing temperature, to be compared with the measured jacket temperature, and to assess the performance after quench tests

Effects of RANS-Type turbulence models on the convective heat loss computed by CFD in the solar two power tower

The effect of the choice of Reynolds-Averaged Navier-Stokes (RANS) type turbulence closure on the Computational Fluid Dynamics (CFD) prediction of convective heat losses from the Solar Two central receiver is considered in this paper for a simplified receiver geometry approximated by flat panels. Computed convective losses at steady state are ~ 2-3% (1%) of the total power absorbed by the receiver, at high (low) wind speed, depending on the turbulence model chosen. The simulation results are consistent with those of available correlations for rough cylinders, if the macroscopic roughness due to the panel edges is accounted for, as well as with the low speed experimental results, within the respective error bars

Thermal-Hydraulic Analysis of the EU DEMO Helium-Cooled Pebble Bed Breeding Blanket Using the GETTHEM Code

The general tokamak thermal-hydraulic model (GETTHEM) has been updated to the most recent version of the EU DEMO helium-cooled pebble bed breeding blanket (BB) design. The GETTHEM results are first benchmarked in a controlled case against the results of 3-D computational fluid-dynamics computations, showing an acceptable accuracy despite the inherent simplifications in the GETTHEM model. GETTHEM is then applied to the evaluation of the poloidal hot spot temperature distribution in an entire BB segment, showing that the maximum temperature in the EUROFER structures overcomes the design limit of 550 °C by more than 50 °C in some blanket modules. A possible mitigation strategy is then proposed and analyzed, based on the idea of cooling the first wall in parallel with the breeding zone, showing that this solution would allow having the EUROFER in its working temperature range in the entire segment, although at the expense of a larger pressure drop

Artificial Neural Network (ANN) modeling of the pulsed heat load during ITER CS magnet operation

Artificial Neural Networks (ANNs) are applied to the development of a simplified transient model of the ITER Central Solenoid (CS), aiming at predicting the evolution of the pulsed heat load from the CS to the LHe bath during plasma operation. The ANNs are trained using the thermal–hydraulic evolution in the CS, computed with the 4C code, due to AC losses. The capability of the ANN model to predict the heat load to the LHe bath is successfully demonstrated in the case of different transients, among which a nominal plasma operating scenario. The gain in speed of the simplified model with respect to the 4C code results is by order of magnitudes, with a small loss of accuracy

CFD analysis of natural convection cooling of the in-vessel components during a shutdown of the EU DEMO fusion reactor

In view of the large neutron fluence expected in a fusion power plant, the maintenance of the in-vessel components (IVC) must be carried out using Remote Handling (RH); however, before the RH robots can intervene, the temperature of the IVCs must be reduced, so a cooldown phase is required after the reactor shutdown before maintenance activities can start. In the EU DEMO two options are being investigated to cool down the Breeding Blanket (BB) structures before maintenance, namely introducing fans to pump air in forced convection in the plasma chamber (after opening the Vacuum Vessel), or letting the air at room temperature cool down the structures by natural convection; if the required downtime is acceptable, the second option is clearly preferred, as it would reduce the cost and complexity of the system. This work analyses the natural convection option via a 3D transient Computational Fluid-Dynamics (CFD) conjugate heat transfer model, to evaluate the required time to cool down the BB

SOLPS-ITER simulations of a CPS-based liquid metal divertor for the EU DEMO: Li vs. Sn

In this work, we study the effect of installing a liquid metal divertor (LMD) using a capillary-porous structure in the EU DEMO tokamak within the same envelope of the baseline solid divertor. We used the SOLPS-ITER code to model the Scrape-Off Layer (SOL) plasma and neutrals, coupled to a target thermal model to enable the self-consistent calculation of the LM target erosion rate, and adopting a fluid neutral model for the sake of simplicity. First calculations considering only D and Li (or Sn) showed a significant reduction of the steady state target heat load with respect to simulations considering only D, thanks to vapor shielding. Nevertheless, the computed peak target heat flux (~31 MW/m2 and ~44 MW/m2 for Li and Sn, respectively) was still larger than/borderline to the power handling limit of the LMD concepts considered. Moreover, the impurity concentration in the pedestal - a proxy for the core plasma dilution/contamination - was computed to be above/close to tolerability limits suggested by previous COREDIV calculations. These results indicate that the operational window of an LMD for the EU DEMO, without any additional impurity seeding, might be too narrow, if it exists, and that Sn looks more promising than Li. A second set of calculations was then performed simulating Ar seeding in the SOL, to further reduce the target heat load, and consequently the metal erosion rate. It was found that the mitigation of the plasma heat load due to Ar radiation in the SOL effectively replaces the radiation associated to vapor shielding in front of the target, thus allowing to operate the LMD in a regime of low target erosion. The resulting operational window was found to be significantly wider, both in terms of tolerable peak target heat flux and of acceptable core plasma contamination

Artificial Neural Networks: a viable tool to design heat load smoothing strategies for the ITER Toroidal Field coils

In superconducting tokamaks, cryoplants provide the helium needed to cool the superconducting magnet systems. The evaluation of the heat load from the magnets to the cryoplant is fundamental for the design of the latter and the assessment of suitable strategies to smooth the heat load pulses induced by the pulsed plasma scenarios is crucial for the operation. Here, a simplified thermal-hydraulic model of an ITER Toroidal Field (TF) magnet, based on Artificial Neural Networks (ANNs), is developed and inserted into a detailed model of the ITER TF winding and casing cooling circuits based on the state-of-the-art 4C code, which also includes active controls. The low computational effort requested by such a model allows performing a fast parametric study, to identify the best smoothing strategy during standard plasma operation. The ANNs are trained using 4C simulations, and the predictive capabilities of the simplified model are assessed against 4C simulations, both with and without active smoothing, in terms of accuracy and computational time