Prediction Of Fuel Temperature Research Articles

A hybrid machine learning approach for improving fuel temperature prediction of research reactors under mix convection regime

Benchmarking results from experiments on research reactors showed that power reactors’ mathematical model produced conservative results in predicting the maximum cladding temperature on hot channels, with the mean difference showing overestimation. This overestimation is an accuracy issue arising from: the rigid demand and requirement for highly specialized expertise needed for input preparation of large and complex mathematical models in a computer program, the simplification and assumptions when translating physical phenomena into mathematical models, the complexity of the cooling regime, and the specific characteristics of research reactors. This paper aims to overcome the accuracy issue using a hybrid method that combines mathematical models, machine learning, and experimental results. Machine learning compensates for the bias between experimental results and mathematical models and discovers the factors affecting the mismatch. Our experimental results indicated that the proposed hybrid method has significantly better accuracy than the power reactors’ mathematical model and can discover the affecting factors.

Experimental investigation on the thermohydraulic parameters of Kartini research reactor under variation of the primary pump flow

An experimental investigation on the thermohydraulic parameters of the Kartini research reactor by varying the primary pump flow has been conducted to study the behavior of fuel and coolant temperatures and heat transfer. The variation of the primary pump flow was physically simulated by gradually reducing the pump rotation while keeping the reactor power at maximum. An experimental tool equipped with seven thermocouple sensors and a Data Acquisition System was inserted into the hottest channel of the reactor core to obtain accurate data of the coolant temperature in the reactor core. This paper presents detailed results and analysis of the investigation. The main result is a unique pattern arising from the fuel and coolant temperature data, which allows us to identify three stages: flow-dominated, chaotic or transition, and natural circulation stages. Based on the difference between the temperature prediction and experimental results, we develop a novel correction factor to quantify the influence of the variation of the primary pump flow on fuel temperature prediction.

Burn-Up Dependent Modelling of Fuel-To-Clad Gap Conductance and Temperature Predictions for Mixed-Oxide Fuel in the ESFR-SMART Core

Abstract Accurate coupled neutronic-thermal-hydraulic analysis of SFRs requires an accurate calculation of the fuel-to-clad gap conductance. In this paper, the gap conductance of the ESFR-SMART MOX pins is investigated through modelling in seven independent fuel performance codes, to provide confidence in results and understand the uncertainties associated with the predictions. This paper presents a comparison of the conductance and predicted fuel temperature distribution between codes. The values produced from the codes are then combined to produce a best-estimate prediction of the gap conductance expressed as a function of nodal fuel rating and burn-up for all seven codes. A fit was applied to the data thus obtained. The spread between results is such that, to 95% confidence, conductance predictions may vary from the correlation by up to a factor of ~4. The gap conductance results show a general increase of conductance with fuel rating and burn-up, from 0.22 at 0 burn-up and 10 kW.m^(-1) to 0.45 at 0 burn-up and 50 kW.m^(-1) and to 1.00 W.?cm?^(-2).K^(-1) at 150 GWd.t^(-1) and 50 kW.m^(-1). Some spread between codes has been noted and appears to be consistent with the spread previously published. There is good agreement between codes at low burn-up for fuel temperature predictions. The spread between codes increases with burn-up due to multiple phenomena including JOG formation and clad swelling.

IMPLEMENTATION AND VALIDATION OF A FISSION GAS RELEASE MODEL FOR CTFFUEL USING THE NEA/OECD IFPE DATABASE

The nuclear reactors themselves are complex systems whose responses are driven by interactions between different physics phenomena within the reactor core. Traditionally, the different physics phenomena have been analyzed separately and its interaction considered via boundary conditions or closure models. However, in parallel with the development of computational technology, multi-physics coupled simulations are being used to obtain accurate predictions thanks to the consideration of the feedback effects on the fly (on-line). In the nuclear systems the fuel temperature is an important feedback parameter used to obtain the nuclear cross sections at given conditions by the neutron kinetics codes. An accurate prediction of temperature profile within the fuel rod involve several physics such as neutron kinetics, mechanics, material behavior and properties, heat transfer, thermal-hydraulics, and even chemistry. The pellet to clad gap conductance is possibly the most important source of uncertainty in the solution of conductivity equation in the fuel rod and the fuel temperature prediction. The gap conductance depends on two effects: the pellet to gap distance and the conductivity of the gas species that fill the gap. In this research work, the authors are focused on improving of the prediction of the gap gas conductivity in CTFFuel by implementing a fission gas release model in the code. The objective of this contribution is the implementation of a transient fission gas release model in CTFFuel and its validation using the experimental data available in the OECD/NEA International Fuel Performance Experiments (IFPE) database. CTFFuel is an isolated fuel heat transfer capability within the framework of CTF code, the state-of-the-art version of the Coolant Boiling in Rod Arrays Code – Two-Fluid (COBRA-TF) sub-channel thermal-hydraulic code. The code is being jointly developed by North Carolina State University (NCSU) and Oak Ridge National Laboratory (ORNL) within the US Department of Energy (DOE) Consortium for Advanced Simulation of LWRs (CASL).

Modeling of gap conductance for LWR fuel rods applied in the BISON code

ABSTRACT A new gap conductance model is proposed in this study as a combination of Toptan’s model and the Ross-Stoute model. A variance-based sensitivity analysis is performed to understand how simulation results depend on all input parameters of the proposed model. Additionally, new modeling options (e.g. fill gas thermal conductivity, temperature jump distance, thermal accommodation coefficient, etc.) are added into the nuclear fuel performance code, BISON. The need for further investigation of the gap heat transfer between fuel and cladding in BISON motivated this study to evaluate its impact on the code’s predictions. New gap conductance modeling is proposed. A series of integral-effects validation tests is performed: (1) to demonstrate the impact of the proposed model on the code’s fuel temperature predictions at the beginning of life and through the reactor’s life; (2) to ensure that the proposed model is capable of accurately modeling gap heat transfer characteristics in real-world problems; and (3) to investigate the impact of the estimation of fission gas release on the fuel temperature predictions with the proposed model. The results indicate that the proposed gap conductance model improves BISON’s predictions.

Computational investigation into heat transfer coefficients of randomly packed pebbles in flowing FLiBe

Using CFD simulations, this study presents: (1) LES and RANS comparisons for a unit cell geometry of heat transferring pebbles in flowing FLiBe; (2) statistical distributions of pebble heat transfer coefficients due to the random packing; (3) development of a heat transfer coefficient correlation for randomly-packed heat transferring pebbles in flowing FLiBe in the representative Fluoride High-temperature Reactor (FHR) operating condition; and (4) comparison of the developed heat transfer coefficient correlation with existing ones obtained in different fluids and pebble sizes. The LES and RANS comparison has shown that the k-ω Shear Stress Transport (SST) with low Reynolds number approach performance gives the best result in comparison to the two eddy-viscosity based k-ε and k-ω SST models.The statistical distribution of pebble heat transfer coefficients due to random packing has been quantified; random arrangements of pebbles result in non-negligible uncertainties in heat transfer coefficients following normal distributions. This uncertainty needs to be accounted for fuel temperature prediction in reactor design and analyses. A Nusselt number correlation for the randomly packed heat transferring pebble in flowing FLiBe has been computationally developed: Nu = 0.016Re0.72Pr0.31.

A new fuel modeling capability, CTFFuel, with a case study on the fuel thermal conductivity degradation

Abstract A new fuel modeling capability, CTFFuel, is developed from the subchannel code, CTF. This code is a standalone interface to the CTF fuel rod models, allowing for fuel rod simulations to be run independently from the fluid. This paper provides an overview of the code with a case study on the thermal conductivity degradation of LWR fuels to demonstrate its capabilities. The modeling of fuel thermal conductivity degradation in the code is improved through the addition of new modeling options to account for the irradiation effects via globally defined parameters. After the initial implementation, a variety of order-of-accuracy tests and code comparisons are performed to test software quality. A controlled analysis is allowed by CTFFuel to verify the numerical scheme of CTF’s conduction solution and to benchmark its fuel temperature predictions against FRAPCON-4.0’s. Overall, the software quality and verification procedure ensures that the new model is coded correctly, that it properly interacts with the rest of the code.

Comparative analysis of different fidelity fuel performance models for fuel temperature predictions

Thermal-hydraulics subchannel models have proven to give an acceptable compromise between modeling fidelity and computational efficiency in coupled multi-physics steady state, depletion, and transient calculations. The accuracy in modeling both gas-gap conductance and fuel thermal conductivity is of significant importance for fuel temperature prediction, which, in turn, is crucial for calculation of Doppler feedback on power. A comparative analysis of fuel performance models of different fidelity was performed using the sub-channel code CTF, and the higher fidelity fuel performance codes FRAPCON and BISON. The purpose of this study was to ascertain the predictive accuracy of the informed fuel rod model in CTF, thus the potential to inform this model using data from higher fidelity fuel performance models. Excellent agreement was found between CTF and FRAPCON, and between CTF and BISON with respect to inside clad temperature as well as to fuel surface and fuel centerline temperatures when the CTF gap conductance was set to the BISON and FRAPCON calculated gap conductance values. With respect to the CTF and FRAPCON comparison, the maximum temperature difference between the two codes for a given power level and burnup value was below 2 degree Kelvin for clad inner surface and fuel surface temperature. For fuel centerline temperature, the maximum temperature difference was found to be below 7 degree Kelvin at the highest power level and burnup value. Similarly, the CTF and BISON comparison resulted in maximum temperature differences less than 5 degree Kelvin for the fuel centerline temperature. These results demonstrate that, if the gap conductance, dimensions, and radial power distribution is correctly set in CTF, the CTF-predicted rod temperature distribution will match closely with higher fidelity tools and licensed industry level fuel performance codes for normal operating conditions.

Evaluation of modeling options for in-pellet power distribution and gap gas conductance for accurate fuel temperature predictions

Having the ability to predict fuel temperatures for efficient multi-physics steady state, depletion, and transient calculations with reasonable accuracy without the added burden of prohibitively expensive computation costs has been a major driving force in the nuclear industry. There are several parameters that have an immense impact on fuel surface and centerline temperatures. Sensitivity studies were performed to investigate the impact of gap gas conductance and internal pin power distribution on the fuel temperature predictions. As a result, areas of improvement in the CTF fuel performance model were identified by separating different effects, and analyzing the sensitivity of results to each model improvement. The performed studies demonstrated the importance of modeling internal pellet power distribution for accurate prediction of fuel centerline temperature. Furthermore, a new gap gas conductance modeling option that leverages the fuel performance code FRAPCON was implemented in the fuel rod model of CTF. Gap gas conductance data was pre-computed as a function of linear heat rate and fuel exposure, and was integrated into CTF as part of the new model. Using FRAPCON as a reference solution, the new FRAPCON-informed gap conductance model of CTF was found to calculate results within 2 degrees Kelvin of FRAPCON predictions with respect to fuel surface temperature. This study indicated the feasibility of developing an efficient framework for informing the low fidelity fuel rod models of thermal-hydraulic codes, in this case CTF, with more accurate pre-computed values by leveraging high fidelity fuel performance codes such as FRAPCON. CTF was able to utilize this tabulated data provided by the FRAPCON fuel performance code as well as to include the above mentioned improvements in each axial node of a given rod to provide a full three-dimensional representation.

Multi-physics code system with improved feedback modeling

Fuel temperature (Doppler) feedback modeling in the coupled sub-channel thermal-hydraulic/time dependent neutron transport codes system CTF/TORT-TD was improved by accounting for the burnup dependence of the fuel thermal conductivity. TORT-TD is a three-dimensional (3D) time dependent neutron-kinetics code based on the discrete ordinates (SN) method. CTF is the Reactor Dynamics and Fuel Modeling Group (RDFMG) version of the sub-channel thermal-hydraulics code COBRA-TF (COlant Boiling in Rod Arrays – Two Fluid). A burnup-dependent fuel rod model, which takes into account the degradation of the fuel thermal conductivity at high burnups and the effects of burnable poisons, such as Gadolinium, was implemented in CTF. The model is applicable to UO2 (uranium dioxide) and MOX (mixed oxide) nuclear fuels – it includes the modified Nuclear Fuel Industries (NFI) model for UO2 fuels and the Duriez/Modified NFI model for MOX fuels. The in-pellet fuel temperature distributions predicted by CTF/TORT-TD were compared to reference CTF/TORT-TD/FRAPCON calculations, in which the fuel rods were modeled with the fuel performance code FRAPCON. These comparisons were carried out for a 4 × 4 pressurized water reactor (PWR) pin array at hot full power (HFP) steady state conditions. The CTF/TORT-TD fuel temperature predictions were consistent with the CTF/TORT-TD/FRAPCON results. This fact demonstrated that CTF with the new fuel thermal conductivity model can predict the temperature field within light water reactor (LWR) fuel rods as accurately as FRAPCON. Therefore, CTF/TORT-TD calculations can be carried out in fast scoping studies instead of the computationally expensive CTF/TORT-TD/FRAPCON calculations. The performed statistical analyses indicated an improved accuracy of fuel temperature calculations relative to the CTF/TORT-TD/FRAPCON reference numerical solution. Furthermore, better agreement between CTF/TORT-TD and CTF/TORT-TD/FRAPCON in calculated neutronic reactivity was found when fuel burnup effects were considered in CTF/TORT-TD. Therefore, the improved CTF/TORT-TD can be seen as a high fidelity multi-physics computational tool capable of providing accurate and efficient simulations for practical reactor core design and safety analysis.

Effect of heat transfer correlations on the fuel temperature prediction of SCWRs

In this paper, we present a numerical analysis of the effect of different heat transfer correlations on the prediction of the cladding wall temperature in a supercritical water reactor at nominal operating conditions. The neutronics process with temperature feedback effects, the heat transfer in the fuel rod, and the thermal-hydraulics in the core were simulated with a three-pass core design.

Application of the finite volume method to the radial conduction model of the CATHENA code

The CATHENA code uses the finite element method (FEM) for the one-dimensional heat conduction model, which determines the temperature distribution from the fuel center to the cladding in the radial direction. However, it is shown that the finite element solutions in the heat source region such as a fuel pellet are converged to exact solutions with an increasing number of the mesh elements. Since the finite volume method (FVM) ensures local and global energy conservation due to an integral conservation over each control volume, the FVM is applied to the CATHENA wall conduction model to avoid the mesh size effect on the fuel temperature prediction. The accuracy and validity of the finite volume model in the CATHENA code are tested against two cases, a steady state and a transient heat conduction case, for which exact solutions are available. The constant temperature on the boundary surface and a uniform internal heat generation rate are assumed for the steady state problem. In the transient heat conduction problem, a cylinder is initially at a uniform temperature and suddenly its boundary surface is subjected to convection with a constant heat transfer coefficient into an ambient at a constant temperature. The steady state solutions by the FVM model are found to give almost the same results as the analytical solutions and consistent results with varying mesh sizes, while the original CATHENA with FEM over-predicts the center temperature with larger mesh sizes. The new model also closely follows the analytic solutions of the dimensionless transient heat conduction equation for a long cylinder.

Computational experience showing the influence of the fuel-to-sheath thermal conductance in reactor fuel temperature predictions

Employing the BACO [1] code, the influence of the pellet-sheath gap thermal conductance models on temperature predictions has been investigated. Four different models have been used for simulating the thermo-mechanical behavior of a reactor fuel element.