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In this paper, a data-assimilation method-was proposed and applied for the burnup distribution of PWR. The burnup distribution is significant to the safety and economy of the reactor, as it is essential for the fuelreloading design and optimization. Due to the burnup distribution can’t be measured directly during the reactor operation, the numerical simulation is widely applied in reactor engineering. However, there are definitely exist differences between the physical model by the numerical simulation and the actual core, which would induce the errors to the simulation values of power distributions and hence to the burnup distributions. Therefore, a data-assimilation method has been proposed based on the three-dimensional variation (3DVAR) algorithm and the neutral network algorithm, aiming at reducing the errors of the burnup-distribution simulations with application of the power-distribution measurements. In our proposed method for the burnup distribution, the 3DVAR algorithm was applied to get the more-accurate burnup distribution, the neutral network algorithm was applied to obtain the complex relations between the burnup distributions and the power distributions which were essential for the 3DVAR. As method verification, the proposed method has been applied to a commercial PWR operated in China. It can be observed that through the data assimilation, the burnupdistribution errors can be reduced notably, as the maximum value of relative errors for power distribution can be notably reduced from 9.53% to 5.11%. Moreover, the key parameters including power-peak factors (Fq and FΔH) can also be improved. As concluded, the data-assimilation method based on the power-distribution measurements is efficient to improve the simulation accuracy of burnup distributions, and could further guarantee the economy and safety of PWR.

Numerical reactor technology describes a variety of physical phenomena in the core of a nuclear reactor through highprecision, highresolution, high confidence and high fidelity numerical simulation method, based on highperformance calculation and multiphysics coupling, reveals the internal laws of various physical phenomena in nuclear reactors from mechanism, and accurately predicts the key safety parameters of nuclear reactors in service. It plays an important role in the whole life cycle of nuclear reactor R&D, design, safety analysis, operation support and decommissioning. This paper systematically introduces the main outcome of the major national science and technology project “Research on Key Technologies of CAP1400 Numerical Reactor” of “Largescale Advanced PWR and HTGR Nuclear Power Plant”. Firstly, the high fidelity reactor physics calculation codes based on deterministic method and Monte Carlo method were developed respectively, and then the pinbypin advanced subchannel analysis code and the fuel rod analysis code based on finemesh were developed. Based on those codes, the CAP1400 numerical reactor system with neutronics/thermalhydraulics/fuel performance multiphysics coupling was established. The numerical reactor system was verified and validated against the international benchmark VERA provided by CASL and AP1000 startup experimental data. For VERA problems, the comparison with the results of MC21/CTF coupling codes shows that the relative deviation of the power distribution of numerical reactor system is less than 25% for both Monte Carlo method and deterministic method. The maximum critical boron concentration deviation is less than 30 ppm. For AP1000 reactor of Sanmen unit 2, the deviations of developed numerical reactor compared with the measurements are as follows: 1) The maximum deviations of gray rod worth are -103 pcm, 73 pcm and 57 pcm, respectively; 2) The maximum relative deviation of black rod worth are 32%, -17% and 08%, respectively; 3) The ITC deviations are -0.597 pcm/℃, 0.280 pcm/℃, and 1570 pcm/℃, respectively. Compared with the industry codes, numerical reactor codes have higher precision. After verification and validation, the numerical reactor codes were applied to simulate the startup experiments of CAP1400 reactor. Taking the Monte Carlo results as references, the absolute deviation of the deterministic numerical reactor code for the critical boron concentration under HZP ARO condition is -236 ppm. The maximum absolute deviation for the value of the gray rod group (MA to MD) is -52 pcm, and for the black rod group, the maximum relative deviation of the value of (M1, M2, AO, SD1 to SD6) is 268%. The relative deviation of the total worth of black rods is -008%. Assembly power distributions of 14 core conditions were compared between Monte Carlo code and deterministic code. The most positive value of relative deviation is 224%, the most negative value is -247%, the average value is -006% and the standard deviation is 102%. The above numerical results show that the developed numerical reactor analysis program has high calculation accuracy and can directly serve the design verification, startup and operation support of CAP1400.

A method of Covariance-Oriented Sample Transformation (COST) has been proposed in our previous work to provide the converged uncertainty analysis results with a minimal sample size. The transient calculation of nuclear reactor is a key part of the reactor-physics simulation, so the accuracy and confidence of the neutron kinetics results have attracted much attention. In this paper, the Uncertainty Quantification (UQ) function of the high fidelity neutronics code NECP-X has been developed based on our home-developed uncertainty analysis code UNICORN, building a platform for the UQ of the transient calculation. Furthermore, the well-known space-time heterogeneous neutron kinetics benchmark C5G7 and its uncertainty propagation from the nuclear data to the interested key parameters of the core have been investigated. To address the problem of “the curse of dimensionality” caused by the large number of input parameters, the COST method has been applied to generate multivariate normal-distribution samples in uncertainty analysis. As a result, the law of the assembly/pin normalized power and their uncertainty with respect to time after introducing an instantaneous perturbation has been obtained. From the numerical results, it can be observed that the maximum relative uncertainties for the assembly normalized power can up to be about 1.65% and the value for the pin-wise power distributions can be about 2.71%.