A method of controlling a nuclear power plant includes obtaining sensor data from one or more sensors of the nuclear power plant, providing the sensor data and a desired plant response to a neural network, wherein the neural network has been previously trained using a simulated nuclear power plant and is structured to determine at least one control system setting to achieve the desired plant response, determining at least one control system setting to achieve the desired plant response with the neural network, and setting or changing at least one control system setting of a control system of the nuclear power plant to the at least one control system setting determined by the neural network.

A method designs nuclear reactors using design variables and metric variables. A user specifies ranges for the design variables and threshold values for the metric variables and selects design parameter samples. For each sample, the method runs three processes, which compute metric variables for thermal-hydraulics, neutronics, and stress. The method applies a cost function to compute an aggregate residual of the metric variables compared to the threshold values. The method deploys optimization methods, either training a machine learning model using the samples and computed aggregate residuals, or using genetic algorithms, simulated annealing, or differential evolution. When using Bayesian optimization, the method shrinks the range for each design variable according to correlation between the respective design variable and estimated residuals using the machine learning model. These steps are repeated until a sample having a smallest residual is unchanged for multiple iterations. The final model assesses relative importance of each design variable.

A method is for controlling a nuclear power plant comprising pressurized water nuclear reactor (3) having a reactor core producing power, a primary circuit (5) connecting the reactor core to a steam generator (9), one or more of control rods (16), which can be moved into the reactor core for controlling the power of the reactor core, an injecting device (22, 23, 24, 26, 28, 30) for injecting boric acid and/or deionized water into the primary circuit (5) for controlling the reactivity of the reactor core.

A high-precision high-fidelity real-time simulation and behavior prediction method and device for a nuclear power station is provided. The method comprises the following steps: (1) constructing a nuclear power station simulator and a physical nuclear power station based on the same design parameters; (2) operating the nuclear power station simulator and the physical nuclear power station in parallel, and obtaining predicted parameters output by the nuclear power station simulator and operation parameters of the physical nuclear power station in real time; (3) comparing the predicted parameters and the operation parameters representing the same physical quantity one by one, and correcting prediction models in the nuclear power station simulator and input parameters of the prediction models by adopting a large-scale concurrent-parallel parameter search and correction algorithm and an artificial intelligence-based mode recognition and correction algorithm until the predicted parameters reach specified precision; and (4) operating the nuclear power station simulator according to a set operation condition to obtain the predicted parameters, thereby completing a behavior prediction of a physical nuclear power station system.

A dynamic characteristic analysis method of DET and RELAP5 coupling based on a universal instrumental variable method includes steps of: constructing a DET simulation model of a discrete dynamic event tree and modifying TRIP cards of an input file by adding universal instrumental TRIP variables according to state transition types of DET simulation objects, the universal instrumental TRIP variable being variable type or logical type; setting a simulation time of the RELAP5, controlling a simulation step, and analyzing an output result file of each simulation step of the RELAP5; backtracking the RELAP5 according to state transition types of DET simulation objects. The dynamic characteristic analysis method has advantages of simplifying TRIP setting process and method of DET state transition objects in an input file of the RELAP5 required for the coupling of DET and RELAP5, reducing a modeling complexity and improving a modeling efficiency.

A method designs nuclear reactors using design variables and metric variables. A user specifies ranges for the design variables and threshold values for the metric variables and selects design parameter samples. For each sample, the method runs three processes, which compute metric variables for thermal-hydraulics, neutronics, and stress. The method applies a cost function to compute an aggregate residual of the metric variables compared to the threshold values. The method deploys optimization methods, either training a machine learning model using the samples and computed aggregate residuals, or using genetic algorithms, simulated annealing, or differential evolution. When using Bayesian optimization, the method shrinks the range for each design variable according to correlation between the respective design variable and estimated residuals using the machine learning model. These steps are repeated until a sample having a smallest residual is unchanged for multiple iterations. The final model assesses relative importance of each design variable.

A method of determination of a nuclear core loading pattern defining the disposition of fuel assemblies includes definition of at least one potential core loading pattern, calculation of predictive bowing of the fuel assemblies at the end of the operation cycle for each potential core loading pattern, the calculation being carried out by an automatic learning algorithm trained on a training data set comprising a plurality of others loading patterns and, for each of them, the measures of bowing of fuel assemblies at the end of cycle, evaluation of the at least one core loading pattern based on the predictive bowing calculations and at least one predetermined criteria, and selection of one of the potential core loading patterns.

There is provided a method of tracking a characteristic line, a method and apparatus of calculating core neutron physics, and a computer-readable storage medium. The method of tracking the characteristic line includes: determining, sequentially from the uppermost level to the lowest level, whether an intersection of the sub-model meeting a first preset condition in each of the plurality of levels and the characteristic line segment meets a second preset condition or not; and obtaining an intersection, that meets the second preset condition, of the sub-model meeting the first preset condition in the lowest level and the characteristic line, so as to obtain a segment correspondence between the characteristic line and the material of the core according to the intersection obtained.

Disclosed is a reactor operation optimization method based on an improved multi-population genetic algorithm. The reactor operation optimization method includes the following steps: defining an operating condition, and designing an operating scheme according to the operating condition; obtaining operating data of the reactor system of the operating scheme through numerical simulation research, and obtaining operation indexes by calculating the operating data; optimizing the operation indexes based on an improved multi-population genetic algorithm to obtain an optimization result; obtaining an optimal operating parameter setting under the operating condition according to the optimization result. The application solves the problem that the design scheme of reactor operation control hardly meets actual operation requirements, and therefore improves operation characteristics of the reactor system.

A configurable unit cell of a core of a nuclear reactor is disclosed herein. The configurable unit cell includes a core block material and a plurality of interchangeable components configured to affect a performance parameter of the core of the nuclear reactor. The configurable unit cell further includes a plurality of channels defined within the core block material. Each channel of the plurality of channels is configured to engage an interchangeable component of the plurality of interchangeable components in an operating configuration. Each channel of the plurality of channels is separated from an adjacent channel of the plurality of channels by a predetermined pitch.