Abstract: The method and apparatus adaptively determine weighting factors within the context of an objective function for handling optimality conditions and constraints within an optimization search. The objective function is defined as a sum of credit and penalty components. The credit components represent the optimality conditions for the problem. The penalty components represent the constraint violations for the problem. Initially, each component is made up of a weight multiplied by a mathematical expression, called a term, that quantifies either an optimality condition or a constraint violation. The set of credit and penalty weights are adaptively determined based on the progress of an optimization search. Both static and dynamic representations of the modified objective function are used to perform the adaption.

Abstract: In a method of determining an operating margin to a given operating limit in a nuclear reactor, operational plant data from an on-line nuclear reactor plant is accessed, and reactor operation is simulated off-line using the operational plant data to generate predicted dependent variable data representative of the given operating limit. The predicted dependent variable data is normalized for evaluation with normalized historical dependent variable data from stored operating cycles of plants having a similar plant configuration to the on-line plant. A time-dependent average bias and a time-dependent uncertainty value for the predicted dependent variable data are determined using the normalized historical dependent variable data, and a risk-tolerance level for the on-line plant is obtained.

Abstract: A method, arrangement and computer program is described for generating a database of selectable fresh fuel bundle designs usable in one or more nuclear reactors. In an example, an initial population of candidate fresh fuel bundle designs may be generated and a set of rod-type changes to make to a given candidate in the initial population may be established. A given candidate fresh fuel bundle may be modified by making at least one rod-type change from the set therein. A core loaded with the modified bundle design may be simulated to generate bundle performance outputs. The bundle performance outputs may be ranked based on a plurality of user-input limits. The modified candidate fresh fuel bundle design may be stored, if the bundle performance outputs meet, or are within an accepted margin to, the user-input limits, so as to generate the database.

Abstract: A method, arrangement and computer program is described for determining a set of standardized rod types for use in a nuclear reactor core. The method may include defining a set of rod type-related limits, and determining, based on the limits, an initial population of rod types to be evaluated for use in cores of a selected number of nuclear reactor plants. Based on the initial population of rod types a database of selectable fresh fuel bundle designs applicable to the one or more cores may be generated. Bundle data related to at least a subset of the selectable fresh fuel bundle designs may be retrieved from the database, and a target number of rod types may be selected from the initial population based on the retrieved bundle data as the set of standardized rod types.

Abstract: In the method, a set of limits applicable to a core may be defined, and a test core loading pattern design, to be used for loading the core, may be determined based on the limits. Reactor operation on at least a subset of the core may be simulated to produce a plurality of simulated results. The simulated results may be compared against the limits, and data from the comparison may indicate whether any of the limits were violated by the core during the simulation. A designer or engineer may use the data to modify the test core loading pattern, creating one or more derivative core loading pattern design(s) for simulation and eventual perfection as an acceptable core loading pattern design for the core.

Abstract: In the method, a set of limits applicable to a test rod pattern design are defined, and a sequence strategy for positioning one or more subsets of the test rod pattern design is established. Reactor operation on a subset of the test rod pattern design, which may be a subset of fuel bundles in a reactor core for example, is simulated to produce a plurality of simulated results. The simulated results are compared against the limits, and data from the comparison is provided to indicate whether any of the limits were violated by the test rod pattern design during the simulation. A designer or engineer may use the data to determine which operator parameters need to be adjusted (e.g., control blade notch positions for example) in order to create a derivative rod pattern design for simulation, and eventually perfect a rod pattern design for a particular core.

Abstract: In the method, a set of limits are defined and a reference core design is generated based on the limits, and includes an initial loading pattern of current fresh fuel bundles arranged in a plurality of fuel locations. A unique subset of fresh fuel bundles is selected for evaluation as the reference core design is subjected to an iterative improvement process. The iterative process includes replacing, at each fuel location, at least one of the current fresh fuel bundles with at least one of the selected fresh fuel bundles, and simulating reactor operation on the reference core design to obtain a plurality of outputs. The outputs may be ranked based on the defined set of limits, and the highest ranked output may be selected as an accepted core design for the nuclear reactor.

Abstract: A method, arrangement and computer program is described for determining a set of standardized rod types for use in a nuclear reactor core. The method may include defining a set of rod type-related limits, and determining, based on the limits, an initial population of rod types to be evaluated for use in cores of a selected number of nuclear reactor plants. Based on the initial population of rod types a database of selectable fresh fuel bundle designs applicable to the one or more cores may be generated. Bundle data related to at least a subset of the selectable fresh fuel bundle designs may be retrieved from the database, and a target number of rod types may be selected from the initial population based on the retrieved bundle data as the set of standardized rod types.

Abstract: In the method, a set of limits applicable to a core may be defined, and a test core loading pattern design, to be used for loading the core, may be determined based on the limits. Reactor operation on at least a subset of the core may be simulated to produce a plurality of simulated results. The simulated results may be compared against the limits, and data from the comparison may indicate whether any of the limits were violated by the core during the simulation. A designer or engineer may use the data to modify the test core loading pattern, creating one or more derivative core loading pattern design(s) for simulation and eventual perfection as an acceptable core loading pattern design for the core.

Abstract: In the method, a set of limits applicable to a core may be defined, and a test fresh fuel loading pattern design, to be used for loading the core, may be determined based on the limits. Reactor operation on at least a subset of the core may be simulated to produce a plurality of simulated results. The simulated results may be compared against the limits, and data from the comparison may indicate whether any of the limits were violated by the core during the simulation. A designer or engineer may use the data to modify the test fresh fuel loading pattern, creating one or more derivative fresh fuel loading pattern design(s) for simulation and eventual perfection as an acceptable fresh fuel loading pattern design for the core.

Abstract: In the method, a set of limits applicable to a test rod pattern design are defined, and a sequence strategy for positioning one or more subsets of the test rod pattern design is established. Reactor operation on a subset of the test rod pattern design, which may be a subset of fuel bundles in a reactor core for example, is simulated to produce a plurality of simulated results. The simulated results are compared against the limits, and data from the comparison is provided to indicate whether any of the limits were violated by the test rod pattern design during the simulation. A designer or engineer may use the data to determine which operator parameters need to be adjusted (e.g., control blade notch positions for example) in order to create a derivative rod pattern design for simulation, and eventually perfect a rod pattern design for a particular core.

Abstract: In the method, a set of limits are defined and a reference core design is generated based on the limits, and includes an initial loading pattern of current fresh fuel bundles arranged in a plurality of fuel locations. A unique subset of fresh fuel bundles is selected for evaluation as the reference core design is subjected to an iterative improvement process. The iterative process includes replacing, at each fuel location, at least one of the current fresh fuel bundles with at least one of the selected fresh fuel bundles, and simulating reactor operation on the reference core design to obtain a plurality of outputs. The outputs may be ranked based on the defined set of limits, and the highest ranked output may be selected as an accepted core design for the nuclear reactor.

Abstract: In the method and apparatus for evaluating a proposed solution to a specific constraint problem, such as boiler water reactor core design, an application specific objective function is configured from a generic The generic objective function definition is a sum of a first number of credit terms plus a sum of a second number of penalty terms. A figure of merit can then be generated for proposed solutions to the constraint problem, and used, for example, in optimizing a solution to the constraint problem.

Abstract: The method and apparatus adaptively determine weighting factors within the context of an objective function for handling optimality conditions and constraints within an optimization search. The objective function is defined as a sum of credit and penalty components. The credit components represent the optimality conditions for the problem. The penalty components represent the constraint violations for the problem. Initially, each component is made up of a weight multiplied by a mathematical expression, called a term, that quantifies either an optimality condition or a constraint violation. The set of credit and penalty weights are adaptively determined based on the progress of an optimization search. Both static and dynamic representations of the modified objective function are used to perform the adaption.