A new methodology to optimize operation cycles in a BWR using heuristic techniques

A new system to optimize fuel assembly design, fuel reload design and control rod patterns design is shown. Fuel assembly optimization is made in two steps.In the first one, a recurrent neural network for the fuel lattice design of the bottom of the fuel assembly is used. In the second one, the top of the fuel assembly is built adding gadolinia to bottom fuel lattice. Fuel reload is optimized by another recurrent neural network whereas the control rod patterns are optimized by an ant colony method. This new system starts building a fresh fuel batch. Later, a seed fuel reload is optimized according to a Haling calculation. Afterwards an iterative process is started: firstly, control rod patterns through the cycle are optimized, once that a new fuel reload with previously optimized control rod patterns is found. If thermal limits cannot be satisfied in this iterative process after several iterations, a new seed fuel reload is designed. If cold shutdown margin cannot be fulfilled, then gadolonia concentration is increased into the fuel assembly. Finally, if energy requirements cannot be fulfilled, then the uranium enrichment of the fuel lattice of the bottom fuel assembly is increased. Results of this new system are successful: thermal limits and cold shutdown margin are fulfilled, and energy requirements are reached.

ANALYSIS OF CS-137 TO CS-134 ACTIVITY RATIO FOR FAILED FUEL EXPOSURE ESTIMATION

The Cs-134 to Cs-137 activity ratio of the Cs-134 and Cs-137 fission products released from failed fuel rods into primary coolant is very useful to identify the exposure along with the fuel batch of the failed fuel. The calculated and measured Cs-137 to Cs-134 radioactivity ratios of failed BWR and PWR fuels are compared and analyzed for better understanding of their relationship. Moreover, the impacts of power uprate and fuel reload outage on calculated Cs-137 to Cs-134 activity ratios are studied and the physics behind the impacts are provided.

LATERAL COOLANT FLOW BETWEEN FUEL ASSEMBLIES IN MIXED CORES

This paper presents the results of an analysis of lateral coolant flow between adjacent fuel assemblies with non-identical spacing grids in a mixed core consisting of TVSA-T mod.1 and TVSA-T mod.2 fuel assemblies. The calculation was carried out using modified subchannel code SUBCAL which allows to calculate 3D thermo-hydraulic characteristics of the coolant flow in the full three fuel assemblies model. This full three fuel assemblies model was created in two variants. The first variant consisted of three hydraulically identical fuel assemblies TVSA-T mod.1, whereas the second variant consisted of two fuel assemblies TVSA-T mod.1 and one fuel assembly TVSA-T mod.2 which mainly differ in types, number and axial coordinate of spacing grids and also in diameter of guide tubes. The influence of mixed core to lateral coolant flow and hence coolant temperature was obtained by comparing these two variants. The power distribution was taken from presumed mixed core fuel reload calculated by macro-code ANDREA. Finally there were also provided a comparison of results achieved by subchannel analysis approach with calculation of similar problem using CFD code ANSYS CFX by TVEL, the fuel supplier.

Combining RAVEN, RELAP5-3D, and PHISICS for Fuel Cycle and Core Design Analysis for New Cladding Criteria

The Nuclear Regulatory Commission (NRC) has considered revision of 10-CFR-50.46C rule (Borchard and Johnson, 2013, “10 CFR 50.46c Rulemaking: Request to Defer Draft Guidance and Extension Request for Final Rule and Final Guidance,” U.S. Nuclear Regulatory Commission, Washington, DC.) to account for burn-up rate effects in future analysis of reactor accident scenarios so that safety margins may evolve as dynamic limits with reactor operation and reloading. To find these limiting conditions, both cladding oxidation and maximum temperature must be cast as functions of fuel exposure. To run a plant model through a long operational transient to fuel reload is computationally intensive, and this must be repeated for each reload until the time of the accident scenario. Moreover for probabilistic risk assessment (PRA), this must be done for many different fuel reload patterns. To perform such new analyses in a reasonable amount of computational time with good accuracy, Idaho National Laboratory (INL) has developed new multiphysics tools by combining existing codes and adding new capabilities. The parallel highly innovative simulation INL code system (PHISICS) toolkit (Rabiti et al., 2016, “New Simulation Schemes and Capabilities for the PHISICS/RELAP5-3D Coupled Suite,” Nucl. Sci. Eng., 182(1), pp. 104–118; Alfonsi et al., 2012, “PHISICS Toolkit: Multi-Reactor Transmutation Analysis Utility—MRTAU,” PHYSOR 2012 Advances in Reactor Physics Linking Research, Industry, and Education, Knoxville, TN, Apr. 15–20.) for neutronic and reactor physics is coupled with the reactor excursion and leak analysis program—three-dimensional (RELAP5-3D) (The RELAP5-3D© Code Development Team, 2014, “RELAP5-3D© Code Manual Volume I: Code Structure, System Models, and Solution Methods,” Rev. 4.2, Idaho National Laboratory, Idaho Falls, ID, Technical Report No. INEEL-EXT-98-00834.) for the loss of coolant accident (LOCA) analysis and reactor analysis and virtual-control environment (RAVEN) (Alfonsi et al., 2013, “RAVEN as a Tool for Dynamic Probabilistic Risk Assessment: Software Overview,” 2013 International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, Sun Valley, ID, May 5–9, pp. 1247–1261.) for the probabilistic risk assessment (PRA) and margin characterization analysis. For RELAP5-3D to process a single sequence of cores in a continuous run required a sequence of restarting input decks, each with different neutronics or thermal-hydraulic (TH) flow region and culminating in an accident scenario. A new multideck input processing capability was developed and verified for this analysis. The combined RAVEN/PHISICS/RELAP5-3D tool is used to analyze a typical pressurized water reactor (PWR).