Serkan Yilmaz

Optimum Discharge Burnup and Cycle Length for PWRs

Abstract This paper discusses the results of a pressurized water reactor fuel management study determining the optimum discharge burnup and cycle length. A comprehensive study was performed considering 12-, 18-, and 24-month fuel cycles over a wide range of discharge burnups. A neutronic study was performed followed by an economic evaluation. The first phase of the study limited the fuel enrichments used in the study to <5 wt% 235U consistent with constraints today. The second phase extended the range of discharge burnups for 18-month cycles by using fuel enriched in excess of 5 wt%. The neutronic study used state-of-the-art reactor physics methods to accurately determine enrichment requirements. Energy requirements were consistent with today’s high capacity factors (>98%) and short (15-day) refueling outages. The economic evaluation method considers various component costs including uranium, conversion, enrichment, fabrication and spent-fuel storage costs as well as the effect of discounting of the revenue stream. The resulting fuel cycle costs as a function of cycle length and discharge burnup are presented and discussed. Fuel costs decline with increasing discharge burnup for all cycle lengths up to the maximum discharge burnup considered. The choice of optimum cycle length depends on assumptions for outage costs.

Genetic algorithm application for burnable poison placement in pwrs with optimized UO2/Gd2O3 fuel pin configurations

In this paper, an efficient genetic algorithm has placed burnable poisons (BPs) into all of the fresh fuel positions in the core employing the optimized BP configurations and techniques developed in two previous papers. Of importance was the previous development of a Kinf filter, which greatly reduced the computational time. The Kinf filter eliminated many of the invalid genotypes/phenotypes before making a precise core depletion analysis. An extensive BP library was generated by the CASMO-4/TABLES-3 codes. The process was automated with a user-friendly program developed for this purpose. The BPs were vendor UO2/Gd2O3 fuel assembly designs used in a reference Three Mile Island Unit 1 core. The optimized UO2/Gd2O3 fuel pin configurations have small residual binding at end of cycle (EOC), and BP loading optimization results with 97.2 ppm soluble boron at EOC while it was 94.4 ppm with the available vendor designs. The result was that optimized UO2/Gd2O3 fuel pin configurations were developed with unique self-shielding properties and residual binding that also provided a 6.89% reduction in the total required Gd amount, providing extra savings in fuel cost.

Genetic algorithm to optimize the UO2/Gd2O3 fuel pin designs in a pressurized water reactor

An efficient and practical genetic algorithm (GA) was developed to optimize the UO2/Gd2O3 fuel pin burnable poison (BP) configurations for fresh fuel assembly (FA) designs loaded in a pressurized water reactor core. The objective of the optimization was to minimize the residual binding due to residual Gd isotopes in the fuel at the end of cycle (EOC). The GA process for creating new BP designs in a coded form called genotypes is generated randomly resulting in a large number of invalid designs. Each new BP design or genotype created by the new GA must be decoded into its corresponding phenotype so that it can be evaluated with a coupled fuel lattice and core depletion calculation. It is essential that most of the invalid designs be eliminated before performing the precise coupled fuel lattice calculation because of the long CPU time that it takes for this calculation. The elimination was accomplished in the new GA by incorporating a beginning-of-cycle (BOC) Kinf filter. The BOC Kinf filter eliminated most of the invalid new genotypes by assigning a high negative penalty to all genotypes that have a BOC Kinf greater than some limit (1.065) for the reference TMI-1 FA. This filter eliminates the need for performing coupled lattice and core depletion calculations for these genotypes. It accelerated the solution process and allowed evaluation of all new genotypes within one day. In this way, the GA minimized the residual binding using an objective function, which maximized the EOC soluble boron (SB) concentration. In essence, the EOC SB or its equivalent EOC keff was maximized.

Application of genetic algorithm to optimize burnable poison placement in pressurized water reactors

An efficient and a practical genetic algorithm tool was developed and applied successfully to Burnable Poisons (BPs) placement optimization problem in the reference Three Mile Island-1 (TMI-1) core. Core BP optimization problem means developing a BP loading map for a given core loading configuration that minimizes the total Gadolinium (Gd) amount in the core without violating any design constraints. The number of UO2/Gd2O3 pins and Gd2O3 concentrations for each fresh fuel location in the core are the decision variables and the total amount of the Gd in the core is in the objective function. The main objective is to develop the BP loading pattern to minimize the total Gd in the core together with the with residual binding at End-of-Cycle (EOC) and to keep the maximum peak pin power and Soluble Boron Concentration (SOB) at the Beginning of Cycle (BOC) both less than their limit values during core depletion. The innovation of this study was to search all of the feasible U/Gd fuel assembly designs with variable number of U/Gd pins and concentration of Gd2O3 in the overall decision space. The use of different fitness functions guides the solution towards desired (good solutions) region in the solution space, which accelerates the GA solution. The main objective of this study was to develop a practical and efficient GA tool and to apply this tool for designing BP patterns of a given core loading.

Optimizing the Placement of Burnable Poisons in PWRs

The principal focus of this work is on developing a practical tool for designing the minimum amount of burnable poisons (BPs) for a pressurized water reactor using a typical Three Mile Island Unit 1 2-yr cycle as the reference design. The results of this study are to be applied to future reload designs. A new method, the Modified Power Shape Forced Diffusion (MPSFD) method, is presented that initially computes the BP cross section to force the power distribution into a desired shape. The method employs a simple formula that expresses the BP cross section as a function of the difference between the calculated radial power distributions (RPDs) and the limit set for the maximum RPD. This method places BPs into all fresh fuel assemblies (FAs) having an RPD greater than the limit. The MPSFD method then reduces the BP content by reducing the BPs in fresh FAs with the lowest RPDs. Finally, the minimum BP content is attained via a heuristic fine-tuning procedure. This new BP design program has been automated by incorporating the new MPSFD method in conjunction with the heuristic fine-tuning program. The program has automatically produced excellent results for the reference core, and has the potential to reduce fuel costs and save manpower.