压水堆核电站堆芯燃料管理与优化研究
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摘要
目前压水堆核电站普遍采用含有可燃毒物的堆芯装料策略。这种堆芯的装料设计优化问题同时包括燃料组件布置优化和新组件的可燃毒物配置优化,控制变量多且相互关联紧密,导致问题的规模和搜索空间巨大,求解极其复杂。目前国际上基本解决了初装堆芯装料优化问题,但对于非初装堆芯装料优化问题还没有好的解决方法,通常采取的简化问题规模的方法和采用的优化算法全局性差、效率低。
为解决非初装堆芯装料优化难题,本文在文献调研和分析的基础上,提出局部脱耦方法,用以简化问题规模、缩小搜索空间;选择特征统计算法进行优化方案的搜索。利用局部脱耦方法结合特征统计算法研制出压水堆组件布置和可燃毒物配置耦合装料优化程序CSALPBP。使用该程序分别对大亚湾核电站第10循环和第12循环进行装料优化计算,结果表明CSALPBP程序具有很高的搜索效率和很好的全局性。
此外,本文利用哈林原理结合工程经验研制了快速实用的堆芯可燃毒物配置优化程序BPopt,其优化效果分别在初装堆芯和非初装堆芯的可燃毒物配置优化问题上得到了验证。利用哈林原理脱耦方法结合特征统计算法优化组件布置,再辅以BPopt程序,可以很好地解决初装堆芯装料优化问题。
压水堆核电站换料设计过程中,堆芯燃料管理计算程序必不可少。本文在第二类边界条件格林函数节块法程序NGFM-N的基础上添加调硼临界计算和燃耗计算,研制出三维堆芯燃料管理计算程序CYCLE;并在国内首次建立比较精确的含钍组件燃耗计算程序系统WIMSD5-SN2D。
最后,研究在不改变反应堆的结构与几何尺寸的前提下,设计新型种子再生含钍燃料组件,进行了压水堆核电站钍铀燃料循环初步研究,给出了一些具有参考价值的结论。
本论文解决了含可燃毒物的压水堆核电站堆芯装料优化难题,并完成了压水堆钍铀循环燃料管理计算程序和钍利用有关研究,这对于当前压水堆核电站的堆芯燃料管理和今后压水堆的钍利用研究具有重要的意义。
The in-core fuel management strategy with burnable poison is widely adopted in pressurized water reactor nuclear power plants nowadays. The in-core fuel loading optimization problem with burnable poison includes both the loading pattern optimization of fuel assemblies and the allocation optimization of burnable poison in new fuel assemblies. The problem has a good many control variables that have very close relation with each other. So the in-core fuel loading optimization problem with burnable poison is very complex because it has large scale and huge searching scope. Now the initial core’s fuel loading optimization problem has been well solved throughout the world. But with so far there is no satisfied solving method for the in-core fuel loading optimization problem of subsequent fuel cycles. Common methods for simplifying the problem’s scale and optimization algorithms adopted have bad global performance and low efficiency.
In order to solve the puzzle of in-core fuel loading optimization of subsequent fuel cycles, local decoupling method is put forward to simplify the optimization problem’s scale and to reduce the optimization problem’s searching scope in this paper. And a new global optimization algorithm, characteristic statistic algorithm, is chosen to search the optimal loading scheme. And a fuel loading optimization code, CSALPBP, is developed to optimize core fuel assemblies’loading pattern and burnable poison’s allocation of new fuel assemblies simultaneously, which uses local decoupling method combined with characteristic statistic algorithm. The CSALPBP code is separately applied on in-core fuel loading optimization of the 10th cycle and the 12th cycle of Daya bay nuclear power plant, and the results show that CSALPBP has very high efficiency and excellent global performance.
Besides, a very fast and practical optimization code for in-core burnable poison’s allocation in new fuel assemblies, BPopt, is developed using the Haling principle combined with some experiences in the engineering in this paper, and BPopt’s optimization ability has been validated separately on in-core burnable poison’s allocation optimization problem of initial reactor and that of subsequent fuel cycles. After use the Haling principle decoupling method combined with characteristic statistic algorithm to optimize in-core fuel assemblies’loading pattern, then use the BPopt code to optimize burnable poison’s allocation in new fuel assemblies for the core of the optimal fuel assemblies’loading pattern, we can well solve initial core’s fuel loading optimization problem.
During the process of refueling design for pressurized water reactor nuclear power plants, in-core fuel management calculation code is needed. In this paper, the critical boron concentration calculation module and depletion calculation module are added to NGFM-N code, which uses the Nodal Green’s Function method on the second boundary condition. And the corresponding three-dimension core fuel management calculation code, CYCLE, is developed. Moreover, the first much accurate burnup calculation system of thorium-uranium fuel assembly,WIMSD5-SN2D, is developed by coupling the fuel lattice physical code of WIMSD5 and fuel assembly physical code of SN2D.
At last, Daya bay nuclear power plant is selected as the referenced reactor, and a new-type seed-blanket thorium fuel assembly is designed without change of physical dimension and structural materials of assemblies and the core in this paper. The preliminary study on the thorium-uranium fuel cycle of pressurized water reactor nuclear power plants is done, and some valuable conclusions are drawn.
In conclusion, the in-core fuel loading optimization puzzle with burnable poison of pressurized water reactor nuclear power plants has got well solved in this paper. Further more, the thorium-uranium cycle fuel management calculation code is developed and the utilization of thorium resource in pressurized water reactor nuclear power plants is studied in this paper. These studies are of very important meaning both for the present in-core fuel management of pressurized water reactor nuclear power plants and for the future thorium’s utilization in pressurized water reactors.
为解决非初装堆芯装料优化难题,本文在文献调研和分析的基础上,提出局部脱耦方法,用以简化问题规模、缩小搜索空间;选择特征统计算法进行优化方案的搜索。利用局部脱耦方法结合特征统计算法研制出压水堆组件布置和可燃毒物配置耦合装料优化程序CSALPBP。使用该程序分别对大亚湾核电站第10循环和第12循环进行装料优化计算,结果表明CSALPBP程序具有很高的搜索效率和很好的全局性。
此外,本文利用哈林原理结合工程经验研制了快速实用的堆芯可燃毒物配置优化程序BPopt,其优化效果分别在初装堆芯和非初装堆芯的可燃毒物配置优化问题上得到了验证。利用哈林原理脱耦方法结合特征统计算法优化组件布置,再辅以BPopt程序,可以很好地解决初装堆芯装料优化问题。
压水堆核电站换料设计过程中,堆芯燃料管理计算程序必不可少。本文在第二类边界条件格林函数节块法程序NGFM-N的基础上添加调硼临界计算和燃耗计算,研制出三维堆芯燃料管理计算程序CYCLE;并在国内首次建立比较精确的含钍组件燃耗计算程序系统WIMSD5-SN2D。
最后,研究在不改变反应堆的结构与几何尺寸的前提下,设计新型种子再生含钍燃料组件,进行了压水堆核电站钍铀燃料循环初步研究,给出了一些具有参考价值的结论。
本论文解决了含可燃毒物的压水堆核电站堆芯装料优化难题,并完成了压水堆钍铀循环燃料管理计算程序和钍利用有关研究,这对于当前压水堆核电站的堆芯燃料管理和今后压水堆的钍利用研究具有重要的意义。
The in-core fuel management strategy with burnable poison is widely adopted in pressurized water reactor nuclear power plants nowadays. The in-core fuel loading optimization problem with burnable poison includes both the loading pattern optimization of fuel assemblies and the allocation optimization of burnable poison in new fuel assemblies. The problem has a good many control variables that have very close relation with each other. So the in-core fuel loading optimization problem with burnable poison is very complex because it has large scale and huge searching scope. Now the initial core’s fuel loading optimization problem has been well solved throughout the world. But with so far there is no satisfied solving method for the in-core fuel loading optimization problem of subsequent fuel cycles. Common methods for simplifying the problem’s scale and optimization algorithms adopted have bad global performance and low efficiency.
In order to solve the puzzle of in-core fuel loading optimization of subsequent fuel cycles, local decoupling method is put forward to simplify the optimization problem’s scale and to reduce the optimization problem’s searching scope in this paper. And a new global optimization algorithm, characteristic statistic algorithm, is chosen to search the optimal loading scheme. And a fuel loading optimization code, CSALPBP, is developed to optimize core fuel assemblies’loading pattern and burnable poison’s allocation of new fuel assemblies simultaneously, which uses local decoupling method combined with characteristic statistic algorithm. The CSALPBP code is separately applied on in-core fuel loading optimization of the 10th cycle and the 12th cycle of Daya bay nuclear power plant, and the results show that CSALPBP has very high efficiency and excellent global performance.
Besides, a very fast and practical optimization code for in-core burnable poison’s allocation in new fuel assemblies, BPopt, is developed using the Haling principle combined with some experiences in the engineering in this paper, and BPopt’s optimization ability has been validated separately on in-core burnable poison’s allocation optimization problem of initial reactor and that of subsequent fuel cycles. After use the Haling principle decoupling method combined with characteristic statistic algorithm to optimize in-core fuel assemblies’loading pattern, then use the BPopt code to optimize burnable poison’s allocation in new fuel assemblies for the core of the optimal fuel assemblies’loading pattern, we can well solve initial core’s fuel loading optimization problem.
During the process of refueling design for pressurized water reactor nuclear power plants, in-core fuel management calculation code is needed. In this paper, the critical boron concentration calculation module and depletion calculation module are added to NGFM-N code, which uses the Nodal Green’s Function method on the second boundary condition. And the corresponding three-dimension core fuel management calculation code, CYCLE, is developed. Moreover, the first much accurate burnup calculation system of thorium-uranium fuel assembly,WIMSD5-SN2D, is developed by coupling the fuel lattice physical code of WIMSD5 and fuel assembly physical code of SN2D.
At last, Daya bay nuclear power plant is selected as the referenced reactor, and a new-type seed-blanket thorium fuel assembly is designed without change of physical dimension and structural materials of assemblies and the core in this paper. The preliminary study on the thorium-uranium fuel cycle of pressurized water reactor nuclear power plants is done, and some valuable conclusions are drawn.
In conclusion, the in-core fuel loading optimization puzzle with burnable poison of pressurized water reactor nuclear power plants has got well solved in this paper. Further more, the thorium-uranium cycle fuel management calculation code is developed and the utilization of thorium resource in pressurized water reactor nuclear power plants is studied in this paper. These studies are of very important meaning both for the present in-core fuel management of pressurized water reactor nuclear power plants and for the future thorium’s utilization in pressurized water reactors.
引文
[1] Haling R K. Operating strategy for maintaining optimum power distribution throughout life. TID-7672, USAEC, 1964.
[2] Kim Y J, Downar T J, Sesonske A. Optimization of Core Reload Design for Low-leakage Fuel Management in Pressurized Water Reactor. Nuclear Science and Engineering, 1987, 96: 85-101.
[3] Suh J S. Optimized Automatic Reload Program for Pressurized Water Reactors Using Simple Direct Optimization Techniques. Nuclear Science and Engineering, 1990, 105:371-382.
[4] Brian V H, Madeline A F. A Study on the Optimization of Integral Fuel Burnable Absorbers Using the Genetic Algorithm Based CIGARO Fuel Management System.Ann. Nucl. Energy, 1997, 24(6):439-448.
[5] Haibach B. A study of the optimization of IFBA using deterministic methods and the genetic algorithm based CIGARO fuel management system, M.S. Thesis, The Pennsylvania State Universtiy, 1996.
[6] Serkan Y. Application of genetic algorithms to optimize burnable poison placement in pressurized water reactors.Ann. Nucl. Energy, 2006, 33:446-456.
[7]杨波,吴宏春.压水堆堆芯可燃毒物装载的优化计算.核动力工程, 2005, 26(3):214-218.
[8] Dechaine M D, Feltus M A. Nuclear Fuel Management Optimization Using Genetic Algotithms. Nucl. Tech, 1995, 111:109-114.
[9] Adem E, Melih G. A PWR reload optimization code (XCore) using artificial neural networks and genetic algorithms[J].Ann. Nucl. Energy, 2003, 30:35-53.
[10]吴宏春,谢仲生,姚栋,等.遗传算法在AC-600堆芯换料优化中的应用研究.核科学与工程, 2000, 20(4):289-296.
[11] Parks G T. Multiobjective Pressurized Water Reactor Reload Core Design by Non-dominated Genetic Algorithm Search. Nuclear Science and Engineering, 1996, 124: 178-187.
[12] Chapot. A New Approach to Use of Genetic Algorithms to the Pressurized ater Reactor’s Management Optimization Problem. Annals of Nuclear Energy, 1999, 26: 641-655.
[13]周胜,胡永明,郑文祥.遗传算法在压水堆平衡循环中的应用研究.核科学与工程, 2002, 22(4):303-308.
[14] David J.Kropaczek. In-core Nuclear Fuel Management Optimization for Pressurized Waters Utilizing Simulated Annealing. Nuclear Technology. 1991, 95:9-31.
[15] Maldonado G I, Paul J T, And David J.Kropaczek. Employing Nodal Generalized Perturbation Theory for the Minimization of Feed Enrichment During Pressurized Water Reactor In-core Nuclear Fuel Management Optimization. Nuclear Science and Engineering, 1995, 121: 312-325.
[16] Jung H L. Incorporation of Neural Networks into Simulated Annealing Algorithm for Fuel Assembly Loading Pattern Optimization in a PWR. Transactions of the American Nuclear Society, 1999, 80: 228-30.
[17] Chaung L, Jiing-Iuan Y, Kuan-Jan L, Zheng-De W. Pressurized Water Reactor Loading Pattern Design Using the Simple Tabu Search. Nuclear Science and Engineering, 1998,129:61-71.
[18] Galperin A, Kimly Y. Application of Knowledge-Based System Methods to In-core Fuel Management. Nuclear Science and Engineering, 1991,109:103-110.
[19] R.van Geemert. Research Reactor In-core Nuclear Fuel Management Optimization by Application of Multiple Cyclic Interchange Algorithms. Nuclear Engineering and design, 1998, 186: 369-377.
[20] Yamamoto. Akio, Noda. Hidefumi. An integrated scoping analysis tool for in-core fuel management of PWR. Journal of Nuclear Science and Technology, 1997, 34 (8): 847-855.
[21] Yamamoto. Akio. A Quantitative Comparison of Loading Pattern Optimization Methods for In-Core Fuel Management of PWR. Journal of Nuclear Science and Technology, 1997, 34(4): 339-347.
[22] Dechaine M D, Madeline A F. Fuel Management Optimization Using Genetic Algorithms and Expert Knowledge. Nuclear Science and Engineering, 1996, 124: 188-196.
[23]王涛,谢仲生.混合遗传算法在压水堆换料优化中的应用.西安交通大学学报, 2005, 39(5):522-525.
[24] Johansen B J. ALPS: An Advanced Interactive Fuel Management Package. Proc. of Topl. Mtg. on Advances in Reactor phys. Vol. III, 324, Knoxville, TN, April 11, 1994.
[25]刘志宏,施工,胡永明.一种新的全局优化算法—统计归纳算法.清华大学学报, 2002,5:580-583.
[26]石秀安,刘志宏,胡永明.中国先进研究堆水平孔道屏蔽设计优化研究.核动力工程,2006.10:87-90.
[27] MICBURN-E Computer Code Manual. Part II, Chapter 7, Volumes 1-3, ARMP-02 Documentation, EPRI NP-4574, 1986.
[28] Edenius M, Forssen B H. CASMO-3:A Fuel Assembly Burnup Program User's Manual. Studsvik Scandpower, INC. 1994:1-3.
[29]截面接口程序CSMAKE使用说明书.北京:清华大学核能与新能源技术研究院反应堆理论研究室.1999.
[30]胡永明,赵险峰.第二类边界条件先进格林函数节块法.清华大学学报(自然科学版),1998,38(4):17-21.
[31]胡永明.反应堆物理数值计算法.长沙:国防科技大学出版社, 2000.
[32] WIMSD: A Neutronic Code for Standard Lattice Physics Analysis. AEA Technology. 2005.
[33] WIMS-D Library Update. Final report of a coordinated research project.IAEA. Vienna, 2006.
[34]二维SN程序SN2D使用说明书.北京:清华大学核能与新能源技术研究院反应堆理论研究室.1999.
[35] Lawrencl R. D, Dorning J. T. A Nodal Green’s Function Method for Multidimensional Neutron Diffusion Calculations. Nucl. Sci.Eng., 1980,76:218-231.
[36] Koebke K, Hetselt L. On the reconstruction of local homogeneous neutron flux and current distribution of light water reactors from nodal schemes. Nucl. Sci.Eng., 1985,91:123-131.
[37] Rempe K R, Smith K S, Henry A F. SIMULATE-3 power reconstruction: methodology and benchmarking. Nucl. Sci.Eng., 1989,103:334-342.
[38] Hobson D H, Morrow D L, Mays C W, etal. NEMO-nodal expansion method optimized BAW-10180-A, Mar. 1993.
[39]胡永明,甘东,罗经宇.粗网节块功率的重构.清华大学学报, 1995, 35(3):1-6.
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[43]邢文训,谢金星.现代优化计算方法.北京:清华大学出版社,1999.
[44] Zhihong Liu, Gong Shi, Yongming Hu, New global optimization algorithm and its application on in-core fuel management, ANS meeting of PHYSOR 2002. 2002.10.6.
[45]刘志宏.压水堆多循环燃料管理优化研究[博士学位论文].北京:清华大学核能与新能源技术研究院, 2003.
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[49] Alvin Radkowsky. Using thorium in a commercial nuclear fuel cycle:How to do it. Nuclear Engineering International. Jan 1999, 44: 534.
[50] Dean Wang. Optimization of a Seed and Blanket Thorium-Uranium Fuel Cycle for Pressurized Water Reactors. MIT,2003.
[51]张家骅,包伯荣.钍-铀核燃料循环研究论文集.上海:中科院上海原子核研究所,1999.9.
[2] Kim Y J, Downar T J, Sesonske A. Optimization of Core Reload Design for Low-leakage Fuel Management in Pressurized Water Reactor. Nuclear Science and Engineering, 1987, 96: 85-101.
[3] Suh J S. Optimized Automatic Reload Program for Pressurized Water Reactors Using Simple Direct Optimization Techniques. Nuclear Science and Engineering, 1990, 105:371-382.
[4] Brian V H, Madeline A F. A Study on the Optimization of Integral Fuel Burnable Absorbers Using the Genetic Algorithm Based CIGARO Fuel Management System.Ann. Nucl. Energy, 1997, 24(6):439-448.
[5] Haibach B. A study of the optimization of IFBA using deterministic methods and the genetic algorithm based CIGARO fuel management system, M.S. Thesis, The Pennsylvania State Universtiy, 1996.
[6] Serkan Y. Application of genetic algorithms to optimize burnable poison placement in pressurized water reactors.Ann. Nucl. Energy, 2006, 33:446-456.
[7]杨波,吴宏春.压水堆堆芯可燃毒物装载的优化计算.核动力工程, 2005, 26(3):214-218.
[8] Dechaine M D, Feltus M A. Nuclear Fuel Management Optimization Using Genetic Algotithms. Nucl. Tech, 1995, 111:109-114.
[9] Adem E, Melih G. A PWR reload optimization code (XCore) using artificial neural networks and genetic algorithms[J].Ann. Nucl. Energy, 2003, 30:35-53.
[10]吴宏春,谢仲生,姚栋,等.遗传算法在AC-600堆芯换料优化中的应用研究.核科学与工程, 2000, 20(4):289-296.
[11] Parks G T. Multiobjective Pressurized Water Reactor Reload Core Design by Non-dominated Genetic Algorithm Search. Nuclear Science and Engineering, 1996, 124: 178-187.
[12] Chapot. A New Approach to Use of Genetic Algorithms to the Pressurized ater Reactor’s Management Optimization Problem. Annals of Nuclear Energy, 1999, 26: 641-655.
[13]周胜,胡永明,郑文祥.遗传算法在压水堆平衡循环中的应用研究.核科学与工程, 2002, 22(4):303-308.
[14] David J.Kropaczek. In-core Nuclear Fuel Management Optimization for Pressurized Waters Utilizing Simulated Annealing. Nuclear Technology. 1991, 95:9-31.
[15] Maldonado G I, Paul J T, And David J.Kropaczek. Employing Nodal Generalized Perturbation Theory for the Minimization of Feed Enrichment During Pressurized Water Reactor In-core Nuclear Fuel Management Optimization. Nuclear Science and Engineering, 1995, 121: 312-325.
[16] Jung H L. Incorporation of Neural Networks into Simulated Annealing Algorithm for Fuel Assembly Loading Pattern Optimization in a PWR. Transactions of the American Nuclear Society, 1999, 80: 228-30.
[17] Chaung L, Jiing-Iuan Y, Kuan-Jan L, Zheng-De W. Pressurized Water Reactor Loading Pattern Design Using the Simple Tabu Search. Nuclear Science and Engineering, 1998,129:61-71.
[18] Galperin A, Kimly Y. Application of Knowledge-Based System Methods to In-core Fuel Management. Nuclear Science and Engineering, 1991,109:103-110.
[19] R.van Geemert. Research Reactor In-core Nuclear Fuel Management Optimization by Application of Multiple Cyclic Interchange Algorithms. Nuclear Engineering and design, 1998, 186: 369-377.
[20] Yamamoto. Akio, Noda. Hidefumi. An integrated scoping analysis tool for in-core fuel management of PWR. Journal of Nuclear Science and Technology, 1997, 34 (8): 847-855.
[21] Yamamoto. Akio. A Quantitative Comparison of Loading Pattern Optimization Methods for In-Core Fuel Management of PWR. Journal of Nuclear Science and Technology, 1997, 34(4): 339-347.
[22] Dechaine M D, Madeline A F. Fuel Management Optimization Using Genetic Algorithms and Expert Knowledge. Nuclear Science and Engineering, 1996, 124: 188-196.
[23]王涛,谢仲生.混合遗传算法在压水堆换料优化中的应用.西安交通大学学报, 2005, 39(5):522-525.
[24] Johansen B J. ALPS: An Advanced Interactive Fuel Management Package. Proc. of Topl. Mtg. on Advances in Reactor phys. Vol. III, 324, Knoxville, TN, April 11, 1994.
[25]刘志宏,施工,胡永明.一种新的全局优化算法—统计归纳算法.清华大学学报, 2002,5:580-583.
[26]石秀安,刘志宏,胡永明.中国先进研究堆水平孔道屏蔽设计优化研究.核动力工程,2006.10:87-90.
[27] MICBURN-E Computer Code Manual. Part II, Chapter 7, Volumes 1-3, ARMP-02 Documentation, EPRI NP-4574, 1986.
[28] Edenius M, Forssen B H. CASMO-3:A Fuel Assembly Burnup Program User's Manual. Studsvik Scandpower, INC. 1994:1-3.
[29]截面接口程序CSMAKE使用说明书.北京:清华大学核能与新能源技术研究院反应堆理论研究室.1999.
[30]胡永明,赵险峰.第二类边界条件先进格林函数节块法.清华大学学报(自然科学版),1998,38(4):17-21.
[31]胡永明.反应堆物理数值计算法.长沙:国防科技大学出版社, 2000.
[32] WIMSD: A Neutronic Code for Standard Lattice Physics Analysis. AEA Technology. 2005.
[33] WIMS-D Library Update. Final report of a coordinated research project.IAEA. Vienna, 2006.
[34]二维SN程序SN2D使用说明书.北京:清华大学核能与新能源技术研究院反应堆理论研究室.1999.
[35] Lawrencl R. D, Dorning J. T. A Nodal Green’s Function Method for Multidimensional Neutron Diffusion Calculations. Nucl. Sci.Eng., 1980,76:218-231.
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