本文選題：GPU加速 + 氟鹽冷卻球床堆　； 參考：《中國科學(xué)院研究生院(上海應(yīng)用物理研究所)》2017年博士論文

【摘要】：氟鹽冷卻球床堆(Pebble-bed fluoride-salt cooled high temperature reactor,PB-FHR)是結(jié)合了多種反應(yīng)堆技術(shù)優(yōu)勢(shì)的新型第四代反應(yīng)堆,采用液態(tài)氟化鹽冷卻劑、內(nèi)嵌包裹燃料顆粒的球形燃料元件,具有良好的經(jīng)濟(jì)和安全特性。PB-FHR堆芯瞬態(tài)分析是反應(yīng)堆設(shè)計(jì)和安全分析的重要環(huán)節(jié),然而目前缺少針對(duì)PB-FHR開發(fā)的堆芯瞬態(tài)分析程序。堆芯瞬態(tài)分析是中子時(shí)空動(dòng)力學(xué)和熱工水力學(xué)的時(shí)空多維耦合計(jì)算問題,計(jì)算耗時(shí)非常長(zhǎng),GPU作為一種新型并行計(jì)算工具,能有效提升數(shù)值模擬程序的計(jì)算速度。本文針對(duì)PB-FHR堆芯的中子物理及熱工水力特性,為PB-FHR建立合理的堆芯瞬態(tài)分析模型,結(jié)合GPU加速技術(shù)研發(fā)PB-FHR三維堆芯瞬態(tài)分析程序,并對(duì)PB-FHR進(jìn)行三維堆芯瞬態(tài)分析。本文基于時(shí)空多群擴(kuò)散理論建立堆芯三維中子動(dòng)力學(xué)模型,在三維圓柱坐標(biāo)的非均勻結(jié)構(gòu)化網(wǎng)格系統(tǒng)下,采用細(xì)網(wǎng)有限體積法及隱式時(shí)間積分方法對(duì)模型進(jìn)行離散和求解。本文基于多孔介質(zhì)模型,在宏觀尺度上建立堆芯熱工水力模型,采用多孔介質(zhì)湍流模型模擬冷卻劑的熱彌散效應(yīng),基于多孔介質(zhì)非熱平衡模型模擬冷卻劑和燃料球的換熱現(xiàn)象,建立燃料球的雙重非均勻結(jié)構(gòu)傳熱模型、熱工水力輔助封閉模型及堆芯球床與側(cè)反射層的耦合傳熱模型,采用同位網(wǎng)格的SIMPLEC算法(Semi-Implicit Method for Pressure Linked Equations-Consistent)求解堆芯熱工水力模型。本文基于偽材料法和Lagrange插值法建立了連續(xù)溫度點(diǎn)的宏觀群常數(shù)計(jì)算方法,建立了瞬態(tài)物理熱工半隱式耦合計(jì)算方法。本文研究了大型七對(duì)角稀疏線性方程組的GPU并行迭代求解算法,在GPU上實(shí)現(xiàn)了2種迭代求解算法(共軛梯度算法(CG)和穩(wěn)定雙共軛梯度法(BICGSTAB))及4種方程預(yù)處理算法(Neumann多項(xiàng)式預(yù)處理算法(POLYN)、不完全Cholesky分解預(yù)處理算法(IC0)、不完全LU分解預(yù)處理算法(ILU0)和幾何代數(shù)多重網(wǎng)格預(yù)處理算法(GAMG),設(shè)計(jì)并研發(fā)了GPU加速的三維堆芯瞬態(tài)分析程序。本文對(duì)GPU堆芯瞬態(tài)分析程序的中子物理和熱工水力求解器展開了校核工作,采用圓柱堆芯中子動(dòng)力學(xué)基準(zhǔn)題對(duì)中子動(dòng)力學(xué)求解器的穩(wěn)態(tài)和瞬態(tài)計(jì)算功能進(jìn)行校核,采用與商用計(jì)算流體力學(xué)軟件FLUENT進(jìn)行結(jié)果對(duì)比的方式對(duì)熱工水力求解器的穩(wěn)態(tài)和瞬態(tài)計(jì)算功能進(jìn)行校核,校核結(jié)果證明了所采用的數(shù)理模型、數(shù)值算法的合理性和正確性。本文對(duì)中子物理和熱工水力求解器的GPU加速性能進(jìn)行了詳細(xì)的分析,證明了GPU加速的有效性,并發(fā)掘出最優(yōu)的求解器組合。對(duì)中子物理求解器的分析結(jié)果表明,GPU并行POLYN-CG求解器具有最高的加速比率(21.65倍),GPU并行GAMG-CG求解器具有較快的收斂速度,但較低的加速比率(13.8倍)和較大的單次迭代計(jì)算量;當(dāng)網(wǎng)格數(shù)量小于2萬時(shí),GPU求解器加速效果不明顯,當(dāng)網(wǎng)格數(shù)量適中時(shí)(2萬到3百萬),GPU并行POLYN-CG算法的計(jì)算耗時(shí)最少,當(dāng)網(wǎng)格數(shù)量達(dá)到3百萬以上時(shí),GPU并行GAMG-CG求解器的計(jì)算耗時(shí)最少。對(duì)熱工水力求解器的分析結(jié)果表明,使用GAMG預(yù)處理算法求解壓力修正方程及冷卻劑溫度方程、POLYN預(yù)處理算法求解其他物理方程可使整體求解速度最快,加速比率最高達(dá)8.39倍。本文參考中科院上海應(yīng)用物理研究所的PB-FHR實(shí)驗(yàn)堆設(shè)計(jì)方案,建立了PB-FHR堆芯模型,并對(duì)該模型進(jìn)行了物理熱工耦合穩(wěn)態(tài)模擬和瞬態(tài)模擬,初步分析了PB-FHR堆芯的穩(wěn)態(tài)及瞬態(tài)運(yùn)行特性,同時(shí)證明了所研發(fā)的程序計(jì)算結(jié)果的合理性。堆芯物理熱工耦合穩(wěn)態(tài)模擬的結(jié)果表明,控制棒插入深度對(duì)堆芯中子通量密度和功率密度的分布形狀具有顯著影響;多孔介質(zhì)孔隙率和阻力對(duì)堆芯壓降及流速具有顯著影響;氟鹽冷卻劑、燃料球表面、燃料球石墨中心及TRISO顆粒之間具有明顯的溫度梯度,燃料球表面溫度受氟鹽溫度的影響較大,燃料球石墨、TRISO顆粒溫度受堆芯功率密度的影響較大。本文進(jìn)行了單根控制棒移動(dòng)、堆芯入口溫度變化、堆芯入口流量變化的瞬態(tài)工況模擬,分析了上述工況下堆芯功率、溫度在時(shí)間和空間上的變化特性及物理熱工的耦合效應(yīng)。結(jié)果表明,單根控制棒移動(dòng)會(huì)產(chǎn)生很大的局部擾動(dòng),使堆芯功率、溫度的幅度和分布形狀均產(chǎn)生較大變化;溫度反饋效應(yīng)能有效控制堆芯功率的變化,但有明顯的滯后性;緩發(fā)中子會(huì)影響堆芯功率的變化速率;入口氟鹽溫度變化對(duì)堆芯氟鹽和燃料球表面的溫度影響顯著,并引入溫度反應(yīng)性,使堆芯功率和溫度發(fā)生變化,但不會(huì)影響堆芯功率及溫度分布的形狀;當(dāng)側(cè)反射層內(nèi)表面附近的氟鹽和燃料球表面溫度變化時(shí),側(cè)反射層內(nèi)表面溫度也受到顯著影響;入口氟鹽流量變化引起堆芯氟鹽、燃料球表面溫度的變化,并引入溫度反應(yīng)性。
[Abstract]:The fluorine salt cooling ball bed reactor (Pebble-bed fluoride-salt cooled high temperature reactor, PB-FHR) is a new type of fourth generation reactor combined with a variety of reactor technical advantages, using liquid fluorinated salt coolant and spherical fuel element embedded with fuel particles, which has good economic and safety characteristics, and.PB-FHR core transient analysis is inverse. There is an important link in the design and safety analysis of the reactor. However, there is a lack of the core transient analysis program developed for PB-FHR. The transient analysis of the core is a time-space multi-dimensional coupling calculation problem of neutron space-time dynamics and thermal hydraulics. The time-consuming calculation is very long. As a new type of calculation tool, GPU can effectively improve the numerical simulation program. In this paper, based on the neutron physics and the thermal hydraulic characteristics of the PB-FHR core, this paper establishes a reasonable core transient analysis model for PB-FHR, and combines the GPU acceleration technology to develop the PB-FHR three-dimensional core transient analysis program, and carries out the three-dimensional core transient analysis of PB-FHR. In this paper, the model is discrete and solved by the finite volume method of fine mesh and the implicit time integration method. Based on the porous medium model, the thermal hydraulic model of the core is established on the macro scale, and the thermal dispersion effect of the coolant is simulated by the multi pore mesoporous turbulence model. In the non thermal equilibrium model of porous media, the heat transfer phenomenon of the coolant and fuel ball is simulated, the dual non-uniform heat transfer model of the fuel ball is established, the thermal hydraulic auxiliary sealing model and the coupled heat transfer model of the core ball bed and the side reflection layer are coupled with the SIMPLEC algorithm of the same bit grid (Semi-Implicit Method for Pressure Linked Equations-Con). Sistent) to solve the core thermal hydraulic model. Based on the pseudo material method and the Lagrange interpolation method, the method of calculating the macroscopic group constants of the continuous temperature points is established, and the transient physical thermal semi implicit coupling calculation method is established. This paper studies the GPU parallel iterative solution algorithm of the large seven diagonal sparse linear equations, and implements 2 kinds of algorithms on GPU. The iterative solution algorithm (conjugate gradient algorithm (CG) and stable dual conjugate gradient method (BICGSTAB)) and 4 equation preprocessing algorithms (Neumann polynomial pre processing algorithm (POLYN), incomplete Cholesky decomposition preprocessing algorithm (IC0), incomplete LU decomposition preprocessing algorithm (ILU0) and geometric algebraic multigrid preprocessing algorithm (GAMG)) are designed and developed for GPU. In this paper, the neutron physics and thermal hydraulic solver of the GPU core transient analysis program is checked. The steady-state and transient calculation functions of the neutron dynamics solver are checked with the neutron dynamic benchmark of the column core, and the software FLUENT is used with the commercial computational fluid dynamics software. The calculation of the steady-state and transient functions of the thermal hydraulic solver is checked in the way of the comparison of the results. The results of the calculation prove the rationality and correctness of the mathematical model and the numerical algorithm used. This paper analyses the GPU acceleration performance of the neutron physics and thermal hydraulic solver, and proves the validity of the acceleration of the GPU. The analysis results of the neutron solver show that the GPU parallel POLYN-CG solver has the highest rate of acceleration (21.65 times), and the GPU parallel GAMG-CG solver has a faster convergence rate, but a lower acceleration ratio (13.8 times) and a larger single iteration calculation; when the number of grids is less than 20 thousand, GPU is solved. The acceleration effect is not obvious. When the number of grids is moderate (20 thousand to 3 million), the GPU parallel POLYN-CG algorithm takes the least time. When the number of grids is over 3 million, the calculation of GPU parallel GAMG-CG solver takes the least time. The analysis results of the thermal hydraulic solver show that the GAMG preprocessing algorithm is used to solve the pressure correction equation and cold. However, the solution of other physical equations by the POLYN pretreatment algorithm can make the overall solution speed the fastest and the acceleration ratio up to 8.39 times. In this paper, the PB-FHR core model is established by the PB-FHR experimental reactor design scheme of the Shanghai Institute of Applied Physics of the Academy of Sciences, and the model of physical thermal coupling steady state and transient simulation is carried out. The steady-state and transient operating characteristics of the PB-FHR core are preliminarily analyzed, and the results are proved to be reasonable. The results of the reactor core physical thermal coupling steady-state simulation show that the insertion depth of the control rod has a significant influence on the neutron flux density and the distribution of the power density of the core, and the porosity and resistance of the porous media. The pressure drop and flow velocity have a significant influence on the core pressure drop and flow velocity, and there is a clear temperature gradient between the fluorine coolant, the fuel ball surface, the fuel ball graphite center and the TRISO particles. The surface temperature of the fuel ball is greatly influenced by the temperature of the fluorine salt. The fuel ball graphite and the TRISO particle temperature are greatly influenced by the power density of the core. The change of core power and temperature in time and space and the coupling effect of physical heat are analyzed. The results show that the single control rod movement will produce a large local disturbance, which makes the core power, the temperature range and the distribution shape all produce. The temperature feedback effect can effectively control the change of the core power, but it has obvious hysteresis; the retarded neutrons will affect the change rate of the core power; the temperature change of the inlet fluorine salt has a significant influence on the temperature of the core fluorine salt and the surface of the fuel ball, and the temperature reactivity is introduced to make the core power and temperature change, but not the shadow. The shape of the core power and temperature distribution; when the surface temperature of the fluorine salt and the fuel ball near the inner surface of the side reflecting layer changes, the inner surface temperature of the side reflector is also significantly affected; the change of the flow rate of the inlet fluorine salt leads to the change of the core fluorine, the surface temperature of the fuel ball and the temperature reactivity.
【學(xué)位授予單位】：中國科學(xué)院研究生院(上海應(yīng)用物理研究所)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類號(hào)】：TL351.1

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