本文選題：多目標(biāo)優(yōu)化　切入點(diǎn)：多相流　出處：《浙江大學(xué)》2017年碩士論文

【摘要】：氣液攪拌反應(yīng)器因具有操作靈活性強(qiáng)、傳質(zhì)效果好、混合效率高等優(yōu)點(diǎn)在過程工業(yè)中廣泛應(yīng)用。反應(yīng)器結(jié)構(gòu)是影響內(nèi)部物料流動、混合、傳質(zhì)及反應(yīng)的重要因素,對氣液攪拌反應(yīng)器結(jié)構(gòu)進(jìn)行優(yōu)化意義重大。早期對氣液攪拌釜的優(yōu)化研究依賴于實(shí)驗(yàn)手段,測量方法受限,需反復(fù)試驗(yàn),太過耗時且成本較高。隨著計算流體力學(xué)(computational fluid dynamics,CFD)技術(shù)的發(fā)展,能快速而相對準(zhǔn)確地獲取反應(yīng)器內(nèi)部詳細(xì)的流場信息。然而基于CFD的優(yōu)化過程通常只考慮單參數(shù)變化,涉及多個參數(shù)則需要通過大量的模擬才能篩選出較優(yōu)結(jié)果,加上多相體系固有的復(fù)雜性,導(dǎo)致計算量巨大且只能得到局部最優(yōu)解。多目標(biāo)遺傳算法(multi-objective evolutionary algorithm,MOEA)具有全局優(yōu)化、并行搜索、快速收斂等特點(diǎn)。本文針對上述問題,提出了將CFD技術(shù)與優(yōu)化算法相結(jié)合的解決方法。以雙層槳?dú)庖簲嚢璺磻?yīng)器為例進(jìn)行結(jié)構(gòu)優(yōu)化,驗(yàn)證了該方法的可行性和有效性。主要工作與研究結(jié)果如下:(1)基于實(shí)驗(yàn)與CFD分析,建立了一種適用于氣液攪拌反應(yīng)器設(shè)計的多目標(biāo)優(yōu)化方法。借助雙電導(dǎo)電極探針和扭矩測量等實(shí)驗(yàn)技術(shù)驗(yàn)證CFD模型,并在MATLAB平臺上整合CFD分析模塊和優(yōu)化算法模塊,引入?yún)?shù)化建模和自動網(wǎng)格生成技術(shù),利用CFD模擬獲取反應(yīng)器內(nèi)部流場信息,以此指導(dǎo)快速非支配排序遺傳算法(non-dominated sorting genetic algorithm,NSGA-Ⅱ)在龐大的求解空間中高效并行尋優(yōu)。通過創(chuàng)建模塊接口,實(shí)現(xiàn)全自動優(yōu)化過程,可以顯著地減少計算量,獲取全局最優(yōu)解。(2)在轉(zhuǎn)速300 rpm,表觀氣速0.02 m/s的空氣-水體系中,采用均一氣泡尺寸假設(shè),將多目標(biāo)優(yōu)化方法應(yīng)用于雙層槳?dú)庖簲嚢韪膬?yōu)化,從而實(shí)現(xiàn)節(jié)能和良好的氣體分散。首先建立以槳葉結(jié)構(gòu)參數(shù)為優(yōu)化變量,以最大氣含率和最小攪拌功率為目標(biāo)函數(shù)的優(yōu)化命題,利用CFD和NSGA-Ⅱ算法耦合求解,得到了PCBDT-PTD(下層斜凹葉圓盤渦輪槳-上層下壓斜葉槳)優(yōu)化槳組合。隨后探討了槳組合類型和設(shè)計變量對目標(biāo)函數(shù)的影響,發(fā)現(xiàn)上層槳為上翻斜葉槳(PTU)時氣體分布效果較差,為PTD時氣體分散性能最好,隨著槳葉傾斜角度增大,氣體分布更均勻,攪拌功率先增加,待傾角大于90°后逐漸減小;下層槳為凹葉槳時載氣性能良好,凹葉片的長徑比增大,載氣性能提高,而葉片切角越大,攪拌功率越低。最后考察了優(yōu)化結(jié)果的可靠性,測得優(yōu)化槳組合的氣含率較高且沿軸向均勻分布,明顯改善了兩槳之間的氣體分散狀況。優(yōu)化后能耗大幅降低,較標(biāo)準(zhǔn)的RT-RT(雙層六直葉圓盤渦輪槳)組合至少降低了 25%。(3)針對反應(yīng)器內(nèi)部氣泡大小分布不均的問題,引入了關(guān)聯(lián)湍流耗散率與氣泡直徑的氣泡尺寸模型,在模型驗(yàn)證的基礎(chǔ)上,對雙層槳?dú)庖簲嚢璺磻?yīng)器進(jìn)行多目標(biāo)優(yōu)化。首先以槳葉結(jié)構(gòu)參數(shù)為優(yōu)化變量,以最大氣液比相界面積和最小攪拌功率為目標(biāo)建立優(yōu)化命題,得到了 PCBDT-PTU(斜凹葉圓盤渦輪槳-上翻斜葉槳)和PCBDT-PTD(斜凹葉圓盤渦輪槳-下壓斜葉槳)兩種優(yōu)化槳組合。然后利用不同槳型揭示了反應(yīng)器內(nèi)部氣泡尺寸分布規(guī)律,闡明了槳組合類型對目標(biāo)函數(shù)的影響。研究發(fā)現(xiàn),葉輪區(qū)的氣泡尺寸沿著排出流方向先變小后逐漸變大,在循環(huán)區(qū)和液面附近氣泡相對較大。此外,PCBDT-PTU優(yōu)化槳組合的局部相界面積峰值最高,而PCBDT-PTD優(yōu)化槳組合的相界面積分布最均勻,均能在低功耗下實(shí)現(xiàn)高效傳質(zhì)。最后,驗(yàn)證了優(yōu)化結(jié)果的準(zhǔn)確性,實(shí)驗(yàn)測得PCBDT-PTU優(yōu)化槳組合的氧傳質(zhì)系數(shù)接近RT-RT標(biāo)準(zhǔn)槳組合的兩倍,能耗較RT-RT降低了 29%。
[Abstract]:The gas-liquid stirred reactor because of its operating flexibility, good mass transfer effect, higher mixing efficiency has been widely used in process industry. The reactor structure is the internal material flow, mixing, mass transfer and reaction of the important factors on the structure of the reactor, gas-liquid mixing optimize significant. Early studies on Optimization of gas-liquid stirred tank depends on experimental method, measurement method is limited, the repeated test, too time-consuming and high cost. With the computational fluid dynamics (computational fluid, dynamics, CFD) technology development, can quickly and accurately obtain relatively detailed flow information within the reactor. However, the optimization of CFD is usually considered based on single parameter changes, involving many a parameter is required by a lot of simulations to optimal results, the inherent complexity of multiphase system and lead to the great amount of calculation, and can only get the local optimal solution . the multi-objective genetic algorithm (multi-objective evolutionary algorithm, MOEA) with global optimization, parallel search, fast convergence characteristics. Aiming at these problems, put forward the solution method of combining CFD technique and optimization algorithm. With double impeller gas-liquid stirred reactor with structure optimization, proves the method is feasible and effective. The main work and research results are as follows: (1) analysis and experiment based on CFD, established a suitable gas-liquid stirred reactor design of the multi-objective optimization method. By means of double electrode electric conductivity probe and torque measurement technique to validate the CFD model, and integrates the CFD analysis module and optimization module on the MATLAB platform. The introduction of parametric modeling and automatic mesh generation technology, simulation of internal flow field information acquisition reactor using CFD, so as to guide the fast non dominated sorting genetic algorithm (non-dominated sorting Genetic algorithm, NSGA- II) efficient parallel optimization in solving large space. By creating a module interface, realize the automatic optimization process, can significantly reduce the amount of computation to obtain the global optimal solution. (2) at the speed of 300 rpm, the air - water system of superficial gas velocity of 0.02 m/s, using uniform bubble the size optimization hypothesis, the multi-objective optimization method is applied to dual impeller gas-liquid stirred tank, in order to achieve energy saving gas and good dispersion. The first to establish the blade structure parameters as optimization variables, the minimum rate and stirring power containing the atmosphere as the optimization objective function, using CFD and NSGA- II algorithm coupled solution, get the PCBDT-PTD (pressure lower pitched blade paddle helical concave blade disk turbine blade under the upper impeller combination. Then optimization) to investigate the effect of impeller combination type and design variables on the objective function, found the upper impeller to turn on the cable when the gas Ye Jiang (PTU) The cloth effect is poor, PTD gas dispersion performance of the best, with the blade tilt angle increases, the gas distribution is more uniform, the stirring power increased, when the angle is larger than 90 degree decrease; the lower impeller is a concave blade when the carrier gas has good performance, concave blade length diameter ratio increases, improve the carrier gas performance, and leaves cutting angle is larger, the lower stirring power. Finally we investigated the reliability of the optimization results, high rate and uniform distribution along the axial direction with the measured optimization of impeller combination gas, improve the gas between the two pitch dispersion conditions. The optimized energy consumption is greatly reduced, compared with the standard RT-RT (double six straight blade turbine impeller) the combination of reduced at least 25%. (3) to solve the problem of bubble reactor size distribution are introduced into the model, the bubble size relation of turbulent dissipation rate and bubble diameter, on the basis of the model validation, the dual Impeller Stirred gas-liquid reactor for multiple targets The blade structure parameters optimization. Firstly as optimization variables, with the maximum specific gas-liquid interfacial area and the minimum mixing power optimization proposition as the goal, the PCBDT-PTU (oblique concave blade disk turbine blade double impeller) and PCBDT-PTD (oblique concave blade disk turbine blade under pressure impeller) two optimization different types of impeller impeller combination. Then reveals the reactor internal bubble size distribution, illustrates the influence of impeller combination type of objective function. The study found that the bubble size along the impeller discharge flow direction decreases first and then increases gradually, in the vicinity of the circulation zone and the bubble level is relatively large. In addition, local optimization PCBDT-PTU impeller combination of interfacial area and the highest peak, PCBDT-PTD optimization of impeller combination of interfacial area distribution is most uniform, which can achieve high efficiency of mass transfer in low power consumption. Finally, verifying the accuracy of the optimization results, the measured PCBDT-PTU optimization The oxygen mass transfer coefficient of the paddle combination is close to two times that of the RT-RT standard paddle combination, and the energy consumption is lower than that of RT-RT by 29%.

【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TQ052.5

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