iPP结晶形态演化研究及结晶参数识别
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摘要
结晶过程是结晶性聚合物在成型加工过程中结构演化的主要形式之一,是影响制品性能的关键因素。随着科技的发展,通过数值模拟研究聚合物结晶形态演化过程已越来越受到关注,而可靠的结晶参数是获得精确结晶演化模拟结果的前提。因此通过实验手段对半结晶聚合物结晶演化过程及结晶动力学进行研究,并基于实验数据,对结晶形态演化模型参数进行识别,获得精确的结晶模型,提高结晶过程预测的准确性有着重要的意义。
本文对静态条件下iPP的等温和非等温结晶过程进行实验研究,分析不同结晶条件对结晶演化过程的影响,并在实验的基础上,基于微分形式的结晶形态演化模型,分别用物理分析方法和遗传算法对模型参数进行优化,最终获得优化的参数。应用优化参数的模拟结果与实验结果比较吻合,验证了模型参数的可靠性。主要工作包括：
1对静态条件下iPP的等温和非等温结晶过程进行实验研究。对不同温度下的等温结晶过程进行实验研究,结果表明,随着温度条件的升高,结晶速率下降,体系中晶体数量减少,晶体尺寸随之增大。采用不同的等速降温形式对非等温结晶过程进行实验研究,结果表明,随着降温速率的增大,结晶速率升高,体系中晶体数量增多,但晶体尺寸随之减小。
2基于微分形式的结晶形态演化模型,对iPP等温、非等温结晶形态演化过程进行分析,基于实验结果,采用最小二乘法获得结晶模型参数。对等温条件下的模拟结果与解析解和实验结果进行对比,结果非常吻合,验证了模型参数的可靠性。
3基于实验数据和结晶演化模拟结果,运用实数编码的遗传算法,建立了结晶形态演化模型参数优化理论和算法。采用该方法对结晶模型参数进行优化,获得优化的结晶模型参数。将优化参数用于结晶形态演化模拟,并将体积转化分数及晶体数目的模拟结果与实验结果进行对比,结果非常吻合。表明采用遗传算法识别获得的模型参数,可以更好地描述结晶形态演化过程。
Crystallization, as the key factor affecting product quality, is one of the major structure evolutions in polymer fabrication. Nowadays, numerical simulation has aroused intense attention throughout the world. The reliable crystallization parameters are the premise of getting precise simulation results of crystallization morphology evolution. Thus, exploring semi-crystallization procedure and crystallization dynamics is meaningful for crystallization evolution model reorganization and optimization.
iPP crystallization under quiescent isothermal and non-isothermal condition has been investigated. Based on the experimental results, a differential system of crystallization evolution has been optimized by physical analysis methods and genetic algorithms. Simulation result using the optimum parameters has a good agreement with the experimental result. The reliability of the crystallization parameters was verified. The main works and achievements are as following:
1. iPP crystallization under quiescent isothermal and non-isothermal condition has been investigated. Quiescent isothermal crystallization processes under different temperature were studied, and the results indicate the crystallization rate decreases, the number of crystals reduces and the size of crystals increases with the temperature increasing. Quiescent non-isothermal crystallization experiments under different cooling rate were conducted, and the results show that the crystallization rate and the number of crystals increases while the size of crystals decreases with the cooling rate increasing.
2. The processes of crystallization morphology evolution of iPP under isothermal and non-isothermal conditions were investigated based on a differential system model. The model parameters were acquired using the least square method based on the experimental results. Comparison results indicate there is a perfect agreement between simulation and analytical calculations under isothermal conditions, and simulations have consistent results with the experimental results under non-isothermal conditions. The reliability of the model parameters was verified.
3. Based on the experiment and simulation result, the theories and algorithms are developed to identify the parameters of crystallization evolution model using real-code Genetic-Algorithms. The parameters of crystallization model were optimized. The optimum parameters were used in the crystallization model, and the crystallization processes were implemented. Comparison of the simulation results with the experimental results shows the simulation results have better consistency with the experiments results. The model using the optimum parameters can describe the crystallization evolution more accurately.
本文对静态条件下iPP的等温和非等温结晶过程进行实验研究,分析不同结晶条件对结晶演化过程的影响,并在实验的基础上,基于微分形式的结晶形态演化模型,分别用物理分析方法和遗传算法对模型参数进行优化,最终获得优化的参数。应用优化参数的模拟结果与实验结果比较吻合,验证了模型参数的可靠性。主要工作包括：
1对静态条件下iPP的等温和非等温结晶过程进行实验研究。对不同温度下的等温结晶过程进行实验研究,结果表明,随着温度条件的升高,结晶速率下降,体系中晶体数量减少,晶体尺寸随之增大。采用不同的等速降温形式对非等温结晶过程进行实验研究,结果表明,随着降温速率的增大,结晶速率升高,体系中晶体数量增多,但晶体尺寸随之减小。
2基于微分形式的结晶形态演化模型,对iPP等温、非等温结晶形态演化过程进行分析,基于实验结果,采用最小二乘法获得结晶模型参数。对等温条件下的模拟结果与解析解和实验结果进行对比,结果非常吻合,验证了模型参数的可靠性。
3基于实验数据和结晶演化模拟结果,运用实数编码的遗传算法,建立了结晶形态演化模型参数优化理论和算法。采用该方法对结晶模型参数进行优化,获得优化的结晶模型参数。将优化参数用于结晶形态演化模拟,并将体积转化分数及晶体数目的模拟结果与实验结果进行对比,结果非常吻合。表明采用遗传算法识别获得的模型参数,可以更好地描述结晶形态演化过程。
Crystallization, as the key factor affecting product quality, is one of the major structure evolutions in polymer fabrication. Nowadays, numerical simulation has aroused intense attention throughout the world. The reliable crystallization parameters are the premise of getting precise simulation results of crystallization morphology evolution. Thus, exploring semi-crystallization procedure and crystallization dynamics is meaningful for crystallization evolution model reorganization and optimization.
iPP crystallization under quiescent isothermal and non-isothermal condition has been investigated. Based on the experimental results, a differential system of crystallization evolution has been optimized by physical analysis methods and genetic algorithms. Simulation result using the optimum parameters has a good agreement with the experimental result. The reliability of the crystallization parameters was verified. The main works and achievements are as following:
1. iPP crystallization under quiescent isothermal and non-isothermal condition has been investigated. Quiescent isothermal crystallization processes under different temperature were studied, and the results indicate the crystallization rate decreases, the number of crystals reduces and the size of crystals increases with the temperature increasing. Quiescent non-isothermal crystallization experiments under different cooling rate were conducted, and the results show that the crystallization rate and the number of crystals increases while the size of crystals decreases with the cooling rate increasing.
2. The processes of crystallization morphology evolution of iPP under isothermal and non-isothermal conditions were investigated based on a differential system model. The model parameters were acquired using the least square method based on the experimental results. Comparison results indicate there is a perfect agreement between simulation and analytical calculations under isothermal conditions, and simulations have consistent results with the experimental results under non-isothermal conditions. The reliability of the model parameters was verified.
3. Based on the experiment and simulation result, the theories and algorithms are developed to identify the parameters of crystallization evolution model using real-code Genetic-Algorithms. The parameters of crystallization model were optimized. The optimum parameters were used in the crystallization model, and the crystallization processes were implemented. Comparison of the simulation results with the experimental results shows the simulation results have better consistency with the experiments results. The model using the optimum parameters can describe the crystallization evolution more accurately.
引文
[1]何曼君,陈维孝,董西侠.高分子物理[M],上海：复旦大学出版社,2000.38-81
[2]Piorkowska E, Galeski A, Haudin J M. Critical assessment of overall crystallization kinetics theories and predictions [J]. Prog. Polym. Sci.,2006,31:549～575
[3]Lorenzo M L D, Silverstre C. Non-isothermal crystallization of polymers [J]. Prog. Polym. Sci.,1999,24:917～950
[4]Long Y, Shanks R A, Stachurski Z H. Kinetics of polymer crystallization [J]. Prog. Polym. Sci.1995,20:651-671
[5]刘结平,莫志深.聚合物结晶动力学[J].高分子通报,1991,4：199-207
[6]殷敬华,莫志深.现代高分子物理学(上册)[M].北京,科学出版社,2001
[7]林少全,林超群.聚乙烯管材专用料的DSC研究[J].现代塑料加工应用,2004,16(5)：38-41
[8]周丽莉,邓鹏扬,吴航等.(3-烃基丁酸-3-烃基戊酸)共聚物异相成核结晶行为[J].应用化学,2006,23(1)：89-93
[9]He X Q, X D M, Yang D C. Isothermal crystallization kinetics of poly(trimethylene terephthalate) under the influence of self-seeding nucleation [J]. Acta. Polymerica Sinica, 2006,3:414～417
[10]李剑,周持兴,王刚等.低等规聚丙烯的等温结晶动力学[J].高分子材料科学与工程,2002,18(6)：106-110
[11]Hertlein C, Saalwachter K, Strobl G. Low-field NMR studies of polymer crystallization kinetics:Changes in the melt dynamics [J]. Polymer,2006,47:7216～7221
[12]Ozawa T. Kinetics of non-isothermal crystallization [J]. Polymer,1971,12:150～158
[13]Sajkiewicz P, Carpaneto L, Wasiak A. Application of the Ozawa model to non-isothermal crystallization of poly(ethylene terephthalate) [J]. Polym.,2001,42 (12):5365～5370
[14]Hammami A, Spruiell J E, Mehrotra A K. Quiescent non-isothermal crystallization kinetics of isotactic polypropylenes[J]. Polym. Eng. Sci.,1995,35:797～804
[15]Li J, Fang Z P, Tong L F. Effect of multi-walled carbon nanotubes on non-isothermal crystallization kinetics of polyamide6 [J]. European Polymer Journal,2006 42(12):3230～3235
[16]Lopez L C, Wilkes G L. Non-isothermal crystallization kinetics of poly (p-phenylene sulphide)[J]. Polymer,1989,30:882～887
[17]Supaphol P, Dangseeyun N, Srimoaon P. Non-isothermal melt crystallization kinetics for poly (trimethylene terephthalate)/poly (butylene terephthalate) blends [J]. Polym. Test, 2004,23:175-185
[18]Jiao C, Wang Z, Liang X. Non-isothermal crystallization kinetics of silane crosslinked polyethylene [J]. Polym. Test,2005,24:71～80
[19]Hong P, Chung W, Hsu C. Crystallization kinetics and morphology of poly (trimethylene terephthalate)[J]. Polymer,2002,43:3335～3343
[20]Zhang Q, Zhang Z, Zhang H. Isothermal and non-isothermal crystallization kinetics of nylon-46[J].Polym Sci Part B:Polym. Phys.,2002,40:1784～1793
[21]Liu T X, Mo Z S, Zhang H F. Non-isothermal melt crystallization behavior of PEDEKmK[J].Polym. Sci.,1998,67(5):815～821
[22]Liu T X, Mo Z S, Zhang H F. Isothermal and non-isothermal melt crystallization kinetic behavior of poly(aryl ether biphenyl ether ketone ketone):PEDEKK[J]. Polym.,1998, 18(4):283～299
[23]An Y X, Dong L S, Mo Z S, et al. Non-isothermal crystallization kinetics of poly (β-hydroxylbutyrate)[J]. Polym. Sci, Polym. Phys.,199,36 (8):1305～1312
[24]Escleine J M, Monasse B, Wey E, et al. Influence of specimen thickness on isothermal crystallization kinetics [J]. Colloid & Polymer Sci.,1984,262:366～373
[25]周林洋.PBT非等温结晶动力学[J].合成树脂及塑料,2003,20(2)：13-15
[26]徐振淼,陈寿羲.光学解偏振法测定高聚物的结晶速度[J].高分子通讯,1979,No3
[27]张志英,康文华,张春玲.高聚物的非等温结晶动力学[J].高分子学报,1992,4：500-503
[28]Tao Hwang, Kamal M R. Morphological modeling of polymer solidification [J]. Polym Eng Sci,2000,40(6):1796～1808
[29]Tao Huang, Rey A D, Kamal M R. Structure evolution of spherulitic crystallization in semicrysatlline polymer films [J]. Macromolecules,1998,31:7791～7799
[30]Swaminarayan S, Charbon. Multi-scale model for polymer crystallization. I:Growth of individual spherulites [J]. Polym. Eng. Sci.,1998,38(4):634～656
[31]Haudin J M, Chenot J L. Numerical and Physical Modeling of Polymer Crystallization Part I:Theoretical and Numerical Analysis [J]. Polymer processing XIX,2004,3:267～274
[32]Monasse B, Smirnova J, Haudin J M, et al. Numerical and Physical Modeling of Polymer Crystallization Part II:Isothermal and Non-isothermal Crystallization Kinetics of a Polypropylene in 2 Dimensions-Experiments and Simulation [J]. Polymer,2004, 3:275-286
[33]Smirnova J, Silva L, Monasse B, et al. Identification of crystallization kinetics parameters by genetic algorithm in non-isothermal conditions [J]. Engineering Computations,2007, 24(5):486～513
[34]Haudin J M, Smirnova J, Silva L, et al. Modeling of Structure Development During Polymer Processing [J]. Polymer Science,2008,50(5):538～549
[35]Boyer S A E, Billon N, Haudin J M. Crystallization kinetics of polypropylenes. Effect of nucleation agents?[J].Suppl,2008,1:603～606
[36]Haudin J M, Boyer S A E. Crystallization of polypropylene at high cooling rates [J]. Suppl, 2009,2(1):857～860
[37]Burger M. Crystal Growth and Impingement in Polymer Melts [J]. International Series of Numerical Mathematics,2003,147:65～74
[38]Wang L X, Li Q, Shen C Y. Numerical Simulation of Crystallization Morphology Evolution for Semi-crystalline Polymers in Injection Molding [J]. Polymer-Plastics Technology and Engineering[ISSN:0360-2559]
[39]唐曙光.基于Excel的实验数据最小二乘法计算探讨[J].大学物理实验,2003,16(4)：43-45
[40]马成良,张海军,李素平.现代试验设计优化方法及应用[M].郑州：郑州大学出版社,2007,70-72
[41]Li W. Zhang S W, Li Y. Simulation and off-line optimization of an acrylonitrile fluidized-bed reactor based on artificial neural network[J]. Chinese Jorunal of Chemical Engineering,2002,10(2):198～201
[42]Chow T T, Zhang G Q, Lin Z, et al. Global optimization of absorption chiller system by genetic algorithm and neural network[J]. Energy and Buildings,20028,34 (1):103～109
[43]Chen C R, Ramaswamy H S. Modeling and optimization of variable retort temperature(VRT) thermal processing using coupled neural networks and genetic algorithms [J]. Journal of Food Engineering,2002,53(3):209～220
[44]Shen C Y, Wang L X, Li Q. Optimization of injection molding process parameters using combination of artificial neural network and genetic algorithm method [J]. Journal of Materials Processing Technology,2007,183:412～418
[45]王小平,曹立明.遗传算法的理论、应用与软件实现[M].西安：西安交通大学出版社,2002,28-34
[46]王利霞.基于数值模拟的注塑成型工艺优化及制品质量控制研究[D].博士论文.郑州：郑州大学,2004
[47]Wang L X, Wang S C. Optimization of the parameters of crystallization kinetics model in non-isothermal conditions by the combination of simulation and genetic [R].郑州大学橡塑模具国家工程研究中心技术报告,2009
[2]Piorkowska E, Galeski A, Haudin J M. Critical assessment of overall crystallization kinetics theories and predictions [J]. Prog. Polym. Sci.,2006,31:549～575
[3]Lorenzo M L D, Silverstre C. Non-isothermal crystallization of polymers [J]. Prog. Polym. Sci.,1999,24:917～950
[4]Long Y, Shanks R A, Stachurski Z H. Kinetics of polymer crystallization [J]. Prog. Polym. Sci.1995,20:651-671
[5]刘结平,莫志深.聚合物结晶动力学[J].高分子通报,1991,4：199-207
[6]殷敬华,莫志深.现代高分子物理学(上册)[M].北京,科学出版社,2001
[7]林少全,林超群.聚乙烯管材专用料的DSC研究[J].现代塑料加工应用,2004,16(5)：38-41
[8]周丽莉,邓鹏扬,吴航等.(3-烃基丁酸-3-烃基戊酸)共聚物异相成核结晶行为[J].应用化学,2006,23(1)：89-93
[9]He X Q, X D M, Yang D C. Isothermal crystallization kinetics of poly(trimethylene terephthalate) under the influence of self-seeding nucleation [J]. Acta. Polymerica Sinica, 2006,3:414～417
[10]李剑,周持兴,王刚等.低等规聚丙烯的等温结晶动力学[J].高分子材料科学与工程,2002,18(6)：106-110
[11]Hertlein C, Saalwachter K, Strobl G. Low-field NMR studies of polymer crystallization kinetics:Changes in the melt dynamics [J]. Polymer,2006,47:7216～7221
[12]Ozawa T. Kinetics of non-isothermal crystallization [J]. Polymer,1971,12:150～158
[13]Sajkiewicz P, Carpaneto L, Wasiak A. Application of the Ozawa model to non-isothermal crystallization of poly(ethylene terephthalate) [J]. Polym.,2001,42 (12):5365～5370
[14]Hammami A, Spruiell J E, Mehrotra A K. Quiescent non-isothermal crystallization kinetics of isotactic polypropylenes[J]. Polym. Eng. Sci.,1995,35:797～804
[15]Li J, Fang Z P, Tong L F. Effect of multi-walled carbon nanotubes on non-isothermal crystallization kinetics of polyamide6 [J]. European Polymer Journal,2006 42(12):3230～3235
[16]Lopez L C, Wilkes G L. Non-isothermal crystallization kinetics of poly (p-phenylene sulphide)[J]. Polymer,1989,30:882～887
[17]Supaphol P, Dangseeyun N, Srimoaon P. Non-isothermal melt crystallization kinetics for poly (trimethylene terephthalate)/poly (butylene terephthalate) blends [J]. Polym. Test, 2004,23:175-185
[18]Jiao C, Wang Z, Liang X. Non-isothermal crystallization kinetics of silane crosslinked polyethylene [J]. Polym. Test,2005,24:71～80
[19]Hong P, Chung W, Hsu C. Crystallization kinetics and morphology of poly (trimethylene terephthalate)[J]. Polymer,2002,43:3335～3343
[20]Zhang Q, Zhang Z, Zhang H. Isothermal and non-isothermal crystallization kinetics of nylon-46[J].Polym Sci Part B:Polym. Phys.,2002,40:1784～1793
[21]Liu T X, Mo Z S, Zhang H F. Non-isothermal melt crystallization behavior of PEDEKmK[J].Polym. Sci.,1998,67(5):815～821
[22]Liu T X, Mo Z S, Zhang H F. Isothermal and non-isothermal melt crystallization kinetic behavior of poly(aryl ether biphenyl ether ketone ketone):PEDEKK[J]. Polym.,1998, 18(4):283～299
[23]An Y X, Dong L S, Mo Z S, et al. Non-isothermal crystallization kinetics of poly (β-hydroxylbutyrate)[J]. Polym. Sci, Polym. Phys.,199,36 (8):1305～1312
[24]Escleine J M, Monasse B, Wey E, et al. Influence of specimen thickness on isothermal crystallization kinetics [J]. Colloid & Polymer Sci.,1984,262:366～373
[25]周林洋.PBT非等温结晶动力学[J].合成树脂及塑料,2003,20(2)：13-15
[26]徐振淼,陈寿羲.光学解偏振法测定高聚物的结晶速度[J].高分子通讯,1979,No3
[27]张志英,康文华,张春玲.高聚物的非等温结晶动力学[J].高分子学报,1992,4：500-503
[28]Tao Hwang, Kamal M R. Morphological modeling of polymer solidification [J]. Polym Eng Sci,2000,40(6):1796～1808
[29]Tao Huang, Rey A D, Kamal M R. Structure evolution of spherulitic crystallization in semicrysatlline polymer films [J]. Macromolecules,1998,31:7791～7799
[30]Swaminarayan S, Charbon. Multi-scale model for polymer crystallization. I:Growth of individual spherulites [J]. Polym. Eng. Sci.,1998,38(4):634～656
[31]Haudin J M, Chenot J L. Numerical and Physical Modeling of Polymer Crystallization Part I:Theoretical and Numerical Analysis [J]. Polymer processing XIX,2004,3:267～274
[32]Monasse B, Smirnova J, Haudin J M, et al. Numerical and Physical Modeling of Polymer Crystallization Part II:Isothermal and Non-isothermal Crystallization Kinetics of a Polypropylene in 2 Dimensions-Experiments and Simulation [J]. Polymer,2004, 3:275-286
[33]Smirnova J, Silva L, Monasse B, et al. Identification of crystallization kinetics parameters by genetic algorithm in non-isothermal conditions [J]. Engineering Computations,2007, 24(5):486～513
[34]Haudin J M, Smirnova J, Silva L, et al. Modeling of Structure Development During Polymer Processing [J]. Polymer Science,2008,50(5):538～549
[35]Boyer S A E, Billon N, Haudin J M. Crystallization kinetics of polypropylenes. Effect of nucleation agents?[J].Suppl,2008,1:603～606
[36]Haudin J M, Boyer S A E. Crystallization of polypropylene at high cooling rates [J]. Suppl, 2009,2(1):857～860
[37]Burger M. Crystal Growth and Impingement in Polymer Melts [J]. International Series of Numerical Mathematics,2003,147:65～74
[38]Wang L X, Li Q, Shen C Y. Numerical Simulation of Crystallization Morphology Evolution for Semi-crystalline Polymers in Injection Molding [J]. Polymer-Plastics Technology and Engineering[ISSN:0360-2559]
[39]唐曙光.基于Excel的实验数据最小二乘法计算探讨[J].大学物理实验,2003,16(4)：43-45
[40]马成良,张海军,李素平.现代试验设计优化方法及应用[M].郑州：郑州大学出版社,2007,70-72
[41]Li W. Zhang S W, Li Y. Simulation and off-line optimization of an acrylonitrile fluidized-bed reactor based on artificial neural network[J]. Chinese Jorunal of Chemical Engineering,2002,10(2):198～201
[42]Chow T T, Zhang G Q, Lin Z, et al. Global optimization of absorption chiller system by genetic algorithm and neural network[J]. Energy and Buildings,20028,34 (1):103～109
[43]Chen C R, Ramaswamy H S. Modeling and optimization of variable retort temperature(VRT) thermal processing using coupled neural networks and genetic algorithms [J]. Journal of Food Engineering,2002,53(3):209～220
[44]Shen C Y, Wang L X, Li Q. Optimization of injection molding process parameters using combination of artificial neural network and genetic algorithm method [J]. Journal of Materials Processing Technology,2007,183:412～418
[45]王小平,曹立明.遗传算法的理论、应用与软件实现[M].西安：西安交通大学出版社,2002,28-34
[46]王利霞.基于数值模拟的注塑成型工艺优化及制品质量控制研究[D].博士论文.郑州：郑州大学,2004
[47]Wang L X, Wang S C. Optimization of the parameters of crystallization kinetics model in non-isothermal conditions by the combination of simulation and genetic [R].郑州大学橡塑模具国家工程研究中心技术报告,2009