H型钢热轧工艺过程数值分析及其仿真技术研究
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摘要
近年来对长型材力学性能的一致性和多样性的要求日趋严格,而其性能主要取决于钢的化学成分、晶粒度、关键的轧制及冷却工艺参数。此前的研究热点主要集中在建立再结晶和相变过程的物理冶金模型,并将其应用于分析板(带)材或者小截面型材轧制过程的数值分析,而对长型材中复杂断面型钢的热轧工艺过程的研究较少。
本文选择中型H型钢热轧工艺过程的综合数值分析为研究课题,分析和预测型钢热轧力能参数和轧件中的微观组织演变,深入到微观层面理解影响H型钢性能的工艺因素。其成果对于建立H型钢热轧全过程的尺寸精度和机械性能预报系统、优化轧制工艺参数等,具有重要的实际应用价值和理论意义。
建立了Q235钢高温整体流变应力模型。利用Gleeble-1500热模拟实验机,对Q235钢的高温变形行为进行了研究,得到了不同温度和变形条件下的流变应力数据。考虑热变形过程中金属动态再结晶的影响,建立了高温整体流变应力模型,在计算流变应力的同时分析了金属内部微观组织的演变过程,突破了传统经验模型仅能对热轧过程进行热力耦合分析的局限,将微观组织分析引入到型钢热轧过程的数值分析中。
建立了Q235钢的奥氏体晶粒加热长大动力学模型。利用带WZK-1可控硅温度控制器的加热炉、MM-6金相显微镜及图像分析仪,研究不同温度下奥氏体晶粒直径与保温时间之间的关系。利用金相实验观测得到的数据,建立了Q235钢的奥氏体晶粒加热长大动力学模型。利用该模型计算热轧坯料的初始奥氏体晶粒尺寸,分析了加热炉保温温度、保温时间对后续奥氏体晶粒的影响。
建立了Q235钢热变形过程中奥氏体晶粒演变动力学模型。用Gleeble-1500热模拟实验机对Q235圆柱试样进行压缩之后,立即用足量冷水淬火,然后沿试样压缩方向进行纵向剖切、研磨、抛光后制成金相试样,对金相试样浸蚀后,采用MM-6图像分析仪观察变形后试样不同部位的奥氏体晶界。建立了Q235奥氏体再结晶预报模型,利用该模型对不同变形条件下的奥氏体晶粒进行预测的平均误差为13.6%,相对于通用C-Mn钢奥氏体再结晶模型15.4%的平均预测误差,其预测精度进一步提高。
建立了多道次H型钢粗轧过程轧制负荷、腰部温度、腰部奥氏体晶粒直径的经验计算公式。尽管有限元结果可以提供轧件变形过程中应力、应变、温度、奥氏体晶粒直径、再结晶分数等数据的形象分布云图,但也存在计算时间长、步骤繁琐等不适应现场快速多变的生产节奏的缺点。所以,在对轧制过程有限元分析模型进行验证的基础上,通过4因素3位级的虚拟正交实验确定了影响H型钢轧制负荷、奥氏体晶粒直径各主要因素的主次顺序,建立了计算多道次H型钢孔型轧制的轧制负荷、腰部温度、腰部奥氏体晶粒直径的经验计算公式,避免了利用埃克隆德公式计算轧制负荷时需要确定轧件瞬时温度的困难。
提出了基于网格重构的多道次型钢热轧过程的数值分析流程。利用PYTHON和FORTRAN程序实现了多道次热轧过程有限元分析模型间节点温度、累积塑性应变、自定义场变量等的数据传递,确保了多道次H型钢大变形塑性过程及其类似变形过程数值分析的完成。并且在改进的ABAQUS软件平台上,成功地对H400×200、H250×125、H200×200规格H型钢粗轧全过程进行了综合数值分析,详细地给出了热轧过程中轧制负荷、轧件温度、轧件变形、以及轧件内奥氏体晶粒的演变过程等的计算结果。并且利用红外测温设备(NEC热像仪TH5104R)及现场监测系统测量的大量数据,验证了轧件温度和轧制负荷数值分析结果的正确性。
利用FORTRAN语言编写VUMAT(自定义材料模型)、UFRIC(自定义摩擦模型)、USDFLD(自定义场变量模型)、FILM(自定义对流换热模型)等用户子程序,实现了自定义整体流变应力模型和再结晶模型的嵌入,提高了有限元模型的计算精度。
通过对热轧过程进行热、力、微观三者之间的耦合分析,给出了工艺参数的调整对微观组织影响的结果,避免了进行轧制规程优化时单纯以轧制负荷、温度、外形尺寸为优化依据,为从微观角度出发提高热轧质量提供了理论依据和技术支持。
The demands of the diversity and consistence of mechanical performances for long products have been going high in recent years, and the mechanical performance depends on the chemical elements of the steel, grain size, and the critical rolling and cooling parameters. The researches were mainly focusing on creating metallurgy models for recrystallization and phase transformation, and were utilized to the rolling processes of strip and small cross-section shape-metal, but leaving the complex cross-section shape-metal under-researched.
This dissertation focuses on the integrated numerical analysis of the medial size H-beam rolling process. The rolling force, temperature and the microstructure were analyzed during the rolling process, so get the knowledge of the effects on the H-beam performances from a microstructure point of view. The results play a vital role in constructing the dimension precision and mechanical performances predications system, optimizing rolling parameters et al.
The dissertation is consisted of the following parts:
First, a unitary flow stress model of Q235 steel was developed. Gleeble-1500 tester system was used to study the plastic deformation behaviors of the material under high temperature. A unitary flow stress model, capable of taking the stress softening caused by recrystallization into account, was created based on the experiments results. The model can be used to calculate the size and volume fraction of the austemte grains, including the flow stress inside the stock during the hot deformation process. So, the interactions between the deformation parameters and microstructure can also be studied at the same time of performing temperature-displacement finite element method (FEM) analyses.
Second, an austenite grain growth model of Q235 steel during the heat up process was developed. Relationship between the austenite grain size and the heat preservation time was studied at different temperature using the WZK-1 heater and the MM-6 graphic analyzer. The model coefficients were figured out by regression analysis of the test results, and it's capable of calculating the origin austenite grain size of the hot stock. So the effects on the grain size of the heater temperature and preservation time could be studied during the following deformation process.
Third, an austenite grain evolution model of Q235 steel during the hot deformation was developed. Hardly after compressed by the punchers of the Gleeble-1500 tester, the cylindrical samples were quenched. Samples were made by splitting along the direction of compressing and polished for austenite grain observation. Eroded in the corrosive mixed by supersaturation picric acid and scour for 5 to 10 minutes at the temperature of 50-70℃, the austenite grain boundaries at different zones of the cross-section , when the compression was barely completed, can be observed by the MM-6 graphic analyzer. The austenite grain recrystallization model of the Q235 material was developed on the results, with a prediction error of 13.6%. Compared with the prediction error of 15.4% of the general C-Mn model, its prediction precision is 11.7% higher.
Fourth, an analysis approaches for numerical analysis of multi-pass shape metal hot rolling process was developed based on element re-mesh. The data transfer between different passes analyses, mainly including the node temperature, the accumulated plastic strain and user defined filed variables, were completed by PYTHON and FORTRAN program. The numerical analysis of the H-Beam hot rolling, a big plastic deformation process, could be completed successfully utilizing the approaches. The efficiency and precision were assured by the re-mesh, data transfer provided by the user-defined programs and the steady state detection provide by the ABAQUS.
Fifth, the experiential formulas were developed for computing the rolling force, temperature, and the austenite grain size at the middle part of H-shape cross section. Although the stress, strain, temperature, and austenite grain size could be presented in detail from the FEM analysis results, it also has the following shortcomings, such as long calculating time, complicated steps etc. And this makes it difficulty to meet with real-time production requirements. The parameters affecting the rolling force and austenite grain size were investigated through four parameters and three levels numerical experiments after the FEM model has been validated by the measuring results.
Sixth, user subroutines were programmed to implement the user-defined models. All kinds of user-defined models could be embedded into the numerical calculating process of the ABAQUS. The following subroutines, including user-defined material (VUMAT), user-defined friction (VFRIC), user-defined field (VSDFLD), and user-defined film (FILM) were presented in the dissertation. The solution precision could be enhanced the embedded subroutines, and the most important part is the analysis of user-defined parameters.
The effects of the hot rolling parameters adjustment on the microstructure were analyzed by the temperature-displacement-microstructure analysis. So the hot rolling schedule optimization could be implemented for improving the quality by the view of microsturuture.
本文选择中型H型钢热轧工艺过程的综合数值分析为研究课题,分析和预测型钢热轧力能参数和轧件中的微观组织演变,深入到微观层面理解影响H型钢性能的工艺因素。其成果对于建立H型钢热轧全过程的尺寸精度和机械性能预报系统、优化轧制工艺参数等,具有重要的实际应用价值和理论意义。
建立了Q235钢高温整体流变应力模型。利用Gleeble-1500热模拟实验机,对Q235钢的高温变形行为进行了研究,得到了不同温度和变形条件下的流变应力数据。考虑热变形过程中金属动态再结晶的影响,建立了高温整体流变应力模型,在计算流变应力的同时分析了金属内部微观组织的演变过程,突破了传统经验模型仅能对热轧过程进行热力耦合分析的局限,将微观组织分析引入到型钢热轧过程的数值分析中。
建立了Q235钢的奥氏体晶粒加热长大动力学模型。利用带WZK-1可控硅温度控制器的加热炉、MM-6金相显微镜及图像分析仪,研究不同温度下奥氏体晶粒直径与保温时间之间的关系。利用金相实验观测得到的数据,建立了Q235钢的奥氏体晶粒加热长大动力学模型。利用该模型计算热轧坯料的初始奥氏体晶粒尺寸,分析了加热炉保温温度、保温时间对后续奥氏体晶粒的影响。
建立了Q235钢热变形过程中奥氏体晶粒演变动力学模型。用Gleeble-1500热模拟实验机对Q235圆柱试样进行压缩之后,立即用足量冷水淬火,然后沿试样压缩方向进行纵向剖切、研磨、抛光后制成金相试样,对金相试样浸蚀后,采用MM-6图像分析仪观察变形后试样不同部位的奥氏体晶界。建立了Q235奥氏体再结晶预报模型,利用该模型对不同变形条件下的奥氏体晶粒进行预测的平均误差为13.6%,相对于通用C-Mn钢奥氏体再结晶模型15.4%的平均预测误差,其预测精度进一步提高。
建立了多道次H型钢粗轧过程轧制负荷、腰部温度、腰部奥氏体晶粒直径的经验计算公式。尽管有限元结果可以提供轧件变形过程中应力、应变、温度、奥氏体晶粒直径、再结晶分数等数据的形象分布云图,但也存在计算时间长、步骤繁琐等不适应现场快速多变的生产节奏的缺点。所以,在对轧制过程有限元分析模型进行验证的基础上,通过4因素3位级的虚拟正交实验确定了影响H型钢轧制负荷、奥氏体晶粒直径各主要因素的主次顺序,建立了计算多道次H型钢孔型轧制的轧制负荷、腰部温度、腰部奥氏体晶粒直径的经验计算公式,避免了利用埃克隆德公式计算轧制负荷时需要确定轧件瞬时温度的困难。
提出了基于网格重构的多道次型钢热轧过程的数值分析流程。利用PYTHON和FORTRAN程序实现了多道次热轧过程有限元分析模型间节点温度、累积塑性应变、自定义场变量等的数据传递,确保了多道次H型钢大变形塑性过程及其类似变形过程数值分析的完成。并且在改进的ABAQUS软件平台上,成功地对H400×200、H250×125、H200×200规格H型钢粗轧全过程进行了综合数值分析,详细地给出了热轧过程中轧制负荷、轧件温度、轧件变形、以及轧件内奥氏体晶粒的演变过程等的计算结果。并且利用红外测温设备(NEC热像仪TH5104R)及现场监测系统测量的大量数据,验证了轧件温度和轧制负荷数值分析结果的正确性。
利用FORTRAN语言编写VUMAT(自定义材料模型)、UFRIC(自定义摩擦模型)、USDFLD(自定义场变量模型)、FILM(自定义对流换热模型)等用户子程序,实现了自定义整体流变应力模型和再结晶模型的嵌入,提高了有限元模型的计算精度。
通过对热轧过程进行热、力、微观三者之间的耦合分析,给出了工艺参数的调整对微观组织影响的结果,避免了进行轧制规程优化时单纯以轧制负荷、温度、外形尺寸为优化依据,为从微观角度出发提高热轧质量提供了理论依据和技术支持。
The demands of the diversity and consistence of mechanical performances for long products have been going high in recent years, and the mechanical performance depends on the chemical elements of the steel, grain size, and the critical rolling and cooling parameters. The researches were mainly focusing on creating metallurgy models for recrystallization and phase transformation, and were utilized to the rolling processes of strip and small cross-section shape-metal, but leaving the complex cross-section shape-metal under-researched.
This dissertation focuses on the integrated numerical analysis of the medial size H-beam rolling process. The rolling force, temperature and the microstructure were analyzed during the rolling process, so get the knowledge of the effects on the H-beam performances from a microstructure point of view. The results play a vital role in constructing the dimension precision and mechanical performances predications system, optimizing rolling parameters et al.
The dissertation is consisted of the following parts:
First, a unitary flow stress model of Q235 steel was developed. Gleeble-1500 tester system was used to study the plastic deformation behaviors of the material under high temperature. A unitary flow stress model, capable of taking the stress softening caused by recrystallization into account, was created based on the experiments results. The model can be used to calculate the size and volume fraction of the austemte grains, including the flow stress inside the stock during the hot deformation process. So, the interactions between the deformation parameters and microstructure can also be studied at the same time of performing temperature-displacement finite element method (FEM) analyses.
Second, an austenite grain growth model of Q235 steel during the heat up process was developed. Relationship between the austenite grain size and the heat preservation time was studied at different temperature using the WZK-1 heater and the MM-6 graphic analyzer. The model coefficients were figured out by regression analysis of the test results, and it's capable of calculating the origin austenite grain size of the hot stock. So the effects on the grain size of the heater temperature and preservation time could be studied during the following deformation process.
Third, an austenite grain evolution model of Q235 steel during the hot deformation was developed. Hardly after compressed by the punchers of the Gleeble-1500 tester, the cylindrical samples were quenched. Samples were made by splitting along the direction of compressing and polished for austenite grain observation. Eroded in the corrosive mixed by supersaturation picric acid and scour for 5 to 10 minutes at the temperature of 50-70℃, the austenite grain boundaries at different zones of the cross-section , when the compression was barely completed, can be observed by the MM-6 graphic analyzer. The austenite grain recrystallization model of the Q235 material was developed on the results, with a prediction error of 13.6%. Compared with the prediction error of 15.4% of the general C-Mn model, its prediction precision is 11.7% higher.
Fourth, an analysis approaches for numerical analysis of multi-pass shape metal hot rolling process was developed based on element re-mesh. The data transfer between different passes analyses, mainly including the node temperature, the accumulated plastic strain and user defined filed variables, were completed by PYTHON and FORTRAN program. The numerical analysis of the H-Beam hot rolling, a big plastic deformation process, could be completed successfully utilizing the approaches. The efficiency and precision were assured by the re-mesh, data transfer provided by the user-defined programs and the steady state detection provide by the ABAQUS.
Fifth, the experiential formulas were developed for computing the rolling force, temperature, and the austenite grain size at the middle part of H-shape cross section. Although the stress, strain, temperature, and austenite grain size could be presented in detail from the FEM analysis results, it also has the following shortcomings, such as long calculating time, complicated steps etc. And this makes it difficulty to meet with real-time production requirements. The parameters affecting the rolling force and austenite grain size were investigated through four parameters and three levels numerical experiments after the FEM model has been validated by the measuring results.
Sixth, user subroutines were programmed to implement the user-defined models. All kinds of user-defined models could be embedded into the numerical calculating process of the ABAQUS. The following subroutines, including user-defined material (VUMAT), user-defined friction (VFRIC), user-defined field (VSDFLD), and user-defined film (FILM) were presented in the dissertation. The solution precision could be enhanced the embedded subroutines, and the most important part is the analysis of user-defined parameters.
The effects of the hot rolling parameters adjustment on the microstructure were analyzed by the temperature-displacement-microstructure analysis. So the hot rolling schedule optimization could be implemented for improving the quality by the view of microsturuture.
引文
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