Prediction of void closure in steel slabs by finite element analysis

Closure of a spherical voids in a steel slab under plane-strain deformation was investigated using the rigidplastic finite-element method. Variations in the major and minor axes of a void from finite element analysis of a void model were related to the minimum principal strain and hydrostatic stress from finite element analysis of a non-void model. The correlation curves were obtained and a method using these curves to predict the void closure progress was proposed. The method was successfully applied to deformation processes such as simple compression, forging and rolling. Since hydrostatic stress also influenced void closure, the effective strain by itself was not sufficiently capable of predicting void closure. However, the effective strain was used to predict void closure for a specific process because it reached about 0.7 in compression or forging and about 0.78 during rolling as the void completely closed.     

Rigid-plastic finite element analysis of plastic deformation of porous metal sheets containing internal void defects

Using rigid-plastic finite element DEFORM-2D and -3D software, this study simulates the plastic deformation of metal sheets at the roll gap during the sheet rolling process. The study focuses specifically upon the deformation of porous metal sheets containing internal void defects. The present numerical analysis investigates the relative density distributions, the void closure behavior, the deformation mechanisms and the stress–strain distributions around the internal voids for various rolling conditions. The influences on the dimensions of the final void of the thickness reduction, the initial internal void dimensions, the friction factors and the relative density are systematically discussed. The critical rolling conditions also investigated. A series of sheet rolling experiments are performed in order to verify the validity of the simulation results. The current numerical results provide a valuable source of reference for the design of pass schedules for porous metals undergoing rolling processes.     

Springback prediction for incremental sheet forming based on FEM-PSONN technology

In the incremental sheet forming (ISF) process, springback is a very important factor that affects the quality of parts. Predicting and controlling springback accurately is essential for the design of the toolpath for ISF. A three-dimensional elasto-plastic finite element model (FEM) was developed to simulate the process and the simulated results were compared with those from the experiment. The springback angle was found to be in accordance with the experimental result, proving the FEM to be effective. A coupled artificial neural networks (ANN) and finite element method technique was developed to simulate and predict springback responses to changes in the processing parameters. A particle swarm optimization (PSO) algorithm was used to optimize the weights and thresholds of the neural network model. The neural network was trained using available FEM simulation data. The results showed that a more accurate prediction of springback can be acquired using the FEM-PSONN model.     

Prediction of influence parameters on the hot rolling process using finite element method and neural network

In the present investigation, a hot rolling process of AA5083 aluminum alloy is simulated using the finite element method. The temperature distribution in the roll and the slab, the stress, strain and strain rate fields, are extracted throughout a steady-state analysis of the process. The main hypotheses adopted in the formulation are: the thermo-viscoplastic behavior of the material expressed by Perzyna constitutive equation and rolling under plane-deformation conditions. The main variables that characterize the rolling process, such as the geometry of the slab, load, rolling speed, percentage of thickness reduction, initial thickness of the slab and friction coefficient, have been expressed in a parametric form giving a good flexibility to the model. The convergence of the results has been evaluated using experimental and theoretical data available in the literature. Since the FE simulation of the process is a time-consuming procedure, an artificial neural network (ANN) has been designed based on the back propagation method. The outputs of the FE simulation of the problem are used for training the network and then, the network is employed for prediction of the behavior of the slab during the hot rolling process.     

A Model to Predict Recrystallization Kinetics in Hot Strip Rolling Using Combined Artificial Neural Network and Finite Elements

A thermo-mechanical model has been developed to establish a coupled heat conduction and plastic flow analysis in hot-rolling process. This model is capable of predicting temperature, strain, and strain rate distributions during hot rolling as well as the subsequent static recrystallization fraction and grain size changes after hot deformation. Finite element and neural network models are coupled to assess recrystallization kinetics after hot rolling. A new algorithm has been suggested to create differential data sets to train the neural network. The model is then used to predict histories of various deformation variables and recrystallization kinetics in hot rolling of AA5083. Comparison between the theoretical and the experimental data shows the validity of the model.     

神经网络与有限元结合在轧机板形预报中的应用研究

通过有限元仿真分析,较准确的模拟了带钢轧制过程,获取对轧机板形影响较大的参数值,并将其结果作为训练样本对神经网络进行训练,建立了较为理想的基于神经网络的板形预测模型,实现了轧制过程中的板形参数的预报。仿真结果表明该神经网络与有限元结合的板形预测模型可获得良好的预测精度,弥补了传统板形预测模型的预测精度不能满足板形在线控制要求的缺陷。     

环件冷辗扩技术现状和发展

简要地介绍了环件冷辗扩原理、冷辗扩工艺、冷辗设备、加工过程控制参数、模具寿命及有限元模拟技术的现状和发展,并指出了环件冷辗扩还缺乏精确而系统性的研究,弹塑性有限元研究才刚刚起步,通过模拟来优化加工过程参数在国际上也几乎没有公开发表的文献。因此,应该从理论、有限元模拟、材料、设备、热处理、模具等多学科联合攻关研究,才能使我国的环件冷辗扩技术跃上一个新的台阶。     

环件冷辗扩技术现状和发展

介绍了环件冷辗扩原理、冷辗扩工艺、冷辗设备、加工过程控制参数、模具寿命及有限元模拟技术的现状和发展。文中指出了环件冷辗扩还缺乏精确而系统性的研究,弹塑性有限元研究才刚刚起步,而在我国还是一个空白。同时,通过模拟来优化加工过程参数在国际上也几乎没有公开发表的文献。因此,应该从理论、有限元模拟、材料、设备、热处理、模具等多学科联合攻关研究,才能使我国的环件冷辗扩技术跃上一个新的台阶。     

Investigation on Temperature Change of Cold Magnesium Alloy Strips Rolling Process with Heated Roll

Magnesium alloy strips are widely used in aerospace, automotive industry, etc., which are difficult to produce through cold forming process due to their poor deformation ability. In this article, we studied whether the rolling process with heated roll could be used to roll cold magnesium alloy strips. Thermal-mechanical finite element simulation of the rolling process, using heated roll and cold strips to produce the magnesium alloy strips, was carried out. Influences of roll temperature, rolling velocity, rolling reduction ratio, and initial strip thickness on the thermal field and the mean temperature of magnesium alloy strips were analyzed. Both the heated area in strips in rolling deformation zone and the mean temperature of strips at exit of rolling deformation zone increase with increasing the roll temperature and/or rolling reduction ratio, and/or with decreasing the rolling velocity and/or initial strip thickness. Finally, a formula was developed to predict the mean temperature of strips under different rolling conditions, which also could be used to calculate the critical value of parameters in rolling process.     

The application of neural networks in the preform design of the upsetting process

Design of the optimum preform for near net shape manufacturing is a crucial step in upsetting process design. In this study, artificial neural networks (ANN) are used to consider different interfacial friction conditions between the top and bottom die and billet interface. Two back propagation neural networks are trained based on finite element analysis results considering ten interfacial friction conditions and varying geometrical and processing parameters, to predict the optimum preform for high strength (HS) steel and commercial aluminum. Neural network predictions were verified for three new problems of both HS steel and commercial aluminum and observed that these are in close match with their simulation counterparts. It was further Experimentally verified with two commercial aluminum specimens and observed that the preform values predicted by ANN are in good agreement with experimental results.     

Predictive modeling of grain refinement during multi-pass cold rolling

Recently, grain refinement and grain misorientation have been experimentally studied for various materials with ultra-fine grained microstructures, which are achieved by the multi-pass cold rolling process. In this paper, a numerical framework is developed to model the evolution of grain size and grain misorientation based on a dislocation density-based material model. Novel finite element models embedded with the dislocation density-based material subroutine are developed to model the plastic deformation and microstructural evolution during the multi-pass cold rolling process. The multi-pass cold rolling processes of commercially pure titanium (CP Ti) and aluminum (AA 1200) are simulated in order to assess the validity of the numerical solution through comparison with experiments. The dislocation density-based material models are developed for CP Ti and AA 1200, which reproduce the observed material constitutive mechanical behavior under various strains, strain rates and temperatures occurring in the cold rolling process. It is shown that the developed model captures the essential features of the material mechanical behaviors and predicts a minimum grain size of below 100 nm after five-pass cold rolling of CP Ti with equivalent strains up to 2.07 and the average incidental dislocation boundary (IDB) misorientation angle increased to 4.6° after six-pass cold rolling of AA 1200 with equivalent strains accumulated to 5.77.     

Application of artificial neural network and Taguchi method to preform design in metal forming considering workability

This study describes a new method of perform design in muti-stage metal forming processes considering workability limited by ductile fracture. The finite element simulation combined with ductile fracture criterion has been performed in order to predict ductile fracture. The artificial neural network using the Taguchi method has been implemented for minimizing objective functions relevant to the forming process. The combinations of design parameters used in finite element simulation are selected by orthogonal array in statistical design of experiments. The orthogonal array and the result of simulation are used as train data for artificial neural networks. The cold heading process is taken as an example of designing preforms which do not form any fracture in the finished product. The results of analysis to validate the proposed design method are presented.     

薄壁变形机匣件限位检测机理分析与预测

为了研究带有一定公差的薄壁机匣件二次装夹变形规律,以约束表面和相关表面为研究对象,建立了机匣件约束表面与相关表面变形关系的数学分析模型。使用有限元法模拟变形机匣件的限位装夹过程,将模拟产生的数据作为BP神经网络的训练样本,借助神经网络的非线性映射能力建立了装夹变形的预测模型。通过对某航空材料7075机匣件作试验分析,验证了所构建的三维有限元模型与神经网络预测模型较为合理,能够为机匣件的加工制造提供反馈,为机匣件的装配分析提供良好的校验。     

Three-dimensional analysis and computer simulation of shape rolling by the finite and slab element method

In this study a new simplified 3-D numerical method and the associated computer program have been developed to simulate the shape rolling process. The 2-D rigid-plastic finite element method (FEM), used for the generalized plane-strain condition, is combined with the slab method. This method, called FSEM (finite and slab element method), reduces the computational effort without losing much accuracy obtained in the 3-D computer simulation of the shape rolling process. The FSEM has been used to develop a computer program, called TASKS for three-dimensional analysis of shape-rolling as a kinematically steady-state process. The program TASKS has been used to simulate the metal flow and the bulge profile in flat rolling of slabs, the shape rolling of a simple H section, and the rolling of a practical H-beam section. In flat rolling, predicted spreads agreed well with experimental results, given in the literature. The metal flow in rolling of a simple H section was compared with results of a full 3-D simulation, obtained by other investigators. The comparison indicated that the present predictions give quite good results. Finally, the predictions made for a practical pass, used in rolling H sections, also compared well with experimental data.     

六辊冷连轧机带钢边降控制性能仿真研究

以首钢京唐公司2 230 mm冷连轧机为研究对象,针对目前国内外板带材生产中被广泛选用的CVC冷轧机机型,运用ABAQUS仿真软件建立了3D有限元模型,对比分析了ESS冷轧机对带钢边降的控制性能,证明ESS冷轧机对带钢边部减薄的控制较好。通过ESS冷轧机3D有限元模型,实现了对超宽薄极限规格带钢轧制过程的模拟;深入分析了ESS冷轧机对带钢边部减薄的控制规律。结合现场轧制数据,对有限元模型进行了现场验证,模拟值与实测值切合度很高,相对误差在10 μm以内,绝对误差在0.69%以内。     

基于遗传神经网络的压铸机座板结构优化设计

在对压铸机合模机构进行结构设计时，利用神经网络的非线性映射能力，通过少量样本的有限元分析结果，训练出表述结构参数间函数关系的神经网络模型，然后利用遗传算法的全局寻优性找到神经网络模型表述的目标函数的最优结构参数，从而解决结构优化设计的瓶颈和智能问题，利用这种优化设计策略，设计了压铸机合模机构座板，结果表明了该方法的高效性。     

Ring rolling process simulation by the three dimensional finite element method

The finite element code “RING” was developed for the analysis of ring rolling. A special feature of the program is the updating procedure in three-dimensional deformation. A spatially fixed mesh system including deforming region of the workpiece is constructed based on the shape changes of the ring at each time step. Several simulations are performed with the program “RING”, and the results are compared with experimental data found in the literature. Good agreement between the simulation results and experiments was obtained in terms of geometrical changes of rings in plain ring rolling and T-shaped profiled ring rolling.     

沟球环件冷辗扩过程中截面变化规律

在沟球环件冷辗扩过程中,环件外径的增长预测和导向辊的位置确定是确保平稳辗扩的条件之一,而这两者的决定因素在于辗扩过程中截面形状变化。采用商业软件ABAQUS/Explicit对冷辗扩过程进行三维建模,预测沟球截面环件的直径增长和截面形状变化过程。在D56G90型冷辗环机上进行实验,测量了不同阶段的环件直径和沟球截面形状。将实验测量结果分别与解析计算结果和有限元计算结果进行比较,得出三者之间的差别,从而发现误差。利用解析结果和实验结果来修正三维有限元模型,以便更加精确地利用有限元模型来预测环件直径的增长规律和截面变化规律。模拟结果可以用于指导环件冷辗扩的工艺制定和生产,以期提高环件的质量。     

冷轧带钢温度演变及影响因素研究

为了探究冷轧过程及轧制工艺参数对带钢温度的影响及演变规律,采用有限元方法对冷轧带钢进行建模,利用温度场反算的方法确定了带钢和轧辊间的传热热流密度,在此基础上通过改变模型参数对带钢温度场进行了模拟计算。结果表明,带钢温度在前4架轧制区呈阶梯式增长趋势,而在末机架出口呈下降趋势;此外,带钢出口温度随轧制速度、道次压下率、摩擦因数、变形抗力等的增加而升高。     

板带轧制边界元模拟系统的开发和利用

为了促进轧机和轧制技术的进一步发展，进一步研究张力对板形的作用机理，需要结合轧件三维变形分析来进行。建立了三维弹塑性问题的边界元方法，并用此方法模拟了冷轧板带三维轧制过程，讨论了改变前、后张力时，轧件的三维变形特点。结果显示：增加张力可以限制金属横向流动，加大厚向变形，使端面厚度更加均匀。由此证明给出的模拟系统在轧制问题的分析中是有效的。