3D FE Analysis of Thermal Behavior of Billet in Rod and Wire Hot Continuous Rolling Process

An FE model was developed to study thermal behavior during the rod and wire hot continuous rolling process. The FE code MSC. Marc was used in the simulation using implicit static arithmetic. The whole rolling process of 30 passes was separated and simulated with several continuous 3D elastic-plastic FE models. A rigid pushing body and a data transfer technique were introduced into this model. The on-line experiments were conducted on 304 stainless steel and GCr15 steel hot continuous rolling process to prove the results of simulation by implicit static FEM. The results show that the temperature results of finite element simulations are in good agreement with experiments, which indicate that the FE model developed in this study is effective and efficient.

Temperature field analysis and its application in hot continuous rolling of Inconel 718 superalloy

A coupled thermo-mechanical model containing metal flow and temperature field for calculating temperature variation has been developed on fourteen-pass hot continuous rolling of round rod for Inconel 718 alloy using 3D elastic-plastic finite element method （FEM）. The temperature of characteristic analysis points in the intermediate cross-section of the workpiece has been simulated at initial temperature ranging from 960 to 1000 ℃ and initial velocity in range of 0.15-0.55 m·s^-1. Based on finite element analysis and microstructural observation in cylindrical hot compression experiments, the appropriate hot continuous rolling technologies have been designed for rod products with different diameters. For a real rolling practice, the simulated surface temperature was examined and is in good agreement with the measured one.

Deformation Stability of GH4033 Superalloy in the Hot Continuous Rolling Process Based on Dynamic Material Model and Finite Element Model

The flow stress behavior of GH4033 superalloy was determined by the hot compression tests at the temperatures of 1223-1473 K and the total strains of 0.6 with the strain rates of 0.001-30.0 s^(-1) by using cylindrical samples.The processing maps based on the dynamic material model(DMM)combined with the corresponding microstructure observations indicate the reasonable processing domain locating at the strain rates of 0.1-1.0 s^(-1) and the deformation temperature of 1273-1423 K.Meanwhile,the numerical simulation based on finite element model(FEM)described the variation of the effective strain,effective strain rate and the temperature for the core node,and unveiled the influence of the hot rolling parameters considering the initial temperature(T_(0))range of 1223-1473 K and the first-stand biting velocity(v_(0))range of 0.15-0.35 m·s^(-1).Furthermore,the deformation stability of GH4033 superalloy in the round rod hot continuous rolling(HCR)process is described and analyzed by coupling the three-dimensional(3-D)processing map,and the spatial trajectory lines were determined by the numerically simulated temperatures,the strains and the strain rates.Finally,the results show that the hot deformation stability of GH4033 can be achieved by the rolling process parameters located at T_(0)=1423 K and v_(0)=0.25 m·s^(-1).Additionally,the practical HCR processes as T_(0)=1423 K and v_(0)=0.15,0.25,0.35 m·s^(-1) were operated to verify the influence of the hot rolling parameters on the hot deformation stability by the microstructure observation of the final products.

Full-length model with multi-point settings for finishing rolling

Thickness,width,temperature,and profile are considered as control targets in process control of hot strip finishing rolling. The pre-calculated settings of the model information include rolling force,cooling water flow between stands,bending force,and roll shifting position. Without changing the load distribution,the interaction among thread speed,rolling force,rolling power,and cooling water flow between stands is comprehensively considered based on the quantifiable relationship among speed,force,and temperature. This paper proposes a full-length multi-point-setting model that uses the settings of strip head to combine the rolling speed diagram with the target finishing mill delivery temperature( FDT) to achieve the calculation of the control parameters along full length of strip. Traditional models cannot effectively predict rolling force of strip body or the maximum and minimum temperatures of FDT. It is also difficult for traditional models to suppress fluctuations in shape accuracy of full-length strip or improve the shape accuracy of the product. Calculation results show that the proposed full-length multi-point-setting model can provide the control parameters for temperature and rolling-force over full length of strip,predict the risk of rolling exceeding the equipment capability,and improve the shape accuracy and rolling stability of hot-rolled products.

Application of FEM to Hot Continuous Rolling Process for Inconel 718 Alloy Round Rod

A finite element model for coupled thermo-meehanical analysis has been developed in hot continuous rolling process for Inconel 718 alloy round rod with diameter of 45 mm. The stability of this alloy is discussed by integration of FEM and processing map reported in literatures. The result shows that the stability of Inconel 718 alloy is analyzed effectively during that process and good stability appears as the initial temperature is 960 ℃ and the initial velocity is from 0. 15 to 0.45 m · s^-1 or the initial temperature is 980 ℃ and the initial velocity is from 0. 15 to 0. 25 m · s^-1.

Mechanical Property Prediction of Strip Model Based on PSO-BP Neural Network

Mechanical property prediction of hot rolled strip is one of the hotspots in material processing research. To avoid the local infinitesimal defect and slow constringency in pure BP algorithm, a kind of global optimization algorithm-particle swarm optimization （PSO） is adopted. The algorithm is combined with the BP rapid training algorithm, and then, a kind of new neural network （NN） called PSO-BP NN is established. With the advantages of global optimization ability and the rapid constringency of the BP rapid training algorithm, the new algorithm fully shows the ability of nonlinear approach of multilayer feedforward network, improves the performance of NN, and provides a favorable basis for further online application of a comprehensive model.