Materials Science Forum Vol. 762

Abstract: The introduction of materials modelling into computer-aided engineering (CAE) processing simulation has become popular in recent years, whereas the fundamental challenge lies in the development of material models that can calculate the properties essential for processing design and simulation. This paper reviews the recent development of such models and the material data that can be calculated include physical, thermophysical, and mechanical properties, as well as phase transformation kinetics. The calculated material data has been used as input to numerous CAE packages for the simulation of casting, welding, forming and heat treatments. Two case studies are presented here, one on the simulation of residual stress in linear friction welding of titanium alloys, and the other on the prediction of distortion and residual stress in heat-treated large steel rings.

Abstract: Mathematical Modeling is an effective technique for prediction of process parameters in industrial processes. Artificial Neural Network (ANN) technique has also been used to recognize a pattern in the given data by training itself. Further the trained network is used for future prediction of process parameters on the basis of the pattern recognition. The mathematical models are based on some ideal assumptions which are not valid in practical industrial conditions. Similarly high variability in industrial data makes pattern recognition difficult for ANN models and leads to high errors of prediction. In the present work, an attempt has been made to develop a hybrid model by integrating two mathematical models and ANN model for prediction of roll force during hot rolling of flat rolled steel products. The mathematical equations for roll force have been derived from the pressure distribution equation derived by Sims and Tselikov. A feed-forward network with back-propagation algorithm has been selected for ANN. All the three methods have been converted into computer code using Visual Basic.Net programming language. The hybrid model has been trained with about 2500 hot rolled steel coil data collected from Bokaro Steel Plant and Rourkela Steel Plant consisting of three different steel grades. The hybrid model has been validated with measured data of about 1000 coils. Combinations of ANN network in hybrid model having different number of hidden neurons and learning rate have been formulated, trained and validated. The final hybrid model has been selected from these combinations which has maximum accuracy. Also Multi-variable optimization technique can be used to find out the values for various input conditions which affect the flow stress and the roll force, minimizing the Root Mean Square Error. When comparing the root mean square error (RMSE) of model, it has been found that the RMSE of hybrid model is about 25% less than that of Mathematical Model.

Abstract: Severe Plastic Deformation (SPD) is well known process for producing nanostructured material from coarse material. Present paper is an effort to integrate the two well known SPD techniques Equal Channel Angular Pressing (ECAP) and Twist Extrusion (TE) to develop a new Hybrid ECAP (HECAP) technique that can produce nanostructured material more economically. In this technique, the specimen is subjected to both ECAP and TE in the same die setup. Finite Element (FE) modeling of metal forming processes has become an important tool for designing feasible production processes, because of its unique capability to describe the complex geometry and boundary conditions. FE Modeling of the above hybrid process is attempted in FORGE. The simulation results clearly depict the change in equivalent strain in the entire specimen on account of this process upto four passes. A comparison is made between FE results of simple ECAP and HECAP upto four passes. The study indicated that equivalent strain is much higher in case of HECAP in comparison to ECAP for same friction conditions. Also, the study is extended to analyse the effect of friction, channel angle and forging force on equivalent strain using current FE model. HECAP opens new possibilities for improving equivalent strain in same number of passes as compared to ECAP. This study is expected to contribute in forming UFG materials that are useful for automobile and aerospace industries.

Abstract: The experimental planning method has been used for the examination of the combined effect of the temperature, strain, strain rate and time elapsed from the end of deformation to the start of quenching parameters of the Thermomechanical Control Processing on the structure and mechanical properties. Simulation of Thermomechanical Control Processing for the definite cross-section of profile by Finite Element Method on the base of the data obtained by the experimental planning method allowed to predict structure and mechanical properties and to develop computer modelling for the different cross-section of rolling profile.

Abstract: Surface Mechanical Attrition Treatment (SMAT) is a recent process that enables to nanocrystallise the surface of metallic alloys. It can thus enhance mechanical properties of the treated material by inducing a grain refinement down to the nanometre scale, in the top surface layer. This nanocrystallisation process leads to different effects that were successively studied on several metallic materials. In the present work, investigations are carried out on the modelling of SMAT. A simulation of the shot dynamics is performed using different process parameters, with the aim to obtain the impact velocity field on the treated surface. This field is then used as an input for a finite element model to predict the induced grain refinement. The evolution of the micro and nanostructures are then calculated using a micromechanical approach, which takes into account the dislocations and their interactions. Coupled with a finite element analysis, this approach enables to deduce the influence of the process on the macroscopic material properties, whatever the geometry of the sample.

Abstract: High quality and low variability in the properties of the products are the main goals in manufacturing. The quality of the product is verified by testing different properties. It can be improved with models developed for event prediction. This paper presents with application examples the modelling steps required for effective process modelling. First, the pre-processing and feature extraction phase are illustrated. The modelling phase concentrates especially on the heteroscedasticity problem that is commonly present in industrial applications. The process monitoring and control parameter optimization based on these models is presented, as well as the solution for the lack of observations for the dependent variable. Many of the developed models are in daily use in different process states in steel industry. They enable the design of new products and the analysis of the effects of different process parameters on variability reduction. The proposed methods are application independent.

Abstract: A fast optimization approach is demonstrated for design optimization of the multi-pass wire drawing process with the multi-objective genetic algorithm, and with the aims at minimizing both power consumption and temperature, via optimizing the process parameters involving pass number, pass schedule, die angle, bearing length and loops on capstan etc. A jump fitness function and a penalty fitness function are proposed for the survival of good designs and killing the bad designs which temperature, die wear factor, delta factor, or ratio of drawing stress to yield stress exceed the limits during optimization. The numerical examples show that the optimizer with the penalty fitness function, when its parameter n ranges from 1 to 2, presents the best performance in finding the minimum power consumption with a limit in temperature. Compared with a reference design, a significant reduction in the total power consumption about 300W, with the well control in temperature, delta factor and die life, has been achieved by the optimization. The penalty fitness function presents the better performance in the reduction of the iteration generations and computational cost to the jump fitness function.

Abstract: The thermo physical parameters of Tm vapor and the range of sublimation temperature have been determined by vapor pressure of metal Tm, and a 2-D axis-symmetric heat transfer model has been developed to investigate the temperature distribution in sublimation furnace. The simulation results show that, due to the heat loss at crucible bottom, the temperature of crucible, solid metal and Tm vapor increases with crucible height increasing, reaches the maximum value in the middle of crucible in height direction, and then decreases rapidly, and the maximum temperature is closer to the heating body temperature with its increasing; at the outside surface of condenser, the temperature decreases sharply, and the temperature curves with various heating body temperature are almost overlapped, the condensing region of Tm vapor is not affected by the heating body temperature; the temperature of upper surface of solid Tm is about 30°C lower than that of heating body, and the absolute and relatively temperature differences decrease correspondingly with increasing of heating body temperature.

Abstract: In this study, finite element simulation and the Taguchi method are employed to optimize the die stress in hot closed die forging process. Investigations are carried out for forging of automotive spring saddle by including all realistic process parameters. The research involved analyzing the effects of flash thickness, billet temperature, die temperature and friction coefficient on effective die stress by means of computer simulation. To obtain the result the forging process was modeled in CATIA V5, 3D Solid Modeling Software, simulated in DEFORM^TM 3D Software, and statistically setup and examined using Taguchis orthogonal array. Analysis of variance (ANOVA) is employed to determine significant parameters.

Abstract: Dynamic recrystallization (DRX) is widely used in industrial hot working processes to control the microstructure and properties of the workpiece and to keep the forming forces low. For the analysis and design of metal forming processes powerful simulation methods, must notably the Finite Element (FE) method, have been developed. Various models are available that consider the coupled evolution of microstructure and flow stress during hot deformation processes. Some of these models have been implemented into FE codes and are widely available now. However, for the implementation of flow stress models incorporating DRX into an FE formulation, special smoothness requirements exist that are not automatically fulfilled by the available flow stress models. This work reviews some conditions that a flow stress model incorporating DRX has to fulfill in order to be consistently embedded into an FE code for large plastic deformation. A specific Sellars-type model is analyzed for consistency with these conditions. It is shown that the use of a classical JMAK equation for the DRX kinetics within these models is problematic for Avrami exponents smaller than or equal to 3, for which the flow stress model is not sufficiently smooth. DRX kinetics based on the work of Cahn are proposed to remedy the differentiability issues.