PHYSICAL SIMULATION OF THERMOMECHANICAL TREATMENT EMPLOYING GLEEBLE 3800 SIMULATOR

Transcription

1 PHYSICAL SIMULATION OF THERMOMECHANICAL TREATMENT EMPLOYING GLEEBLE 3800 SIMULATOR ABSTRACT ROMAN KUZIAK Institute for Ferrous Metallurgy, Gliwice, POLAND The paper will focus on the characterization of methodology of the physical simulation of thermomechanical processing which presently is widely employed for the purpose of material behaviour characterisation during the deformation process. Next aim is to present the capability of the methods in the design and optimization of real technological processes. For this purpose, wire rod rolling of bainitic steels will be considered. The Gleeble 3800 simulator, which was used in the presented investigations, is capable of performing multi-stage deformation experiments under precisely controlled conditions of temperature, strain, strain rate and time. This feature of the experiment allows the detailed investigation of the deformation parameters effect on the microstructure evolution in processed metals and alloys. 1. INTRODUCTION The exact knowledge of plastic flow behaviour of metals and alloys at elevated temperatures is essential for design and optimization of high temperature processes such as: casting, thixoforming, thermomechanical processing, and welding. In the case of steels, for example, a number of phases and phase aggregates exist at elevated temperatures that, to a first approximation, can be discussed referring to the Fe C diagram (Fig.1). Each phase indicated in the phase diagram of Figure 1 shows its specific deformation behaviour that is strain, strain rate, temperature, chemical composition and initial microstructure dependent [1]. Fig.1. Iron carbon phase diagram. As is seen in Figure 1, the austenite exhibits the widest range of stability of all the phases. As a result, most technological operations connected to the steel processing at high temperatures are conducted on a material that is entirely in the austenitic state. This situation gave rise to numerous publications concerning the plastic properties of the austenite phase, see for example [2-6]. Below the austenite phase field are two phase aggregates namely: ferrite+austenite and austenite+cementite. The plastic working in the austenite+ferrite two phase 1

2 region has attracted a substantial scientific interest due to the capability of such a process to give rise to a combination of high strength and ductility in plain carbon steels without the necessity of using of microalloying additions [7-9]. With regards to the plastic behaviour of the austenite+cementite mixture, there has been some interest in the superplastic flow occurring when ultrafine microstructure is produced by deformation in this range [10-12]. Below the eutectoid temperature there are two phase fields, namely, ferrite+pearlite (hypoeutectoid steels) and ferrite+cementite (hypereutectoid steels). The plastic properties of the ferrite+cementite aggregates, and most recently the ferrite phase in Interstitial Free steels, have been intensively investigated over the last decade due to the possible industrial application of so called ferritic rolling process [13-15]. Over the years, the design and optimization of hot deformation processes has often been carried out by means of expensive and time consuming industrial trials. The recent developments of numerical codes capable of simulating thermal mechanical and microstructural phenomena that occur during the hot working operations is rapidly changing this approach [16]. However for the numerical modelling to be an effective tool in process design and optimization, a detailed knowledge of the constitutive behaviour, including the interrelations between plastic flow and microstructure evolution, must be known. The constitutive behaviour has a great effect on the material performance during the plastic deformation and the resulting postdeformation microstructure. This behaviour can adequately be identified trough the advanced analysis of the experimental data gained in the course of physical simulation of plastic working with the use of powerful thermomechanical simulators. The importance of accurate simulation of plastic working processes to provide material characteristics has been widely recognised and introduced into practice. This paper describes the function and the outcome of the experiments conducted employing Gleeble 3800 thermomechanical simulator. The Gleeble simulators are capable of performing several types of experiments providing data that can be processed for use in process design and optimization. 2. EXPERIMENTAL FUNCTIONS OF GLEEBLE SIMULATORS Each forming process is characterised by a unique range of processing parameters comprising temperature, total strain, strain rate and inter pass time (Table 1) The knowledge of the mechanical properties of the material under defined range of processing parameters is fundamental for the process modelling using advanced numerical methods. Evaluation of flow stress of material undergoing the deformation is the prime objective of the plastometric tests, such as tension, torsion, and compression. All these options are available for use on the Gleeble systems. The two essential functions of the Gleeble system comprise: Conducting physical simulation of thermal mechanical processes. Providing material characteristics for numerical simulations. Physical simulation consists in reproducing the thermal mechanical paths typical for industrial processes on small samples. For process simulation, two approaches have been developed. In the first approach, the effect of plastic deformation is characterised in terms of effective strain and strain rate. There is a large body of evidence that such approach is a reasonable approximation of hot deformation processes, at least, while deforming a material under certain conditions, for example at elevated temperatures. However, on specific occasions, the evolution of the microstructure can be dependent on the deformation paths. In the second type of experiments, strain distribution in the work-piece also is simulated. A comparison of the capabilities of the Gleeble 3800 system to reproduce the deformation conditions prevailing in the most demanding technological processes is shown in Figure 2. 2

3 Table 1. Examples of hot rolling conditions. Rolling process Type Rolls Nominal strain Each pass Total Nominal strain rate (s -1 ) Inter-pass time (s) Plate Reverse Flat Shape Reverse Caliber Bar Full Caliber Wire Rod Full Continuous Caliber Hot strip Roughing Flat Finishing Flat Interval between deformations (s) Wire rod mill Gleeble systems Hot strip mill Strain rate (s -1 ) Fig.2. Comparison of the experimental capabilities of the physical simulation method employing the Gleeble system with industrial rolling mills. An important requirement for thermomechanical simulators concerns a high degree of control over the experimental parameters. The methodology of the particular test should be oriented towards reproducing the experimental conditions in a most accurate way possible. This is very important in the light of necessity to separate each metallurgical phenomenon involved in the microstructure development in connection with particular effects of chemical composition and deformation conditions. The Gleeble system offers exceptional degree of control over the test performance due to advanced servohydraulic system and the computer controlled feed back control execution of the deformation programme. Every deformation experiment conducted on the Gleeble system can be finished with quenching. This function of the simulator allows the study of the microstructure restoration processes in more detail. 3. PHYSICAL SIMULATION OF THERMOMECHANICAL PROCESSING This chapter presents two aspects of the physical simulation of TMCP method, namely, processing map development and the reproduction of real technological conditions to provide the data for process design and optimization. 3

4 3.1. PROCESSING MAPS DEVELOPMENT FOR PROCESS DESIGN AND OPTI- MIZATION Because the knowledge of the deformation mechanism in submicron grained materials is still incomplete, the design of the plastic working operations should be based upon the description of the interconnections between the plastic deformation and microstructural evolution. Of special interest from the technological point of view are the mechanisms of flow localisation such as shear bands formation and thermally induced softening. In such a case, a very capable way of plastic working process design and optimization consists in generating so called processing maps [17]. The processing maps are developed on the basis of the principles of Dynamic Materials Model considering the workpiece under hot working conditions as the power dissipator. Based upon the model formulations, one may assume that certain elements of the metal processing system, including the workpiece, are stores and sources of energy, and the workpiece itself is the device for dissipating of energy. The instantaneous power dissipated at a given strain rate consists of two complementary parts, i.e., G content and J content representing, respectively, the temperature rise and microstructural dissipation. Several metallurgical processes make contribution to power dissipating, and these processes are linked with characteristic ranges of efficiencies of power dissipation. These processes, occurring during the deformation, may include dynamic recovery and recrystallisation, internal fracture by void formation end wedge cracking, dissolution or coarsening of particles and phases, shear bands formation, spheroidization of acicular structures, and deformation induced phase transformations or precipitation. The factor that partitions power between J and G content is the strain-rate sensitivity (m) of flow stress. The efficiency coefficient, which is frequently used to analyse the process from the energetic point of view is given by the following equation [18]: J 2m η= = (1) Jmax m+ 1 Based upon the knowledge of the strain-rate sensitivity, also a continuum criterion for obtaining flow instability during hot deformation could be formulated: m m+ 1 ξ( & ε) = + m< 0 ln( & ε) The regions in which the instability parameter ( ε) ξ & is negative delineate the regimes (strain rate temperature) of flow instability. When two or more dissipation processes occur simultaneously, the value of J will reach the maximum when the energy of dissipation partitions equally into the all processes. As a result of the processing map development, the hot working process could be designed in terms of the controlled contribution of several irreversible processes that are controlled by the energy input and dissipation by dynamic metallurgical processes. The processing maps are used for the hot forming plastic process design and optimization. The main advantage of applying this concept to plastic working operations design is that processing maps define safe regions for deformation in terms of temperature and strain rate. As an example of using the processing maps, the results of the investigation aimed at identifying different structural mechanisms initiated in the nickel based superalloys will be demonstrated. These mechanisms were investigated in work [18] and are shown in Figure 3. Figure 4 shows the microstructures of the samples deformed in the Gleeble 3800 system with deformation parameters indicated in Figure 3. Generally, the investigation confirmed the mechanisms indicated in this Figure. 4 (2)

5 1 4 3 INSTABILITY ADIABATIC SHEAR BANDS INSTABILITY CRACKING log strain rate DRX (FINE GRAINS) 2 DRX GRAIN GROWTH Temperature ( o C) Fig.3. Different microstructural mechanisms occurring during the deformation of Inconel 718 superalloy after [18]. DRX Dynamic Recrystallisation Fig.4. Microstrustures of the φ10 15 mm Inconel 718 samples deformed to a logarithmic strain of 1 in the Gleeble 3800 system at temperatures and strain rates indicated in Figure DESIGN OF THE CHEMICAL COMPOSITION OF BAINITIC STEELS FOR WIRE ROD AND COOLING CONDITIONS AFTER TMCP Low-carbon precipitation strengthened bainitic steels are recently intensively investigated due to the capability of these steels to develop high strength and ductility in ultimate products. To identify the effect of thermomechanical processing and cooling conditions after deformations on the mechanical properties of the bainitic steels, the simulations characterized in Figure 5 were conducted using Gleeble 3800 simulator. The samples having the dimensions mm were heated to 1200 C, held at this temperature for 60 seconds, and than cooled using a strictly defined temperature versus time pattern. Six deformations were conducted 5

6 during the first stage of the cooling, namely, at 1100, 1050 and 980 C or, alternatively, at 800 C. Three deformations were imposed at the last deformation temperature. The effective strains at each deformation are indicated in Figure 5, and the strain rates were, respectively, 1, 2, 10, 20, 50 s -1. The cooling from the last deformation temperature was composed of two stages: fast cooling at a rate of 15 C/s (schedules 1, 3, and 4) or 5 C/s (schedule 2) to 550 C, and than one or two-stage slow cooling. The slow cooling stage in schedule 1 and 4 was conducted at a rate of 0.2 C/s. Two-stage slow cooling was conducted at a rate of 1.5 C/s from 550 to 400 C, and than at a rate of 0.5 C/s from 400 C to room temperature. It is noteworthy that the last deformation temperature is the only difference between schedules 1 and o C/60s ε 1 =0.2 ε 2 =0.3 Temperature ε 3 =ε 4 =ε 5 = o C/s 5 o C/s T d =980 o C (sch.1-3) T d =800 o C (sch.4) 1.5 o C/s 0.2 o C/s 0.5 o C/s 3 Time Fig.5. Physical simulation of wire rod rolling and different cooling conditions in the Stelmor line. After this treatment, the microstructure of the samples was investigated and the mechanical properties were measured using non-standard test samples. The mechanical properties of the samples subjected to the physical simulations are given in Table 2, and the microstructures of the samples are shown in Figures 6 and 7. The structure of all the samples is composed of a the mixtures of different types of bainite and incomplete transformation products. It is interesting that the slowest cooling conditions (schedule 1 and 4) resulted in the lowest strength of the samples in comparison to other schedules. Table 2. Mechanical properties of the samples of bainitic steel defined in Fig.5. Heat Schedule R 0.2 (MPa) R m (MPa) A 3.4 (%) Z (%) /4 (a) (b) (c) Fig.6. Microstructures of the samples of bainitic steel investigated in the light microscope: (a) sample 6

7 after schedule 1; (b) sample after schedule 2; (c) sample after schedule 3. (a) (b) (c) Fig.7. Microstructures of the samples of bainitic steel investigated in the scanning microscope: (a) sample after schedule 1; (b) sample after schedule 2; (c) sample after schedule 3. Very important problem connected to the technology of bainitic steels production is a proper design of their chemical composition to obtain desirable structures. Figure 8 shows the cooling cycle applied to the samples from two different bainitic steels. The bainite start and finish temperatures are marked on the cooling curve for both steels. Figure 9 shows the microstructure of granular bainite developed in the sample of heat NiTiB. On the contrary, Figure 10 shows the lower bainite microstructure developed in the sample of heat MoVB Temperature, C NiTiB (heat 1079) MoVB (heat 1080) Time, s Fig.8. Effect of the steels chemical composition and bainite start and finish temperatures. Fig.9. Granular bainite microstructure developed in the sample from heat 1079 under the experiment conditions defined in Figure 8. 7

8 Fig.10. Lower bainite microstructure developed in the sample from heat 1080 under the experiment conditions defined in Figure SUMMARY The focus of the chapter was the characterisation of the experimental methodology used in the physical simulation of plastic working processes and for the purpose of material behaviour characterization. It was demonstrated that the physical simulation of technological processes can provide valuable information regarding the material s response to processing parameters. This information can be used in technological process design and/or optimization. The quality and extent of the information provided depends on the capability of thermomechanical simulator. The material characteristics provided by the method can be used for computer simulation of real processes. BIBLIOGRAPHY 1. Marder A.R., The Effect of Carbon Content, Test Temperature, and Strain Rate on the Strain-Rate Sensitivity of Fe-C Alloys, Trans. Metall. Soc. AIME, 245, June 1969, Bargar D.L., The High Temperature and High Strain-Rate Behavior of a Plain Carbon and an HSLA Steel, J. Mech. Working Technol., 14, 1987, Ludwigson D.C., Modified Stress-Strain Relation for FCC metals and alloys, Metall. Trans., 2, 1971, Chen Y.W., Tobler R.L., Fills B.J., Coakley K.J., Constitutive Behavior Modelling of Steels Under Hot-Rolling Conditions, NIST Technical Note , Materials Reliability Series, April Hatta N., Kokado J, Kikuchi S., Takuda H., Modelling on Flow Stress of Plain Carbon Steel at elevated Temperatures, Steel Res., 56, 1985, Sakai S., Sakai T., Takeishi K., Hot Deformation of Austenite in a Plain Carbon Steel, Trans ISIJ, 17, 1977, Saito Y. Et al., Controlling of Microstructure and Mechanical Properties Utilizing Deformation Resistance in Plate Rolling, Kawasaki Steel Techn. Rep., No.9, March 1984, Pandai R., Yue S., Dynamic Transformtion of Austenite to Ferrite in Low Carbon Steel, ISIJ Int., 34, 1994, No.3, Preistner R., Ali L., Strain Induced Transformation in C-Mn Steel during Single Pass Rolling, Mat. Sci. Techn., 9, February 1993, Walser B., Sherby O.D., Mechanical Behavior of Superplastic Ultrahigh Carbon Steels at Elevated Temperature, Metall. Trans.A, 10A, 1979, Marder A.R., The Effect of Carbon Content, Test Temperature, and Strain Rate on the Strain-Rate Sensitivity of Fe-C Alloys, Trans. Metall. Soc. AIME, 245, June 1969, Wray P.J., High Temperature Plastic-Flow Behavior of Mixtures of Austenite, Cementite, Ferrite, and Pearlite in Plain-Carbon Steels, Metall. Trans. A, 15A, November 1984, Um Kyung-Keun et al., Effect of Initial Sheet Thickness on Shear Deformation in Ferritic Rolling of IF-Steel Sheets, ISIJ Int., 40, 2000, No.1, Paepe A., Herman J.C., and Leroy V., Deep Drawable Ultra Low Carbon Ti IF Steels Hot Rolled in the Ferrite Region, Steel Res., 68, 1997, No.22, Tomitz A, and Kaspar R., Ferritic Rolling to Produce Soft Deep-Drawable Thin Hot Strips, Steel. Res., 71, 2000, No. 6-7, Lenard J.G., Pietrzyk M., Cser L., Mathematical and Physical Simulation of the Properties of Hot Rolled Products, Elsevier, Venugopal S., Mannan S.L. and Prasad Y.V.R.K., Optimisation of Hot Workability in Stainless Steel-Type AISI 304L Using Processing Maps, Metall. Trans. A, 23A, November 1992,

9 18. Srinivasan N. and Prasad Y.V.R.K. Microstructural Control in Hot Working In-718 Superalloy Using Processing Map, Metall. Trans. A, 25A, October 1994,