Modeling and Simulation for Material Selection and Mechanical Design Part 3 ppt

a, of 1670 kJ=m2 h K for water cooling. In this calculation, the finish rolling temperature is 1123 K, the coiling temperature is 873 K and transformation is completed before coiling. The traveling time through the run-out table can be shortened from 11.5 to about 5 sec by increasing the heat transfer coeffi- cient up to 5020 kJ=m2 h K, as shown in Fig. 30(b). The figure, however, shows the undesirable situation where the temperature of steel drops to about 800 K which is below the bainite-start temperature (about 823 K for 0.5mass%C steel) and bainite which deteriorates the quality of steel might appear. This situation can be avoided by changing the cooling condition. Figure 30(c) shows the suitable cooling condition in which the water cooling is stopped just before the transformation start and restarted at about 20% transformation. Figure 29 Simulation of temperature and progress of transformation of 0.5 mass%C steel under different cooling conditions on run-out table of a hot-strip mill. Copyright 2004 by Marcel Dekker, Inc. All Rights Reserved. Figure 31 Temperature changes of steel at two different positions in the direction of width on the run-out table. Figure 32 Temperature change of steel at two different positions in the direction of width on the run-out table. Cooling condition was modified from that in Fig. 31. Copyright 2004 by Marcel Dekker, Inc. All Rights Reserved. axis, (A e1 ÀT P ) 1=2 where T P is the mean transformation temperature of pear- lite, representing hardness of pearlite because the pearlite hardness depends on the lamella spacing of pearlite which depends upon the under-cooling from A e1 temperature. Conditions A and B in Fig. 33 correspond to those inFigs.31and32. This result indica tes that the fluctuations of properties due to the var- iation of temperature along the width can be compensated by controlling the water-cooling intensity. 4. Effect of Fluctuations of Coiling Temperature on Mechanical Properties Coiling temperature is fluctuated widthwise by the fluctuations of water cooling intensity even though the finish rolling temperature is constant, and this coiling temperature fluctuation affects the mechanical properties due to the change in the transformation temperature. Figure 34 shows an example of the calculated results for 0.5mass%C steel sheets with thickness Figure 33 Changes in the index of hardness, (A e1 ÀT P ) 1=2 , in which TP is the mean pearlite transformation temperature, along the width under two different conditions. Copyright 2004 by Marcel Dekker, Inc. All Rights Reserved. 853 K and 913 K. The fluctuations of the index of hardness do not vary in the order of traveling speed; the fluctuations for 400 mpm are the largest among three traveling speeds. This variation is also related to the cooling rate before and during transformation. The faster the traveling speed, the longer the water-cooling time, in the case where the intensity for water cooling is constant regardless of the traveling speed. This is due to the change in the water-cooling temperature range depending on the finish roll- ing temperature, the coiling temperature, the traveling speed, and the thick- ness. In this calculation, the water-cooling time for 300 mpm is too short to affect the transformation behavior greatly. This is the reason why the fluctuations in transformation temperature for 400 mpm are greatest in Fig. 35. These results depend on the chemical composition of steel and the capacity of the hot-strip mill, such as the water-cooling intensity and the length of the run-out table. Accordingly, the pre-calculation by this type Figure 35 Effect of traveling speed of steel through the run-out table on the relationship between the fluctuations of coiling temperature, DCT, and those of the index of pearlite hardness, (A e1 ÀT P ) 1=2 . Copyright 2004 by Marcel Dekker, Inc. All Rights Reserved. of mathematical model is very useful for designing cooling facilities and determining cooling conditions for obtaining a more uniform quality product. VIII. CONCLUSION In this chapter, mathematical models for predicting microstructural evolu- tion during hot deformation and subsequent cooling, and mechanical prop- erties from the resultant microstructure of steels were explained. These models include so me empirical parameters although they are based on theory. This is because mechanisms of some phenomena are still unclear; for instance, solute-drag effect on recrystallization and transformation. The model calculating mechanical properties from microstructure is much more phenomenological. To extend the applicability, the empirical para- meters should be replaced by those obtained from theories. Although the models include some empirical parameters, they are very useful for investigating production conditions such as chemical composi- tions, processing conditions and so on. The accuracy of predicted mechan- ical properties is satisfactory. It is noted that these models should be widely used for off-line simulation of designing steel compositions and processing condition and on-line simulation for guaranteeing mechanical properties of steels. REFERENCES 1. Proceedings of International Conference on Physical Metallurgy of Thermo- mechanical Processing of Steels and Other Metals; ISIJ: Tokyo, 1988. 2. Yue, S., Ed. Proceedings of International Symposium. on Mathematical Modelling of Hot Rolling of Steel; CIM: Quebec, 1990. 3. ISIJ Int., 1992, 32. 4a. Avrami, M.J. Chem. 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Sato, K.; Suehiro, M.; Tetsu-to-Hagane. 1991, 77, 1328. 81. Suehiro, M.; Senuma, T.; Yada, H.; Sato, K. ISIJ Int. 1992, 32, 433. Copyright 2004 by Marcel Dekker, Inc. All Rights Reserved. Copyright 2004 by Marcel Dekker, Inc. All Rights Reserved. 2 Design Simulation of Kinetics of Multicomponent Grain Boundary Segregations in the Engineering Steels Under Quenching and Tempering Anatoli Kovalev and Dmitry L. Wainstein Physical Metallurgy Institute, Moscow, Russia I. INTRODUCTION The basic factors controlling grain boundary segregations (GBS) in engi- neering steels are discussed. In contrast to singl e-phase alloys, in engineer- ing steels, the multicomponent segregation is developed simultaneously with undercooled austenite transformations and martensite decomposition. Based on these reasons, the influence of steel phase composition and kinetics on concurrent segregations is discussed. It is established that grain boundary enrichment by harmful impurities (S and P) is possible after car- bon and nitrogen segregation dissolution. Two models of GBS are described. The dynamic model of segregation during quenching is based on the solution of independent diffusion and adsorption–desorption equa- tions for various impurities in steel. The model of multicomponent segrega- tion under tempering considers the influence of alloying and tempering parameters on concentration and thermodyn amic acti vity of carbon in the a-solid solution. Copyright 2004 by Marcel Dekker, Inc. All Rights Reserved. [...]... within boundaries significantly, and carbides block the dislocation movement This is the reason for peak stresses under plastic Copyright 2004 by Marcel Dekker, Inc All Rights Reserved Figure 3 (a) Brittle fracture through primary austenite grains and (b) martensite pack boundaries in steel 0 .35 C–1.5Mn–0.1P Tempering at 35 08C, 1 hr (SEM) deformation and, consequently, formation of grain boundary cracks... in this temperature range which is sufficient for diffusion at a distance of 10 mm for 1 hr at 35 08C [1] The temperature of steel for quenching is sufficiently high for intensive diffusion of P in austenite with the formation of equilibrium GBS [9], and quenching fixes this enrichment The level of P segregation depends on the austenitization temperature and increases when the temperature decreases below... is proportional to b2 The values of b for steel samples containing 0. 03% and 0.1% P at the temper embrittlement state are equal to À0.54 and 0.22 sec, respectively Taking into account dependencies (2) and (3) , one can conclude that effective intergranular cohesion surface energy in steel with higher P concentration decreases in g0: 03 =g0:1 ¼ b2 =b2 ¼ 6:04 times 0: 03 0=1 B Ductile Intergranular Fracture... segregating elements (for example N, C, S, and P) occupy equal positions on GB, described by the ‘‘site competition’’ term The peculiarity of GBS formation consists of diffusion of alloying elements and impurities from bulk to interface The migration mechanisms for substitial and interstitial impurities are different The reason for this is that the adsorption centers on interface are different for these two... tempering at 30 0–4008C, one can see an abnormal drop in impact strength At higher tempering temperatures, the impact strength increases again (see Fig 1) [8] The intergranular fracture of steel tempered at 30 0–4008C is due to the action of two unfavorable factors: enrichment of grain boundaries by P during austenitization and formation of lamellar Fe3C particles along the primary austenite grains and martensite... polycrystalline foil samples were tempered at 823K for 4 hr in a work chamber of electron spectrometer ESCALAB MK2 after quenching from austenitization temperature of 132 3K The segregation energy of P was determined using Eq (6) based on surface and bulk impurity concentration Figure 14 shows the dependence of the P segregation energy and its bulk content in alloy For the diluted solid solutions, Eseg is... All Rights Reserved ð16Þ where K0 is the coefficient of equilibrium distribution of the element between solid and liquid phases [33 ]; T is the melting temperature of the pure solvent; CL and CS are concentrations of impurity in the liquid and solid solutions, respectively An experimental method for determination of binding energy of impurity atoms to grain boundary is used The analysis of large number... heating to dissolve inclusions As a rule, the large and lamellar oxysulfides that did not embrittle steel are dissolved After their dissolution, segregation of O, S, P, and precipitation, disperse particles during steel cooling occurs In low-alloyed steels, precipitates could be sulfides of chromium and manganese (MnS, CrS), and aluminum nitride, AlN These particles build a dense network on grain boundaries... GRAIN BOUNDARY SEGREGATION AND PROPERTIES OF ENGINEERING STEELS Chemical composition and structure of the grain boundary influences various properties of engineering steels The following are some of these properties: inclination to temper and heat brittleness, resistance to hydrogen embrittlement, corrosion, delayed fracture, and creep The intergranular fracture is the main reason for decrease of many steel... carbide precipitation; and grain boundary segregations could appear during the equilibrium or non-equilibrium processes of element redistribution in steel The concentration of microstresses on grain boundaries cause the initiation of cracking and acts as the primary reason for brittleness The enrichment of grain boundaries by harmful impurities is a major and common condition for development of various . these models should be widely used for off-line simulation of designing steel compositions and processing condition and on-line simulation for guaranteeing mechanical properties of steels. REFERENCES 1 Int. 1992, 32 , 297. 43. Enomoto, M.; Atkinson, C. Acta Metall. Mater. 19 93, 41, 32 37. 44. Enomoto, M. Tetsu-to-Hagane 1994, 80, 6 53. 45. A ˚ gren, J. ISIJ Int. 1992, 32 , 291. 46. Anderson, J. water cooling is stopped just before the transformation start and restarted at about 20% transformation. Figure 29 Simulation of temperature and progress of transformation of 0.5 mass%C steel under