MODELLING OF MICROSTRUCTURE EVOLUTION IN HOT WORK TOOL STEELS DURING SERVICE

Transcription

1 Informatyka w Technologii Materiaów Publihing Houe AKAPIT Vol. 9, 2009, No. 2 MODELLING OF MICROSTRUCTURE EVOLUTION IN HOT WORK TOOL STEELS DURING SERVICE FRIEDRICH KRUMPHALS 1, THOMAS WLANIS 1, CHRISTOF SOMMITSCH 1, IVAN HOLZER 2, BERNHARD SONDEREGGER 2, VOLKER WIESER 3 1 Chritian Doppler Laboratory for Material Modelling and Simulation, Chair of Metal Forming, Univerity of Leoben, Franz-Joef-Strae 18, 8700 Leoben, Autria 2 Intitute for Material Science and Welding, Univerity of Technology, Kopernikugae 24, 8010 Graz, Autria 3 Böhler Edeltahl GmbH & Co KG, Mariazellertrae 25, 8605 Kapfenberg, Autria Correponding Author: Correponding Autor: friedrich.krumphal@mu-leoben.at (F. Krumphal) Abtract To etablih a reliable lifetime prediction of hot work tool teel during ervice, it i neceary to characterize the initial microtructure a well a it evolution during application ince the material propertie depend on the microtructural configuration. The microtructure evolution during heat treatment i imulated with the oftware MatCalc, where the precipitation kinetic i of particular interet. The invetigated X38CrMoV5-1 hot work tool teel, which ha a bcc lattice tructure, form a ditinct dilocation cell and ubgrain tructure, repectively, which i decribed by a dilocation denity model for thermal creep uing the rate theory with particular conideration of the ubgrain boundary behaviour. The precipitation calculation with MatCalc are compared with microtructural invetigation. Key word: hot work tool teel, extruion, microtructure modelling, dilocation denity evolution 1. INTRODUCTION Hot work tool teel are commonly in ue a tool for manufacturing procee of metallic material at elevated temperature. Since the loading of the tool during hot metal working, e.g. extruion, i often near the elatic limit, the lifetime i much horter in comparion to the Cr-teel for energy application [2]. Here, the microtructure evolution of the hot work tool teel X38CrMoV5-1 i invetigated during heat treatment a well a in thermomechanical loading condition, which occur during ervice. Therefore, the precipitation kinetic during heat treatment i calculated, uing the cientific program MatCalc [3] in order to get initial condition for a ubequent dilocation denity imulation of creep loading uing the rate theory with particular conideration of the ubgrain boundary behaviour [1]. Subgrain a well a precipitation limit the dilocation movement and their diameter i a key parameter in determining the creep rate under varying condition. Two different load cae, repreenting die loading during both, aluminium and copper extruion [8], and the reulting microtructure evolution are demontrated in thi work. 2. HEAT TREATMENT SIMULATION AND COMPARISON WITH EXPERIMENTAL INVESTIGATIONS The chemical compoition of the hot work tool teel X38CrMoV5-1 i hown in table 1 and a tandard heat treatment condition to achieve a hardne of about HRC i depicted in figure 1. The ISSN

2 INFORMATYKA W TECHNOLOGII MATERIAÓW hardening temperature i 1020 C, with a holding time of one hour and following annealing at 550 C and 580 C for two hour. Table 1. Chemical compoition of BÖHLER W400 hot work tool teel. Grade \ weight % C Si Mn Cr Mo V Fe X38CrMoV bal. Fig. 1. Temperature-time profile for the conidered hot work tool teel X38CrMoV5-1 during heat treatment after hot working. Fig. 2. Evolution of the phae fraction of the precipitate during the heat treatment. To get a more reaonable delineation, the amount of M 7 C 3 i divided by 10. Fig. 3. Evolution of the number of particle per volume during heat treatment. The temperature decreae from 1200 C at the beginning imulate the cooling from the prior hot working proce. The heating up to autenitization temperature in indutrial procee i performed tepwie with three hold point to aure a homogeneou temperature ditribution in the billet. However, for the MatCalc imulation the exact timetemperature hitory of the heating up i not that important. The controlled cooling rate from autenitizing temperature i = 8, and after each annealing tep the material i cooled by air. The precipitation kinetic are imulated with the oftware MatCalc, the phae fraction f of the precipitate, namely MX (V(C,N)), M 3 C (Fe 3 C), M 6 C (Cr 6 C), M 7 C 3 (Cr 7 C 3 ), M 23 C 6, (Cr 23 C 6 ), M 2 C (Mo 2 C) and Lave phae are hown in figure 2, the particle number N per volume i depicted in figure 3 and the related mean radiu Rv mean i diplayed in figure 4. Primary MX phae wa not conidered o far, becaue the phae amount wa not determined quantitatively and additionally, the formation of primary phae in the liquid metal cannot be imulated in MatCalc. However, with the known primary phae fraction, the amount of diolved carbon content in the matrix could be reduced by the amount of carbon, which ha been ued for the formation of the primary carbide and thu the influence of primary carbide on the precipitation kinetic of econdary carbide could be conidered. Secondary phae MX, M 3 C and M 7 C 3 form during heating up and diolve again during the autenitization at 1020 C. During the econd annealing tep, the fraction of M 23 C 6 increae ignificantly in comparion to M 6 C, M 7 C 3, M 2 C and Lave phae a depicted in figure 2. After the heat treatment i finihed, the main exiting phae fraction are M 3 C, MX and M 23 C 6 (M 3 C: green line, MX: red line, M 23 C 6 brown line in figure 2-4). The number of particle N per volume reache a quaitable condition at the end of the heat treatment, except for Lave phae (figure 3). Dilocation reaction (dipole forming, cutting, immobilizing) and precipitation have a trong influence onto dilocation tructure evolution. The maller and numerou a particle population the more it will affect dilocation glide. 229

3 INFORMATYKA W TECHNOLOGII MATERIAÓW M 3 C precipitation are far the larget econdary particle that form during the heat treatment, which i depicted in figure 4. The ignificantly higher growth rate of the other econdary phae during the 30 C higher econd annealing period i remarkable. Microtructure invetigation after heat treatment mainly indicated bainitic tructure a well a fraction of tempered martenite. So far, only the ize of M 3 C carbide ha been analyzed quantitatively, ee figure 5. The mean radiu i 75 ± 20 nm, which i in the ame range a in the calculation ( 100 nm). The precipitation tate after the heat treatment, the thermal and mechanical loading condition, the initial dilocation denity a well a ubgrain ize are key parameter in the ued phyically baed dilocation model according to Ghoniem et al. [1]. Since the conidered thermal load are lower than the lat annealing tep in the heat treatment, a contant precipitation tate a initial condition i aumed and the following focu lie on the invetigation of the dilocation tructure Concept of the model The bai of the model i to decribe the dilocation tructure evolution by: the generation and immobilization of dilocation at ubgrain boundarie, i.e. multiplication a well a annihilation of dilocation due to interaction procee, the recovery of the tatic dilocation at the boundarie a well a the aborption of mobile dilocation in the cell wall, the generation of dilocation by emiion from the cell wall, the dynamic of nucleation and growth of ubgrain from Fig. 4. Evolution of the mean radiu of the precipitate during heat treatment. dilocation within the cell a well a (a) (b) (c) Fig. 5. TEM-invetigation of the bainitic microtructure how econdary precipitation at grain boundarie (M 3 C, MX, marked with arrow), large primary MX carbide (marked with circle in (c)) and generally a high dilocation denity. All image are 4 m in width. 3. MODELLING OF THE DISLOCATION STRUCTURE EVOLUTION DURING SERVICE the ubgrain growth due to coalecence driven by the ubboundary energy. Hence the total dilocation denity ge, i eparated into three categorie of dilocation, namely mobile m, tatic, and boundary dilocation b to conider all the pecific dilocation dynamic mentioned above. The temporal evolution of the mobile dilocation denity m i given in equation 1 with v g a the glide 230

4 INFORMATYKA W TECHNOLOGII MATERIAÓW velocity of the dilocation, a a parameter for the dilocation emiion, R ub i the ubgrain radiu, h g the ditance between two dilocation in the ubgrain boundary, v m c the creep velocity of mobile dilocation and determine the dynamic annihilation ditance: Read Frank ource Immobilization d dt m 0.5 vg m FrankReadource Rub v 2 g hg Emiion from cell wall m 3/ 2 8v c m m v g (1) Static recovery Dynamic recovery The evolution equation for decribing the tatic dilocation denity i given in equation (2), where v c denote the creep velocity of tatic dilocation: d dt m vg 2R ub Immobilization 8 vc hg Static recovery mvg Dynamic recovery (2) The principle, which i valid for all three dilocation categorie are dilocation generation by: Frank-Read ource and emiion of dilocation at cell wall ( m ), immobilization ( ), aborption and tatic recovery ( b ) a well a the decreae of dilocation denity due to: tatic and dynamic recovery ( m, ), coalecence and growth ( b ). A further important parameter, which i included in the formula of the glide velocity v g, i the pace length between foret dilocation. When the tatic dilocation denity decreae, increae, which mean eaier gliding and following fater annihilation of mobile dilocation. The effect of olute and precipitation, which trengthen the material, are conidered in the evolution of the boundary dilocation denity, which can be een in equation (3). The input parameter from the precipitation calculation Rv mean,i and N i, for even different type (i=1..7) of precipitation, which are depicted in figure 3 and 4, are introduced into the model: d dt b 81 2 vc hg Aborption of dilocation and tatic recovery 7 2 b M 2 g pg mean, i Rv N i g Rub 1 i Coalecence and growth of ubgrain (3) with the parameter decribing the annihilation at the ubgrain boundary, v c the creep velocity of tatic dilocation, M g the mobility of ubgrain, p g the driving force of the ubgrain boundary, Rv mean,i the radiu of precipitation cla i, N i the related number of particle per volume and g the urface energy of the ubgrain boundary. The microtructure calculation can be compared with FE-Simulation and experiment [6,8] via the reulting true inelatic train rate d/dt, which i an additional output of the model: d 1 m vgb (4) dt M where M = 3 i the Taylor factor for the bcc lattice tructure [7] and b i the burger vector Calculation of the dilocation denity evolution during thermo-mechanical load During autenitization at 1020 C for one hour, the total dilocation denity decreae, but during quenching bainite and martenite form, thi caue high tree and train in the lattice tructure, generating dilocation. The total dilocation denity after autenitization and quenching, to produce mainly bainitic tructure in our cae, can be aumed to be ge =10 12 m -2, i.e. m = m -2, = m -2 and b = m -2 [10] and R ub = m. The dilocation denity calculation in thi paper are executed for contant mechanical load of 370MPa at 500 C (figure 6a), which hould repreent a heavily loaded point in the liner for aluminium extruion application [8,9] and 750MPa at 570 C (figure 6b), which i a realitic cae for copper extruion [4, 5] and that i near the elatic limit at thee condition. Calculation were performed with MathCad TM with the initial condition a mentioned before and the loading time wa et to 40 hour ( econd), which equal to pre cycle in typical extruion procee, however the cyclicality of loading ha been neglected o far. The total dilocation denity at a load of 370MPa and 500 C increae very lowly (figure 6a), the main mechanim i the formation of a table ubgrain tructure, i.e. the dilocation denity in the cell wall increae ignificantly wherea the mobile a well a the tatic dilocation denity finally decreae and the ubgrain ize almot remain contant. The macrocopic train after 40 hour of loading i mall in comparion to the train occurring at 231

5 INFORMATYKA W TECHNOLOGII MATERIAÓW the conidered higher thermo-mechanical load cae (figure 6b), where the dilocation tructure immediately begin to change and a ditinctive ubgrain tructure i formed. Remarkable i the reulting higher dilocation denity of ge = m -2 in comparion to m -2 for the lower load cae. The diagram alo how that a contant total dilocation denity production rate (lope of blue curve in figure 6a,b) develop with progre in time. a) fairly comparable, while the reult for the econd conidered thermo-mechanical load cae agree better. Remarkable i that the dilocation denity model exhibit a contant lope (d log / d log t), contrary to the ABAQUS model reult. Inelatic train 1.E-03 1.E-04 1.E-05 1.E-06 1.E-07 1.E-08 a) Dilocation denity model ABAQUS Simulation 1.E-09 1.E-10 1.E+00 1.E+01 1.E+02 1.E+03 1.E+04 1.E+05 1.E+06 Time [] b) Dilocation denity model ABAQUS Simulation 1.E-01 1.E-02 b) Inelatic train 1.E-03 1.E-04 1.E-05 1.E-06 1.E-07 1.E-01 1.E+00 1.E+01 1.E+02 1.E+03 1.E+04 1.E+05 1.E+06 Time [] Fig. 7. Comparion of the calculated (thi work, brown curve) a well a FE-imulated ([8], blue curve) inelatic train for 370MPa at 500 C (a) and 750MPa at 570 C (b). 4. CONCLUSIONS AND OUTLOOK Fig. 6. Evolution of the mobile ( m, green line), tatic (, brown line), boundary ( b, red line) and total ( ge, blue line) dilocation denity [m -2 ] at 500 C and 370MPa (a) and 570 C and 750MPa (b) in double logarithmic cale. To validate the dilocation denity model, the reulting inelatic train i compared (figure 7) with ABAQUS calculation including an elaticvicoplatic Chaboche type contitutive model that ha been validated by a comprehenive experimental program [8]. The ABAQUS imulation output for the accumulated vicoplatic train for 370MPa at 500 C after 40 hour amount to , wherea the reult from the microtructure model i , which i In thi work it wa hown, that by applying phyical baed model, the microtructure evolution of hot work tool teel during both heat treatment and indutrial ervice can be decribed. Precipitation of econdary phae during annealing wa modelled in order to conider the ignificant influence of the precipitation tate on the mobility of dilocation. However, poible further precipitation reaction during ervice, which wa related to hort time dilocation creep, were neglected. On the bai of two choen example, i.e. aluminium extruion and copper extruion, repreentative load were applied to calculate the evolution of mobile, tatic and boundary dilocation denitie a well a of the ubgrain tructure. Reulting inelatic accumulated train were compared with the outcome of a contitutive formerly validated model. 232

6 INFORMATYKA W TECHNOLOGII MATERIAÓW To further validate the microtructure calculation, the econdary hardening carbide in the material will be analyed after the heat treatment a well a during ervice in more detail. The model for the calculation of the dilocation denity and ubgrain ize evolution will be verified by dilocation denity meaurement a well a via the reulting inelatic train, which can be compared to both macrocopically meaured and vicoplatically imulated value. Additionally, damage evolution a well a lifetime etimation of hot work tool teel hall be modelled in order to make progre in both material development and proce optimization. 8. Sommitch, C., Sievert, R., Wlani, T., Günther, B., Wieer, V., Modelling of creep-fatigue in container during aluminium and copper extruion, Computational Material Science, 39, 2007, Sommitch, C., Krumphal, F., Stotter, C., Dendl, D., Wlani, T., Huber, D., Wieer, V., Lifetime comparion of different hot work tool teel for extruion tool in aluminium extruion, Proc. ET 08-Ninth International Aluminium Extruion Technology Seminar and Expoition, Orlando, 2, 2008, Weinert, P., Modellierung de Kriechen von ferritich/martenitichen 9-12% Cr-Stählen auf mikrotruktureller Bai, PhD thei, Univerity of Technology, Graz, 2001 (in German). REFERENCES 1. Ghoniem, N., Matthew, J., Amodeo, R., A dilocation model for creep in engineering material, Re Mechanica, 29, 1990, Holzer, I., Rajek, J., Kozechnik, E., Cerjak, H.-H., Simulation of the precipitation kinetic during heat treatment and ervice of creep reitant martenitic 9-12% Cr Steel, Proc. Material for Advanced Power Engineering, Liege, 2006, Kozechnik, E., Sonderegger, B., Holzer, I., Rajek, J., Cerjak, H., Computer imulation of the precipitate evolution during indutrial heat treatment of complex alloy, Material Science Forum, , 2007, Krumphal, F., Wlani, T., Sommitch, C., Buchner, B., Huber, D., Redl, C., Wieer, V., Creep fatigue in hot work tool teel during copper extruion, Proc. Sixth International Conference on Low Cycle Fatigue, Berlin, ed, Portella, P.D. et al., DVM Berlin, 2008, Krumphal, F., Wlani, T., Sommitch, C., Redl, C., Creep fatigue of multi-part container during hot extruion of copper Simulation and experimental comparion, Computer Method in Material Science, 7, 2007, Mitter, W., Haberfellner, K., Danzer, R., Stickler, C., Lifetime prediction of hot work tool teel, Lab. Report, Journal of Heat Treatment and Material Science (HTM), 52, 1997, Orlova, A., Miclicka, K., Dobe, F., Choice of evolution equation for internal tre in creep, Material Science and Engineering, A194, 1995, MODELOWANIE ROZWOJU MIKROSTRUKTURY STALI NARZDZIOWYCH PODCZAS OBRÓBKI CIEPLNEJ I PRACY W WARUNKACH EKSPLOATACYJNYCH Strezczenie Tematem pracy jet przewidywanie czau pracy narzdzi w warunkach ekploatacyjnych. Kocowe wanoci wyrobu zale od jego pocztkowej mikrotruktury oraz zmian tej mikrotruktury podcza wytwarzania. Dlatego za gówny cel pracy potawiono obie modelowanie rozwoju mikrotruktury podcza proceu obróbki cieplnej oraz pracy narzdzi w warunkach ekploatacyjnych. Modelowanie ewolucji mikrotruktury ze zczególnym uwzgldnieniem kinetyki wydziele wykonano z wykorzytaniem pakietu MatCalc. W pracy analizie poddano tal narzdziow X38CrMoV5-1 o trukturze bcc, która tworzy wyran truktur dylokacyjn oraz podziarnow. Wykonane obliczenia numeryczne poddano równie weryfikacji dowiadczalnej. Submitted: October 24, 2008 Submitted in a revied form: December 1, 2008 Accepted: December 18,