computer aided heat treatment planning system for quenching and tempering

8/8/2019 Computer Aided Heat Treatment Planning System for Quenching and Tempering

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Com puter Aided H eat Treatment Planning System for Quenching and Temp eringLei zhangl*, Radhakrishnan ~um sho tha m an l,Yiming ~ o n ~ ' ,inwu ~ a n ~ ' ,marjit Kumar s ingh l

1Department of Mechanical Engineering, Worcester Polytechnic Institute, Worcester, M A 0 1609Keywo rds: Heat treatment; Heat treatment planning system; Finite Difference Me thod; Quenc hing;Tempering

AbstractFurnaces are widely used for the heat treatment of mass production parts. So to optimize the heattreating process is of great significance, and will greatly takes the advantage to save energy. In thispaper, an analytical tool "Computerized Heat Treating and Planning System for Quenching andTempering" has been developed, which is to predict the temperature profile of load in batch as well ascontinuous furnace during heating, quenching and tempering of steel, then to provide information aboutthe m echanical properties as Quenche d and T empered and finally to optimize the heat treatment processdesign with the aim to save energy and reduce cost. This tool is suitable for heat treating plants,workshops and also captive heat treaters. The calculation is the hybrid of numerical simulation andempirical equations. Therefore it is convenient for heat treating industry and furnace m anufacturing.

1. IntroductionHeat treatment can be defined as a combination of heating and cooling operations applied to a m etal oralloy in solid state. It is an important manufacturing process, which controls the mechanical propertiesof metals, therefore contributes to the product quality.Heat treatment industry has 15 billion dollars business in USA. M eanwhile it is also of the main energyconsumer. Most heat treating processes have the heating process in furnace as the first step. There themicrostmcture and mechanical properties undergo changes and most of energy is consumed. However,currently, the heating process is mainly based on experience. Therefore, the heat transfer simulation inheat treatment furnace is of great importance for the prediction and control of the ultimatemicrostmcture and properties of the workpieces and reduction of energy consumption. Studies havebeen don e to simulate the heating process of workpieces in heating furnace, such as reheating furnace ofbillet, bar and slab which are of rectangular or round sections in rolling and steel plants Some workmainly focus on the combustion problem in boiler or combustor, while the heat transfer between heatresource and load is simple [5-s1. Howeve r, there are few studies exactly about the simulation of the heattreatment processes of castings, forgings or machined workpieces, which are very popular inautomotive, machinery and equipment m anufacturing industries. These kinds o f workpieces are usuallyof complicated shape and many workpieces are processed in a load in furnace. Therefore the heattransfer between furnace and workpieces, among workpieces and inside workpieces are verycomplicated. In previous study, a method was given to calculate the heating time for workpieces witharbitrary shape [91. How ever, the study is based on unchanged furnace temperature.

* Corresponding author.E-mail address: [email protected]. (Lei ZHANG).

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Integrated Computational Materials Engineering: Lessons from Many Fields

Edited by: Deborah WhitisTMS (The Minerals, Metals & Materials Society), 2007


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In order to optimize the heat treating process, a computerized tool is desired to simulate the thermalprocess as well as the m icrostmcture evolution o f the steel materials, therefore the heat treating processparameters can be optimally determined to ensure the materials property as required, and at the sametime the production cycle time can be m inimized s o that the manufacturing cost and energy consum ptioncan be reduced. In previous years, the thermal analysis mode ls for loaded furnace, CHT-bf for batchfurnaces and CHT-cf for continuous furnaces, have been developed and validated for modeling andsimulating the heating up process [10-121. When the part and part load is given with specified furnaceinformation, the temperature profiles of the load are computed for the parts both on the surface and inthe core, as well as in different location of the furnace. The temperature profiles are compared againstthe given thermal schedule to evaluate if the soaking time is necessary and sufficient to ensure thequality o f the materials property control. With the h elp of using C HT-bflcf, the alternative load designsand thermal schedule determination can be evaluated for optimal solutions.Bu t CHT-bflcf only has heating proce ss mod el. In this paper, in order to expanded CHT-bf and CHT-cfinto an entire heat treating process to estimate the materials property change during and after the heattreating process, a computerized heat treatment planning system for quenching and tempering of steel,CH T-qlt, has been developed . CH T-qlt is developed based on CHT-bflcf It includes the simulationmodel o f quenching and tempe ring process for predicting the tempe rature profile of load in batch as wellas continuous furnace during heating, quenching and tempering of steel. The microstmcture evolutionduring the thermal process is simulated based o n the analysis of the cooling rate at different location ofthe workpiece and the phase transformation during the cooling process. Finally the mechanicalproperties, mainly the hardness distribution, are estimated based on the resultant microstmcture. Therelationship between hardness and other properties, such as ultimate tensile strength, yield strength,toughne ss and elongation, is show n based o n empirical know ledge found in literature.

2. Mathematical Model DevelopmentIn heat treatment processes, the heat transfer processes involve three modes: the radiation, conductionand convection, as well as the furnace model. To simplify, the following assumptions are made:

The furnace temperature is uniform. The furnace serves as a heating resource and heatstorage as well.Atm osphere temperature is uniform and is the same as furnace.

2.1 RadiationIn the heat treatment processes of workpieces, there are two kinds of radiation heat transfer: fromfurnace to workpieces and from workpieces to w orkpieces.The radiation betw een furnace and the outside layer of a workpiece:

where o is the Stenfan-Boltzmann constant, E is emissivity, F vw 0 e is the view factor of workpiece tofurnace, A is the exposure surface area of the workp iece, T f , , an d T w p are the temperatures o f furnace andworkpiece respectively.The radiation betw een the outside layer of the workpiece and workp iece:

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where F ~ w p l ~ w p 2s the view factor of workpiece 1 to w orkpiece 2, TWp1 an d T w p 2 are the temperatures ofworpiece 1 and workpiece 2 respectively.The view factors of workpieces to furnace and of workpieces to workpieces can be estimated by the loadpattern [ll. 1212.2 Convection and cooling modelThe convection heat transfer between furnace and the workpiece, and between w orkpiece and quen chantis denoted as follows:

Qconv = conv .A .(fie -Twp ( 4 4Qconv = quent .A .(Twp - Tquent )

wh ere hcon, is the con vectio n film coe fficient, which c an be calculated by fo llow ing equ ation:

where L* is the characteristic length, L* = A1/2. Nu,, s the Nusselt numb er. It is related to thegeometrical features of workpiece, load pattern, thermal properties of atmosphere and circulation fan.The calculations of Nu,, are different for natural con vection and forced convec tion ["' 12]. Heat transfercoefficient can be determined by experimental approach.2.3 Conduction m odelFourier equation for the conduction in the solid, such as workpiece, furnace walls, fixtures, and trays/baskets is given as

2.4 Furnace modelThe furnace model contains the PID (Proportional, Integral and Derivative) control, available heat forgas-fired furnaces, and heat terms such as heat input by fan, heat loss from furnace do or and walls, heatstorage in the furnace wall and auxiliaries and heat loss by coo ling tubes for some special furnaces. Theeffective heat input is

where KpID is the PID control coefficient, KAH s the available heat coefficient, Q gross s the gro ss heatinput, At is the time step.

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The heat storage in the furnace wall can be calculated by

where Qgro,, is the heat loss, Qgro,, s the heat storage in load, and Qgrosss the heat input by fan. henthe furnace temperature is calculated as follows:

fce

7 ' Q:tol , 1C I, cPlwhere nfi, is the total number of furnace wall and auxiliaries, w , nd cp, are the weight and specific heatof the furnace aux iliaries.2.5 Microstructure and ~ r o ~ e r t i e sre diction model

In the transformation model the prog ress of transformation for the d iffusion reactions is followed by anAvrami-Johnson-Mehl equation, assuming additivity, while the fraction of martensite formed is modeledas a function of holding temperature below the m artensite start temperature.For the diffusion phase transformations of austenite to ferrite and pearlite, the formation o f a new phaseon cooling is only possible once the temperature is below the equilibrium transformation temperature.This temperature is dependen t on the alloy content of the steel.The kinetics of the growth of ferrite and pearlite are described using the A vrami-Johnson-Mehl equationW I.

where w s the volume fraction of austenite transformed, b an d n are the coefficient and exponent of theaustenite transformation kinetics, t is the time, and t , is the start time.The values of b an d n are evaluated from the given TTT diagram except for ferrite for which it isassumed that n = 1.Mo re generally it can be stated that:

where the subscripts s and f indicate start and finish, respectively. In a TTT diagram, w s s usuallychosen to be 1% an d i f ' , 9%, but other percentages may also be chosen.

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The volume fraction of martensite is then modeled using an equation proposed by Koistinen andMarburger [4].Belo w the m artensite start tempe rature M s, it is assumed that the remaining austenite is transformed intomartensite ac cording to equation as:

where WM is the transformed volume fraction of austenite into martensite, MSis the martensite starttemperature, Mf is the martensite finish temp erature, and T is the transformation tem perature, T IMS.It can be observed from the abov e equations, to calculate b, n and w w e need only Ts and tffro m the TTTdiagram, and t from the cooling curve.

The properties of the steel are determined by their microstmcture. Various equations are used to mapthe properties of steels based on their microstmctures.Since hardness is a function of % Martensite as well as % carbon content (Fig. I), thus regressionanalysis is being used to get the hardness at a specific martensitic percentage.

HsrdngssHRC

Figure 1 Relationship between hardness, carbon contentand amo unt of martensite [I4'Hardne ss=f(C%, Martensite% ), i. e.,

where x--C%, a , b, c are constants, which can be obtained from the relationship shown in Fig. 1Ultimate T ensile Strength, Yield Stress, Toughn ess and Elongation are all related to H ardness, and som eof these relationships a re available in the literatures. Therefore, an approach is to build a database usingthe data from handbooks and literature and use some empirical relations to populate the database and isused to properties prediction in CHT-qlt.

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3. Design of Compu ter-aided Heat T reatment Planning System-CHT-qltFig. 2 shows the function flow-chart, which is the schematic representation of the sequence ofoperations in CHT-q/t.

Initial condition-orkpiece 1 Furnace 1 Load pattern Thermal schedule 4

I Module 3 I

BE1k ot t r ic~ l I T T prol ilc D9

Cooling

Module 1Workp~ece lass~f~cat~onenmeshment

Workp~ece hape class ~f~cat~ onEnmeshment by Blot no

Heat transfer for gas quenching in same furnaceused in heating

Heat transfer for gas quenching in differentfurnace

082 1

I I Heat transfer for oil quenching in tank(load v~ithixture, single v~orkpi ecewithout fixture) I I

Fuir DB +083

workpiece and insidethe workpiece

I Module 4 I-Lrucspiieic DB Module 2Heat~ngI Phase transformation prediction I / nl lm, r \Heatterm &Mapping of microstruc ture to properties IuAustenite to pearlite I bainite I martensite)Comparing cooling curve with TTT diagram todetermine microstructure

Module 5Tempering

Heating below austenizing temperature

V U L W U L V

hfechanicalafter Quenching

Output 4Heat term &

temperatures

D8 6 Module 6Tcrr trirlr, p ope tico Property pred~ct~ony emp~r~calquat~onsCB after Tempering

Figure 2: Function flow-chart of CHT-qltCHT-q/t contains four basic operations. Heating: consists of heating the parts in batch as well ascontinuous furnace. Cooling: can be done in batch furnace, continuous furnace and in tank. Quenching:

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is a rapid cooling of metals from an elevated temperature to a low temperature. In CHT-q/t, gas andliquid quenching of the entire load has been considered. Gas quenching can be done in the same furnaceused in heating or in a different furnace particularly used for quenching. Tank is used for liquidquenching. Tempering: can be defined as a process, which consists of heating hardened steel to atempera ture below the low er critical temp erature, and followed by cooling in air or at any desired rate.CHT-q/t utilizes several databases to facilitate the thermal analysis, microstmcture evolution analysis,and property estimation. DB1 - Material Database: Along with material name, material type, thermalproperties such as density, specific heat, conductivity, emissivity etc., this database contains thematerials TTT diagrams in tabular format for all the materials going to be heat-treated. DB2 - FurnaceDatabase: It consists of different kind of furnaces (both batch and continuous) for heating andquenchin g. It also includes tank used for liquid quench ing. DB3 - Atmosphere Database: It contains theatmosph ere present inside the furnace. DB4 - Quenchant Database: The quenchant database contains thequenchant types, including the physical properties of the quenchants such as viscosity, boiling point,latent heat of vaporization, density and specific heat capacity. It also consists of the convective heattransfer coefficient "h" vs. blower horse power. DB5 - Tempering Properties Database: It contains theempirical relations needed to predict the phase transforma tion and properties after tempe ring.

4. Case studies - results and d iscussionThe system has been applied to the focus group members of Center for Heat Treating Excellence(CHTE), W PI. Here two case studies are given.4.1 Case 1This case study is oil quenching o f a huge part, which weigh ed 2580 lbs (Fig. 3). The part was heated inthe Pit furnace for almost 900 minutes and was moved from the pit furnace using an overhead crane andwa s quenched in this tank.

Figure 3: Workpiece in the furnace and the thermocouplelocationsCHT-qlt 3D model wa s used to calculate this case. The calculation space step used here was 2 in., whichcan save calculation time, therefore 2016 elements was obtained by enmeshing the part. The totalcalculating tim e is around l0m in. and the results were shown below.

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Figure 4: Comparison of results between calculated and measured during processThe calculating temperature profiles were plotted in Fig. 4 with the measured results. From the start ofheating stage, the calculation temperature increase almost as quickly as the measurement shows. Theyalmost get to the high temp erature at the sam e time . The temperature error is within 30 OF, and therelative error is around 3%. Then quenching starts, the inside temperature was measured. It is observedthat the prediction results match very well with the measurem ents from the quenching sta rt.The temperature profiles plotted in C HT-q lt interface is shown on Fig . 5. And the predicted properties ina part section are displayed in Fig. 6 .

Figure 5: Cooling curves with TTT diagram Figure 6: HI3 Hardness distribution on the partsurface (front view)4.1 Case 2This is high pressure quenchin g case using argon w ith 12 bar Turb o treater. The workpiece is a cylinderwith 1.125" diameter by 4" long, weighted 21bs, and is made of Alloy Steel 4340. Fig . 7 shows the loadpattern.

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Figure 7: Arrangement of workpieces in the basket and the thermocouple locationsThe parts were arranged in vertically in the basket as shown in the Fig. 7. And 3 thermocouple wereattached to the load 2 were inside the probe and one right next to the workpiece to measure the gastemperature during the process. The load was quenched from 850 "C to the room temperature. In thiscase totally 3840 elem ents was obtained, and it ran around 15 min.The calculatiilg results are displayed in Fig 8, it is 1 e n clear that all the parts are fast cooled almost at the sainerate . and the! ar e also ver! n ell nhe n co mpared with the ineasured results.

Figure 8: Com parison of results between calculated and measured during the quenchprocess

5. ConclusionsCHT-qlt developed based on CHT-bflcJ; it includes the simulation model of quenching and temperingprocess to predict the temperature profile o f load in batch as well as continuou s furnace during heating,quenching and tempering of steel, then to provide information about the mechanical properties asquenched & tempered based on the cooling rate and phase transformation analysis, and finally tooptimize the heat treatment process design with the aim to save energy and red uce cost.

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Two case studies are presented, which shows the calculated results are basically in agreement with themeasured one and reasonable.Acknowledgement

The authors are grateful to the help for case studies from Bodycote Thermal Processing, American HeatTreating, Sousa Corporation.ReferencesK. S. Chapman et al., "Modeling And Parametric Studies Of Heat Transfer In A Direct-FiredBatch Reheating Furnace", Journal Of Heat Treating, 8(2) (1990), 137- 146.K. S. Chapman, S. Ramadhyani, R. Viskanta, "Modeling And Analysis Of Heat Transfer In ADirect-Fired Continuous Reheating Furnace", Heat Transfer In Combustion Systems (1989),35-44.W. Halliday, "Computer Control Model For Continuous Reheat Furnaces", Metallurgia,57(10) (1990), 412-3.D. 0.Marlow, "Modeling Direct-Fired Annealing Furnaces For Transient Operations", Appl.Math. Modeling, 20(1996), 3 5-40.

M.S. Liu, C.K. Choi, and C.W. Leung, "Startup Analysis Of Oil-Fired Furnace - TheSmoothing Monte Carlo Model Approach", Heat AndMass Transfer, 37(2001), 449-457.F. R. Steward, P, Cannon, "The Calculation Of Radiative Heat Flux In A Cylindrical FurnaceUsing The Mote Carlo Method", International Journal Of Heat And Mass Transfer ,14(1971), 245-262.E. P. Keramida et al., "The Discrete Transfer Radiation Model In A Natural Gas-FiredFurnace", International Journal For Numerical Methods In Fluids, 34(2000), 449-462.F. Liu, H.A. Becker, Y. Bindar, "A Comparative Study Of Radiative Heat Transfer ModelingIn Gas-Fired Furnaces Using The Simple Grey Gas And The Weighted-Sum-Of Grey-GasesModels", International Journa l Of Heat AndMass Transfer ,4 1(1998), 33 57-337 1.M. Gao et al., "Estimating Equilibration Times And HeatingICooling Rates In HeatTreatment Of Parts With Arbitrary Geometry", Journal Of Materials Engineering AndPerformance, 9(1) (2000), 62-7 1.Q. Lu, R. Vader, J. Kang and Y. Rong, M. Hoetzl, "Development of A Computer-Aided HeatTreatment Planning System", Heat Treatment of Metals, March 2002, pp. 65-70J. Kang, Y. Rong, W. Wang, "Numerical simulation of heat transfer in loaded heat treatmentfurnaces", Journal of Physics, 4(120)(2004), 545-553.J. Kang, T. Huang, R. Pumshothaman, W. Wang, Y. Rong, "Modeling and simulation of heattransfer in loaded continuous heat treatment furnace", Transactions of Materials an d HeatTreatment,25(5)(2004), 764-768.Torsten Ericsson, "Principles of Heat Treating of steel", ASM Handbook, vol. 4--HeatTreating, (1991), 3-19.P. D. Hodgson, K. M. Browne, R. K. Gibbs, T. T. Pham and D. C. Collinson, "TheMathematical Modeling of Temperature and Microstructure During Spray Cooling",Proceeding of the$rst international conference on quenching and control of distortion, ASMInt, (1992),4 1.

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computer aided heat treatment planning system for quenching and tempering

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