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[Type text]Casting Simulation For Your Foundry’sProfitability Using Hybrid Method Software.ABSTRACT: followed in foundries, i.e. trial and error method, lots The present work aims of money, energy and timeat introducing simulation at are wasted. Even thenall stages of casting to process is not controlledreduce defects and accurately. Foundries mostlyincreasing the productivity follow lot of heuristics whichand profitability of the they come out with theirfoundry. The work presents experience in that casting.the simulation of a castingusing FDM software and Process operations andvarious plots of the casting. casting are to be controlledThe work describes the in a very accurate fashion.various stages and One of the approaches thatpredictions involved with a can be adopted is simulation,complex casting simulation. which is now becoming aThe journal also presents the part of every industry.detail about mathematics Computer aided castinginvolved in it. simulation helps us in visualizing the real world KEYWORDS: Casting, environment casting processCasting simulation, FDM in a mere few steps ofsimulation, SOLIDCast. inputs.INTRODUCTION: Simulation has become On estimating the an important tool in almostdefects in the casting in all foundries. Simulationcomponents major portion is plays a major role in allbecause of the design casting stages. The main aimproblems and minor portion of all the foundry makers willis caused by manufacturing. be to produce profitable andThe cost involved is also very high quality components tohigh. Casting process survive in this competitivesimulation and analysis for era. This may be one of thevarious defects is considered reasons “why now a day’sto be one of the major simulation has become anproductivity tools. unavoidable part of casting production”. Considering theconventional approach 1
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[Type text] The Shortening of lead And also quite often it istimes, producing higher required to design to riseringquality and improving yield and gating designs whichof the casting, Simulation were not originally part ofcan be used. Casting casting design. If the abilitysimulation eliminates shop- of the product to be cast isfloor trials and achieving of already checked anddesired quality is made optimized already in theeasier. Casting simulation design stage, a lot of uselessrequires domain knowledge, works can be avoided.and must be fast, powerful,easy to use and accurate. • Opticast Simulation. Solidification simulation uses FDM based method of heat transfer calculation combined with a uniqueSIMULATION: 3D CAD MODEL tracking of volumetric The computer aided changes in the metal, to STL FILEanalysis is carried out by predict the temperature andusing a Finite Difference and volumeCAE IMPORT TO changes in a castingvector modulus based as it is poured, solidified and ENVIRONMENT RUNNERSoftware, “SOLIDCast”. cooled. DESIGN MATERIALSOLIDCast is a PC based tool FlowCast FINITE ELEMENT is MODEL full SYSTEM athat is used for simulating featured MESH CFD simulation, INPUTSthe pouring of hot metal of based in the navier stokesvirtually and casting alloy equations MESH fluidCALCULATION for flow. WEIGHTS GENERATIONinto the sand, shell,investment, or permanent OptiCast is a optimizingmolds, and the subsequent methodology VIEW FACTOR CALCULATION followed MOLD DATA INPUT tosolidification and cooling optimize the consideredprocess. casting START process with CASTING 100% considering the parameters &RISER SIMULATION SINGLE CYCLE The analysis is of design variables,preceded in three stages. constraints and objective FLOWCAST function.SIMULATION • Solidification Simulation The CASTPIC PLOTS NO! ACCEPT following flow • FlowCast chart CHECKING FOR gives simulation DEFECTS YES! REJECT 2 REDESIGN
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[Type text]the steps followed in theexperimental simulation of acasting using SOLIDCast. Pattern material: Aluminum Type of pattern: Match plate Type of mold: Silica sand. Pouring temperature: 1400-1450°C Theoretical Pouring Time: 6.67 s. Table-1: Metal composition S. Element Percent No. age 1 Carbon 3.3 2 Silicon 1.9 3 Manganes 0.7 e 4 Sulphur 0.1 5 Phosphoru 0.15 s 6 Chromium 0.4 7 Copper 0.4 PARAMETERS CONSIDERED: The analysis is governed by set of equations for continuum of mass andMODEL DETAILS TAKEN energy. Fluid flow isFOR STUDY: governed by Navier stokesComponent for study: Equation.Clutch housing of 407 tractor 3
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[Type text] … is imported to the SOLIDCast environment. System and(1) required parameters are to be specified.P= RT …… (2) DISCRETISATION: 2R + = (ρ v –ρ)/ρL Finite difference……(3) method of discretisation is Name of the alloy, followed over a complexthermal conductivity, specific physicalheat, density, initial domaintemperature, solidification to formtemperature, freezing range,latent heat of fusion are all athe MATERIAL PARAMETERSto be specified. Types of mold, initialtemperature, thermalconductivity, specific heat,density are the MOLDPARAMETERS need to bespecified. SOLIDIFICATION POINTAND NIYAMA CRITERION is tobe specified. Values for HEATTRANSFER COEFFICIENTS arealso to be specified. computational domain. The The flow chart given in discretised model may havefig.1 gives the steps involved millions of cubes, and thein simulation. heat transfer equations areEXPERIMENTAL applied to each cube, overSIMULATION: and over. Heat Transfer A complex 3D Equations applied anddimensional model is iterations are carried outconsidered for simulation over the domain till theand to plot the required solution converges.results. STL file of the model 4
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[Type text]PHYSICAL DOMAIN: by a process of applying “View Factor” calculations to the mesh. The View Factor Calculation takes intoCOMPUTATIONAL account the visibility of allDOMAIN: mold surfaces to all other mold surfaces as well as the surrounding environment, and adjusts the conditions at each surface accordingly. View factors are applied to every surface in contact with ambient conditions, so it doesn’t matter if the mold is created as a part of the model, or by meshing. SOLIDIFICATION SIMULATION: The equations given SOLIDCast runs thebelow gives the applied heat filling analysis and followedtransfer equations and the by solidification analysis.equation for temperature (Fig.3 and Fig.4).prediction at the final node. Solidification simulationThe accuracy of the results enables visualization of theof numerical simulation last freezing regions or hotdepends upon the size of the spots. This facilitates themesh, material property placement and design ofdata, and the heat transfer risers and risering aids incoefficients specified for the order to increase yield whilemold interface. ensuring casting soundnessQ = [ KA(Tn1-T n2)(∆t/x) ] ……. without expensive and time(4) consuming trial runs.Q = hA(Tn1-T n2) ∆t …….(5) FLOWCAST SIMULATION:Tf = Ti + ∑Q/Vρc …….(6) FLOWCast allows visualizing the flow of moltenVIEWFACTOR metal through gatingCALCULATION: systems and filling the mold. The variations in radiant FLOWCast, Modelsheat loss can be simulated conduction, convection and radiation in the mold cavity, 5
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[Type text]allowing to analyze the to the Solidus Point. This cancasting model and gating help to locate isolated areasdesign to predict and of molten metal within theminimize flow related defects casting and to get a generalsuch as misruns due to idea of progressivepremature solidification, or solidification in various areasoxide formation, or mold of the casting. The isolatederosion due to excessive area is the area that is pronevelocities during filling . to shrinkage. (Fig. 11).FLOWCast enables to viewprogressive temperature, CRITICALFRACTIONfluid velocity, and fluid SOLIDIFICATION TIME:pressure during the fill, from Critical Fraction Solidany angle of view. Time records the time, for _ each part of the casting to ……. reach the Critical Fraction(7) Solid Point. This is the point at which the alloy is solidρ((∂v/∂t)+v. ∆v) = 2 enough that liquid feed-∆p+µ∆ v+f …….(8) metal can no longer flow. Critical Fraction Solid Time is generally a better indication than Solidification Time. This ..(9) plot gives a good indication of whether any contraction that forms will be able to be fed by liquid feed metal .. within the risers or feeders. The result critical fraction(10) solid time plot noted that there are few isolated pools of molten metal. (Fig. 13). .. TEMPERATURE GRADIENT(11) Temperature Gradient is a measure of variation in temperature within aSOLIDIFICATION TIME casting. Temperature Solidification time Gradient is calculated atshows the time, for each part each node within the castingof the casting to become as that point hits the Niyamacompletely solid, i.e., to cool Point on the cooling curve. 6
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[Type text]Temperature Gradient can feed any area which is pronebe used to get an idea of to contraction, to avoidwhether there was good or shrinkage porosity in thepoor directional solidification casting. (Fig. 16)at various points within thecasting. Higher temperature Cast Iron is one of the mostgradients are good, as complex alloys in terms ofsteeper temperature how it solidifies and howgradients mean a greater volume changes affect thedriving force for likelihood of shrinkagesolidification. The brightest porosity.areas indicate those areas The example showed awith the lowest temperature hypereutectic cast iron. Ingradients, and the poorest this case, expansion startsdirectional solidification. (Fig. immediately upon14) solidification.(Fig. 12)COOLING CURVES SOLIDCast predicts well the These curves describe volume changes based onhow a single point in a theoretical calculations forcasting behaves as it cools, the behavior of iron andwhen its temperature is graphite in the solidificationplotted against time. As the process.casting loses heat NIYAMA CRITERION(superheat) to the mold, itcools down, remaining a Niyama has been usedliquid until it begins to extensively for shrinkagesolidify. The point that prediction and directionalsignifies the onset of solidification in castings,solidification is called the until the use of moreliquidus point. Once the advanced calculations suchalloy is completely solid, we as the Material Densitysay that it has reached the Function. Lower the value,Solidus Point. After higher the probability ofreaching this point, the shrinkage. Niyama criterionmetal begins to cool more plot (Fig. 12) shows littlerapidly as a solid. As the shrinkage porosity in thecasting solidifies, it gradually castings.changes from a fully liquid COOLING RATEmaterial to a fully solidmaterial. We depend on the Cooling Rate is aflow of liquid feed metal to measure of how quickly a 7
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[Type text]casting is cooling down fill material / castingmeasured at each point in interface cells at the start ofthe casting as that point hits the filling simulation, andthe Niyama Point on the then at regular intervalscooling curve. Cooling Rate during the simulation. Eachcan be an indication of one of the particles releasedmaterial quality. Areas of the from each fill material /casting that cool rapidly casting interface cell isgenerally have a more tracked in time while thefavorable grain structure, filling simulation is executed.with less deposition of The particles can be watchedpartially-soluble compounds while it moves during theat the grain boundaries. The simulation, and also displayplot (Fig. 15) shows most of the particle movement afterthe sections have the lowest a simulation is complete. Thecooling rates. plot (Fig. 9) shows the fluid particle flow with respect toHOT SPOT time governed by navierSOLIDIFICATION stokes equation (Eqn.8). Hot Spot plotting is a MODULUS VECTORfunction that locates thermal METHOD:centers or hot spots withinthe casting by comparing The method is useful forsolidification times or critical the identification of hot spotsfraction solid times of points and the simulation of feedingwithin local areas. The range paths accurately. Thisof values is always 0 to 10, approach uses the directionand generally the value of the largest thermalplotted is around 1.1 or 1.2. gradient at any point inside a casting to move along a pathThe hot spot plot (Fig. 10) which leads to a hot spot.does not give an indicationof the severity of the defect, Consider a section of castingas it does not take showing iso-solidificationcontraction/expansion into time contoursaccount. But it gives a goodindication of areas whichmay have problems.FLOW PATH LINES FLOWCast releases agroup of particles from the 8
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[Type text] For determining the largest temperature gradient at any point Pi inside the casting, the vector modulus method is followed. Fig. 17 & Fig.18 shows the values computed at two points Pi(x,y,z). CONCLUSION:When the temperature Ti ofmolten metal at a location Pi Casting simulation isreaches the solidus value, the mathematical way ofthe nearest location Pi+1 predicting a casting process.along the temperature The objective function ofgradient is the one most maximizing the yield,likely to supply Pi with liquid minimizing shrinkage andmetal compensate for minimizing solidification timesolidification shrinkage. are all found to be greatly achieved using HybridPi , Pi+1 , Pi+2, ……………… Ph method software. Simulationrepresents the feeding path should become anin reverse. indispensable tool in all foundries, minimizing time, The approach to energy spent and money,locating hot spots and thus maximizing profit. Thetracing fluid metal flow paths plot for various parametersreduces the complexity of and defects very well gives acomputation by at least an good idea for redesign andorder magnitude as there is re-simulation done with nono longer the need to cost of time. Casting processdetermine temperature simulation has become anexhaustively at all points industry standard. Noinside a casting. foundry that produces high quality castings can consider simulation as unnecessary. REFERENCES: 1. Ravi.B, Srinivasan.M.N (1990), Hot Spots in castings: Computer aided location and experimental validation 9
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[Type text]2. Campbell, John, (2003), 7. Durgesh Joshi, RaviThe new metallurgy of cast B(2007), Feedability Analysismetals, CASTINGS (2ND and optimization driven byEdition), Butterworth- casting simulation, IndianHienemann, Burlington-MA foundry journal.01803. 8. Rundman B. Karl, Metal3. Ravi B,(2008),Casting Casting, Reference forSimulation and MY4130.optimization;Benefits,Bottlenecks, and Best practices. 9. Ravi B, Srinivasan M.N, (1990)Casting solidification4. ASM Handbook (1992), analysis by vector modulusASM International, the method, International JournalMaterials Information of Cast Metals.Company. 10. Heine, Loper &5. Joshi D, Ravi B (2008), Rosenthal (2005), PrinciplesClassification and simulation of Metal Casting, Tatabased design of 3D junctions McGraw Hill, New Delhi.in castings. 11. Anderson D. John, (1995),6. Louvo Arno, M.Sc, CT- Computational FluidCastech Inc. O.Y(1997), Dynamics, The Basics WithCasting simulation as a trool Applications, Tata McGrawin concurrent engineering, Hill Series.International ADI andsimulation conference. 10
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[Type text] Fig.1 Meshed Model Fig.2 Material properties 11
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