1. [Type text]
Casting Simulation For Your Foundry’s
Profitability Using Hybrid Method Software.
ABSTRACT: followed in foundries, i.e.
trial and error method, lots
The present work aims of money, energy and time
at introducing simulation at are wasted. Even then
all stages of casting to process is not controlled
reduce defects and accurately. Foundries mostly
increasing the productivity follow lot of heuristics which
and profitability of the they come out with their
foundry. The work presents experience in that casting.
the simulation of a casting
using FDM software and Process operations and
various plots of the casting. casting are to be controlled
The work describes the in a very accurate fashion.
various stages and One of the approaches that
predictions involved with a can be adopted is simulation,
complex casting simulation. which is now becoming a
The journal also presents the part of every industry.
detail about mathematics Computer aided casting
involved in it. simulation helps us in
visualizing the real world
KEYWORDS: Casting, environment casting process
Casting simulation, FDM in a mere few steps of
simulation, SOLIDCast. inputs.
INTRODUCTION: Simulation has become
On estimating the an important tool in almost
defects in the casting in all foundries. Simulation
components major portion is plays a major role in all
because of the design casting stages. The main aim
problems and minor portion of all the foundry makers will
is caused by manufacturing. be to produce profitable and
The cost involved is also very high quality components to
high. Casting process survive in this competitive
simulation and analysis for era. This may be one of the
various defects is considered reasons “why now a day’s
to be one of the major simulation has become an
productivity tools. unavoidable part of casting
production”.
Considering the
conventional approach
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The Shortening of lead And also quite often it is
times, producing higher required to design to risering
quality and improving yield and gating designs which
of the casting, Simulation were not originally part of
can be used. Casting casting design. If the ability
simulation eliminates shop- of the product to be cast is
floor trials and achieving of already checked and
desired quality is made optimized already in the
easier. Casting simulation design stage, a lot of useless
requires 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 unique
SIMULATION: 3D CAD MODEL
tracking of volumetric
The computer aided changes in the metal, to
STL FILE
analysis is carried out by predict the temperature and
using a Finite Difference and volumeCAE
IMPORT TO
changes in a casting
vector modulus based as it is poured, solidified and
ENVIRONMENT
RUNNER
Software, “SOLIDCast”. cooled.
DESIGN
MATERIAL
SOLIDCast is a PC based tool FlowCast
FINITE ELEMENT
is MODEL full SYSTEM
a
that is used for simulating featured MESH CFD simulation, INPUTS
the pouring of hot metal of based in the navier stokes
virtually and casting alloy equations MESH fluidCALCULATION
for flow.
WEIGHTS
GENERATION
into the sand, shell,
investment, or permanent OptiCast is a optimizing
molds, and the subsequent methodology
VIEW FACTOR
CALCULATION
followed
MOLD DATA
INPUT
to
solidification and cooling optimize the considered
process. 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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the steps followed in the
experimental simulation of a
casting 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 and
MODEL DETAILS TAKEN
energy. Fluid flow is
FOR STUDY:
governed by Navier stokes
Component for study: Equation.
Clutch housing of 407 tractor
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… is imported to the SOLIDCast
environment. System and
(1) required parameters are to
be specified.
P= RT …… (2)
DISCRETISATION:
2
R + = (ρ v –ρ)/ρL
Finite difference
……(3)
method of discretisation is
Name of the alloy, followed over a complex
thermal conductivity, specific physical
heat, density, initial domain
temperature, solidification
to form
temperature, freezing range,
latent heat of fusion are all a
the MATERIAL PARAMETERS
to be specified.
Types of mold, initial
temperature, thermal
conductivity, specific heat,
density are the MOLD
PARAMETERS need to be
specified.
SOLIDIFICATION POINT
AND NIYAMA CRITERION is to
be specified.
Values for HEAT
TRANSFER COEFFICIENTS are
also to be specified.
computational domain. The
The flow chart given in discretised model may have
fig.1 gives the steps involved
millions of cubes, and the
in simulation.
heat transfer equations are
EXPERIMENTAL applied to each cube, over
SIMULATION: and over. Heat Transfer
A complex 3D Equations applied and
dimensional model is iterations are carried out
considered for simulation over the domain till the
and to plot the required solution converges.
results. STL file of the model
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PHYSICAL DOMAIN: by a process of applying
“View Factor” calculations to
the mesh. The View Factor
Calculation takes into
COMPUTATIONAL
account the visibility of all
DOMAIN: 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 the
below gives the applied heat
filling analysis and followed
transfer equations and the
by solidification analysis.
equation for temperature
(Fig.3 and Fig.4).
prediction at the final node.
Solidification simulation
The accuracy of the results
enables visualization of the
of numerical simulation
last freezing regions or hot
depends upon the size of the
spots. This facilitates the
mesh, material property
placement and design of
data, and the heat transfer
risers and risering aids in
coefficients specified for the
order to increase yield while
mold interface.
ensuring casting soundness
Q = [ 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 molten
VIEWFACTOR metal through gating
CALCULATION: systems and filling the mold.
The variations in radiant FLOWCast, Models
heat loss can be simulated conduction, convection and
radiation in the mold cavity,
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allowing to analyze the to the Solidus Point. This can
casting model and gating help to locate isolated areas
design to predict and of molten metal within the
minimize flow related defects casting and to get a general
such as misruns due to idea of progressive
premature solidification, or solidification in various areas
oxide formation, or mold of the casting. The isolated
erosion due to excessive area is the area that is prone
velocities during filling . to shrinkage. (Fig. 11).
FLOWCast enables to view
progressive temperature, CRITICALFRACTION
fluid velocity, and fluid SOLIDIFICATION TIME:
pressure during the fill, from Critical Fraction Solid
any 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 solid
ρ((∂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 a
SOLIDIFICATION TIME casting. Temperature
Solidification time Gradient is calculated at
shows the time, for each part each node within the casting
of the casting to become as that point hits the Niyama
completely solid, i.e., to cool Point on the cooling curve.
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Temperature Gradient can feed any area which is prone
be used to get an idea of to contraction, to avoid
whether there was good or shrinkage porosity in the
poor directional solidification casting. (Fig. 16)
at various points within the
casting. Higher temperature Cast Iron is one of the most
gradients are good, as complex alloys in terms of
steeper temperature how it solidifies and how
gradients mean a greater volume changes affect the
driving force for likelihood of shrinkage
solidification. The brightest porosity.
areas indicate those areas The example showed a
with the lowest temperature hypereutectic cast iron. In
gradients, and the poorest this case, expansion starts
directional solidification. (Fig. immediately upon
14) solidification.(Fig. 12)
COOLING CURVES SOLIDCast predicts well the
These curves describe volume changes based on
how a single point in a theoretical calculations for
casting behaves as it cools, the behavior of iron and
when its temperature is graphite in the solidification
plotted against time. As the process.
casting loses heat NIYAMA CRITERION
(superheat) to the mold, it
cools down, remaining a Niyama has been used
liquid until it begins to extensively for shrinkage
solidify. The point that prediction and directional
signifies the onset of solidification in castings,
solidification is called the until the use of more
liquidus point. Once the advanced calculations such
alloy is completely solid, we as the Material Density
say that it has reached the Function. Lower the value,
Solidus Point. After higher the probability of
reaching this point, the shrinkage. Niyama criterion
metal begins to cool more plot (Fig. 12) shows little
rapidly as a solid. As the shrinkage porosity in the
casting solidifies, it gradually castings.
changes from a fully liquid
COOLING RATE
material to a fully solid
material. We depend on the Cooling Rate is a
flow of liquid feed metal to measure of how quickly a
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casting is cooling down fill material / casting
measured at each point in interface cells at the start of
the casting as that point hits the filling simulation, and
the Niyama Point on the then at regular intervals
cooling curve. Cooling Rate during the simulation. Each
can be an indication of one of the particles released
material quality. Areas of the from each fill material /
casting that cool rapidly casting interface cell is
generally have a more tracked in time while the
favorable grain structure, filling simulation is executed.
with less deposition of The particles can be watched
partially-soluble compounds while it moves during the
at the grain boundaries. The simulation, and also display
plot (Fig. 15) shows most of the particle movement after
the sections have the lowest a simulation is complete. The
cooling rates. plot (Fig. 9) shows the fluid
particle flow with respect to
HOT SPOT time governed by navier
SOLIDIFICATION stokes equation (Eqn.8).
Hot Spot plotting is a MODULUS VECTOR
function that locates thermal METHOD:
centers or hot spots within
the casting by comparing The method is useful for
solidification times or critical the identification of hot spots
fraction solid times of points and the simulation of feeding
within local areas. The range paths accurately. This
of values is always 0 to 10, approach uses the direction
and generally the value of the largest thermal
plotted is around 1.1 or 1.2. gradient at any point inside a
casting to move along a path
The hot spot plot (Fig. 10) which leads to a hot spot.
does not give an indication
of the severity of the defect, Consider a section of casting
as it does not take showing iso-solidification
contraction/expansion into time contours
account. But it gives a good
indication of areas which
may have problems.
FLOW PATH LINES
FLOWCast releases a
group of particles from the
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9. [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 of
molten metal at a location Pi Casting simulation is
reaches the solidus value, the mathematical way of
the nearest location Pi+1 predicting a casting process.
along the temperature The objective function of
gradient is the one most maximizing the yield,
likely to supply Pi with liquid minimizing shrinkage and
metal compensate for minimizing solidification time
solidification shrinkage. are all found to be greatly
achieved using Hybrid
Pi , Pi+1 , Pi+2, ……………… Ph method software. Simulation
represents the feeding path should become an
in reverse. indispensable tool in all
foundries, minimizing time,
The approach to
energy spent and money,
locating hot spots and
thus maximizing profit. The
tracing fluid metal flow paths
plot for various parameters
reduces the complexity of
and defects very well gives a
computation by at least an
good idea for redesign and
order magnitude as there is
re-simulation done with no
no longer the need to
cost of time. Casting process
determine temperature
simulation has become an
exhaustively at all points
industry standard. No
inside 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
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10. [Type text]
2. Campbell, John, (2003), 7. Durgesh Joshi, Ravi
The new metallurgy of cast B(2007), Feedability Analysis
metals, CASTINGS (2ND and optimization driven by
Edition), Butterworth- casting simulation, Indian
Hienemann, Burlington-MA foundry journal.
01803.
8. Rundman B. Karl, Metal
3. Ravi B,(2008),Casting Casting, Reference for
Simulation and MY4130.
optimization;Benefits,Bottlen
ecks, and Best practices. 9. Ravi B, Srinivasan M.N,
(1990)Casting solidification
4. ASM Handbook (1992), analysis by vector modulus
ASM International, the method, International Journal
Materials Information of Cast Metals.
Company.
10. Heine, Loper &
5. Joshi D, Ravi B (2008), Rosenthal (2005), Principles
Classification and simulation of Metal Casting, Tata
based design of 3D junctions McGraw Hill, New Delhi.
in castings.
11. Anderson D. John, (1995),
6. Louvo Arno, M.Sc, CT- Computational Fluid
Castech Inc. O.Y(1997), Dynamics, The Basics With
Casting simulation as a trool Applications, Tata McGraw
in concurrent engineering, Hill Series.
International ADI and
simulation conference.
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11. [Type text]
Fig.1 Meshed Model
Fig.2 Material properties
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Fig. 3 Mold Properties
Fig. 4 Weights calculation Fig. 5
Simulation Setup
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Fig. 6 Filling simulation Fig. 7
Solidification simulation
Fig. 8 FlowCast simulation
Fig. 9 Flow path lines
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Fig. 10 Hot spot plot Fig.11
Solidification time
Fig. 12 Niyama criterion Fig. 13
Critical fraction solid point
Fig.14 Temperature Gradient Fig. 15 Cooling
rate
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Fig. 16 Cooling curve
Fig.17&18 point values using vector modulus method
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