Der Einfluss thermophysikalischer Daten auf die numerische

Transcription

Der Einfluss thermophysikalischer Daten auf die numerische
Einfluss thermophysikalischer Daten auf die Simulation
Der Einfluss thermophysikalischer
Daten auf die numerische Simulation
von Gießprozessen
Tagung des Arbeitskreises Thermophysik,
4. – 5.3.2010
Karlsruhe, Deutschland
E. Kaschnitz
Österreichisches Gießerei-Institut
Leoben, Österreich
1
Einfluss thermophysikalischer Daten auf die Simulation
Numerical simulation in metal part production:
¾ Differential equations describing the physical phenomena are
usually highly non-linear and coupled
¾ Analytical solutions are not obtainable
¾ Numerical approximations by means of Finite Methods (e.g.
Finite Elements, Finite Differences, ...)
¾ Need of high computing power (computing times hours, days,
weeks), parallelization of processes
¾ Simulated processes: casting, welding, forging, heat treatment,
rolling, cutting …
¾ Accurate thermo-physical and -mechanical properties are
urgently needed
2
Einfluss thermophysikalischer Daten auf die Simulation
Geometry
Process
at
He
ed
as
re
le
tu
Re
ra te
pe ra
m ng
Te ooli
C
Material
Thermal
Model
Heat transfer
Air gap
Strain
Material
model
Mechanical
Model
ge
n
a
ch n
ed e
e ai
c
s
u g
a tr
nd han
ph s
i
s
es se c
r
t
s ha
p
Shrinkage
Distortion
Residual stress
Cold shots
Microstructure
Segregation
Thermal model: fluid flow, heat transfer, diffusion
Material model: macro-, meso- micro-model
Mechanical model: elasto-, plasto-, visco-model
And Combinations
3
Einfluss thermophysikalischer Daten auf die Simulation
Density and volume expansion of Al-17Si-4Cu:
1.10
2750
Teutectic Tliquidus
Tsolidus
1.08
Density, kg.m
-3
2650
1.06
2600
2550
1.04
2500
Volume Expansion
2700
1.02
2450
2400
1.00
0
100
200
300
400
500
600
700
Temperature, °C
4
Einfluss thermophysikalischer Daten auf die Simulation
Thermal diffusivity of Al-17Si-4Cu:
Thermal diffusivity, mm2 . s-1
70
60
solidus
temperature
50
eutectic
temperature
40
30
20
10
liquidus
temperature
Fit to the measured data
Initial heating
Col 7 vs Col 8
Col 9 vs Col 10
f vs Col 12
0
100
200
300
400
500
600
700
Temperature, °C
5
Einfluss thermophysikalischer Daten auf die Simulation
Influence of volume thermal expansion data on feeding of
castings:
¾ Alloys are (usually) contracting during solidification (up to
several percent)
¾ Shrinkage has to be compensated in order to get a sound
casting
¾ Additional material is provided from an extra reservoir by
hydrostatic or external pressure (feeding)
¾ If feeding is disturbed, shrinkage cavities or porosity will be
found in the final casting – leading to scrap
¾ feeding channels must not been frozen until solidification of
casting (directional solidification towards the feeders)
¾ Precise volume expansion (contraction) data in the vicinity of
the solidification region must be known
6
Einfluss thermophysikalischer Daten auf die Simulation
Example: Liquid and solidification shrinkage due to density
change during cooling – porosity and shrinkage cavity
7
Einfluss thermophysikalischer Daten auf die Simulation
Example: Solidification of a gear housing
8
Einfluss thermophysikalischer Daten auf die Simulation
Volume thermal expansion (contraction) depends also on:
¾ Exact chemical composition – an alloy designation has (wide)
composition ranges for each element
¾ Solidification speed – competition between thermal and mass
diffusion (lever rule, Scheil, back diffusion models)
¾ Global vs. local equilibrium at solidification front – development
of different phases
¾ Melt treatment (inoculation, grain refinement, modification,
degassing
9
Einfluss thermophysikalischer Daten auf die Simulation
Influence of linear thermal expansion data on distortion of
castings:
¾ When solidified, the casting shrinks from its high temperature
dimensions to room temperature
¾ In the mold, the (relatively soft) casting is more or less
constrained and follows the dimensions of the (stiff) mold
(plastically deformed at high temperature)
¾ When the casting is shaked out of mold, it can shrink freely
¾ Different regions of the casting are at different temperatures at
shake-out – shrinkage is locally different
¾ The local shrinkage (elastic part) equals to thermal expansion x
local temperature difference to room temperature
¾ Each region has an individual shrinkage – that can lead to
distortion (plastic contributions ease the stress but increase
distortion)
10
Einfluss thermophysikalischer Daten auf die Simulation
Example: V-shaped high-pressure die-casting – temperature
distribution until shake-out
11
Einfluss thermophysikalischer Daten auf die Simulation
Example: V-shaped high-pressure die-casting – distortion in xdirection during free cooling
12
Einfluss thermophysikalischer Daten auf die Simulation
V-shaped high-pressure die-castings are produced at ÖGI
High-pressure die-casting machine
V-shaped specimens
13
Einfluss thermophysikalischer Daten auf die Simulation
Dimensions of the V-shaped specimens are measured and
compared to simulation
14
Einfluss thermophysikalischer Daten auf die Simulation
Influence of linear thermal expansion data on distortion of
castings:
¾ Different regions of the casting are at different temperatures at
shake-out – shrinkage is locally different (plastic strain can
also happen in the die – some stress is already present at
shake-out)
¾ The local shrinkage leads to distortion
¾ After machining, the stress distribution changes – also the
distortion
¾ Similar problems arise at heat treatment of metal parts
15
Einfluss thermophysikalischer Daten auf die Simulation
Influence of linear thermal expansion and thermal conductivity
data on die life expectance (high-pressure die-casting):
¾ After filling of the cavity the hot melt is in direct contact with the
cooler tool steel
¾ The steel surface is heated rapidly, the material expands in the
vicinity of the surface
¾ The surface layer gets under heavy compressive stress – can
be beyond the yield stress
¾ This leads to plastic deformation of the surface layer
¾ After removing of the casting, a lubricant-water mixture is
sprayed at the surface – rapid cooling
¾ The cooled surface layer gets under tension stress – the
material is now “too short” – cracking of the surface under
tension stress
16
Einfluss thermophysikalischer Daten auf die Simulation
Temperatures at a tool-steel die-surface in high-pressure diecasting:
800
600
Casting in die
Air
Spray Air
cooling cooling cooling
600
500
400
200
0
300
-200
200
-400
Cut of a fraction of die
and melt
100
Die closed
Die open
-600
Die open Die closed
0
-800
0
10
20
30
40
50
60
Time, s
17
Stress, MPa
Temperature, °C
400
Einfluss thermophysikalischer Daten auf die Simulation
Tool-steel die in high-pressure die-casting during solidification:
After 1 second
Temperature
Normal stress in vertical direction
18
Einfluss thermophysikalischer Daten auf die Simulation
Tool-steel die in high-pressure die-casting during solidification:
After 5 seconds
Temperature
Normal stress in vertical direction
19
Einfluss thermophysikalischer Daten auf die Simulation
Tool-steel die in high-pressure die-casting during solidification:
After 20 seconds
Temperature
Normal stress in vertical direction
20
Einfluss thermophysikalischer Daten auf die Simulation
Tool-steel die in high-pressure die-casting at open die:
After 30 seconds
Temperature
Normal stress in vertical direction
21
Einfluss thermophysikalischer Daten auf die Simulation
Tool-steel die in high-pressure die-casting during spraying:
After 40 seconds
Temperature
Normal stress in vertical direction
22
Einfluss thermophysikalischer Daten auf die Simulation
Tool-steel die in high-pressure die-casting at the end of cycle:
After 55 seconds
Temperature
Normal stress in vertical direction
23
Einfluss thermophysikalischer Daten auf die Simulation
Examples of die damage:
Thermal fatigue cracks
Fracture of the entire die
2
1
10mm
24
Einfluss thermophysikalischer Daten auf die Simulation
Influence of linear thermal expansion and thermal conductivity
data on die life expectance simulation (high-pressure die-casting):
¾ Plastic deformation at heating leads to cracking during rapid
cooling
¾ Smaller linear thermal expansion lowers thermal stress
¾ Higher thermal conductivity removes heat faster – smaller
temperature gradients – lower thermal stress
¾ just a few percent change in thermal conductivity of the tool
steel changes peak temperature at the surface for several
degrees – that can have a tremendous influence in die life
expectance (up to a factor of 10)
¾ Search for a tools steel with higher thermal conductivity is
ongoing
25
Einfluss thermophysikalischer Daten auf die Simulation
Warmarbeitsstahl von Rovalma HTCS-130:
Wärmeleitfähigkeit, W/Km
60
40
20
Rovalma HTCS-130
Datenblatt STM Stahl
1.2343 (W300 ISODISC)
W360 ISOBLOC
0
0
100
200
300
400
500
600
700
Temperatur, °C
26
Einfluss thermophysikalischer Daten auf die Simulation
Influence of thermal conductivity on microstructure simulation of
castings:
¾ Mechanical properties (aluminum, magnesium) depend on
¾Melt cleaning, degassing, grain refinement, modification
¾Correct fluid flow, feeding technique
¾ Solidification speed (thermal conductivity of the mold)
¾ Rapid solidification leads to fine grain and small secondary
dendrite arms in the microstructure – superior mechanical
properties
¾ Local cooling of crucial regions of a casting
27
Einfluss thermophysikalischer Daten auf die Simulation
Simulation of the cooling time:
Casting with grey iron core
Casting with quartz sand core
28
Einfluss thermophysikalischer Daten auf die Simulation
Microstructure (position 7 mm from surface):
Casting with grey iron core
Casting with quartz sand core
DAS 20 µm
200µm
DAS 61 µm
200µm
29
Einfluss thermophysikalischer Daten auf die Simulation
Conclusions: How in(accurate) thermal conductivity and thermal
expansion data influences the quality of casting simulations
¾ Volume thermal expansion of the solidifying melt can lead to
shrinkage porosity – with inaccurate data cavities can be
predicted when casting is sound and vice versa
¾ Linear thermal expansion is responsible for thermal strain –
with inaccurate data the final distortion of the casting and
residual stresses are not correctly predicted
¾ Thermal conductivity of the mold determines the heat removal
from the solidifying casting – with inaccurate data the
microstructure will develop different in simulation and reality
¾ Thermal conductivity and linear thermal expansion of a die are
responsible for the amount of (cycling) compression and
tension stress – inaccurate data lead to a completely wrong
prediction of cracking (lifetime)
30
Einfluss thermophysikalischer Daten auf die Simulation
31