Developments in Heat Transfer Part 12 ppt

Later Proulx et al [Proulx, 1985] predicted the trajectory and temperature history of alumina and copper particles injected into ITP torch and discussed the particle loading effects in a

gap and results in higher ignition delay and decrease discharge energy and reduces MRR

It was found by many researchers that the influential machining factors on MRR are the

current intensity and voltage

Usually EDM is carried out by electrical sparks between the electrode and the workpiece

using a single discharge for each electrical pulse Some researchers have carried out experiments using a multi-electrode discharging system, delivering additional discharge simultaneously from a corresponding electrode connected serially The design of electrode was based on the concept of dividing an electrode into multiple electrodes, which are electrically insulated The energy efficiency were claimed to be better than the conventional

EDM without any significant difference in work suface finish

Material removal rate is expressed as the ratio of the difference in volume of the workpiece before and after machining to the machining time, i.e.:

Fig 13 Relationship between current and MRR

Relationship of MRR with current during machining of aluminum and steel using brass and copper electrodes are illustrated in Fig 13 It is to be noted that at a low current MRR is very low, but with increase in current MRR increases sharply At a low current, a small quantity

of heat is generated and a substantial portion of it is absorbed by the surroundings and the

more heat is generated and a substantial quantity of heat is utilized in material removal However, the highest material removal rate was observed during machining of aluminum using copper electrodes Comparatively low thermal conductivity of brass as an electrode material doesn’t allow absorbing much of the heat energy and most of the heat is utilized in removal of material from aluminum workpiece of low melting point But during machining

of steel using copper electrodes, comparatively smaller quantity of heat is absorbed by the

work material due to its low thermal conductivity As a result MRR becomes very low

4.4 Micro cracks

During the spark discharge in EDM the temperature is usually in the range of 8,000°C to

20,000°C After the spark the work surface is immediately cooled rapidly by the dielectric fluid Repeated heating to a very high temperature followed by rapid cooling develops micro-cracks on the work surface Micro-cracks on the work surface are a major problem in

EDM They strongly influence on the fatigue strength of the part machined by EDM

Micro-cracks in the surface and loose grains in the subsurface resulted from thermal shock causes surface damage and leads to degradation of both strength and reliability Comparing the

SEM images in Fig 14 it can be observed that more micro-cracks were formed during EDM

with a higher current of 6.5 Amp as shown in Fig 14 (a) compared to that with a low current

of 2.5 Amp as illustrated in Fig 14 (b) More heat is developed during EDM at a higher current heating the work surface to a higher temperature followed by rapid cooling As a

result more micro-cracks are found at a higher current A larger t on results more cracks as it can be observed comparing the Figs 14 (c) and 14 (d) However, it was suggested by Lee & Tai, 2003 that when the pulse voltage is maintained at a constant value of 120 V, it is possible to avoid the formation of cracks if machining is carried out with a current in the range of 12-16 A together with pulse duration of 6-9 µs

4.5 Recast layer

There are three layers created on the top of the base metal which are spattered EDM surface layer, recast layer and Heat Affected Zone (HAZ) Recast layer consists of dielectric fluid, molten electrode and molten workpiece that are melted during EDM machining and

solidified Usually recast layer has a higher hardness when compared to the base metal The recast layer is also known as white layer because it often appears as a bright white layer in a

sectional view under magnification It occurs as the second layer under the spattered EDM

surface layer This layer is formed by the un-expelled molten metal solidifying in the crater The recast layer is usually very thin and it can be removed by finishing operations Recast layer can cause problems in some applications due to stress cracking or premature failure Recast structure greatly affects die fatigue strength and shortens its service life This is because the recast layers have micro-cracks and discharge craters that cause bad surface quality HAZ consists of two layers: a hardened layer and the annealed layer The depth of the hardened layer depends on the machining conditions Usually the depth is 0.002mm for finish cut and 0.012 mm for rough cut Below the hardened layer there is a layer which was cooled slowly and as a result, the layer is annealed Its hardness is 2 to 5 points below the same of the base metal Its thickness may be 0.05mm for finish cut and 0.2mm for rough cut

(a) I=6.5 Amp; ton=10 µs

(b) I=2.5 Amp; ton=10 µs

(c) I=2.5 Amp; ton=10 µs

Fig 14 Influence of current and pulse-on time on micro cracks

As stated above, a higher current and a higher pulse-on time produce a spark with more energy, melt more materials from the workpiece and the electrode Consequently higher thickness of recast layer is found at a current of 6.5 Amp, Fig 15 (a) compared to that at a current of 2.5 Amp, Fig 15 (b) Similarly, thickness of the recast layer was found to be at a higher pulse-on time, Fig 15 (c) compared to that at a shorter pulse-on time, Fig 15 (d)

Hwa-Teng Lee et al., 2004 also stated that R a and average white layer thickness tend to

increase at higher values of pulse current and t on However, they found that for extended

pulse-on duration MRR, R a and crack density all decrease

(a) tav 22.1 µm: I= 6.5 Amp; ton =10µs

(b) tav 18.1 µm: I= 2.5 Amp; ton=10 µs

(c) tav 21.3 µm: I= 2.5 Amp; ton=10 µs

(d) tav 12.5 µm: I= 2.5 Amp; ton=1.5 µs Fig 15 Thickness of recast layer at different machining conditions

5 Conclusion

From the above discussions the following conclusions can be drawn:

1 Electrodes undergo more wear along its cross-section compared to that along its length

2 Electrode wear increases with increase in current and voltage Wear of copper electrodes is less than that of brass electrodes This is due to the higher thermal conductivity and melting point of copper compared to those of brass

3 During machining of mild steel, electrodes undergo more wear than during machining

of aluminum This is due to the fact that thermal conductivity of aluminum is higher to that of mild steel which causes comparatively more heat energy to dissipate into the electrode during machining of mild steel

4 Wear ratio decreases with increase in current, but decreases with increase in gap voltage The highest wear ratio was found during machining of aluminum using a copper electrode

5 MRR increases sharply with increase in current In the present study, highest MRR was obtained during machining of aluminum using a brass electrode

6 Micro cracks are found on the machined surface The tendency of formation of micro cracks increases during EDM with a higher current and larger pulse-on time

7 A recast layer was found on the machined surface which consists of the molten materials from the workpiece and the electrode that could not be flushed away completely by the dielectric fluid A thicker layer of recast layer was formed on the work surface machined with a higher current and pulse-on time

Islamic University Malaysia (IIUM) for its continuous help during the research work Also, the author likes to appreciate the help of the staff and the technicians of the Department of Manufacturing and Materials Engineering, International Islamic University Malaysia

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Thermal Treatment of Granulated Particles by Induction Thermal Plasma

M Mofazzal Hossain1 and Takayuki Watanabe2

Tokyo Institute of Technology,

of fine powders since couple of decades as a clean reactive heat source [Fan, 1997], [Watanabe, 2004] ITP technology may ensure essentially the in-flight one-step melting, short melting time, and less pollution compared with the traditional technologies that have been using in the glass industries for the vitrification of granulated powders Moreover ITP technology may be very effective in the thermal treatment of porous micro particles and downsizing the particle size During in-flight treatment of particles, it is rear to have experimental records of thermal history of particles; only some diagnosis of the quenched particles is possible for the characterization Thus, the numerical analysis is the only tool to have comprehensive characterization of the particle thermal history and energy exchange during in-flight treatment Thus, for numerical investigation it is the challenge to predict the trajectory and temperature history of the particles injected into the ITP torch Among others Yoshida et al [Yoshida, 1977] pioneered the modeling of particle heating in induction plasmas; though their work assumed the particle trajectory along the centerline of the torch only Boulos [Boulos, 1978] developed a model and comprehensively discussed the thermal treatment of alumina powders in the fire ball of argon induction plasma Later (Proulx et al) [Proulx, 1985] predicted the trajectory and temperature history of alumina and copper particles injected into ITP torch and discussed the particle loading effects in argon induction plasma

In this chapter we shall discuss the in-flight thermal treatment mechanism of silica glass powders by ITP and to optimize the plasma discharge parameters, particle size and feed-rate of input powders that affect the quenched powders size, morphology, and compositions The thermal treatment of injected particles depends mainly on the plasma-particle heat transfer efficiency, which in turn depends to a large extent on the trajectory and temperature history of the injected particles To achieve that goal, a plasma-particle interaction model has been developed for argon-oxygen plasma, including a nozzle inserted

soda-lime-438

into the torch for the injection of carrier gas and soda-lime-silica glass powders This model

can be used to demonstrate the particle loading effects and to optimize the parameters that

govern the particles trajectory, temperature history, quenched particles size and

plasma-particle energy exchange efficiency This model may be used to optimize the plasma and

particle parameters for any combination of plasma gases for example argon-oxygen or argon

nitrogen etc

2 Modeling

2.1 Plasma model

The schematic geometry of the ITP torch is presented in Fig.1 The torch dimensions and

discharge conditions are tabulated in Table 1 The overall efficiency of the reactor is assumed

to be 50%, thus, plasma power is set to 10 kW The torch dimension, power and induction

frequency may vary and can be optimized through the simulation The model solves the

conservation equations and vector potential form of Maxwell’s equations simultaneously

under LTE (local thermodynamic equilibrium) conditions, including a metal nozzle inserted

into the torch It is assumed that plasma flow is 2-dimensioanl, axi-symmetric, laminar,

steady, optically thin, and electromagnetic fields are 2-dimensional Adding the source terms

to the conservation equations, the plasma-particle interaction and particle loading effects

have been taken into account In this model, the conservation equations are as follows:

Mass conservation:

C p

Distance to initial coil position (L1)

Length of injection tube (Lt)

Distance to end of coil position (L2)

Torch length (L3)

Coil diameter (dc)

Wall thickness of quartz tube (Twall)

Inner radius of injection tube (r1)

Outer radius of injection tube (rt)

Outer radius of inner slot (r2)

Inner radius of outer slot (r3)

1 mm 4.5 mm 6.5 mm 21.5 mm 22.5 mm

32 mm Plasma power

Working frequency

Working pressure

Flow rate of carrier gas (Q1)

Flow rate of plasma gas (Q2)

Flow rate of sheath gas (Q3)

10 kW

4 MHz 0.1 MPa

4 ∼ 9 L/min of Argon

2 L/min of Argon

22 L/min Argon & 2 L/min Oxygen Table 1 Torch dimensions & discharge conditions

Energy conservation:

E

r p p

440

2.1.1 Boundary conditions

The boundary conditions for the mass, momentum, energy and species conservation

equations are: at the inlet, gas temperature was set to 300 K and uniform velocity profiles

are assumed based on the given flow rates; on the axis of symmetry, the symmetry

conditions are imposed; on the walls, no-slip condition is assumed; the outer wall

temperature is set to 350 K; and, at the exit, axial gradients of all fields are set equal to zero

The inserted nozzle is assumed to be water cooled at 300 K On the nozzle wall, the velocity

is set to zero The boundary conditions for the vector potential form of Maxwell’s equation

are the same as those described in reference [Mostaghimi, 1998]

2.1.2 Computational procedure and thermophysical properties

The conservation equations, which are listed in previous section, are solved numerically

using the SIMPLER algorithm of Patankar [Patankar, 1980] The algorithm is based on a

control-volume finite-difference scheme for solving the transport equations of

incompressible fluids Calculations are performed for a 44 (in radial direction) by 93 (in axial

direction) non-uniform grid system

Thermodynamic and transport properties of argon and oxygen gases required for the

simulation are mass density, specific heat at constant pressure, viscosity, electrical and

thermal conductivity and radiative loss coefficient The transport properties, which are

function of temperature, are calculated under LTE conditions using Chapman-Enskog first

approximation to Boltzmann equation [Tanaka, 2000] The effective diffusion coefficient of

species is calculated based on the following equations:

, 1

1 i

m i

i ij

j i j

y D

x D

1.1

2.628 10

2

i j ij

The ambipolar diffusion coefficient for ions can be approximated as D a=D ion (1+T e/ ion) As

the thermal equilibrium condition i.e T h= e= ion was applied thus, D a ≅ 2D ion

2.2 Particle model

The following assumptions are made in the analysis of plasma-particle interactions in the

ITP torch; the particle motion is two-dimensional, only the viscous drag force and gravity

affect the motion of an injected particle, the temperature gradient inside the particle is

neglected, and the particle charging effect caused by the impacts of electrons or positive ions

is negligible The particle charging effects have not been intensively studied yet However,

the electromagnetic drag forces caused by the particle charging of the injected particles are

negligible compared with those by neutrals and charged particles due to negligible electrical

conductivity of soda-lime-silica powders Thus, the momentum equations for a single

spherical particle injected vertically downward into the plasma torch can be expressed as

follows:

( )

34

The particle temperature, liquid fraction and diameter are predicted according to the

following energy balances:

2

2 for 1000 1600,

Drag coefficient C Df is calculated using Eq (15) and the property variation at the particle

surface layer and the non-continuum effects are taken into account by Eq (16) and (17)

24 1 0.11 2.0 < 21.0

24

1 0.189

e e

e D

e

e e

R R

R C

R

R R

442

1 2

To take into account the steep temperature gradient between plasma and particle surface,

the Nusselt correlation can be expressed by Eq (19) [Lee, 1985] The non-continuum effect is

taken into account by Eq (20) [Chen, 1983]

2.2.1 Particle source terms

Let us assume Nt0 be the total number of particles injected per unit time, nd is the particle

size distribution, and nr is the fraction of Nt0 injected at each point through the injection

nozzle Thus, the total number of particles per unit time traveling along the trajectory (l, k)

corresponding to a particle diameter dl injected at the inlet point rk is:

For the sake of computation, the particle concentration nr in the inlet is assumed to be

uniform and to be separated into five injection points, which are at radial positions of 0.3,

0.45, 0.6, 0.75 and 0.9 mm In the present computation the particles diameter distribution is

assumed to be Maxwellian (similar to experiment) The particle size and corresponding

distribution fraction are presented in Table 2 In the present computation, the powder is

assumed to be composed of seven size particles according to its diameter and deviation The

average particle diameter is 58 μm and the maximum deviation is 67% As a result, there are

35 different possible trajectories of the injected particles The injection velocity of the

particles is assumed to be equal to the injection velocity of carrier gas

Table 2 Particle size and corresponding distribution fraction

To take into account the particles loading effects, particles source terms for the mass,

momentum, energy and species conservation equations have been calculated in the same

fashion as described in reference [Proulx, 1985], using the Particle-Source-In Cell (PSI-CELL)

approach [Crowe,1977], where the particles are regarded as sources of mass, momentum

and energy The source terms in the mass and species conservation equation, S is the net C p

efflux rate of particles mass in a computational cell (control volume) Assuming the particles

are spherical, the efflux rate of particle mass for the particle trajectory (l, k) that traverses a

given cell (i, j) is:

The net efflux rate of particle mass is obtained by summing over all particles trajectories

which traverse a given cell (i, j):

( , ) , C l k,

C

p ij p ij

l k

The source terms for momentum conservation equations are evaluated in the same fashion

as that of mass conservation equation In this case, the efflux rate of particles momentum for

the particle trajectory (l, k) traversing a given cell (i, j) is:

The calculation is started by solving the plasma temperature and flow fields without

injection of any particles Using these conversed temperature and flow fields, particles

trajectories together with particle temperature and size histories are calculated The particle

444

source terms for the mass, momentum and energy conservation equations for each control volume throughout the torch are then predicted The plasma temperature and flow fields are predicted again incorporating these particle source terms The new plasma temperature and flow fields are used to recalculate the particles trajectories, temperature and size histories Calculating the new source terms and incorporating them into conservation equations constitute the effects of plasma-particle interaction, thereby completing the cycle

of mutual interaction The above computation schemes are repeated until convergence The physical properties of soda-lime-silica glass powders used in the present investigation are listed in Table 3

Latent heat of fusion

Latent heat of vaporization

2300 kg/m3

800 J/kg-K 80%

1000~1600 K

2500 K 3.69×105 J/kg 1.248×107 J/kg Table 3 Physical properties of soda-lime-silica glass powders

3 Simulated results

The calculation has been carrier out for a plasma power of 10 kW, reactor pressure 0.1 MPa and induction frequency 4 MHz The discharge conditions are tabulated in Table 1 In this study, attention is given to the plasma-particle interaction effects on individual particle trajectory, velocity, and temperature history along the trajectories for different carrier gas flow-rate and powder feed-rates Attention also paid to investigate how the plasma-particle energy exchange process is affected by the particle loading effects Two aspects of the thermal treatment are investigated: the behavior of the individual particles, and the global effects of the particles on the plasma fields The carrier gas flow-rate is very vital in determining the individual particle trajectories, and the allowable powder feed-rate Figure

2 shows the isotherms in the torch for a carrier gas flow-rate of 6 L/min argon and various powder feed-rates The other discharge conditions are the same as presented in Table 1 A comparison among the isotherms clearly reveals the intense cooling around the torch centerline that increases with powder feed-rate However, the plasma temperature away from the centerline of the torch remains almost unaffected by higher powder feed-rates This

is because the

individual particle trajectories are not widely outbound in the radial direction; rather the trajectories are very close to the torch axis Thus, the plasma-particle interaction around the centerline is very crucial at higher powder feed-rate The same kind of arguments is proposed by Ye et al [Ye, 2000] to explain the particle trajectories for alumina and tungsten particles The effects of carrier gas flow-rates on the individual particle trajectories are presented in Fig 3, for the particle diameter of 50 μm and a feed-rate of 5 g/min It is comprehended that the higher flow-rate of carrier gas enhances the axial velocity of the particles, because the initial axial velocity of the particles depends on carrier gas flow rate;

as a result the trajectories become closer to the torch axis at higher flow-rate The individual particle temperature history along the trajectory is also influenced by the carrier gas flow-

rate and powder feed-rate Figure 4 shows the effects of carrier gas flow-rate on the particle

temperature for a feed-rate of 5 g/min It is found that the particle temperature along the

trajectory decreases at higher carrier gas flow-rate The main reason is the cooling of plasma

at Fig 2 Effects of powder loading on the isotherms for a carrier gas flow-rate of 6 L/min

higher carrier gas flow-rate that leads less heat transfer to particles Figure 5 describes the

effects of powder feed-rate on the particle temperature along the trajectory Like the

flow-rate of carrier gas, the higher feed-flow-rate of powder also causes intense cooling of plasma;

thus, the heat transfer to particles decreases what results lower particle temperature At this

stage of investigation, it is indeed necessary to discuss the energy transfer mechanism to

particles The energy transfer is affected by the particles physical properties, plasma

temperature, and velocity The last two parameters are affected to a large extent by the

carrier gas flow-rate and powder loading The net energy transfer to particles is calculated

by integrating the energy transfer rate to the particles injected per unit time over the

residence time for all the particle trajectories Mathematically the net energy transfer to

particles (Qnet) can be expressed as follows:

160140120100806040200

Feed-rate: 10 Feed-rate: 5

Feed-rate: 0

0K 1kK 2kK 3kK 4kK 5kK 6kK 7kK 8kK 9kK 10kK 11kK

Radius [mm]

Fig 2 Effects of powder loading on the isotherms for a carrier gas flow-rate of 6 L/min

Powder feed-rate: 5 g/min

Carrier gas flow-rate: 4 Carrier gas flow-rate: 6 Carrier gas flow-rate: 7 Carrier gas flow-rate: 9

Axial distance from top of the torch [mm]

Fig 3 Effects of carrier gas flow-rate on the particle trajectories for a powder feed-rate of

5 g/min

0 20 40 60 80 100 120 140 160 180 0

Carrier: 4 Carrier: 6 Carrier: 7 Carrier: 9

flow-0 20 40 60 80 100 120 140 160 180 0

5

No loading effect With loading effect

Average diameter: 58 μ m Powder feed-rate: 5 g/min

Carrier gas flow-rate [lpm]

Fig 6 Effects of powder loading and carrier gas flow-rate on the plasma-particle energy transfer

448

50 100 150 200 250

300

Carrier gas flow-rate: 9 lpm

Without loading effect With loading effect

Powder feed-rate [g/min]

Fig 7 Particle loading effects on plasma-particle energy transfer at various powder feed-rate the energy transfer to particle by about 44% The powder loading effect and the dependence

of energy transfer to particles on the powder feed-rate is presented in Fig 7, for a carrier gas flow-rate of 9 L/min It can be noticed that energy transfer to particles increases linearly with feed-rate in the absence of particle loading effect; however, when particle loading effect

is taken into account, energy transfer to particles yet increases with feed-rate but with a declined slop The main reason is the intense local cooling of plasma around the torch centerline under dense particle loading It is also evident that the particle loading effect is pronounced at higher powder feed-rate

4 Experimental

4.1 Setup

The experimental setup consists of a plasma torch (Fig 1), a reaction chamber, powder feeder, and a power supply unit (4 MHz, 20 kW) The plasma torch consists of a water-cooled co-axial quartz tube surrounded by a three-turn induction coil The granulated soda-lime-silica glass powders are prepared by spray-drying method from the reagents of

Na2CO3, CaCO3 and SiO2 with the composition of Na2O:16, CaO:10 and SiO2:74 in wt% The mean diameter and porosity of soda-lime-silica glass powders are 58 μm and 80%, respectively The plasma discharge conditions are the same as those described in Table 1 in the modeling section The soda-lime-silica glass powders are injected into ITP torch along with the carrier gas at a rate of 5-20 g/min and the quenched powders are collected on a water-cooled ceramic block at 340 mm from the nozzle exit

4.2 Characterization of plasma-treated particles

The treatment quality of the powders is characterized by the vitrification degree, the surface morphology, cross-sectional structure and composition of the quenched powders The