Raton (Florida, USA): CRC
Press, Inc.
Lavan, Z., Thomson, J.
(1977). Experimental study
of thermally stratified hot
water storage tanks.
Solar Energy 19.
Lienhard, J.H. IV, Lienhard,
J.H. V. (2004). A heat
transfer textbook.
Cambridge
(Massachusetts, USA)
techniques, with important
applications
not only in new products
design and development,
but also in the
improvement of the
design of existing
products. In short, the
methodology consists
firstly to select the
appropriate mixtures from
which the response
knowledge in the foundry
industry.
(Ferreira et al., 2005).
The ability of heat to flow
across the casting and
through the interface from
the casting to
the mold directly affects
the evolution of
solidification and plays a
notable role in
determining the
x1, x2 and x3 independent
variables; 1,
2 and 3 are linear
coefficients; 12, 13 and
23 are cross product
coefficients and 11, 22
and
33 are the quadratic
coefficients (Kwak, 2005).
In general Eq. (9) can be
written in matrix form
(Aslan, 2007).
Y = bX + (
curves in different points
of the
system were simulated.
Also, a mathematical
model of optimization was
proposed and
finally an analysis by the
factorial design of the
considered parameters
was made.
2. Methodology of the
numerical simulation
The finite e
a maximum or a minimum
of a function of the design
parameters (Aslan, 2007).
Factorial
design is a useful tool in
order to characterize
multivariable processes. It
gives the
possibility to analyze the
important influent factors
of the process, and to
iden
three-dimensions.
However, in this work the
analysis was accomplish in
2-D, which is
illustrated in Figure 1(b).
Some material properties
of Cu-5 wt %Zn alloy were
taken from
the reference Miettinen
(Miettinen, 2001), the
other properties were
taken from
Lalovic (model C). It can be
observed that the highest
temperature profile
corresponds to
model A, followed by
model C and last by model
B, mainly after the
solidification range.
Although not presented, a
similar behavior has
occurred at other positions
i
surfaces (Kwak, 2005). The
design
procedure of response
surface methodology is as
follows (Gunaraj &
Murugan, 1999):
i. Designing of a series of
experiments for adequate
and reliable measurement
of the
response of interest.
ii. Developing a
mathematical m
Table 1. The boundary
condition was the
convection phenomenon
and this phenomenon
was applied to the outside
walls of the sand mold, as
shown in Table 1. The
convection
transfer coefficient at the
mold wall was considered
constant in this work, due
to lac
process of the alloy Cu-5
wt %Zn
during 1.5 h of cooling. It
was optimized through the
factorial design in three
levels, where
the considered parameters
were: temperature of the
mold, the convection in the
external
mold and the generation of
heat during t
overcome the lack of data
and achieve a
better understanding of
how changes in
composition within a
specification range of an
alloy
may affect solidification
properties, it is highly
desirable to develop
experimental techniques
or computer models for
calc
the widely used Scheil
relationship, which
assumes uniform solute
concentration in the
liquid but no diffusion in
the solid (Shi & Guo,
2004):
= 1
(4)
where ko the equilibrium
partition coefficient of the
alloy.
Eq. (1) defines the heat
flux (Radov
shape castings is
microporosity, formed due
to the combined effects of
volumetric shrinkage
upon solidification.
Developing a model to
predict the formation of
microporosity in
solidifying metal castings
is one way of helping.
Porosity in castings is a
de
VUT FEI Brno, vol. 13, ISBN
80-214-1346-8, pp. 41.
Fisher L.S. (1976). The
thermodynamics and some
practical aspects of
thermally layered heat
storage
in water. Turnberry
(Scotland): NATO Science
Commitee Conference on
Thermal
Energy.
Garg, H.P., Mullick,
3. Result and discussion
The result for solidification
was discussed for some
particular cases, at
condition given in
lines 7, 8 and 9 from Table
1, which correspond
respectively to the lowest
temperatures for
each mathematical model
of latent heat releas
We may conclude that, in
relation to the desiccated
emulsion system, the
numerical model
enabled us to identify
weak points of the design.
These drawbacks consist in
the fact that,
under certain conditions,
local spots might occur
where uncontrolled
tempe
nalysis was, L m
the first factor
ection phenomen
gnificant influenc
ical model) with
bles and interact
e of standard gra
cts the microstr
Correlations betw
n in the literatu
() and seconda
increases with de
n of temperature
It can be observ
owed by model
Properties and Numerical
Modeling-Simulation of
Phase Changes Material
375
Goldstein, M. (1961). Some
physical chemical aspects
of heat storage. Roma
Italy, UN
Conference on New Source
of Energy.
Jirku T, Fiala P, Kluge M.
(May 2010). Magnetic
resonant h
the water from the oil.
t=10.8 s, with
the magnetron output of
P=800W and frequency
f=2.4GHz. Figure 31 shows
the distribution
of temperature rise in the
process of exsiccation;
here, the indicated aspects
include the heat
generated through the
Joule loss
Vener, C. (1997). Phase
change thermal energy
storage. The Department
of The Built Environment
Brighton, University of
Brighton, Brighton.
Verdonschet, J.K.M. (1981).
Thermal storage system
based on the heat of
adsorption in air-based
solar heating system
State University of Ponta
Grossa UEPG
Brazil
1. Introduction
Throughout the
manufacturing industry,
casting process simulation
has been widely
accepted as an important
tool in product design and
process development to
improve yield
and casting quality.
Ca
applies principles and
techniques at the data
collection stage so as to
ensure the generation
of valid, precise, and
accurate engineering
conclusions (Xiao & Vien,
2004). It is a very
economic way of extracting
the maximum amount of
complex information an
Therefore, Eq. (2) is
actually dependent on two
factors: temperature and
solid fraction. The
solid fraction can be a
function of a number of
solidification variables. But
in many systems,
especially when
undercooling is small, the
solid fraction may be
as
release, (Z) rep
factorial design is
re for the inferio
by (0) and for the
three dimensiona
am of Cu-5 wt %Z
e, 2010)
factors) and thei
ection phenomen
presents the resu
s shown in Table
or state of the v
superior state by
Convection and
(b)
al and (b) bi
mandatory when the
problem involves a large
number of factors (Khajeh,
2009). On the
other hand, since only two
levels are used, the models
that may be fit to these
designs are
somewhat restricted. If a
more sophisticated model
is needed, as for the
locat
solidified part of the
crystal and the enthalpy of
the solid increases and
thus the latent heat
will decrease (Radovic &
Lalovic, 2005). Due to this
fact, another way to
represent the
change of the solid fraction
during solidification can be
written as (R
ENME 371 Product Engineering and Manufacturing
Quiz 4 -
SOLUTIONS
Answer the following. Time available is 20 min.
1. 2 points. For a product under development, four criteria (a, b, c, and d) are established and rated
as follows: Criterion a is more import
ENME 371 Product Engineering and Manufacturing Dr. Thamire
Study Guide for Quiz # 4
Functional Decomposition
Concept Generation, Selection, and Testing
Going through lecture notes may be sufficient for this quiz, although reading the text will certainly
h
Fig. 4. (a) Thermal
gradient (K/m) in vector
form and (b) Heat flux
(W/m2) in vector form
(line 9 of Table 1)
In order to simulate the
cooling curves, two points
were considered, as shown
in Figure 5:
one located in the core
(point 2) and the other in
the
almost uniform
temperature is observed.
In the geometric structure
of the mold there is a
core constituted of sand
that is represented by a
white circle in Figure 3(b),
which can be
verified also in Figure 1(a).
In Figure 4 the results of
the thermal grad
(9)
where x1, x2,xk are the
input factors which
influence the response y;
o, ii (i=1, 2,m), ij
(i=1, 2,m; j=1,2,m)
are unknown parameters
and is a random error.
The coefficients,
which should be
determined in the secondorder model, are obtained
by the le
aph was accompl
Convection and
ructure character
ween dendritic s
ure (Rosa et al.
ary (SDAS) or pr
ecreasing (SDAS)
e evolution at p
ved again, that th
and last by mod
hart (which was o
ptimized using a
on a highly fra
oncerning conditi
d point 2
terakis
et al.,
d x3, based in Ta
gure 7. In this fig
vel (p) of 95%, sho
opted for this an
e main effect of
rameter 2 (conve
lease form).
Figure 7, two sig
d x3 (mathemati
dependent variab
alysis, other type
(a)
n parameter affe
c arm spacings.
are well known
e