The purpose of the present study is to select from the
open literature a set of correlations that collectively give a
good overall performance prediction at design and off-
design conditions for a range of different compressors
with conventio nal blade pro les (pro les with circular or
parabolic camber lines). A quasi-one-dimensional numerical
model will then be developed in the form of a FORTRAN
program. The program will be subsequently coupled to a
surge prediction model also written in FORTRAN and
previously develo ped at Cran eld by Gill and Elder [10]
and Escuret and Elder [11].
It is intended that these two prediction programs will be
nally incorporated (as subroutines) into an optimization
program for geometry settings. This is mentioned in more
detail later on.
2 CORRELATION REVIEW
There are two basic requirements for the prediction of stage
performance of an axial ow compressor [12]. The rst is
knowledg e of the variation in the outlet ow angle as a
function of the inlet ow angle, and the second is knowledge
of the variation in the losses or ef ciency, again as a
function of inlet ow angle. Cetin
et al.
[13] described
work that had been directed towards selecting the most
promising correlations for off-design loss coef cient and
deviation from the literature and improving them to account
for transonic and three-dimensional effects. Miller and
Wasdell [3] and Wright and Miller [4] presented a different
set of correlations that had originated from other sou rces but
subsequ ently improved to account for effects such as
Reyno lds number and compressibility. They were successful
in predicting the off-design performance for a selection of
high-sp eed compressors.
The work described in this p aper required individual
bladerow analysis to ensure that the axia l mismatching
between rotor and stator blades was captured at off-design
condit ions. Moreover, the correlation set had to offer stable
convergence for the whole comp ressor operating range.
Resultin g from these considerations, the moss successful
correlation set suggested in reference [13] was chosen for
comparison with those given in references [3] and [4]. In
each case, the actual method is similar and can be summar-
ized as follows: rstly, a blade loading parameter is found
such as the equivalent diffusion ratio
D
eq
at the minimum
loss incidence
i
ml
. The velocity and ow angle te rms that
correspon d to th is minimum loss cond ition are estimated by
assuming that
V
a
remains constant at inlet and exit to the
bladerow and
a
1 ml
and
a
2 ml
are given by the correlations for
i
ml
and
d
ml
. The corresponding pro le loss parameter,
o
p ml
, is then estimated for the minimum loss incidence
condit ion using a co rrelation based upon the classic Lieblein
approach [14]. Secondly, the shock loss
o
s
is found for high
inlet Mach numbers, estimated from a simple, normal shock
analysis. Finally, the combined magnitude of
o
pml
and
o
s
is
corrected for the actual incidence, using a suitable function
that approximates the blade loss c haracteristic. The deviation
is also corrected for the actual incidence. The effects of
endwall lo ss
o
ew
and blockage
K
B
are subseque ntly
introdu ced to give the total loss coef cient
o
tot
.
2.1 Selected correlations
Table 1 lists the origin of each set of correlations u sed
within this study. The suggested method for estimating
o
p
in reference [13] was the Koch and Smith technique,
presented in detail in reference [15]. The in uences of
streamtube contraction, Rey nolds number, Mach n umber
and blade surface roughness upon the loss were included to
produce an effective model that was found to give agree-
ment with test results for compressors with a wide range of
design parameters. The correlations used to account for off-
design incidence and deviation in set 1 were those of
Creveling [16]. This choice was also based upon the ndings
given in reference [13], where it was shown th at the equation
set gave the best agreemen t with the available test data.
The shock loss coef cient,
o
s
, was estimated from two
different models, one for each set. In set 1, the techniqu e
was again that suggested in reference [13], where the
subson ic but su percritical loss was found with the Jansen
and Moffatt method [17] and the supersonic loss was found
with the Swan method [18]. The second model, used in set 2,
was that of Schwenk
et al.
[19] applied in the same way as
given in reference [4]. This particu lar loss component is a
dif cult mechanism to approximate well, in particular the
interaction of the passage shock wave and the suction
surface boundary layer is a major factor that should be
consid ered. As sonic conditions are approached, the ow
becomes very sensitive to c hanges in ow area and a blade-
to-blade description may not be very suitable. Bearing these
facts in mind, the loss model employed within a simple one-
dimensio nal mean-line code such as this is likely to be, at
best, a fair approximation of the magnitude and general
trend of such a complex system. Figure 1, taken from
reference [19], shows a simple representation of the passage
shock mechanism. The position of the bow wave intersec-
tion point with the suction surface is determined, and the
suction surface Mach number is then estimated at that point
using the Prandt–Meyer expansion angle
n
. The total
pressure loss across the normal shock wave at this point,
P
01
¡P
02
, is then found from the average of the upstream
and suction surface Mach numbers.
The methods given in references [18] and [19] are quite
similar, and both follow the above procedure for supersonic
inlet Mach numbers. Subson ic inlet conditions that have
exceeded a critical level and caused a supersonic patch on
the suction surface result in a weaker shock wave, and this is
estimated in reference [17] by a simple law that increases
o
p
as
M
1
increases. Alte rnatively, for set 2, the Schwenk
et al.
method is applied for
M
1
ˆ
1:0 and a linear relationship is
assumed between this loss value and that for the critical
subson ic
M
1 cr
where the loss is taken to be zero. The actual
A06101 # IMechE 2002 Proc Instn Mech Engrs Vol 216 Part A: J Power and Energy
AXIAL COMPRESSOR PERFORMANCE MODELLING WITH A QUASI-ONE-DIMENSIONAL APPROACH 183