To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
be a finite group. We denote by
the probability that two randomly chosen elements of
generate a nilpotent subgroup and by
the set of elements
is a nilpotent subgroup. A group
is called an
is a subgroup of
. We prove that if
is soluble. Also, we classify semisimple
In the present work, a recently developed in-house 2D CFD code is used to study the effect of gas turbine stator blade roughness on various performance parameters of a two-dimensional blade cascade. The 2D CFD model is based on a high resolution flux difference splitting scheme of Roe (1981). The Reynolds Averaged Navier-Stokes (RANS) equations are closed using the zero-equation turbulence model of Baldwin-Lomax (1978) and two-equation Shear Stress Transport (SST) turbulence model. For the smooth blade, results are compared with experimental data to validate the model. Finally, a correlation between roughness Reynolds number and loss coefficient for both turbulence models is presented and tested for three other roughness heights. The results of 2D turbine blade cascades can be used for one-dimensional models such as mean line analysis or quasi-three-dimensional models e.g. streamline curvature method.