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Numerical Heat Transfer, Part A: Applications
An International Journal of Computation and Methodology
Volume 69, 2016 - Issue 12
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Original Articles

Computational optimization of the internal cooling passages of a guide vane by a gradient-based algorithm

, &
Pages 1311-1331 | Received 19 Jul 2015, Accepted 22 Nov 2015, Published online: 02 May 2016
 

ABSTRACT

To keep the spatially averaged temperature and thermal stress of gas turbine blades and guide vanes within a permissible level, the present research concentrates on the optimization of the internal cooling passages in a guide vane. The main purpose is to search for the most optimal sizes, distributions, and shapes of internal cooling channels located in a guide vane. Cylindrical cooling passages and newly built passages shaped by Bezier curves are both considered in this investigation. In order to maintain the shapes of the cooling channels within the scale of the vane profile, a new technique is suggested to discretize the vane into the components, and then the outline of the passages is built based on the components. The optimization of sizes, locations, and shapes of the cooling passages is solved as a single-objective problem using a gradient-based optimization algorithm, i.e., the globally convergent method of moving asymptotes (GCMMA). The optimized result displays a substantial reduction in both the spatially averaged temperature and thermal stress of the vane, and the related configurations are included and discussed in the investigation.

Nomenclature

d=

hydraulic diameter

E=

elasticity tensor

h=

convective heat transfer coefficient

n=

number

Nu=

Nusselt number

Pr=

Prandtl number

R=

rotation matrix

Re=

Reynolds number

T=

translation matrix

T0=

the initial temperature distribution

uik, lik=

the upper and lower moving asymptotes of the design variables xi

xik=

the ith variable in the kth iteration

xi, yi=

center coordinates of the ith cooling hole

x, y=

global coordinates

Xf, yf=

reference point coordinate of the local coordinate system

Δxi=

the disturbance of xik

X0=

the matrix of shape design variables

β=

thermal elasticity tensor

ε=

strain tensor

Θf=

rotation angle between local coordinate and global coordinate

λ=

thermal conductivity

μ=

fluid viscosity

ν=

speed of fluid

ρ=

density of air

ρk=

global convergence control parameter in the kth iteration

σ=

the stress tensor

Nomenclature

d=

hydraulic diameter

E=

elasticity tensor

h=

convective heat transfer coefficient

n=

number

Nu=

Nusselt number

Pr=

Prandtl number

R=

rotation matrix

Re=

Reynolds number

T=

translation matrix

T0=

the initial temperature distribution

uik, lik=

the upper and lower moving asymptotes of the design variables xi

xik=

the ith variable in the kth iteration

xi, yi=

center coordinates of the ith cooling hole

x, y=

global coordinates

Xf, yf=

reference point coordinate of the local coordinate system

Δxi=

the disturbance of xik

X0=

the matrix of shape design variables

β=

thermal elasticity tensor

ε=

strain tensor

Θf=

rotation angle between local coordinate and global coordinate

λ=

thermal conductivity

μ=

fluid viscosity

ν=

speed of fluid

ρ=

density of air

ρk=

global convergence control parameter in the kth iteration

σ=

the stress tensor

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