Yüksek basınç türbinleri için kayıp terimleri doğrulanmışbir boyutlu tasarım kodunun geliştirilmesi
Development of a meanline design tool specialized forhigh pressure turbine with corrected loss system
Yazar: MUHAMMET ENSAR YAZGAN
Danışman: DOÇ. DR. LEVENT ALİ KAVURMACIOĞLU
İstanbul Teknik Üniversitesi / Lisansüstü Eğitim Enstitüsü / Makine Mühendisliği Ana Bilim Dalı / Isı-Akışkan Bilim Dalı
Derece: Yüksek Lisans, 2024
Konu: Makine Mühendisliği = Mechanical Engineering

Özet:
Gaz türbinli motorlar, termik santrallerde elektrik üretmek amacıyla enerji
dönüşümünde; kara, hava ve denizde çeşitli ulaşım türlerine güç sağlamak amacıyla
yaygın olarak kullanılmaktadır. Gaz türbin motorlarının ilk gelişmelerinden günümüze
kadar malzeme ve üretim teknolojilerinin gelişmesi ve ihtiyaçlarının güncellemesi
sebebiyle daha kapsamlı gaz türbini motorları geliştirilmeye başlandı. Daha yüksek
sıcaklık ve basınçlara dayanıklı malzemeler sayesinde, türbin kanat yüklemeleri ve
basınç oranı artarak akış alanındaki hızlar yükselmiştir. Akış alanındaki hızların
yükselmesi transonik türbin teknolojisinin gelişmesini beraberinde getirmiştir.
Transonik türbinler, akış alanında Mach sayısının 0.8'in üstüne çıktığı türbinlerdir.
Mach sayısındaki artış verimi ve performansı daha kritik hale getirmektedir. Bununla
beraber şok kayıplarına hassasiyet gibi zorluklar sebebiyle kanat profillerinin
aerodinamik tasarımına ayrılması gereken zaman artmaktadır. Bu noktada tasarımın
önemli aşamalarından biri olan 1 boyutlu tasarım aşamasında, detay tasarımda elde
edilecek olan tasarıma en yakın aerodinamik tasarım parametreleri ve meridyonel
görünüş belirlenerek, daha yüksek doğrulukla süreç önemli derecede kısaltılmış olur. 1
boyutlu tasarım, türbin kademesinin orta düzleminde, termodinamik çevrim ve
aerodinamik denklemleri kullanarak türbinin her istasyonunda geometrik ve aerotermal
sonuçların hesaplanabildiği tasarımdır. 1 boyutlu tasarım, akıştaki ikincil akışlar, kanat
ucu akışı gibi 3 boyutlu fenomenlerin hakim olması sebebiyle kayıp mekanizmaları ilgili
bağıntılar ve düzeltme katsayıları ile beslenerek daha doğru sonuçlar vermektedir. Bu
çalışmada, literatürde kabul görmüş PWA-5594-92 türbini 3 boyutlu olarak modellenip,
hesaplamalı akışkanlar yöntemi (HAD) ile performans değerleri hesaplanmıştır. Elde
edilen veriler, ilgili türbinin test verileri ile karşılaştırıldığında çok yakın sonuçlar
alınarak doğrulaması yapılmıştır. Türbin kademelerindeki kayıp mekanizmasına ait her
bir kayıp tipi için düzeltme katsayılarının belirlenmesi ve bunun sonucunda
oluşturulacak 1 boyutlu tasarım kodundaki kayıp ifadelerinin minimum hatalarla
hesaplanması amaçlanmaktadır. PWA-5594-92 türbininin farklı test çalışma
noktalarındaki bilinmeyen parametreler, HAD analizleri ile detaylı şekilde
hesaplanarak 1 boyutlu tasarım kodunun aerodinamik ve performans çıktıları ile
karşılaştırlmıştır. Bunun sonucunda, elde edilen bulgular 1 boyutlu tasarım kodunun
toplam türbin performasını maksimum %2.5 sapma değeri ile yakalayabildiğini
göstermektedir.

Abstract:
Gas turbine engines are widely used in power generation to produce electricity for
energy conversion and to operate on land, air and sea to power various types of transport.
Gas turbine engines basically consist of 3 main parts: compressor, combustion chamber
and power turbine. The air taken from the environment is compressed in the compressor
to increase its temperature and pressure, and the compressed air is mixed with fuel in
the combustion chamber to increase its energy. In the turbine, which is the next stage,
this high-energy fluid passes between the turbine blades, creating shaft power, and with
this shaft power, the cycle of the gas turbine cycle is completed by providing the rotation
of the compressor stage. Finally, the air from the turbine is discharged to the outside
environment. Since the early development of gas turbine engines, more comprehensive
gas turbine engines have been developed due to the development of materials and
manufacturing technologies and changing requirements. Thanks to materials resistant
to higher temperatures and pressures, turbine blade loading and pressure ratio have
increased, which has led to higher speeds in the flow field. The increase in flow field
speeds has driven the development of transonic turbine technology. Transonic turbines
are turbines where the Mach number in the flow field exceeds 0.8. As the flow field
changes, flow phenomena such as shocks can occur in the turbine passage and these
phenomena have a significant impact on the blade design. As Mach numbers increase,
the sensitivity of the flow to surface curvature increases. The increase in Mach number
makes efficiency and performance more critical. However, the challenges such as
sensitivity to shock losses increase the time required for aerodynamic design of airfoils.
Turbine design takes place in several stages due to the high number of thermodynamic
and aerodynamic unknowns. Turbine design stages are divided into three according to
the level of detail: 1-D design, 2-D design and 3-D design. At each design stage, the
unknowns are reduced and the design of the stationary and rotating blades is completed
as a result of the 3D design. In 1D design, the design cycle is continued until the desired
performance values are reached. 1-D design is the design in which geometric and
aerothermal results can be calculated at each station of the turbine using the
thermodynamic cycle and aerodynamic equations in the mid-plane of the turbine stage.
In the 1D design, under specified boundary conditions, unknowns such as flow
coefficient, load coefficient and Zweifel are estimated and meridional view and flow
angles are calculated. Since the airfoil profile radius, chord lengths and blade angles are
calculated, the profile, which is part of the 2D design, can be created. The flow field is
created by creating and stacking profiles of all radius. With 2D CFD analysis,
performance targets are achieved by neglecting the effects of 3D phenomena. If thexx
objectives such as flow angles, degree of reaction, throat area and efficiency are
different from the 1D design, the 1D design is updated by going back to the beginning
of the cycle. At this point, if the aerodynamic design parameters and meridional
appearance closest to the design to be obtained in the detail design are determined in the
1-D design phase, which is one of the important stages of the design, the total design
process will be significantly reduced. Since the 1D design is designed with certain
assumptions, it is very difficult to calculate 3D phenomena such as secondary flows in
the flow and blade tip flow at this stage. In order to reduce these difficulties and to
predict turbine losses accurately, loss mechanisms have been developed. Loss
mechanisms investigate the major sources of total loss in the turbine stage. Turbine
losses can be mainly classified as profile losses, secondary losses, blade tip clearance
losses and trailing edge losses. Throughout history, different models have been
developed for loss mechanisms. Loss models for axial turbines were accelerated by the
studies of Ainley and Mathieson in 1951. The accumulation of knowledge on this
subject has increased by successive additions. The studies of Kacker and Okapuu in
1982 are among the most frequently used models in the industry. The Kacker and
Okapuu loss model is used in this study due to its high acceptance in the literature. Since
the flow in the turbine stage is governed by 3-dimensional phenomena, the loss
mechanisms give more accurate results by feeding the relevant relations with correction
coefficients. In this study, the widely known turbine PWA-5594-92 is modeled in 3D
and its performance characteristics are calculated using the computational fluid method
(CFD) as a reference for the loss mechanism correction coefficients. The reason for the
reference turbine study is that the aerodynamic data such as temperature and pressure in
the documentation of the PWA-5494-171 turbine are mostly given at the inlet and outlet
of the turbine, and the Mach, flow angle parameters at the mid-station have a significant
effect on the validation. It was decided to create a reference study in order to increase
the accuracy by accessing more data under different test conditions and to provide a
source for future studies. In order to perform the reference turbine analysis, the stator
and rotor blades were modeled in 3D. For this purpose, the point cloud of the blade
profiles at 3 radial locations were taken and modeled in the design program.
Aerodynamic design criteria such as surface curvature of the blades, profile thickness
distribution, narrowing characteristics in the passage area between the blades, blade
attack and trailing edge thicknesses were taken into consideration during this modeling
in order to obtain accurate results. In addition to the matching of the airfoils, the stacking
of the airfoils at different radial locations is based on the reference turbine. The radial
alignment in the stationary part is taken into account as it can affect the mass flow rate
through the turbine stage. In the case of rotating parts, the radial distribution of the mass
flow rate passing radially between the blades and therefore the radial distribution of the
degree of reaction is also taken into account. After this design stage, 3D airfoils were
designed. In order to run 3D CFD analyses of the PWA-5494-171 turbine, a solution
mesh is needed to solve the flow equations. The quality of these elements affects the
accuracy of CFD analysis and the convergence of the analysis. With a higher quality
solution mesh, the solution can be reached in less iterations. In addition, the Y+ criterion
is kept below 5 in the k-w SST turbulence model used in the CFD analysis to solve the
boundary layer instead of the wall function. CFD analysis is very successful in solving
the complex flow through the boundary layer in the turbine stage and between the
blades. For this, a customized program for turbomachinery was used. When the obtained
data was compared with the test data of the relevant turbine at 3 different points, very
close results were obtained and verified. In these results, the average difference inxxi
efficiency was 0.66% and the average difference in velocity ratio was 1.7%. In addition
to the performance results, static pressure distributions on the blade, static pressure in
the flow field and Mach number distributions at the design point were provided. Since
measurements could be taken during the test on the stationary part, a comparison was
made with the test results. However, no test results were available for the rotating part
due to instrumentation difficulties. For this reason, it was compared with the estimated
static pressure distribution. In this study, a 1-D algorithm that can design a turbine in 1-
D has been developed. The designed 1D code aims to approach the performance and
aerodynamic results of the turbine at the detail level throughout the design stages. In
this design code, correction coefficients affecting the pressure loss term in each blade
are used in the loss mechanism model. In this way, the calculated terms such as
temperature, pressure and speed are approximated to the correct result. This design code
is developed in two different stages. First, the correction coefficients are determined
with an analysis code to validate the reference turbine study. Then, the analysis code
calculates the performance results of an existing turbine under different inlet conditions
or turbine rotor speeds. For this reason, the radius of the meridional view of the turbine,
axial position, blade angles, number of blades and throat area in the stator are input. It
is aimed to determine the correction coefficients for each loss term of the loss
mechanism in the turbine stages and to calculate the loss terms in the 1-D design code
with minimum errors. The unknown parameters at different test operating points of the
PWA-5594-92 turbine are calculated in detail by CFD analysis and compared with the
aerodynamic and performance outputs of the 1-D design code. The results show that the
1D design code is able to capture the overall turbine performance with a maximum
deviation of 2.3%. However, this accuracy is lower than the station-based comparison.
The reason why the deviations in the results are lower at the turbine stage but higher at
the station level is that the axial velocity distribution from the blade root to the blade tip
of the reference turbine is not linear, in other words, the value of the average axial
velocity in the radial direction is different from the value of the axial velocity in the
mean mid-plane.