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
- Tez No: 863646
- Danışmanlar: DOÇ. DR. LEVENT ALİ KAVURMACIOĞLU
- Tez Türü: Yüksek Lisans
- Konular: Makine Mühendisliği, Mechanical Engineering
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2024
- Dil: Türkçe
- Üniversite: İstanbul Teknik Üniversitesi
- Enstitü: Lisansüstü Eğitim Enstitüsü
- Ana Bilim Dalı: Makine Mühendisliği Ana Bilim Dalı
- Bilim Dalı: Isı-Akışkan Bilim Dalı
- Sayfa Sayısı: 95
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.
Özet (Çeviri)
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.
Benzer Tezler
- Development of an axial compressor design and blade profile generation tool
Eksenel kompresör tasarım ve kanat profili oluşturma programı geliştirilmesi
MUSTAFA MAZAN
Yüksek Lisans
İngilizce
2024
Makine Mühendisliğiİstanbul Teknik ÜniversitesiMakine Mühendisliği Ana Bilim Dalı
PROF. DR. MESUT GÜR
- Francis turbine design and optimization by using CFD
HAD analizleri yardımı ile francis türbin tasarımı ve optimizasyonu
BERK CAN DUVA
Yüksek Lisans
İngilizce
2016
Enerjiİstanbul Teknik ÜniversitesiEnerji Bilim ve Teknoloji Ana Bilim Dalı
PROF. DR. HABİL METE ŞEN
PROF. DR. ERKAN AYDER
- Organik rankine sistemi ve türbininin tasarımı
Organic rankine system and turbine design
NURİYE ANIL GÜRLEK
Yüksek Lisans
Türkçe
2016
Enerjiİstanbul Teknik ÜniversitesiUçak ve Uzay Mühendisliği Ana Bilim Dalı
PROF. DR. FIRAT OĞUZ EDİS
- Short-term wind power generation forecasting by coupling numerical weather prediction models and machine learning algorithms
Sayısal hava tahmin modeli ve makine öğrenmesi algoritmaları ile kısa dönemli rüzgar enerjisi üretim tahmin modeli oluşturmak
CEM ÖZEN
Doktora
İngilizce
2022
Enerjiİstanbul Teknik ÜniversitesiMeteoroloji Mühendisliği Ana Bilim Dalı
PROF. DR. ALİ DENİZ
- Design and meta-heuristic based optimization of axial-flux induction generator for variable speed wind turbines
Değişken hızlı rüzgâr türbinleri için eksenel akılı asenkron generatör tasarımı ve meta-sezgisel yöntemlerle optimizasyonu
BATI EREN ERGUN
Yüksek Lisans
İngilizce
2024
Elektrik ve Elektronik Mühendisliğiİstanbul Teknik ÜniversitesiElektrik Mühendisliği Ana Bilim Dalı
DOÇ. DR. MEHMET ONUR GÜLBAHÇE