João Roberto Barbosa

EFFECTS OF TURBINE TIP CLEARANCE ON GAS TURBINE PERFORMANCE

There are many different sources of loss in gas turbines. The turbine tip clearance loss is the focus of this work. In gas turbine components such as compressor and turbine the presence of rotating blades necessitates a small annular tip clearance between the rotor blade tip and the outer casing. This clearance, although mechanically necessary, may represent a source of large loss in a turbine. The gap height can be a fraction of a millimeter but can have a disproportionately high influence on the stage efficiency. A large space between the blades and the outer casing results in detrimental leakages, while contact between them can damage the blades. Therefore, the evaluation of the sources of the performance degradation independently presents useful information that can aid in the maintenance action. As part of the overall blade loss the turbine tip clearance loss arises because at the blade tip the gas does not follow the intended path and therefore does not contribute to the turbine power output and interacts with the outer wall boundary layer. Increasing turbine tip clearance causes performance deterioration of the gas turbine and therefore increases fuel consumption. The increase in turbine tip clearance may as a result of rubs during engine transients and the interaction between the blades and the outer casing. This work deals with the study of the influence of the turbine tip clearance on a gas turbine engine, using a turbine tip clearance model incorporated to an engine deck. Actual data of an existing engine were used to check the validity of the procedure. This paper refers to a single shaft turbojet engine under development, operating under steady state condition. Different compressor maps were used to study the influence of the curve shapes on the engine performance. Two cases were considered for the performance simulation: constant corrected speed and constant maximum cycle temperature.© 2008 ASME

MULTIPLE FAULTS DETECTION OF GAS TURBINE BY MLP NEURAL NETWORK

This paper describes a procedure to measure the performance of detection and isolation of multiple faults in gas turbines using artificial neural network and optimization techniques. It is on a particular form of artificial neural networks, the traditional multi-layer perceptron (MLP). Error back-propagation and different activation functions are used. The main goal is to recognize single, double and triple faults in a turboshaft engine, whose performance data were output from a gas turbine simulator program, tuned to represent the engine running at an existing power station. MLP network is a nonlinear interpolation function usually made of input layer, hidden-layer and output-layer, with different neuronal units, but in this work, only one hidden-layer was used. Weights were altered by error back-propagation from the initial values established from a seed fixed between 0 and 1. The activation function in the MLP algorithm is the sigmoid function. The best moment to stop the training process and avoid the over fitting problem was chosen by cross-validation. Optimization of convergence error was achieved using the momentum criteria and reducing the oscillation problem in all nets trained. Several configurations of the neural network have been compared and evaluated, using several noise graduations incorporated to the data, aiming at finding the network most suitable to detect and isolate multiple faults in gas turbines. Based on the results obtained it is inferred that the procedure reported herein may be applied to actual systems in order to assist in maintenance programs, at least.Copyright

Part-Load Versus Downrated Industrial Gas Turbine Performance

For distributed power generation, sometimes the available gas turbines cannot match the power demands. It has been usual to uprate an existing gas turbine in the lower power range by increasing the firing temperature and speeding it up. The development costs are high and the time to make it operational is large. In the other hand, de-rating an existing gas turbine in the upper power range may be more convenient since it is expected to cut significantly the time for development and costs. In addition, the experience achieved with this engine may be easily extrapolated to the new engine. This paper deals with the performance analysis of an existing gas turbine, in the range of 25 MW, de-rated to the range of 18 MW, concerning the compressor modifications that could be more easily implemented. Analysis is performed for the base engine, running at part-load of MW. A variable geometry compressor is derived from the existing one. Search for optimized performance is carried out for new firing temperatures. A variable geometry turbine analysis is performed for new NGV settings, aiming at better cycle performance.© 2004 ASME

Performance Study of a 1 MW Gas Turbine Using Variable Geometry Compressor and Turbine Blade Cooling

This work presents the performance study of a 1 MW gas turbine including the effects of blade cooling and compressor variable geometry. The axial flow compressor, with Variable Inlet Guide Vane (VIGV), was designed for this application and its performance maps synthesized using own high technological contents computer programs. The performance study was performed using a specially developed computer program, which is able to numerically simulate gas turbine engines performance with high confidence, in all possible operating conditions. The effects of turbine blades cooling were calculated for different turbine inlet temperatures (TIT) and the influence of the amount of compressor-bled cooling air was studied, aiming at efficiency maximization, for a specified blade life and cooling technology. Details of compressor maps generation, cycle analysis and blade cooling are discussed.Copyright

Gas Turbine Fault Detection and Isolation Using MLP Artificial Neural Network

This work deals with a nonlinear model, based on a particular form of artificial neural networks, ANN, for application to gas turbines fault diagnosis. The traditional multi-layer perceptron (MLP) is used, with error back-propagation and different activation functions. The application of the model is illustrated using test data from a gas turbine simulation computer program. A specially developed computer program is used to simulate the engine in operation, generating all needed engine data for both baseline and deteriorated engine. A test case using a turboshaft engine is used to demonstrate the capacity of this ANN to identify faults that may occur during engine operation.Copyright

Gas Turbine Performance Simulation Using an Optimized Axial Flow Compressor

Gas turbines need to operate efficiently due to the high specific fuel consumption. In order to reach the best possible efficiency the main gas turbine components, such as compressor and turbine, need to be optimized. This work reports the use of two specially developed computer programs: AFCC [1, 2] and GTAnalysis [3, 4] for such purpose. An axial flow compressor has been designed, using the AFCC computer program based on the stage-stacking technique. Major compressor design parameters are optimized at design point, searching for best efficiency and surge margin. Operation points are calculated and its characteristics maps are generated. The calculated compressor maps are incorporated to the GTAnalysis computer program for the engine performance calculation. Restrictions, like engine complexity, manufacture difficulties and control problems, are not taken into account.Copyright

Influence of Variable Geometry Transients on the Gas Turbine Performance

During the design of a gas turbine it is required the analysis of all possible operating points in the gas turbine operational envelope, for the sake of verification of whether or not the established performance might be achieved. In order to achieve the design requirements and to improve the engine off-design operation, a number of specific analyses must be carried out. This paper deals with the characterization of a small gas turbine under development with assistance from ITA (Technological Institute of Aeronautics), concerning the compressor variable geometry and its transient operation during accelerations and decelerations. The gas turbine is being prepared for the transient tests with the gas generator, whose results will be used for the final specification of the turboshaft power section. The gas turbine design has been carried out using indigenous software, developed specially to fulfill the requirements of the design of engines, as well as the support for validation of research work. The engine under construction is a small gas turbine in the range of 5 kN thrust / 1.2 MW shaft power, aiming at distributed power generation using combined cycle. The work reported in this paper deals with the variable inlet guide vane (VIGV) transients and the engine transients. A five stage 5:1 pressure ratio axial-flow compressor, delivering 8.1 kg/s air mass flow at design-point, is the basis for the study. The compressor was designed using computer programs developed at ITA for the preliminary design (meanline), for the axisymmetric analysis to calculate the full blade geometry (streamline curvature) and for the final compressor geometry definition (3-D RANS and turbulence models). The programs have been used interatively. After the final channel and blade geometry definition, the compressor map was generated and fed to the gas turbine performance simulation program. The transient study was carried out for a number of blade settings, using different VIGV geometry scheduling, giving indication that simulations needed to study the control strategy can be easily achieved. The results could not be validated yet, but are in agreement with the expected engine response when such configuration is used.Copyright

Hybrid Neural System for Gas Turbine Diagnostics: An Optimization Strategy

New health monitoring strategies were developed in the last decade aiming at improvement of gas turbines safety and reliability. Real time methodologies have been considered of major concern for safe operation at least cost. This paper describes a hybrid system approach for turboshaft faults diagnosis, using data obtained from a tuned high fidelity gas turbine simulator program, including those for multiple faults deteriorated performance. Kohonen neural network was used to analyze similarity together with an optimization strategy to reduce the volume of data used in the diagnostics phase. A Multi-Layer Perceptron (MLP) was used for training and validation. The MLP and Kohonen networks were tested for several configurations, in order to improve diagnosis. The hybrid system was also tested with noise-contaminated data and it was verified the capability of the neural approach to detect and isolate multiple faults better than the MLP alone. The results showed that the optimization strategy reduced significantly the database patterns and improved the learning process, demonstrating high precision to diagnose gas turbine operation problems. The reliability of the proposed system is explained both qualitatively and quantitatively.© 2010 ASME

A Comparison of Loss Models Using Different Radial Distribution of Loss in an Axial Turbine Streamline Curvature Program

The streamline computer codes published in the open literature and used to analyze the performance of axial flow turbines have employed a particular loss model chosen from a number of existing prediction methods. It is well known that the performance prediction methods developed for one-dimensional models concentrates the losses at the blade mid-height. When used in a streamline curvature model, however it is necessary to distribute these losses along the blade span. However the way to distribute the losses is not unique, as is clear from the open literature. Some methods seem to be an arbitrary procedure, with a shortcoming in representing the real flow behavior within the blade row. In this paper, two different loss distribution models were implemented in a streamline curvature program specially developed for the study of axial flow turbine performance. The study seeks to establish which one best represents the reality of the complex flow physics occurring within a blade row. Three different loss models were also implemented in the program to check their reliability and validity when combined with different loss distribution systems. Performance maps for a single-stage turbine were generated by means of different combinations of loss models and radial loss distributions. The computed result for each case was compared with available experimental data of a single-stage turbine.Copyright

AN OBJECT-ORIENTED PARALLEL FINITE-VOLUME CFD CODE

This paper concerns the parallelization and optimization of an in-house three-dimensional unstructured finite-volume computational fluid dynamics (CFD) code. It aims to highlight the use of programming techniques in order to speedup computation and minimize memory usage. The motivation for developing an in-house solver is that commercial codes are general and sometimes simulations are not in agreement with actual phenomena. Moreover, in-house models can be developed and easily integrated to the solver. The original code was initially written in Fortran 77 though the most recent added subroutines include Fortran 90 features. Due to language restrictions and the initial project objectives, issues such as memory usage minimization were not considered. The new code uses an object-oriented paradigm aiming to enhance code reuse and increase efficiency during application development. The parallel code is fully written in Fortran 90 using MPI and hence portable to different architectures. Numerical experiments of typical 3D cases, such as flat plate with uniform incoming flow and a converging-diverging supersonic nozzle, were carried out showing good parallel efficiency. The serial version of the ported code has shown a considerable reduction on the execution time compared to the original code. Convergent solutions agree with the solution of the original code.Copyright