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Ghenadie Bulat - One of the best experts on this subject based on the ideXlab platform.

  • large eddy simulations of isothermal confined swirling flow in an Industrial Gas turbine
    International Journal of Heat and Fluid Flow, 2015
    Co-Authors: Ghenadie Bulat, W P Jones, S Navarromartinez
    Abstract:

    Abstract The paper describes the results of a computational study of the strongly swirling isothermal flow in the combustion chamber of an Industrial Gas turbine. The flow field characteristics are computed using large eddy simulation in conjunction with a dynamic version of the Smagorinsky model for the sub-grid-scale stresses. Grid refinement studies demonstrate that the results are essentially grid independent. The LES results are compared with an extensive set of measurements and the agreement with these is overall good. The method is shown to be capable of reproducing the observed precessing vortex and central vortex cores and the profiles of mean and rms velocities are found to be captured to a good accuracy. The overall flow structure is shown to be virtually independent of Reynolds number.

  • reacting flow in an Industrial Gas turbine combustor les and experimental analysis
    Proceedings of the Combustion Institute, 2015
    Co-Authors: Ghenadie Bulat, Ekaterina Fedina, Christer Fureby, Wolfgang Meier, Ulrich Stopper
    Abstract:

    Abstract In this investigation the physics of the reacting swirling flow of a commercial Industrial Gas turbine burner (SGT-100) was researched using combustion Large Eddy Simulation (LES) and experiments. In the experimental studies the flow field, temperature and major species concentrations were measured using Particle Image Velocimetry (PIV), OH Planar Laser-Induced Fluorescence (OH-PLIF), one-dimensional laser Raman scattering and OH chemiluminescence imaging. For the finite-rate chemistry LES, two global and two skeletal reaction mechanisms were utilized to evaluate the accuracy and tradeoffs of global and skeletal reaction mechanisms. This type of assessments has previously been carried out for simple flames but not for Industrial flames at laboratory conditions with detailed measurement data. The LES predictions generally show very good agreement with the experimental data for the flow field, temperature and major species. Different reaction mechanisms do not affect the flow field as much as the temperature and species profiles, which show clear imprints of the selected reaction mechanism. The results further indicate that the Industrial flame is best captured with the skeletal reaction mechanisms, whilst the global mechanisms predict too compact flames. The results from the skeletal reaction mechanisms are then used in conjunction with the experimental data to assess the flame characteristics which best can be described as interacting flamelets embedded in an environment of distributed reaction zones.

  • no and co formation in an Industrial Gas turbine combustion chamber using les with the eulerian sub grid pdf method
    Combustion and Flame, 2014
    Co-Authors: Ghenadie Bulat, W P Jones, A J Marquis
    Abstract:

    Abstract The advances in computing power and numerical schemes allow Large Eddy Simulation (LES) to use more detailed turbulent combustion models as well as to be applied to real Gas turbine combustors. In this work, we investigate the emissions formation in an Industrial Gas-turbine combustion chamber using LES with an Eulerian stochastic sub-grid pdf model with reduced chemistry. Sub-grid stresses are represented by a dynamic version of the Smagorinsky model and sub-grid species fluctuations are characterised by eight stochastic fields. The chemistry was represented by an ARM reduced GRI 3.0 mechanism with 15 reaction steps and 19 species. All calculations were carried out using a detailed block-structured mesh capturing all geometrical features of the Siemens SGT-100 burner operating at a pressure of 3 bar. The influence of the radiation heat losses was investigated and the impact of an alternative 4-step chemical mechanism was discussed. The results show good agreement with the experimental data. The NO formation rates were quantified with prompt NO dominating the thermal and N 2 O formation paths.

  • experimental study of Industrial Gas turbine flames including quantification of pressure influence on flow field fuel air premixing and flame shape
    Combustion and Flame, 2013
    Co-Authors: Ulrich Stopper, Wolfgang Meier, Rajesh Sadanandan, Michael Stohr, Manfred Aigner, Ghenadie Bulat
    Abstract:

    Abstract A commercial swirl burner for Industrial Gas turbine combustors was equipped with an optically accessible combustion chamber and installed in a high-pressure test-rig. Several premixed natural Gas/air flames at pressures between 3 and 6 bar and thermal powers of up to 1 MW were studied by using a variety of measurement techniques. These include particle image velocimetry (PIV) for the investigation of the flow field, one-dimensional laser Raman scattering for the determination of the joint probability density functions of major species concentrations, mixture fraction and temperature, planar laser induced fluorescence (PLIF) of OH for the visualization of the flame front, chemiluminescence measurements of OH* for determining the lift-off height and size of the flame and acoustic recordings. The results give insights into important flame properties like the flow field structure, the premixing quality and the turbulence–flame interaction as well as their dependency on operating parameters like pressure, inflow velocity and equivalence ratio. The 1D Raman measurements yielded information about the gradients and variation of the mixture fraction and the quality of the fuel/air mixing, as well as the reaction progress. The OH PLIF images showed that the flame was located between the inflow of fresh Gas and the recirculated combustion products. The flame front structures varied significantly with Reynolds number from wrinkled flame fronts to fragmented and strongly corrugated flame fronts. All results are combined in one database that can be used for the validation of numerical simulations.

R C Reed - One of the best experts on this subject based on the ideXlab platform.

  • oxidation of nickel based single crystal superalloys for Industrial Gas turbine applications
    Acta Materialia, 2011
    Co-Authors: A Sato, Y L Chiu, R C Reed
    Abstract:

    Abstract The oxidation resistance of three prototype single-crystal nickel-based superalloys for Industrial (electricity-generating) Gas turbine applications is studied. All contain greater quantities of Cr than in most existing single-crystal superalloys; two are alloyed with Si. All alloys are found to be marginal Al 2 O 3 -formers, with the performance being better at 1000 °C rather than 900 °C, and when Si is added. Microstructural analysis indicates that the ability to form an Al 2 O 3 layer is better in the interdendritic regions; the dendritic regions are prone to internal oxidation. In all cases, an outer scale of Cr 2 O 3 is formed which is in contact with either Ta 2 O 5 (at 1000 °C) or NiTa 2 O 6 (at 900 °C). To explain the results, the factors known to influence the rate of Al 2 O 3 scale formation are considered. A model is developed to predict whether any given alloy composition will form a continuous Al 2 O 3 scale. This is used to rationalize the dependence of Al 2 O 3 scale formation on alloy composition in these systems. It is useful for the purposes of alloy design.

Silvio Simani - One of the best experts on this subject based on the ideXlab platform.

  • model based robust fault detection and isolation of an Industrial Gas turbine prototype using soft computing techniques
    Neurocomputing, 2012
    Co-Authors: Hasan Abbasi Nozari, Silvio Simani, Mahdi Aliyari Shoorehdeli, Hamed Dehghan Banadaki
    Abstract:

    This study proposes a model-based robust fault detection and isolation (RFDI) method with hybrid structure. Robust detection and isolation of the realistic faults of an Industrial Gas turbine in steady-state conditions is mainly considered. For residual generation, a bank of time-delay multilayer perceptron (MLP) models is used, and in fault detection step, a passive approach based on model error modelling is employed to achieve threshold adaptation. To do so, local linear neuro-fuzzy (LLNF) modelling is utilised for constructing error-model to generate uncertainty interval upon the system output in order to make decision whether a fault occurred or not. This model is trained using local linear model tree (LOLIMOT) which is a progressive tree-construction algorithm. Simple thresholding is also used along with adaptive thresholding in fault detection phase for comparative purposes. Besides, another MLP neural network is utilised to isolate the faults. In order to show the effectiveness of proposed RFDI method, it was tested on a single-shaft Industrial Gas turbine prototype model and has been evaluated based on the Gas turbine data. A brief comparative study with the related works done on this Gas turbine benchmark is also provided to show the pros and cons of the presented RFDI method.

  • fault diagnosis of an Industrial Gas turbine prototype using a system identification approach
    Control Engineering Practice, 2008
    Co-Authors: Silvio Simani, Ron J Patton
    Abstract:

    In this work, a model-based procedure exploiting analytical redundancy for the detection and isolation of faults on a Gas turbine simulated process is presented. The main point of the paper consists of exploiting an identification scheme in connection with dynamic observer or filter design procedures for diagnostic purposes. Thus, black-box modelling and output estimation approaches to fault diagnosis are in particular advantageous in terms of solution complexity and performance achieved. Moreover, the suggested scheme is especially useful when robust solutions are considered for minimising the effects of modelling errors and noise, while maximising fault sensitivity. In order to experimentally verify the robustness of the solution obtained, the proposed FDI strategy has been applied to the simulation data of a single-shaft Industrial Gas turbine plant in the presence of measurement and modelling errors. Hence, extensive simulations of the test-bed process and Monte Carlo analysis are the tools for assessing experimentally the capabilities of the developed FDI scheme, when compared also with different data-driven diagnosis methods.

  • dynamic system identification and model based fault diagnosis of an Industrial Gas turbine prototype
    Mechatronics, 2006
    Co-Authors: Silvio Simani, Cesare Fantuzzi
    Abstract:

    In this paper, a model-based procedure exploiting analytical redundancy for the detection and isolation of faults on a Gas turbine process is presented. The main point of the present work consists of exploiting system identification schemes in connection with observer and filter design procedures for diagnostic purpose. Linear model identification (black-box modelling) and output estimation (dynamic observers and Kalman filters) integrated approaches to fault diagnosis are in particular advantageous in terms of solution complexity and performance. This scheme is especially useful when robust solutions are considered for minimise the effects of modelling errors and noise, while maximising fault sensitivity. A model of the process under investigation is obtained by identification procedures, whilst the residual generation task is achieved by means of output observers and Kalman filters designed in both noise-free and noisy assumptions. The proposed tools have been tested on a single-shaft Industrial Gas turbine prototype model and they have been evaluated using non-linear simulations, based on the Gas turbine data.

A Sato - One of the best experts on this subject based on the ideXlab platform.

  • oxidation of nickel based single crystal superalloys for Industrial Gas turbine applications
    Acta Materialia, 2011
    Co-Authors: A Sato, Y L Chiu, R C Reed
    Abstract:

    Abstract The oxidation resistance of three prototype single-crystal nickel-based superalloys for Industrial (electricity-generating) Gas turbine applications is studied. All contain greater quantities of Cr than in most existing single-crystal superalloys; two are alloyed with Si. All alloys are found to be marginal Al 2 O 3 -formers, with the performance being better at 1000 °C rather than 900 °C, and when Si is added. Microstructural analysis indicates that the ability to form an Al 2 O 3 layer is better in the interdendritic regions; the dendritic regions are prone to internal oxidation. In all cases, an outer scale of Cr 2 O 3 is formed which is in contact with either Ta 2 O 5 (at 1000 °C) or NiTa 2 O 6 (at 900 °C). To explain the results, the factors known to influence the rate of Al 2 O 3 scale formation are considered. A model is developed to predict whether any given alloy composition will form a continuous Al 2 O 3 scale. This is used to rationalize the dependence of Al 2 O 3 scale formation on alloy composition in these systems. It is useful for the purposes of alloy design.

Ron J Patton - One of the best experts on this subject based on the ideXlab platform.

  • fault diagnosis of an Industrial Gas turbine prototype using a system identification approach
    Control Engineering Practice, 2008
    Co-Authors: Silvio Simani, Ron J Patton
    Abstract:

    In this work, a model-based procedure exploiting analytical redundancy for the detection and isolation of faults on a Gas turbine simulated process is presented. The main point of the paper consists of exploiting an identification scheme in connection with dynamic observer or filter design procedures for diagnostic purposes. Thus, black-box modelling and output estimation approaches to fault diagnosis are in particular advantageous in terms of solution complexity and performance achieved. Moreover, the suggested scheme is especially useful when robust solutions are considered for minimising the effects of modelling errors and noise, while maximising fault sensitivity. In order to experimentally verify the robustness of the solution obtained, the proposed FDI strategy has been applied to the simulation data of a single-shaft Industrial Gas turbine plant in the presence of measurement and modelling errors. Hence, extensive simulations of the test-bed process and Monte Carlo analysis are the tools for assessing experimentally the capabilities of the developed FDI scheme, when compared also with different data-driven diagnosis methods.