Experimental analysis of oxygen-methane combustion inside a gas turbine reactor under various operating conditions

Energy ◽  
2015 ◽  
Vol 86 ◽  
pp. 105-114 ◽  
Author(s):  
Mohamed A. Habib ◽  
Medhat A. Nemitallah ◽  
Pervez Ahmed ◽  
Mostafa H. Sharqawy ◽  
Hassan M. Badr ◽  
...  
Keyword(s):  
Gas Turbine ◽  
Experimental Analysis ◽  
Methane Combustion ◽  
Operating Conditions

scholarly journals Quantifying the Effect of Kinetic Uncertainties on NO Predictions at Engine-Relevant Pressures in Premixed Methane-Air Flames

2019 ◽  
Author(s):  
Antoine Durocher ◽  
Gilles Bourque ◽  
Jeffrey M. Bergthorson
Keyword(s):  
Gas Turbine ◽  
High Pressures ◽  
Reaction Pathway ◽  
Methane Combustion ◽  
Operating Conditions ◽  
Combustion Model ◽  
Atmospheric Conditions ◽  
N2o Production ◽  
Large Variability ◽  
Kinetic Rates

Abstract Accurate and robust thermochemical models are required to identify future low-NOx technologies that can meet the increasingly stringent emissions regulations in the gas turbine industry. These mechanisms are generally optimized and validated for specific ranges of operating conditions, which result in an abundance of models offering accurate nominal solutions over different parameter ranges. At atmospheric conditions, and for methane combustion, a relatively good agreement between models and experiments is currently observed. At engine-relevant pressures, however, a large variability in predictions is obtained as the models are often used outside their validation region. The high levels of uncertainty found in chemical kinetic rates enable such discrepancies between models, even as the reactions are within recommended rate values. The current work investigates the effect of such kinetic uncertainties in NO predictions by propagating the uncertainties of 30 reactions, that are both uncertain and important to NO formation, through the combustion model at engine-relevant pressures. Understanding the uncertainty sources in model predictions and their effect on emissions at these pressures is key in developing accurate thermochemical models to design future combustion chambers with any confidence. Lean adiabatic, freely-propagating, laminar flames are therefore chosen to study the effect of parametric kinetic uncertainties. A non-intrusive, level 2, nested sparse-grid approach is used to obtain accurate surrogate models to quantify NO prediction intervals at various pressures. The forward analysis is carried up to 32 atm to quantify the uncertainty in emissions predictions to pressures relevant to the gas turbine community, which reveals that the NO prediction uncertainty decreases with pressure. After performing a Reaction Pathway Analysis, this reduction is attributed to the decreasing contribution of the prompt-NO pathway to total emissions, as the peak CH concentration and the CH layer thickness decrease with pressure. In the studied lean condition, the contribution of the pressure-dependent N2O production route increases rapidly up to 10 atm before stabilizing towards engine-relevant pressures. The uncertain prediction ranges provide insight into the accuracy and precision of simulations at high pressures and warrant further research to constrain the uncertainty limits of kinetic rates to capture NO concentrations with confidence in early design phases.

Flow Analysis of High Pressure Catalytic Combustor for Gas Turbine

1995 ◽  
Author(s):  
Y. Tsujikawa ◽  
S. Fujii ◽  
H. Sadamori ◽  
S. Ito ◽  
S. Katsura
Keyword(s):  
High Pressure ◽  
Natural Gas ◽  
Gas Turbine ◽  
Flow Analysis ◽  
Methane Combustion ◽  
Single Step ◽  
Operating Conditions ◽  
Experimental Investigations ◽  
Gas Temperature ◽  
Radial Convection

The objective of this paper is modeling the mechanism of high temperature catalytic oxidation of natural gas, or methane. The model is two-dimensional steady-state, and includes axial and radial convection and diffusion of mass, momentum and energy, as well as homogeneous (gas phase) and heterogeneous (gas-surface) single step irreversible chemical reactions within a catalyst channel. Experimental investigations were also made of natural gas, or methane combustion in the presence of Mn-substituted hexaaluminate catalysts. Axial profiles of catalyst wall temperature, and gas temperature and gas composition for a range of gas turbine combustor operating conditions have been obtained for comparison with and development of a computer model of catalytic combustion. Numerical calculation results for low pressure agree well with experimental data. The calculations have been extended for high pressure (10 atms) operating conditions of gas turbine.

Experimental Characterization of a Hydrogen Fuelled Combustor With Reduced NOx Emissions for a 10 MW Class Gas Turbine

2008 ◽  
Author(s):  
Stefano Cocchi ◽  
Michele Provenzale ◽  
Valerio Cinti ◽  
Luciano Carrai ◽  
Stefano Sigali ◽  
...  
Keyword(s):  
Gas Turbine ◽  
Methane Combustion ◽  
Steam Injection ◽  
Operating Conditions ◽  
Nox Emission ◽  
Pollutant Emissions ◽  
Nox Emissions ◽  
Combustion Mode ◽  
Test Rig ◽  
North East

In the frame of a research project launched in 2006 (partly funded by Regione Veneto, a local institution in the North-East of Italy), ENEL and Nuovo Pignone are developing an innovative “zero emission” gas turbine cycle suitable for power generation. The gas turbine, a GE10-1 model, is manufactured by Nuovo Pignone and will be installed at ENEL’s coal-fired Fusina power plant, near Venice. The turbine, rated for 11 MWe, is equipped with a diffusive flame combustor and is suitable for operation with 100% hydrogen as main fuel over the entire load range. Hydrogen is available at Fusina site as by-product of petrochemical plants. Natural gas will be used as start-up and back-up fuel, and NOx emission abatement will be achieved by means of steam injection. Load operation will be possible with hydrogen only, with methane or hydrogen-methane mixtures (in case of reduced availability of hydrogen) and with or without steam injection. In order to support the combustion system’s design, experimental activities have been carried over a prototypical combustor, installed on a combustion test rig at ENEL’s experimental facility, located in Sesta (Tuscany). The test rig has been upgraded in order to permit full-scale combustor operation. Tests have been planned with the aim of providing a complete screening of combustion system’s sensitivity to minor hardware modification (three different burners and two different liners, designed for diffusive combustion, have been available) and operating conditions (sensitivity to cycle parameters and effect of steam injection). Special instrumentations have been installed for a detailed monitoring of hot parts’ metal temperature, combustion-driven pressure oscillations and pollutant emissions. A water-cooled camera has been installed for direct flame visualization. The experimental campaign is still on-going and only the default combustor configuration has been tested so far. However, collected results indicate safe combustor operation in both hydrogen and methane combustion mode: metal temperatures have never exceeded warning limits and pressure pulsation have been extremely quiet. NOx emission during hydrogen operation in dry combustion mode have been proven to be roughly 3 times higher than in dry methane combustion mode. Steam injection has been proven to be effective in reducing NOx emissions down to contractual values. Additional efforts are in progress to obtain a further reduction of emission level. Finally, experimental results have been processed in order to set up a simple NOx emissions’ model, accounting for NOx production in any possible operating mode.

scholarly journals Quantifying the Effect of Kinetic Uncertainties on NO Predictions at Engine-Relevant Pressures in Premixed Methane–Air Flames

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Antoine Durocher ◽  
Gilles Bourque ◽  
Jeffrey M. Bergthorson
Keyword(s):  
Gas Turbine ◽  
High Pressures ◽  
Reaction Pathway ◽  
Methane Combustion ◽  
Operating Conditions ◽  
Combustion Model ◽  
Atmospheric Conditions ◽  
N2o Production ◽  
Large Variability ◽  
Kinetic Rates

Abstract Accurate and robust thermochemical models are required to identify future low-NOx technologies that can meet the increasingly stringent emissions regulations in the gas turbine industry. These mechanisms are generally optimized and validated for specific ranges of operating conditions, which result in an abundance of models offering accurate nominal solutions over different parameter ranges. Under atmospheric conditions, and for methane combustion, relatively good agreement between models and experiments is currently observed. At engine-relevant pressures, however, a large variability in predictions is obtained as the models are often used outside their validation region. The high levels of uncertainty found in chemical kinetic rates enable such discrepancies between models, even if the reactions are within recommended rate values. This work investigates the effect of such kinetic uncertainties in NO predictions by propagating the uncertainties of 30 reactions that are both uncertain and important to NO formation, through the combustion model at engine-relevant pressures. Understanding the uncertainty sources in model predictions and their effect on emissions at these pressures is key in developing accurate thermochemical models to design future combustion chambers with any confidence. Lean adiabatic, freely propagating, laminar flames are therefore chosen to study the effect of parametric kinetic uncertainties. A nonintrusive, level 2, nested sparse-grid approach is used to obtain accurate surrogate models to quantify NO prediction intervals at various pressures. The forward analysis is carried up to 32 atm to quantify the uncertainty in emissions predictions to pressures relevant to the gas turbine community, which reveals that the NO prediction uncertainty decreases with pressure. After performing a reaction pathway analysis (RPA), this reduction is attributed to the decreasing contribution of the prompt-NO pathway to total emissions, as the peak CH concentration and the CH layer thickness decrease with pressure. In the studied lean condition, the contribution of the pressure-dependent N2O production route increases rapidly up to 10 atm before stabilizing toward engine-relevant pressures. The uncertain prediction ranges provide insight into the accuracy and precision of simulations at high pressures and warrant further research to constrain the uncertainty limits of kinetic rates to capture NO concentrations with confidence in early design phases.

scholarly journals A Comparative Study on Fault Detection Methods for Gas Turbine Combustion Systems

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 389
Author(s):  
Jinfu Liu ◽  
Zhenhua Long ◽  
Mingliang Bai ◽  
Linhai Zhu ◽  
Daren Yu
Keyword(s):  
Fault Detection ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Operating Conditions ◽  
Detection Methods ◽  
Distribution Model ◽  
Outlet Temperature ◽  
Combustion System ◽  
Comparison Results ◽  
Gas Turbine Combustion

As one of the core components of gas turbines, the combustion system operates in a high-temperature and high-pressure adverse environment, which makes it extremely prone to faults and catastrophic accidents. Therefore, it is necessary to monitor the combustion system to detect in a timely way whether its performance has deteriorated, to improve the safety and economy of gas turbine operation. However, the combustor outlet temperature is so high that conventional sensors cannot work in such a harsh environment for a long time. In practical application, temperature thermocouples distributed at the turbine outlet are used to monitor the exhaust gas temperature (EGT) to indirectly monitor the performance of the combustion system, but, the EGT is not only affected by faults but also influenced by many interference factors, such as ambient conditions, operating conditions, rotation and mixing of uneven hot gas, performance degradation of compressor, etc., which will reduce the sensitivity and reliability of fault detection. For this reason, many scholars have devoted themselves to the research of combustion system fault detection and proposed many excellent methods. However, few studies have compared these methods. This paper will introduce the main methods of combustion system fault detection and select current mainstream methods for analysis. And a circumferential temperature distribution model of gas turbine is established to simulate the EGT profile when a fault is coupled with interference factors, then use the simulation data to compare the detection results of selected methods. Besides, the comparison results are verified by the actual operation data of a gas turbine. Finally, through comparative research and mechanism analysis, the study points out a more suitable method for gas turbine combustion system fault detection and proposes possible development directions.

Chemical Reactor Network Application to Emissions Prediction for Industial DLE Gas Turbine

2006 ◽  
Author(s):  
I. V. Novosselov ◽  
P. C. Malte ◽  
S. Yuan ◽  
R. Srinivasan ◽  
J. C. Y. Lee
Keyword(s):  
Gas Turbine ◽  
Chemical Reactor ◽  
Kinetic Mechanism ◽  
Chemical Kinetic ◽  
Operating Conditions ◽  
Reacting Flow ◽  
Ongoing Research ◽  
Chemical Reactor Network ◽  
Reaction Zones ◽  
Reactor Network

A chemical reactor network (CRN) is developed and applied to a dry low emissions (DLE) industrial gas turbine combustor with the purpose of predicting exhaust emissions. The development of the CRN model is guided by reacting flow computational fluid dynamics (CFD) using the University of Washington (UW) eight-step global mechanism. The network consists of 31 chemical reactor elements representing the different flow and reaction zones of the combustor. The CRN is exercised for full load operating conditions with variable pilot flows ranging from 35% to 200% of the neutral pilot. The NOpilot. The NOx and the CO emissions are predicted using the full GRI 3.0 chemical kinetic mechanism in the CRN. The CRN results closely match the actual engine test rig emissions output. Additional work is ongoing and the results from this ongoing research will be presented in future publications.

Numerical Simulation of Gas Flow and Heat Transfer in Cross-Wavy Primary Surface Channel for Microtubine Recuperators

2005 ◽  
Author(s):  
H. X. Liang ◽  
Q. W. Wang ◽  
L. Q. Luo ◽  
Z. P. Feng
Keyword(s):  
Heat Transfer ◽  
Numerical Simulation ◽  
Gas Turbine ◽  
Numerical Study ◽  
High Reliability ◽  
Three Dimensional ◽  
Operating Conditions ◽  
Flow And Heat Transfer ◽  
High Heat Transfer ◽  
The Cross

Three-dimensional numerical simulation was conducted to investigate the flow field and heat transfer performance of the Cross-Wavy Primary Surface (CWPS) recuperators for microturbines. Using high-effective compact recuperators to achieve high thermal efficiency is one of the key techniques in the development of microturbine in recent years. Recuperators need to have minimum volume and weight, high reliability and durability. Most important of all, they need to have high thermal-effectiveness and low pressure-losses so that the gas turbine system can achieve high thermal performances. These requirements have attracted some research efforts in designing and implementing low-cost and compact recuperators for gas turbine engines recently. One of the promising techniques to achieve this goal is the so-called primary surface channels with small hydraulic dimensions. In this paper, we conducted a three-dimensional numerical study of flow and heat transfer for the Cross-Wavy Primary Surface (CWPS) channels with two different geometries. In the CWPS configurations the secondary flow is created by means of curved and interrupted surfaces, which may disturb the thermal boundary layers and thus improve the thermal performances of the channels. To facilitate comparison, we chose the identical hydraulic diameters for the above four CWPS channels. Since our experiments on real recuperators showed that the Reynolds number ranges from 150 to 500 under the operating conditions, we implemented all the simulations under laminar flow situations. By analyzing the correlations of Nusselt numbers and friction factors vs. Reynolds numbers of the four CWPS channels, we found that the CWPS channels have superior and comprehensive thermal performance with high compactness, i.e., high heat transfer area to volume ratio, indicating excellent commercialized application in the compact recuperators.

A Self-Correcting and Self-Checking Gas Turbine Meter

1982 ◽  
Vol 104 (2) ◽  
pp. 143-149 ◽  
Author(s):  
W. F. Z. Lee ◽  
D. C. Blakeslee ◽  
R. V. White
Keyword(s):  
Gas Turbine ◽  
Operating Conditions ◽  
Exit Angle ◽  
Test Results ◽  
Main Rotor ◽  
Calibration Accuracy

A new metering concept of a self-correcting and self-checking turbine meter is described in which a sensor rotor downstream from the main rotor senses and responds to changes in the exit angle of the fluid leaving the main rotor. The output from the sensor rotor is then electronically combined with the output from the main rotor to produce an adjusted output which automatically and continuously corrects to original meter calibration accuracy. This takes place despite changes in retarding torques, bearing wear and/or upstream conditions occurring in field operations over those which were experienced during calibration. The ratio of the sensor rotor output to the main rotor output at operating conditions is also automatically and continuously compared with that at calibration conditions. This provides an indication of the amount of accuracy deviation from initial calibration that is being corrected by the sensor rotor. This concept is studied theoretically and experimentally. Both the theory and test results (laboratory and field) confirm the concept’s validity and practicability.

Combustion Tuning for a Gas Turbine Power Plant Using Data-Driven and Machine Learning Approach

2021 ◽  
Vol 143 (3) ◽  
Author(s):  
Suhui Li ◽  
Huaxin Zhu ◽  
Min Zhu ◽  
Gang Zhao ◽  
Xiaofeng Wei
Keyword(s):  
Machine Learning ◽  
Power Plant ◽  
Gas Turbine ◽  
Operating Conditions ◽  
Data Driven ◽  
Ann Model ◽  
Promising Alternative ◽  
Combustion Performance ◽  
Wide Range ◽  
Gas Turbine Power Plant

Abstract Conventional physics-based or experimental-based approaches for gas turbine combustion tuning are time consuming and cost intensive. Recent advances in data analytics provide an alternative method. In this paper, we present a cross-disciplinary study on the combustion tuning of an F-class gas turbine that combines machine learning with physics understanding. An artificial-neural-network-based (ANN) model is developed to predict the combustion performance (outputs), including NOx emissions, combustion dynamics, combustor vibrational acceleration, and turbine exhaust temperature. The inputs of the ANN model are identified by analyzing the key operating variables that impact the combustion performance, such as the pilot and the premixed fuel flow, and the inlet guide vane angle. The ANN model is trained by field data from an F-class gas turbine power plant. The trained model is able to describe the combustion performance at an acceptable accuracy in a wide range of operating conditions. In combination with the genetic algorithm, the model is applied to optimize the combustion performance of the gas turbine. Results demonstrate that the data-driven method offers a promising alternative for combustion tuning at a low cost and fast turn-around.

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