Optimisation of CO Turndown for an Axially Staged Gas Turbine Combustor

2021 ◽  
Author(s):  
Jacob Rivera ◽  
Robert Gordon ◽  
Mohsen Talei ◽  
Gilles Bourque
Keyword(s):  
Gas Turbines ◽  
Chemical Reactor ◽  
Operating Conditions ◽  
Operating Characteristics ◽  
Gas Turbine Combustor ◽  
Network Modelling ◽  
Chemical Reactor Network ◽  
Industrial Gas Turbines ◽  
Reactor Network ◽  
The Impact

Abstract This paper reports on an optimisation study of the CO turndown behaviour of an axially staged combustor, in the context of industrial gas turbines (GT). The aim of this work is to assess the optimally achievable CO turndown behaviour limit given system and operating characteristics, without considering flow-induced behaviours such as mixing quality and flame spatial characteristics. To that end, chemical reactor network modelling is used to investigate the impact of various system and operating conditions on the exhaust CO emissions of each combustion stage, as well as at the combustor exit. Different combustor residence time combinations are explored to determine their contribution to the exhaust CO emissions.

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.

Optimisation of CO Turndown for an Axially Staged Gas Turbine Combustor

2020 ◽  
Author(s):  
Jacob E. Rivera ◽  
Robert L. Gordon ◽  
Mohsen Talei ◽  
Gilles Bourque
Keyword(s):  
Residence Time ◽  
Parametric Study ◽  
Gas Turbines ◽  
Flow Reactor ◽  
Operating Conditions ◽  
Independent Effect ◽  
Inlet Temperature ◽  
Operating Characteristics ◽  
Two Stage ◽  
The Impact

Abstract This paper reports on an optimisation study of the CO turndown behaviour of an axially staged combustor, in the context of industrial gas turbines (GT). The aim of this work is to assess the optimally achievable CO turndown behaviour limit given system and operating characteristics, without considering flow-induced behaviours such as mixing quality and flame spatial characteristics. To that end, chemical reactor network modelling is used to investigate the impact of various system and operating conditions on the exhaust CO emissions of each combustion stage, as well as at the combustor exit. Different combustor residence time combinations are explored to determine their contribution to the exhaust CO emissions. The two-stage combustor modelled in this study consists of a primary (Py) and a secondary (Sy) combustion stage, followed by a discharge nozzle (DN), which distributes the exhaust to the turbines. The Py is modelled using a freely propagating flame (FPF), with the exhaust gas extracted downstream of the flame front at a specific location corresponding to a specified residence time (tr). These exhaust gases are then mixed and combusted with fresh gases in the Sy, modelled by a perfectly stirred reactor (PSR) operating within a set tr. These combined gases then flow into the DN, which is modelled by a plug flow reactor (PFR) that cools the gas to varying combustor exit temperatures within a constrained tr. Together, these form a simplified CRN model of a two-stage, dry-low emissions (DLE) combustion system. Using this CRN model, the impact of the tr distribution between the Py, Sy and DN is explored. A parametric study is conducted to determine how inlet pressure (Pin), inlet temperature (Tin), equivalence ratio (ϕ) and Py-Sy fuel split (FS), individually impact indicative CO turndown behaviour. Their coupling throughout engine load is then investigated using a model combustor, and its effect on CO turndown is explored. Thus, this aims to deduce the fundamental, chemically-driven parameters considered to be most important for identifying the optimal CO turndown of GT combustors. In this work, a parametric study and a model combustor study are presented. The parametric study consists of changing a single parameter at a time, to observe the independent effect of this change and determine its contribution to CO turndown behaviour. The model combustor study uses the same CRN, and varies the parameters simultaneously to mimic their change as an engine moves through its steady-state power curve. The latter study thus elucidates the difference in CO turndown behaviour when all operating conditions are coupled, as they are in practical engines. The results of this study aim to demonstrate the parameters that are key for optimising and improving CO turndown.

scholarly journals Industrial Gas Turbine Performance: Compressor Fouling and On-Line Washing

2014 ◽  
Vol 136 (10) ◽  
Author(s):  
Uyioghosa Igie ◽  
Pericles Pilidis ◽  
Dimitrios Fouflias ◽  
Kenneth Ramsden ◽  
Panagiotis Laskaridis
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Engine Performance ◽  
Operating Conditions ◽  
Compressor Cascade ◽  
Compressor Blades ◽  
Turbine Performance ◽  
Industrial Gas Turbines ◽  
On Line ◽  
The Impact

Industrial gas turbines are susceptible to compressor fouling, which is the deposition and accretion of airborne particles or contaminants on the compressor blades. This paper demonstrates the blade aerodynamic effects of fouling through experimental compressor cascade tests and the accompanied engine performance degradation using turbomatch, an in-house gas turbine performance software. Similarly, on-line compressor washing is implemented taking into account typical operating conditions comparable with industry high pressure washing. The fouling study shows the changes in the individual stage maps of the compressor in this condition, the impact of degradation during part-load, influence of control variables, and the identification of key parameters to ascertain fouling levels. Applying demineralized water for 10 min, with a liquid-to-air ratio of 0.2%, the aerodynamic performance of the blade is shown to improve, however most of the cleaning effect occurred in the first 5 min. The most effectively washed part of the blade was the pressure side, in which most of the particles deposited during the accelerated fouling. The simulation of fouled and washed engine conditions indicates 30% recovery of the lost power due to washing.

Prediction of NOx and CO Emissions from an Industrial Lean-Premixed Gas Turbine Combustor Using a Chemical Reactor Network Model

2013 ◽  
Vol 27 (3) ◽  
pp. 1643-1651 ◽  
Author(s):  
Jungkyu Park ◽  
Truc Huu Nguyen ◽  
Daero Joung ◽  
Kang Yul Huh ◽  
Min Chul Lee
Keyword(s):  
Gas Turbine ◽  
Network Model ◽  
Chemical Reactor ◽  
Gas Turbine Combustor ◽  
Chemical Reactor Network ◽  
Lean Premixed ◽  
Reactor Network

scholarly journals A coupled flow and chemical reactor network model for predicting gas turbine combustor performance

2020 ◽  
Vol 24 (3 Part B) ◽  
pp. 1977-1989
Author(s):  
Seyfettin Hataysal ◽  
Ahmet Yozgatligil
Keyword(s):  
Gas Turbine ◽  
Network Model ◽  
Chemical Reactor ◽  
Gas Turbine Combustor ◽  
Actual Performance ◽  
Flow Network ◽  
Average Temperature ◽  
Chemical Reactor Network ◽  
Segregated Flow ◽  
Reactor Network

Gas turbine combustor performance was explored by utilizing a 1-D flow network model. To obtain the preliminary performance of combustion chamber, three different flow network solvers were coupled with a chemical reactor network scheme. These flow solvers were developed via simplified, segregated and direct solutions of the nodal equations. Flow models were utilized to predict the flow field, pressure, density and temperature distribution inside the chamber network. The network model followed a segregated flow and chemical network scheme, and could supply information about the pressure drop, nodal pressure, average temperature, species distribution, and flow split. For the verification of the model?s results, analyses were performed using CFD on a seven-stage annular test combustor from TUSAS Engine Industries, and the results were then compared with actual performance tests of the combustor. The results showed that the preliminary performance predictor code accurately estimated the flow distribution. Pressure distribution was also consistent with the CFD results, but with varying levels of conformity. The same was true for the average temperature predictions of the inner combustor at the dilution and exit zones. However, the reactor network predicted higher elemental temperatures at the entry zones.

Uncertainty Analysis of the Chemical Reactor Network Approach for Predicting the Pollutant Emissions in a Double-Swirl Combustor

2020 ◽  
Vol 142 (9) ◽  
Author(s):  
Hamidreza Khodayari ◽  
Fathollah Ommi ◽  
Zoheir Saboohi
Keyword(s):  
Uncertainty Analysis ◽  
Thermal Power ◽  
Chemical Reactor ◽  
Operating Conditions ◽  
Pollutant Emissions ◽  
Inlet Temperature ◽  
Computational Domain ◽  
Experimental Database ◽  
Chemical Reactor Network ◽  
Reactor Network

Abstract The purpose of this study is to predict the pollutant emissions generated within an aero-engine combustor model using the computational fluid dynamics-chemical reactor network (CFD-CRN) approach by modeling combustion in highly swirled flows. The selected test case is a laboratory double swirled combustor that came with an extensive experimental database from previous works for CH4/air diffusion flames at atmospheric pressure. The CFD-CRN modeling approach is initiated by solving Reynolds-averaged Navier–Stokes (RANS) equations for a 3D computational domain. The numerically achieved time-averaged values of the velocity components are in good agreement with the experimental data for two different thermal power. The CRN is obtained by dividing the flow field into ideal chemical reactors using various filters on the CFD results. The temperature, axial velocity, CH4, and O2 mass fractions distributions are selected as the splitting criteria for constructing the CRN. An uncertainty analysis is carried out to investigate the effects of different splitting approaches for the temperature criteria since it significantly affected the pollutant emissions in the gas turbine combustor. The simulations of the pollutant emissions are performed via the detailed gas-phase chemical kinetic mechanism of GRI-Mech 3.0. The nonlinear distribution of the temperature intervals result in lower uncertainty and provide reliable results even with a small number of ideal reactors. Also, it is observed that the CRN can be used in different operating conditions and provide suitable results if it is constructed with exceptional consideration. Moreover, a parametric study is performed by varying the equivalence ratio and air inlet temperature to investigate the trends of the NO and CO emissions.

Emission prediction in conceptual design of the aircraft engines using augmented CRN

2017 ◽  
Vol 121 (1241) ◽  
pp. 1005-1028 ◽  
Author(s):  
Z. Saboohi ◽  
F. Ommi
Keyword(s):  
Conceptual Design ◽  
Gas Turbines ◽  
Chemical Reactor ◽  
Aviation Fuel ◽  
Analytical Prediction ◽  
Design Phase ◽  
Detailed Chemistry ◽  
Chemical Reactor Network ◽  
Conceptual Design Phase ◽  
Reactor Network

ABSTRACTThe semi-analytical prediction of pollutants emissions from gas turbines in the conceptual design phase is addressed in this paper. The necessity of this work arose from an urgent need for a comprehensive model that can quickly provide data in the conceptual design phase. Based on the available inputs data in the initial phases of the design process, a chemical reactor network (CRN) is defined to model the combustion with a detailed chemistry. In this way, three different chemical mechanisms are studied for Jet-A aviation fuel. Furthermore, the droplet evaporation for liquid fuel and the non-uniformity in fuel-air mixture are modelled. The results of a developed augmented modelling tool are compared with the pollutants data of two annular engine's combustors. The CRN results have good agreement with the actual engine test rig emissions output. In conclusion, the augmented CRN has shown to be efficient in predicting engine emissions with a very short executing time (few seconds) using a small CPU requirement such as a personal computer.

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