Research on Prediction of NOx Emission Performance of Marine Gas Turbine Under Variable Operating Conditions

2020 ◽  
Author(s):  
Jian Li ◽  
Zhitao Wang ◽  
Tielei Li ◽  
Shuying Li
Keyword(s):  
Gas Turbine ◽  
Chemical Reactor ◽  
Operating Conditions ◽  
Nox Emissions ◽  
Chemical Reactor Network ◽  
Computational Fluid Dynamics Cfd ◽  
Reactor Network ◽  
D Model ◽  
Operating Points ◽  
Variable Operating Conditions

Abstract With the global warming, many countries pay more attention to environmental pollution. The NOx emissions has become an important index when gas turbine designed. This paper provides a method for predicting NOx emissions of marine gas turbine under variable operating conditions. Firstly build the 3-D model of combustor. The characteristic regions of combustor were divided according to the reaction principle. Then build the chemical reactor network (CRN) models of different characteristic regions. According to the NOx emissions of several specific operating points simulated by computational fluid dynamics (CFD), fit the relation between residence time and operating conditions by Newton interpolation in the CRN models. Then the prediction model of NOx emissions of gas turbine was established by using neural network. The NOx emissions under 0.7∼1.0 working conditions and 0.019∼0.023 fuel-air ratios can be predicted efficiently.

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.

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.

Numerical Investigation of NOx Emissions Characteristics of a Natural Gas Premixed Burner Based on Chemical Reactor Network Model

2019 ◽  
Author(s):  
Bin Mu ◽  
Fulin Lei ◽  
Weiwei Shao ◽  
Xunwei Liu ◽  
Zhedian Zhang ◽  
...  
Keyword(s):  
Experimental Data ◽  
High Pressure ◽  
Chemical Reactor ◽  
Nox Emission ◽  
Recirculation Region ◽  
Nox Emissions ◽  
Nox Formation ◽  
Chemical Reactor Network ◽  
Thermal Nox ◽  
Reactor Network

Abstract Numerical optimization of nitrogen oxides (NOx) formation is an essential factor during developing low pollution combustor of gas turbine. The Computational Fluid Dynamics-Chemical Reactor Network (CFD-CRN) hybrid method has a great advantage in fast and accurate prediction of combustor NOx emissions. In this work, a hybrid CFD-CRN approach is established to predict pollutant emissions of a lean premixed model burner for gas turbine applications. Several criteria are compared for separating the combustor into chemically and physically homogeneous zones, and the crucial parameters such as residence time and flue gas recirculation ratio are calculated. The CRN model is preliminarily verified with experimental data. The effects of pressure and fuel-air unmixedness on NOx formation are subsequently investigated. In addition, the effects of changes in fuel/air flow distribution and crucial parameters of CRN model on NOx emissions are also estimated under different pressures and fuel-air unmixedness. The combustor is divided into several zones including reaction preheating region, flame front region, flame transition region, post flame region, main recirculation region and corner recirculation region based on CFD results of fuel-air mixing characteristics, velocity field, temperature field, distribution of OH mass fraction and Damkohler number. The complex CRN model has the advantage of predicting NOx emission characteristics under higher Tad conditions compared with the simple model, and its prediction of NOx emission shows good agreement with experimental data under various equivalence ratio conditions. The structure and distribution of several regions of CRN model are analogous but not significant when Reynolds number exceeds 105 under high pressure. The pathway analysis shows that the NOx emission gradually decreases through N2O and NNH mechanisms, resulted from the decreasing concentration of O radical under low Tad and high pressure. However, the pressure could significantly promote thermal NOx formation resulting form increase of temperature. The fuel-air unmixedness results in the increase of maximum flame temperature, which has significant effect on change of the CRN regions-separating. The fuel-air unmixedness causes the significant increasing of thermal NOx formation.

Gas Turbine Diagnostics Under Variable Operating Conditions

2007 ◽  
Author(s):  
Igor Loboda ◽  
Yakov Feldshteyn ◽  
Sergiy Yepifanov
Keyword(s):  
Gas Turbine ◽  
Health Monitoring ◽  
Correct Diagnosis ◽  
Diagnostic System ◽  
Diagnostic Technique ◽  
Operating Conditions ◽  
Diagnostic Process ◽  
Ambient Conditions ◽  
Operating Points ◽  
Variable Operating Conditions

Operating conditions (control variables and ambient conditions) of gas turbine plants and engines vary considerably. The fact that health monitoring has to be uninterrupted creates the need for a run time diagnostic system to operate under any conditions. The diagnostic technique described in this paper utilizes the thermodynamic models in order to simulate gaspath faults and uses neural networks for the faults localization. This technique is repeatedly executed and the diagnoses are registered. On the basis of these diagnoses and beforehand known faults, the correct diagnosis probabilities are then calculated. The present paper analyses the influence of the operating conditions on a diagnostic process. In the technique, different options are simulated of a diagnostic treatment of the measured values obtained under variable operating conditions. The mentioned above probabilities help to compare these options. The main focus of the paper is on the so called multipoint (multimode) diagnosis that groups the data from different operating points (modes) to set only a single diagnosis.

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