Investigation of Oxy-Fuel Combustion through Reactor Network and Residence Time Data

Oxy-fuel combustion is a promising strategy to minimize the environmental impact of combustion-based energy conversion. Simple and flexible tools are required to facilitate the successful integration of such strategies at the industrial level. This study couples measured residence time distribution with chemical reactor network analysis in a close-to-reality combustor. This provides detailed knowledge about the various mixing and reactive characteristics arising from the use of the two different oxidizing streams.

Optimisation of CO Turndown for an Axially Staged Gas Turbine Combustor

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.

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

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.

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

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.

A review on the applications of the chemical reactor network approach on the prediction of pollutant emissions

Purpose The purpose of this paper is to review the applications of the chemical reactor network (CRN) approach for modeling the combustion in gas turbine combustors and classify the CRN construction methods that have been frequently used by researchers. Design/methodology/approach This paper initiates with introducing the CRN approach as a practical tool for precisely predicting the species concentrations in the combustion process with lower computational costs. The structure of the CRN and its elements as the ideal reactors are reviewed in recent studies. Flow field modeling has been identified as the most important input for constructing the CRNs; thus, the flow field modeling methods have been extensively reviewed in previous studies. Network approach, component modeling approach and computational fluid dynamics (CFD), as the main flow field modeling methods, are investigated with a focus on the CRN applications. Then, the CRN construction approaches are reviewed and categorized based on extracting the flow field required data. Finally, the most used kinetics and CRN solvers are reviewed and reported in this paper. Findings It is concluded that the CRN approach can be a useful tool in the entire process of combustion chamber design. One-dimensional and quasi-dimensional methods of flow field modeling are used in the construction of the simple CRNs without detailed geometry data. This approach requires fewer requirements and is used in the initial combustor designing process. In recent years, using the CFD approach in the construction of CRNs has been increased. The flow field results of the CFD codes processed to create the homogeneous regions based on construction criteria. Over the past years, several practical algorithms have been proposed to automatically extract reactor networks from CFD results. These algorithms have been developed to identify homogeneous regions with a high resolution based on the splitting criteria. Originality/value This paper reviews the various flow modeling methods used in the construction of the CRNs, along with an overview of the studies carried out in this field. Also, the usual approaches for creating a CRN and the most significant achievements in this field are addressed in detail.

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

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.

Predictions of NOx and CO emissions from a low-emission concentric staged combustor for civil aeroengines

This study is aimed to establish a detailed chemical reactor network model based on the analysis of complex reaction flowfield structures in aeroengine combustors, so that the emissions of nitrogen oxides and carbon monoxide from advanced civil aeroengines can be predicted quickly and accurately. In this study, a low-emission concentric staged combustor with three axial swirlers is designed for civil aeroengines, and numerical simulations of the three-dimensional reaction flowfields of the combustor during four load phases of takeoff, climb, approach, and idle, are conducted. Based on the numerical results, a simple chemical reactor network model with seven perfectly stirred reactors and a detailed chemical reactor network model using up to 15 perfectly stirred reactors are established. Using the developed chemical reactor network models and the detailed JP10 chemical reaction mechanism—composed of 374 step elementary reactions and 82 species, the emission variations of nitrogen oxides and carbon monoxide are predicted and compared with those estimated using an empirical formula and with the numerical results as a function of the combustion load. Using a combined chemical reactor network–computational fluid dynamics analysis method, the variations of the formation path, the mechanism, and the amounts of nitrogen oxides in the combustor and in the perfectly stirred reactors, are analyzed as a function of the combustion load. In addition, the effects of fuel and air pilot-to-total ratio on nitrogen oxides emissions for the 100% load condition are also analyzed. It is found that at high loads, the production rate of the thermal NO is the highest, while at low loads, the production rate of the prompt NO is the highest. The nitrogen oxide is mainly produced in the pilot zone and the recirculation zone, while its production in the outer main stage zone is low. The results show that the NOx emissions predicted by the complex chemical reactor network model are most consistent with those elicited using the empirical formula.