Equivalent Reactor Network Model for Simulating the Air Gasification of Polyethylene in a Conical Spouted Bed Gasifier

2014 ◽  
Vol 28 (11) ◽  
pp. 6830-6840 ◽  
Author(s):  
Yupeng Du ◽  
Qi Yang ◽  
Abdallah S. Berrouk ◽  
Chaohe Yang ◽  
Ahmed S. Al Shoaibi
Keyword(s):  
Network Model ◽  
Spouted Bed ◽  
Reactor Network

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

Use of a Reactor Network Model in the Design and Operation of a New Type of Membrane Wall Entrained Flow Gasifier

2013 ◽  
Vol 27 (10) ◽  
pp. 6322-6332 ◽  
Author(s):  
Zhiwei Yang ◽  
Zhe Wang ◽  
Yuxin Wu ◽  
Zheng Li ◽  
Weidou Ni
Keyword(s):  
Network Model ◽  
Entrained Flow ◽  
Entrained Flow Gasifier ◽  
New Type ◽  
Reactor Network

Prediction and Validation of Major Gas and Tar Species from a Reactor Network Model of Air-Blown Fluidized Bed Biomass Gasification

2015 ◽  
Vol 29 (4) ◽  
pp. 2437-2452 ◽  
Author(s):  
Addison K. Stark ◽  
Richard B. Bates ◽  
Zhenlong Zhao ◽  
Ahmed F. Ghoniem
Keyword(s):  
Fluidized Bed ◽  
Network Model ◽  
Biomass Gasification ◽  
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.

A reactor network model for predicting NOx emissions in gas turbines

Fuel ◽  
2010 ◽  
Vol 89 (9) ◽  
pp. 2202-2210 ◽  
Author(s):  
Vincent Fichet ◽  
Mohamed Kanniche ◽  
Pierre Plion ◽  
Olivier Gicquel
Keyword(s):  
Network Model ◽  
Gas Turbines ◽  
Nox Emissions ◽  
Reactor Network

Formation and Control of Sulfur Oxides in Sour Gas Oxy-Combustion: Prediction Using a Reactor Network Model

2015 ◽  
Vol 29 (11) ◽  
pp. 7670-7680 ◽  
Author(s):  
Dominik Bongartz ◽  
Santosh J. Shanbhogue ◽  
Ahmed F. Ghoniem
Keyword(s):  
Network Model ◽  
Sulfur Oxides ◽  
Reactor Network ◽  
And Control ◽  
Sour Gas

A Hybrid Lumped Parameter/Neural Network Model for Spouted Bed Drying of Pastes with Inert Particles

2012 ◽  
Vol 30 (11-12) ◽  
pp. 1342-1353 ◽  
Author(s):  
J. T. Freire ◽  
F. B. Freire ◽  
M. C. Ferreira ◽  
B. S. Nascimento
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Spouted Bed ◽  
Lumped Parameter ◽  
Inert Particles

Modeling of Pollutant Formation in Gas Turbine Combustors Using Fast Reactor Network Model

2020 ◽  
Author(s):  
Piyush Thakre ◽  
Ivana Veljkovic ◽  
Vincent Lister ◽  
Graham Goldin
Keyword(s):  
Gas Turbine ◽  
Network Model ◽  
Chemical Mechanism ◽  
Combustion Model ◽  
Detailed Chemistry ◽  
Pollutant Formation ◽  
Flamelet Generated Manifold ◽  
Temperature Solution ◽  
Reactor Network ◽  
Industrial Gas Turbine

Abstract We present a robust, fast, and highly-automated Reactor Network model within a single simulation framework in Simcenter STAR-CCM+. An industrial gas turbine combustor operating at 3 bar is numerically investigated using the GRI 3.0 chemical mechanism. A baseline CFD solution with RANS and Flamelet Generated Manifold combustion model was used to create the network of reactors. A number of model variations have been investigated, such as the use of constant pressure vs. perfectly stirred reactors. Two options for the temperature solution are considered, namely temperature mapped from the CFD solution and temperature computed from an equation of state. Different numbers of reactors are investigated to understand the overall sensitivity on the key combustion results. It was found that with appropriate clustering variables, using a few thousand reactors provide a reasonable representation of the species fields. The simulation results are compared with the available experimental data for the combustor. The NOx and CO emissions predictions with the Reactor Network model perform better than the baseline CFD model. The Reactor Network model was about ∼3 orders of magnitude faster than a detailed chemistry CFD of the same combustor.

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