scholarly journals CFD modeling of unsteady Counterflow flame into Rhodium catalytic chamber

Author(s):  
Ali Edalati-Nejad ◽  
Sayyed Aboozar Fanaee ◽  
Maryam Ghodrat
TAPPI Journal ◽  
2015 ◽  
Vol 14 (1) ◽  
pp. 51-60
Author(s):  
HONGHI TRAN ◽  
DANNY TANDRA

Sootblowing technology used in recovery boilers originated from that used in coal-fired boilers. It started with manual cleaning with hand lancing and hand blowing, and evolved slowly into online sootblowing using retractable sootblowers. Since 1991, intensive research and development has focused on sootblowing jet fundamentals and deposit removal in recovery boilers. The results have provided much insight into sootblower jet hydrodynamics, how a sootblower jet interacts with tubes and deposits, and factors influencing its deposit removal efficiency, and have led to two important innovations: fully-expanded sootblower nozzles that are used in virtually all recovery boilers today, and the low pressure sootblowing technology that has been implemented in several new recovery boilers. The availability of powerful computing systems, superfast microprocessors and data acquisition systems, and versatile computational fluid dynamics (CFD) modeling capability in the past two decades has also contributed greatly to the advancement of sootblowing technology. High quality infrared inspection cameras have enabled mills to inspect the deposit buildup conditions in the boiler during operation, and helped identify problems with sootblower lance swinging and superheater platens and boiler bank tube vibrations. As the recovery boiler firing capacity and steam parameters have increased markedly in recent years, sootblowers have become larger and longer, and this can present a challenge in terms of both sootblower design and operation.


Author(s):  
B. S. Soroka

The article considers the role and place of water and water vapor in combustion processes with the purpose of reduction the effluents of nitrogen oxides and carbon oxide. We have carried out the complex of theoretical and computational researches on reduction of harmful nitrogen and carbon oxides by gas fuel combustion in dependence on humidity of atmospheric air by two approaches: CFD modeling with attraction of DRM 19 chemical kinetics mechanism of combustion for 19 components along with Bowman’s mechanism used as “postprocessor” to determine the [NO] concentration; different thermodynamic models of predicting the nitrogen oxides NO formation. The numerical simulation of the transport processes for momentum, mass and heat being solved simultaneously in the united equations’ system with the chemical kinetics equations in frame of GRI methane combustion mechanism and NO formation calculated afterwards as “postprocessor” allow calculating the absolute actual [CO] and [NO] concentrations in dependence on combustion operative conditions and on design of furnace facilities. Prediction in frame of thermodynamic equilibrium state for combustion products ensures only evaluation of the relative value of [NO] concentration by wet combustion the gas with humid air regarding that in case of dry air – oxidant. We have developed the methodology and have revealed the results of numerical simulation of impact of the relative humidity of atmospheric air on harmful gases formation. Range of relative air humidity under calculations of atmospheric air under impact on [NO] and [CO] concentrations at the furnace chamber exit makes φ = 0 – 100%. The results of CFD modeling have been verified both by author’s experimental data and due comparing with the trends stated in world literature. We have carried out the complex of the experimental investigations regarding atmospheric air humidification impact on flame structure and environmental characteristics at natural gas combustion with premixed flame formation in open air. The article also proposes the methodology for evaluation of the nitrogen oxides formation in dependence on moisture content of burning mixture. The results of measurements have been used for verification the calculation data. Coincidence of relative change the NO (NOx) yield due humidification the combustion air revealed by means of CFD prediction has confirmed the qualitative and the quantitative correspondence of physical and chemical kinetics mechanisms and the CFD modeling procedures with the processes to be studied. A sharp, more than an order of reduction in NO emissions and simultaneously approximately a two-fold decrease in the CO concentration during combustion of the methane-air mixture under conditions of humidification of the combustion air to a saturation state at a temperature of 325 K.


2019 ◽  
Vol 46 (2) ◽  
pp. 101-112
Author(s):  
Nidhal Hnaien ◽  
Saloua Marzouk ◽  
Lioua Kolsi ◽  
Hatem Gasmi ◽  
Habib Ben Aissia ◽  
...  
Keyword(s):  
Wall Jet ◽  

2015 ◽  
Vol 2015 (19) ◽  
pp. 991-1025
Author(s):  
Irene Chu ◽  
Alonso Griborio ◽  
Paul Pitt ◽  
Meei-Lih Ahmad ◽  
Guoji Chiu ◽  
...  
Keyword(s):  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Meisam Babanezhad ◽  
Iman Behroyan ◽  
Ali Taghvaie Nakhjiri ◽  
Azam Marjani ◽  
Mashallah Rezakazemi ◽  
...  

AbstractHerein, a reactor of bubble column type with non-equilibrium thermal condition between air and water is mechanistically modeled and simulated by the CFD technique. Moreover, the combination of the adaptive network (AN) trainer with the fuzzy inference system (FIS) as the artificial intelligence method calling ANFIS has already shown potential in the optimization of CFD approach. Although the artificial intelligence method of particle swarm optimization (PSO) algorithm based fuzzy inference system (PSOFIS) has a good background for optimizing the other fields of research, there are not any investigations on the cooperation of this method with the CFD. The PSOFIS can reduce all the difficulties and simplify the investigation by elimination of the additional CFD simulations. In fact, after achieving the best intelligence, all the predictions can be done by the PSOFIS instead of the massive computational efforts needed for CFD modeling. The first aim of this study is to develop the PSOFIS for use in the CFD approach application. The second one is to make a comparison between the PSOFIS and ANFIS for the accurate prediction of the CFD results. In the present study, the CFD data are learned by the PSOFIS for prediction of the water velocity inside the bubble column. The values of input numbers, swarm sizes, and inertia weights are investigated for the best intelligence. Once the best intelligence is achieved, there is no need to mesh refinement in the CFD domain. The mesh density can be increased, and the newer predictions can be done in an easier way by the PSOFIS with much less computational efforts. For a strong verification, the results of the PSOFIS in the prediction of the liquid velocity are compared with those of the ANFIS. It was shown that for the same fuzzy set parameters, the PSOFIS predictions are closer to the CFD in comparison with the ANFIS. The regression number (R) of the PSOFIS (0.98) was a little more than that of the ANFIS (0.97). The PSOFIS showed a powerful potential in mesh density increment from 9477 to 774,468 and accurate predictions for the new nodes independent of the CFD modeling.


Processes ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 1048
Author(s):  
Xipeng Guo ◽  
Joel Godinez ◽  
Nicholas J. Walla ◽  
Armin K. Silaen ◽  
Helmut Oltmann ◽  
...  

In a steel-refining ladle, the properties of manufactured steel can be notably degraded due to the presence of excessive inclusions. Stirring via gas injection through a porous plug is often used as part of the steel-refining process to reduce these inclusions. In this paper, 3D computational fluid dynamics (CFD) modeling is used to analyze transient multiphase flow and inclusion removal in a gas-stirred ladle. The effects of gas stirring with bubble-inclusion interaction are analyzed using the Euler–Euler approach for multiphase flow modeling, while the effects of inclusions aggregation and removal are modeled via a population balance model (PBM).


Indoor Air ◽  
2021 ◽  
Author(s):  
Douaa Al Assaad ◽  
Shen Yang ◽  
Dusan Licina

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