Fast and accurate CFD-model for NOx emission prediction during oxy-fuel combustion of natural gas using detailed chemical kinetics

Schluckner, Christoph; Gaber, Christian; Landfahrer, Martin; Demuth, Martin; Hochenauer, Christoph

doi:10.1016/j.fuel.2019.116841

Cited by 73 publications

(26 citation statements)

References 36 publications

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“…However, this would increase the number of species to be transported as well as the solution matrix. Hence, NO x models are commonly decoupled from the main reaction mechanism, computing their reaction rates in a post-processing step through the converged temperature and species concentration values [51,52,53].…”

Section: Thermal No X Post-processingmentioning

confidence: 99%

Experimental and numerical study of NO formation in a domestic H2/air coaxial burner at low Reynolds number

López-Ruiz

Alava

Urresti

et al. 2021

Energy

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Section: Thermal No X Post-processingmentioning

confidence: 99%

Experimental and numerical study of NO formation in a domestic H2/air coaxial burner at low Reynolds number

López-Ruiz

Alava

Urresti

et al. 2021

Energy

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“…This indicates if the engine operating conditions are adjusted through speed, torque, fuel injection, etc., the birth amount of NOx emissions changes; the optimization of NOx emission formation by engine control is possible and highly requested for a healthy driving [13,14]. In the previous studies, understanding the formation process was required to optimize the NOx emission, and researches based on the thermodynamics or Computational Fluid Dynamics (CFD) have been conducted such as the NOx emission prediction using chemical kinetics, skeletal mechanisms, 2D/3D models, and two-zone thermodynamic model [15][16][17][18][19]. They made it possible to aware of what factors influence the NOx formation and reduction.…”

Section: Introductionmentioning

confidence: 99%

Prediction of engine NOx for virtual sensor using deep neural network and genetic algorithm

Kim

Park

Shin

et al. 2021

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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The Nitrogen Oxides (NOx) from engines aggravate natural environment and human health. Institutional regulations have attempted to protect the human body from them, while car manufacturers have tried to make NOx free vehicles. The formation of NOx emissions is highly dependent on the engine operating conditions and being able to predict NOx emissions would significantly help in enabling their reduction. This study investigates advanced method of predicting vehicle NOx emissions in pursuit of the sensorless engine. Sensors inside the engine are required to measure the operating condition. However, they can be removed or reduced if the sensing object such as the engine NOx emissions can be accurately predicted with a virtual model. This would result in cost reductions and overcome the sensor durability problem. To achieve such a goal, researchers have studied numerical analysis for the relationship between emissions and engine operating conditions. Also, a Deep Neural Network (DNN) is applied recently as a solution. However, the prediction accuracies were often not satisfactory where hyperparameter optimization was either overlooked or conducted manually. Therefore, this study proposes a virtual NOx sensor model based on the hyperparameter optimization. A Genetic Algorithm (GA) was adopted to establish a global optimum with DNN. Epoch size and learning rate are employed as the design variables, and R-squared based user defined function is adopted as the object function of GA. As a result, a more accurate and reliable virtual NOx sensor with the possibility of a sensorless engine could be developed and verified.

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“…However, the drivers of forced cooling increase the energy consumption of the system. Moreover, the high reaction temperature of oxycombustion may lead to high levels of NO x emissions because N 2 is present in both industrial syngas (Schluckner et al 2020) and air separating oxygen (Khallaghi et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Key CO2 capture technology of pure oxygen exhaust gas combustion for syngas-fueled high-temperature fuel cells

Wang

Lei

et al. 2021

Int J Coal Sci Technol

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Integrated gasification fuel cells (IGFCs) integrating high-temperature solid oxide fuel cell technology with CO2 capture processes represents highly-efficient power systems with negligible CO2 emissions. Flame burning with pure oxygen is an ideal method for fuel cell exhaust gas treatment, and this report describes experimental and numerical studies regarding an oxy-combustor for treating the exhaust gas of a 10 kW IGFC system anode. The applied simulation method was verified based on experiments, and the key performance indices of the combustor were studied under various conditions. It was determined that 315 K was the ideal condensation temperature to obtain flame stability. Under these pure oxygen flame burning conditions, CO was almost completely converted, and the dry mole fraction of CO2 after burning was ≥ 0.958 when there was up to 5% excess O2. Overall, 5% excess O2 was recommended to maximize CO2 capture and promote other environmental considerations. Additionally, the optimal tangential fuel jet angle to control the liner temperature was approximately 25°. The total fuel utilization had to be high enough to maintain the oxygen flame temperature of the anode exhaust gas below 1800 K to ensure that the system was environmentally friendly. The results presented herein have great value for designing IGFCs coupled with CO2 capture systems.

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Fast and accurate CFD-model for NOx emission prediction during oxy-fuel combustion of natural gas using detailed chemical kinetics

Cited by 73 publications

References 36 publications

Experimental and numerical study of NO formation in a domestic H2/air coaxial burner at low Reynolds number

Experimental and numerical study of NO formation in a domestic H2/air coaxial burner at low Reynolds number

Prediction of engine NOx for virtual sensor using deep neural network and genetic algorithm

Key CO2 capture technology of pure oxygen exhaust gas combustion for syngas-fueled high-temperature fuel cells

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