scholarly journals Development of a soot concentration estimation library for industrial combustion applications using Lagrangian parcel tracking

2021 ◽  
Author(s):  
Raymond Alexander
Keyword(s):  
Human Health ◽  
Gas Phase ◽  
Diffusion Flames ◽  
Soot Formation ◽  
Computational Cost ◽  
Soot Concentration ◽  
Cfd Simulations ◽  
Concentration Estimation ◽  
Low Computational Cost ◽  
Harmful Effects

Soot emissions from combustion devices are known to have harmful effects on the environment and human health. This project leverages existing knowledge in soot modelling and soot formation fundamentals to develop a stand-alone, computationally inexpensive soot concentration estimator to be linked to CFD simulations as a post-processor. The estimator consists of a library generated using the hystereses of soot-containing fluid parcels, which relates soot concentration to the aggregated gas-phase environment histories to which a fluid parcel has been exposed. The estimator can be used to relate soot concentration to computed parcel hystereses through interpolation techniques. The estimator shows the potential ability to produce accurate predictions with very low computational cost in laminar coflow diffusion flames. Results also show that as flame data representing a broader set of conditions is added to the library, the estimator becomes applicable to a wider range of flames.

scholarly journals Development of a soot concentration estimation library for industrial combustion applications using Lagrangian parcel tracking

2021 ◽  
Author(s):  
Raymond Alexander
Keyword(s):  
Human Health ◽  
Gas Phase ◽  
Diffusion Flames ◽  
Soot Formation ◽  
Computational Cost ◽  
Soot Concentration ◽  
Cfd Simulations ◽  
Concentration Estimation ◽  
Low Computational Cost ◽  
Harmful Effects

Soot emissions from combustion devices are known to have harmful effects on the environment and human health. This project leverages existing knowledge in soot modelling and soot formation fundamentals to develop a stand-alone, computationally inexpensive soot concentration estimator to be linked to CFD simulations as a post-processor. The estimator consists of a library generated using the hystereses of soot-containing fluid parcels, which relates soot concentration to the aggregated gas-phase environment histories to which a fluid parcel has been exposed. The estimator can be used to relate soot concentration to computed parcel hystereses through interpolation techniques. The estimator shows the potential ability to produce accurate predictions with very low computational cost in laminar coflow diffusion flames. Results also show that as flame data representing a broader set of conditions is added to the library, the estimator becomes applicable to a wider range of flames.

scholarly journals Development of a soot concentration estimator for industrial combustion applications

2021 ◽  
Author(s):  
Sepehr Bozorgzadeh
Keyword(s):  
Adverse Effects ◽  
Human Health ◽  
Atmospheric Pressure ◽  
Soot Formation ◽  
Soot Concentration ◽  
Important Goal ◽  
Cfd Simulations ◽  
Preliminary Results ◽  
Volume Fractions ◽  
Entire History

Soot emissions from combustion devices are known to have adverse effects on the environment and human health. Thus, the development of techniques to reduce soot formation and emissions remains an important goal of researchers and industry. This study leverages existing knowledge in soot modelling and soot formation fundamentals to develop a stand-alone, computationally inexpensive soot concentration estimator, to be linked to CFD simulations as a post-processor. The estimator was developed using fluid parcel tracking techniques that can track entire history to which a particle or fluid parcel has been exposed. Preliminary results suggest that the estimator is capable of predicting peak and emitted soot volume fractions in atmospheric pressure flames.

scholarly journals Development of a soot concentration estimator for industrial combustion applications

2021 ◽  
Author(s):  
Sepehr Bozorgzadeh
Keyword(s):  
Adverse Effects ◽  
Human Health ◽  
Atmospheric Pressure ◽  
Soot Formation ◽  
Soot Concentration ◽  
Important Goal ◽  
Cfd Simulations ◽  
Preliminary Results ◽  
Volume Fractions ◽  
Entire History

Soot emissions from combustion devices are known to have adverse effects on the environment and human health. Thus, the development of techniques to reduce soot formation and emissions remains an important goal of researchers and industry. This study leverages existing knowledge in soot modelling and soot formation fundamentals to develop a stand-alone, computationally inexpensive soot concentration estimator, to be linked to CFD simulations as a post-processor. The estimator was developed using fluid parcel tracking techniques that can track entire history to which a particle or fluid parcel has been exposed. Preliminary results suggest that the estimator is capable of predicting peak and emitted soot volume fractions in atmospheric pressure flames.

Modelling of Soot Formation in Spray Combustors

1983 ◽  
Author(s):  
S. S. Koussa
Keyword(s):  
Experimental Data ◽  
Liquid Phase ◽  
Gas Phase ◽  
Soot Formation ◽  
Soot Concentration ◽  
Practical Application ◽  
Combustion Modelling

A model for the prediction of the distribution of soot concentration in spray combustors is presented. Both gas-phase and liquid-phase soot formation have been considered. The methods have been developed within the constraints on detailed combustion modelling for practical application. Some predictions are assessed by comparison with published experimental data. It is concluded that predictions of the same quality as those of gaseous-fuelled combustors may be obtained neglecting liquid-phase soot formation in case of light fuels.

Aerodynamic prediction of a projectile fitted with fins

2018 ◽  
Vol 28 (5) ◽  
pp. 1218-1236 ◽  
Author(s):  
Cédric Decrocq ◽  
Bastien Martinez ◽  
Marie Albisser ◽  
Simona Dobre ◽  
Patrick Gnemmi ◽  
...  
Keyword(s):  
Long Range ◽  
Computational Cost ◽  
Preliminary Design ◽  
Cfd Simulations ◽  
Content Type ◽  
Speed Up ◽  
Computational Fluid Dynamics Cfd ◽  
Lifting Surfaces ◽  
Time Accuracy ◽  
Low Computational Cost

Purpose The present paper deals with weapon aerodynamics and aims to describe preliminary studies that were conducted for developing the next generation of long-range guided ammunition. Over history, ballistic research scientists were constantly investigating new artillery systems capable of overcoming limitations of range, accuracy and manoeuvrability. While futuristic technologies are increasingly under development, numerous issues concerning current powdered systems still need to be addressed. In this context, the present work deals with the design and the optimization of a new concept of long-range projectile with regard to multidisciplinary fields, including flight scenario, steering strategy, mechanical actuators or size of payload. Design/methodology/approach Investigations are conducted for configurations that combine existing full calibre 155 mm guided artillery shell with a set of lifting surfaces. As the capability of the ammunition highly depends on lifting surfaces in terms of number, shape or position, a parametric study has to be conducted for determining the best aerodynamic architecture. To speed-up this process, initial estimations are conducted thanks to low computational cost methods suitable for preliminary design requirements, in terms of time, accuracy and flexibility. The WASP code (Wing-Aerodynamic-eStimation-for-Projectiles) has been developed for rapidly predicting aerodynamic coefficients (static and dynamic) of a set of lifting surfaces fitted on a projectile fuselage, as a function of geometry and flight conditions, up to transonic velocities. Findings In the present study, WASP predictions at Mach 0.7 of both normal force and pitching moment coefficients are assessed for two configurations. Originality/value Analysis is conducted by gathering results from WASP, computational-fluid-dynamics (CFD) simulations, wind-tunnel experiments and free-flight tests. Obtained results demonstrate the ability of WASP code to be used for preliminary design steps.

scholarly journals An Artificial Neural Network for the Low-Cost Prediction of Soot Emissions

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4787 ◽  
Author(s):  
Mehdi Jadidi ◽  
Stevan Kostic ◽  
Leonardo Zimmer ◽  
Seth B. Dworkin
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Soot Formation ◽  
Computational Cost ◽  
Concentration Field ◽  
Performance Testing ◽  
Training Data ◽  
Soot Concentration ◽  
Data Set ◽  
Artificial Neural

Soot formation in combustion systems is a growing concern due to its adverse environmental and health effects. It is considered to be a tremendously complicated phenomenon which includes multiphase flow, thermodynamics, heat transfer, chemical kinetics, and particle dynamics. Although various numerical approaches have been developed for the detailed modeling of soot evolution, most industrial device simulations neglect or rudimentarily approximate soot formation due to its high computational cost. Developing accurate, easy to use, and computationally inexpensive numerical techniques to predict or estimate soot concentrations is a major objective of the combustion industry. In the present study, a supervised Artificial Neural Network (ANN) technique is applied to predict the soot concentration fields in ethylene/air laminar diffusion flames accurately with a low computational cost. To gather validated data, eight different flames with various equivalence ratios, inlet velocities, and burner geometries are modeled using the CoFlame code (a computational fluid dynamics (CFD) parallel combustion and soot model) and the Lagrangian histories of soot-containing fluid parcels are computed and stored. Then, an ANN model is developed and optimized using the Levenberg-Marquardt approach. Two different scenarios are introduced to validate the network performance; testing the prediction capabilities of the network for the same eight flames that are used to train the network, and for two new flames that are not within the training data set. It is shown that for both of these cases the ANN is able to predict the overall soot concentration field very well with a relatively low integrated error.

scholarly journals Effect of the Preheated Oxidizer Temperature on Soot Formation and Flame Structure in Turbulent Methane-Air Diffusion Flames at 1 and 3 atm: A CFD Investigation

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3671
Author(s):  
Subrat Garnayak ◽  
Subhankar Mohapatra ◽  
Sukanta K. Dash ◽  
Bok Jik Lee ◽  
V. Mahendra Reddy
Keyword(s):  
Mole Fraction ◽  
Air Temperature ◽  
Reaction Rate ◽  
Volume Fraction ◽  
Diffusion Flames ◽  
Soot Formation ◽  
Flame Structure ◽  
Soot Volume Fraction ◽  
Computational Domain ◽  
Pressure Elevation

This article presents the results of computations on pilot-based turbulent methane/air co-flow diffusion flames under the influence of the preheated oxidizer temperature ranging from 293 to 723 K at two operating pressures of 1 and 3 atm. The focus is on investigating the soot formation and flame structure under the influence of both the preheated air and combustor pressure. The computations were conducted in a 2D axisymmetric computational domain by solving the Favre averaged governing equation using the finite volume-based CFD code Ansys Fluent 19.2. A steady laminar flamelet model in combination with GRI Mech 3.0 was considered for combustion modeling. A semi-empirical acetylene-based soot model proposed by Brookes and Moss was adopted to predict soot. A careful validation was initially carried out with the measurements by Brookes and Moss at 1 and 3 atm with the temperature of both fuel and air at 290 K before carrying out further simulation using preheated air. The results by the present computation demonstrated that the flame peak temperature increased with air temperature for both 1 and 3 atm, while it reduced with pressure elevation. The OH mole fraction, signifying reaction rate, increased with a rise in the oxidizer temperature at the two operating pressures of 1 and 3 atm. However, a reduced value of OH mole fraction was observed at 3 atm when compared with 1 atm. The soot volume fraction increased with air temperature as well as pressure. The reaction rate by soot surface growth, soot mass-nucleation, and soot-oxidation rate increased with an increase in both air temperature and pressure. Finally, the fuel consumption rate showed a decreasing trend with air temperature and an increasing trend with pressure elevation.

scholarly journals Computing Expectiles Using k-Nearest Neighbours Approach

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 645
Author(s):  
Muhammad Farooq ◽  
Sehrish Sarfraz ◽  
Christophe Chesneau ◽  
Mahmood Ul Hassan ◽  
Muhammad Ali Raza ◽  
...  
Keyword(s):  
Computational Cost ◽  
Real Life ◽  
Distance Measures ◽  
Computational Time ◽  
High Dimensional ◽  
Test Error ◽  
Nearest Neighbours ◽  
Comparable Performance ◽  
Asymmetric Least Squares ◽  
Low Computational Cost

Expectiles have gained considerable attention in recent years due to wide applications in many areas. In this study, the k-nearest neighbours approach, together with the asymmetric least squares loss function, called ex-kNN, is proposed for computing expectiles. Firstly, the effect of various distance measures on ex-kNN in terms of test error and computational time is evaluated. It is found that Canberra, Lorentzian, and Soergel distance measures lead to minimum test error, whereas Euclidean, Canberra, and Average of (L1,L∞) lead to a low computational cost. Secondly, the performance of ex-kNN is compared with existing packages er-boost and ex-svm for computing expectiles that are based on nine real life examples. Depending on the nature of data, the ex-kNN showed two to 10 times better performance than er-boost and comparable performance with ex-svm regarding test error. Computationally, the ex-kNN is found two to five times faster than ex-svm and much faster than er-boost, particularly, in the case of high dimensional data.

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