54 results found
Tsagkaridis M, Rigopoulos S, Papadakis G, 2022, Analysis of turbulent coagulation in a jet with discretised population balance and DNS, Journal of Fluid Mechanics, ISSN: 0022-1120
Tian B, Liu A, Chong CT, et al., 2021, Measurement and simulation of sooting characteristics by an ATJ-SKA biojet fuel and blends with Jet A-1 fuel in laminar non-premixed flames, Combustion and Flame, Vol: 233, Pages: 1-15, ISSN: 0010-2180
We investigate the sooting propensity of an Alcohol-to-Jet-Synthetic Kerosene with Aromatics (ATJ-SKA) biojet fuel. The soot volume fraction and primary particle size in the pre-vaporised diffusion flames using ATJ-SKA biojet and blends with Jet A-1 at atmospheric conditions were measured experimentally and compared to numerical simulations. The measurements were conducted using extinction calibrated laser induced incandescence (LII). The soot volume fractions measured using the ATJ-SKA fuel do not show significant differences relative to measurements with Jet A-1. A comparison of the chemical composition of the fuels suggests that the Degree of Unsaturation (DoU) may not determine the sooting propensity of biojet fuels. The SEM analysis shows that diffusion flames using neat Jet A-1 produce finer soot particles and larger number density compared to the biojet and biojet surrogate. The soot model employs a semi-detailed chemical kinetic mechanism and a physical model which integrates the population balance equation governing the soot particle size distribution with an in-house reactive flow solver for multicomponent ideal gases. The model predicts the maximum soot volume fraction (SVFm) in the neat biojet case and the blended cases with Jet A-1 fuels within an error margin of 13% of the measured values. However, the predicted soot volume fraction distribution patterns differ from the measured one and the possible causes are discussed.
Liu A, Luo KH, Rigopoulos S, et al., 2021, Effects of the electric field on soot formation in combustion: a coupled charged particle PBE-CFD framework, Combustion and Flame, ISSN: 0010-2180
In this article, a coupled PBE-CFD framework has been proposed to study counterflow non-premixed flames and soot formation under an external electric field. This framework integrates the population balance equation (PBE) for nanoparticle dynamics into an in-house CFD solver for the multicomponent reactive flows. Different electric properties have been considered in this model. An ion mechanism used in both fuel-rich and fuel-lean combustion is combined with a detailed chemistry for neutral gaseous species and small-size aromatics to retain the full chemistry. In order to model soot particles carrying charges and the movement of the reacting fluid medium in the electric field, a second PBE for the production and transport of charges on soot particles is introduced for the first time and incorporated into the original PBE for the number density of particles. Also, the electric force for the gas mixture is included in the momentum equations. The electric drift velocities for ions and soot particles are also considered in the transport equations of ions and the PBE of soot particles, respectively. The simulations have shown that the presence of the electric field modifies the stagnation plane of the counterflow flames and reduces the soot formation in both rich-fuel and lean-fuel conditions in agreement with experimental observations. The application of the soot particle charging model, accompanied by a proper electric correction factor on the nanoparticle processes of nucleation and surface growth, significantly improves the stability of the flame structure. The introduction of the electric correction factor reveals that the suppression of soot formation in an electric field is mainly caused by the inhibited chemical reactions of the PAH nucleation and particle surface growth, which is more important than the electric drift of the charged particles. Reducing the critical size of the particle charging process enhances the electric drift of nascent soot, thus lessening i
Papadakis G, Rigopoulos S, Mikhaylov K, 2021, Reconstruction of large scale flow structures in a stirred tank from limited sensor data, AIChE Journal, Vol: 67, Pages: 1-16, ISSN: 0001-1541
We combine reduced order modelling and system identification to reconstruct the temporal evolution of large scale vortical structures behind the blades of a Rushton impeller. We performed Direct Numerical Simulations at Reynolds number 600 and employed proper orthogonal decomposition (POD) to extract the dominant modes and their temporal coefficients. We then applied the identification algorithm, N4SID, to construct an estimator that captures the relation between the velocity signals at sensor points (input) and the POD coefficients (output). We show that the first pair of modes can be very well reconstructed using the velocity time signal from even a single sensor point. A larger number of points improves accuracy and robustness, and also leads to better reconstruction for the second pair of POD modes. Application of the estimator derived at Re=600 to the flows at Re=500 and 700, shows that it is robust with respect to changes in operating conditions.
Ding T, Readshaw T, Rigopoulos S, et al., 2021, Machine learning tabulation of thermochemistry in turbulent combustion: An approach based on hybrid flamelet/random data and multiple multilayer perceptrons, Combustion and Flame, Vol: 231, Pages: 1-23, ISSN: 0010-2180
A new machine learning methodology is proposed for speeding up thermochemistry computations in simulations of turbulent combustion. The approach is suited to a range of methods including Direct Numerical Simulation (DNS), Probability Density Function (PDF) methods, unsteady flamelet, Conditional Moment Closure (CMC), Multiple Mapping Closure (MMC), Linear Eddy Model (LEM), Thickened Flame Model, the Partially Stirred Reactor (PaSR) method (as in OpenFOAM) and the computation of laminar flames. In these methods, the chemical source term must be evaluated at every time step, and is often the most expensive element of a simulation. The proposed methodology has two main objectives: to offer enhanced capacity for generalisation and to improve the accuracy of the ANN prediction. To accomplish the first objective, we propose a hybrid flamelet/random data (HFRD) method for generating the training set. The random element endows the resulting ANNs with increased capacity for generalisation. Regarding the second objective, a multiple multilayer perceptron (MMP) approach is developed where different multilayer perceptrons (MLPs) are trained to predict states that result in smaller or larger composition changes, as these states feature different dynamics. It is shown that the multiple MLP method can greatly reduce the prediction error, especially for states yielding small composition changes. The approach is used to simulate flamelets of varying strain rates, one-dimensional premixed flames with differential diffusion and varying equivalence ratio, and finally the Large Eddy Simulation (LES) of /air piloted flames Sandia D, E and F, which feature different levels of local extinction. The simulation results show very good agreement with those obtained from direct integration, while the range of problems simulated indicates that the approach has great capacity for generalisation. Finally, a speed-up ratio of 12 is attained for the reaction step.
Sun B, Rigopoulos S, Liu A, 2021, Modelling of soot coalescence and aggregation with a two-population balance equation model and a conservative finite volume method, Combustion and Flame, Vol: 229, Pages: 1-19, ISSN: 0010-2180
The objective of the present paper is to develop a population balance approach for modelling soot formation that distinguishes between coalescence and aggregation and accounts for finite-rate fusing of primary particles within aggregates, while providing a numerically accurate description of primary particle surface growth and oxidation within aggregates. To this end, the recently developed conservative finite volume sectional method for the solution of the population balance equation (PBE) due to Liu and Rigopoulos (2019, Combust. Flame 205, 506–521) is extended to a two-PBE approach that allows for a more accurate modelling of primary particle surface growth and oxidation and furthermore involves a timescale for the fusing of primary particles. The accuracy of the numerical method is first tested by calculating the self-preserving distributions of aggregates with varying fractal dimension. Subsequently, the one-PBE and two-PBE approaches are coupled with CFD and applied to the simulation of the Santoro laminar non-premixed co-flow sooting flame. The results show that both approaches can provide good prediction of the soot volume fraction, but the two-PBE approach yields a significant improvement in the prediction of soot morphology. At present, the information available for modelling the gradual fusing of soot primary particles is based on experiments on silica and titania nanoparticles, and therefore a comprehensive study of the impact of the sintering model parameters is conducted. Finally, conclusions are drawn regarding the predictive potential of the one-PBE and two-PBE approaches.
Readshaw T, Ding T, Rigopoulos S, et al., 2021, Modeling of turbulent flames with the large eddy simulation–probability density function (LES–PDF) approach, stochastic fields, and artificial neural networks, Physics of Fluids, Vol: 33, Pages: 1-17, ISSN: 1070-6631
This work proposes a chemical mechanism tabulation method using artificial neural networks (ANNs) for turbulent combustion simulations. The method is employed here in the context of the Large-Eddy Simulation (LES)–Probability Density Function (PDF) approach and the method of stochastic fields for numerical solution, but can also be employed in other methods featuring real-time integration of chemical kinetics. The focus of the paper is on exploring an ANN architecture aiming at improved generalization, which uses a single multilayer perceptron (MLP) for each species over the entire training dataset. This method is shown to outperform previous approaches which take advantage of specialization by clustering the composition space using the Self-Organizing Map (SOM). The ANN training data are generated using the canonical combustion problem of igniting/extinguishing one-dimensional laminar flamelets with a detailed methane combustion mechanism, before being augmented with randomly generated data to produce a hybrid random/flamelet dataset with improved composition space coverage. The ANNs generated in this study are applied to the LES of a turbulent non-premixed CH4/air flame, Sydney flame L. The transported PDF approach is used for reaction source term closure, while numerical solution is obtained using the method of stochastic fields. Very good agreement is observed between direct integration (DI) and the ANNs, meaning that the ANNs can successfully replace the integration of chemical kinetics. The time taken for the reaction source computation is reduced 18-fold, which means that LES–PDF simulations with comprehensive mechanisms can be performed on modest computing resources.
Ma C, Zou X, Li A, et al., 2021, Evolution of MoO3 nanobelts and nanoplatelets formation with flame synthesis, Proceedings of the Combustion Institute, Vol: 38, Pages: 1289-1297, ISSN: 0082-0784
A co-flow premixed flat flame is applied to form MoO3 nanobelts and nanoplatelets in the gas phase. An experimental study is conducted with a thermophoretic sampling particle diagnostic (TSPD) technique to reconstruct the evolution of nanostructure formation. In order to investigate the growth mechanism of the nanobelts and nanoplatelets, samples were directly taken along the centerline at different positions in the flame to represent the essential morphological variations of material. Based on the sample information collected by TEM, a growth mechanism of nanobelts and nanoplatelets is proposed. The results indicate that nanobelts and nanoplatelets with well-defined structure are successfully synthesized in premixed flame. The precursor temperature has a significant impact on the morphology by affecting the vapor concentration in the flame. For synthetic nanobelts,the intermediate particles tend to grow along a specific direction with small surface energy, and the final morphology is determined by particle attachment. In contrast, the initial growth of the nanoplatelets is mainly characterized by vapor surface deposition/growth, and the formation of the final morphology relies on the coalescence of large particles and small particles.
Cheng X, Gao Z, Ren F, et al., 2021, Experimental and kinetic modeling study on sooting tendencies of alkylbenzene isomers, Fuel, Vol: 283, ISSN: 0016-2361
Alkylbenzenes are major aromatic constituents of real transportation fuels and important surrogate components. In this study, 4 kinds of C8H10 and 8 kinds of C9H12 alkylbenzenes were tested in a laminar diffusion flame to investigate the influence of chemical structure on sooting tendency. The laser induced incandescence (LII) technique was applied to obtain the 2D distribution of soot volume fraction for calculating the yield sooting index (YSI) of test fuels. The processes of fuel oxidation and soot formation were simulated by a detailed chemical kinetic mechanism. The mechanism includes all C8H10 and C9H12 alkylbenzenes and includes species ranging from reactant to carbon particle. The simulation results of defined YSI were in good agreement with the experimental values. A database of sooting tendencies was established by experimental data, which shows that the number of substituents is positively correlated with the sooting tendency and that the sooting tendency of meta-substituent species is higher than other isomers. Through the analysis of reaction pathway and sensitivity, it was found that the main production pathway of A4 (pyrene) is via alkylbenzenes combination reactions at the early stage of combustion. The experimental database presented in this study is systematic and comprehensive for C8H10 and C9H12 alkylbenzenes, and is thus expected to be useful for soot model development and validation.
Tian B, Liu AX, Chong CT, et al., 2021, Experimental and numerical study on soot formation in laminar diffusion flames of biodiesels and methyl esters, Proceedings of the Combustion Institute, Vol: 38, Pages: 1335-1344, ISSN: 1540-7489
Biodiesel and blends with petroleum diesel are promising renewable alternative fuels for engines. In the present study, the soot concentration generated from four biodiesels, two pure methyl esters, and their blends with petroleum diesel are measured in a series of fully pre-vapourised co-flow diffusion flames. The experimental measurements are conducted using planar laser induced-incandescence (LII) and laser extinction optical methods. The results show that the maximum local soot volume fractions of neat biodiesels are 24.4% - 41.2% of pure diesel, whereas the mean soot volume fraction of neat biodiesel cases was measured as 11.3% - 21.3% of pure diesel. The addition of biodiesel to diesel not only reduces the number of inception particles, but also inhibits their surface growth. The discretised population balance modelling of a complete set of soot processes is employed to compute the 2D soot volume fraction and size distribution across the tested flames. The results show that the model also demonstrates a reduction of both soot volume fraction and primary particle size by adding biodiesel fuels. However, it is not possible to clearly determine which factors are responsible for the reduction from the comparison alone. Moreover, analysis of the discrepancies between numerical and experimental results for diesel and low-blending cases offers an insight for the refinement of soot formation modelling of combustion with large-molecule fuels.
Tang HY, Rigopoulos S, Papadakis G, 2020, A methodology for coupling DNS and discretised population balance for modelling turbulent precipitation, International Journal of Heat and Fluid Flow, Vol: 86, ISSN: 0142-727X
In this paper, we present a methodology for simulating nanoparticle formation in a turbulent flow by coupling Direct Numerical Simulation (DNS) and population balance modelling. The population balance equation (PBE) is solved via a discretisation method employing a composite grid that provides sufficient detail over the wide range of particle sizes reached during the precipitation process. The coupled DNS/PBE approach captures accurately the strong interaction between the dynamics of turbulent mixing and particle formation processes. It also allows the calculation of the particle size distribution (PSD) of the product and enables an investigation on how it is controlled by turbulent mixing. Finally, it provides the statistics of kinetic processes and their timescales so that further analysis can be performed. The methodology is applied to the simulation of experiments of hydrodynamics and nanoparticle precipitation in a T-mixer (Schwertfirm et al., 2007, Int. J. of Heat and Fluid Flow 28, pp. 1429-1442; Schwarzer et al., 2006, Chem.Eng. Sci. 61, pp. 167-181), and the agreement with the experimental results is very good.
Liu A, Garcia CE, Sewerin F, et al., 2020, Population balance modelling and laser diagnostic validation of soot particle evolution in laminar ethylene diffusion flames, Combustion and Flame, Vol: 221, Pages: 384-400, ISSN: 0010-2180
Laminar diffusion flames present an elementary configuration for investigating soot formation and validating kinetic models before these are transferred to turbulent combustors. In the present article, we present a joint experimental and modelling investigation of soot formation in a laminar co-flow burner. The diffusion flames are analysed with the aid of laser diagnostic techniques, including elastic light scattering (ELS), planar laser-induced fluorescence of OH (OH-PLIF) and line-of-sight attenuation (LOSA), to measure the spatial distribution of soot, gas phase species and the line-of-sight integrated soot volume fraction (ISVF), respectively. The experimental dataset is supplemented by location-specific TEM images of thermophoretically sampled soot particles. The simulation of the sooting flames is carried out with a recently developed discretisation method for the population balance equation (Liu and Rigopoulos, 2019, Combust. Flame 205, 506-521) that accomplishes an accurate prediction of the particle size distribution, coupled with an in-house CFD code. By minimising numerical errors, we ensure that the discrepancies on the modelling side are mainly due to kinetics and are able to carry out an investigation of alternative models. We include a complete set of soot kinetics for PAH-based nucleation and condensation, HACA-based surface growth and oxidation as well as size-dependent aggregation, and consider three different gas phase reaction mechanisms (ABF, BBP and KM2). Based on predictions of the gas phase composition and particle size distribution of soot, modelled counterparts of the laser diagnostic signals are computed and compared with the experimental measurements. The approach of directly predicting signals circumvents the difficulties of explicitly representing the OH concentration in terms of the measured OH-PLIF data and avoids using ‘hybrid’ modelled and measured values to approximate the OH concentration. Moreover, the LOSA signal is
Rigopoulos S, 2019, Modelling of soot aerosol dynamics in turbulent flow, Flow, Turbulence and Combustion, Vol: 103, Pages: 565-604, ISSN: 1386-6184
Aerosol dynamics plays an important role in the modelling of soot formation in combustion processes, as it is responsible for predicting the distribution of size and shape of soot particles. The distribution is required for the correct prediction of the rates of surface processes, such as growth and oxidation, and furthermore it is important on its own because new regulations on particulate emissions require control of the number of smaller particles. Soot formation is strongly dependent on the local chemical composition and thermodynamic conditions and is therefore coupled with fluid dynamics, chemical kinetics and transport phenomena. Comprehensive modelling of soot formation in combustion processes requires coupling of the population balance equation, which is the fundamental equation governing aerosol dynamics, with the equations of fluid dynamics. The presence of turbulence poses an additional challenge, due to the non-linear interactions between fluctuating velocity, temperature, concentrations and soot properties. The purpose of this work is to review the progress made in aerosol dynamics models, their integration with fluid dynamics and the models for addressing the turbulence-soot interaction.
Tang H, Papadakis G, Rigopoulos S, 2019, Coupling direct numerical simulations with population balance modelling for predicting turbulent particle precipitation in a T-mixer, 11th International Symposium on Turbulence and Shear Flow Phenomena (TSFP11), Publisher: TSFP
In this study we develop a methodology for predicting the particle size distribution(PSD)inparticulate process, a process used for producing particulate materials,by coupling population balance modelling and direct numerical simulation. Itis employed in investigating the turbulent precipitation of BaSO4in a T-mixer.The high resolution allowed us to capture the dominating mechanisms.Particle formation is most intense in the impingementand the reactantconsumption in each precipitation mechanism depends on the mixing intensity.Different particle formation statesand their characteristics on the PSD in the early stage arethenidentified.Comparisonwith an ideal reactor showsthat the distribution can be controlled by altering the mixing environment.
Liu A, Rigopoulos S, 2019, A conservative method for numerical solution of the population balance equation, and application to soot formation, Combustion and Flame, Vol: 205, Pages: 506-521, ISSN: 0010-2180
The objective of this paper is to present a finite volume method for the discretisation of the population balance equation with coagulation, growth and nucleation that combines: (a) accurate prediction of the distribution with a small number of sections, (b) conservation of the first moment (or any other single moment) in a coagulation process, (c) applicability to an arbitrary non-uniform grid, and (d) speed and robustness that make it suitable for combining with a CFD code for solving problems such as soot formation in flames. The conservation of the first moment of a distribution with respect to particle volume is of particular importance for two reasons: it is an invariant during a coagulation process and it represents conservation of mass. The method is based on a geometric evaluation of the double integrals arising from the finite volume discretisation of the coagulation terms and an exact balance of coagulation source and sink terms to ensure moment conservation. Extensive testing is performed by comparison with analytical solutions and direct numerical solutions of the discrete PBE for both theoretical and physically important coagulation kernels. Finally, the method is applied to the simulation of a laminar co-flow diffusion sooting flame, in order to assess its potential for coupling with CFD, chemical kinetics, transport and radiation models. The results show that accurate solutions can be obtained with a small number of sections, and that the PBE solution requires less than one fourth of the time of the complete simulation, only half of which is spent on the discretisation (the remaining being for the evaluation of the temperature dependence of the coagulation kernel).
Sewerin F, Rigopoulos S, 2019, Algorithmic aspects of the LES-PBE-PDF method for modeling soot particle size distributions in turbulent flames, Combustion Science and Technology, Vol: 191, Pages: 766-796, ISSN: 0010-2202
In recent times, the LES-PBE-PDF framework has been developed to couple large eddy simulation (LES) and population balance models (PBE) for the description of soot formation in turbulent hydrocarbon flames. This approach is based on a modeled evolution equation for the LES-filtered probability density function (pdf) associated with the instantaneous gas composition and soot particle size distribution. Here, the interaction of turbulence with chemical reactions and soot formation can be represented without approximations on part of the chemical and soot formation kinetics, while effects due to turbulent transport and molecular diffusion require closure. In view of an efficient numerical solution scheme, we previously proposed to combine a statistically equivalent reformulation of the joint scalar-number density pdf based on Eulerian stochastic fields with a time-explicit adaptive grid discretization in particle size space and a fractional time stepping scheme. In this article, we present algorithmic aspects and relay implementational details for a consistent semi-discrete formulation of the PBE fractional step as well as an effective dynamic load balancing scheme for both the chemical reaction and PBE fractional steps. Considering soot formation in the Delft III turbulent diffusion flame as a test case, we show that the persisting load imbalance is almost negligible on average and give evidence of linear strong scaling on a modern high performance computer for moderate numbers of compute nodes.
Koniavitis P, Rigopoulos S, Jones W, 2018, Reduction of a detailed chemical mechanism for a kerosenesurrogate via RCCE-CSP, Combustion and Flame, Vol: 194, Pages: 85-106, ISSN: 0010-2180
Detailed mechanisms for kerosene surrogate fuels contain hundreds of species and thousands of reactions, indicating a necessity for reduced mechanisms. In this work, we employ a framework that combines Rate-Controlled Constrained Equilibrium (RCCE) with Computational Singular Perturbation (CSP) for systematic reduction based on timescale analysis, to reduce a detailed mechanism for a jet fuel surrogate with n-dodecane, methylcyclohexane and m-xylene. Laminar non-premixed flamelets are utilised for the CSP analysis for different strain rates and therefore different scalar dissipation rate, covering the flammable region of strain rates for the surrogate fuel.Two RCCE-reduced mechanisms are developed via an RCCE-CSP methodology, one with 17 and one with 42 species, and their accuracy is assessed in a range of cases that test the performance of the reduced mechanism under both non-premixed and premixed conditions and its dynamic response. These include non-premixed flamelets with varying strain rate, laminar premixed flames for a range of equivalence ratios and pressures, flamelets ignited by an artificial pilot or by hot air, and unsteady flamelets with time-dependent strain rate.The profiles of both major and minor species, as well as important combustion characteristics such as the ignition strain rate and the laminar flame speed, are investigated. The structure of non-premixed flamelets is very well predicted, while the premixed flames are overall well predicted apart from a few deviations in certain species and an underprediction in the laminar flame speed. Apart from the large reduction in dimensionality, the reduction in computational time is also considerable (up to 19 times). As the detailed mechanism comprises 367 species and 1892 reactions, this paper presents the first application of RCCE to a mechanism of this size, as well as a comprehensive validation in a set of cases that include non-premixed and premixed laminar flames, atmospheric and elevated pressur
Sewerin F, Rigopoulos S, 2018, An LES-PBE-PDF approach for predicting the soot particle size distribution in turbulent flames, Combustion and Flame, Vol: 189, Pages: 62-76, ISSN: 0010-2180
In this article, we combine the large eddy simulation (LES) concept with the population balance equation (PBE) for predicting, in a Eulerian fashion, the evolution of the soot particle size distribution in a turbulent non-premixed hydrocarbon flame. In order to resolve the interaction between turbulence and chemical reactions/soot formation, the transport equations for the gas phase scalars and the PBE are combined into a joint evolution equation for the filtered pdf associated with a single realization of the gas phase composition and the soot number density distribution. With view towards an efficient numerical solution procedure, we formulate Eulerian stochastic field equations that are statistically equivalent to the joint scalar-number density pdf. By discretizing the stochastic field equation for the particle number density using an explicit adaptive grid technique, we are able to accurately resolve sharp features of evolving particle size distributions, while keeping the number of grid points in particle size space small. Compared to existing models, the main advantage of our approach is that the LES-filtered particle size distribution is predicted at each location in the flow domain and every instant in time and that arbitrary chemical reaction mechanisms and soot formation kinetics can be accommodated without approximation. The combined LES-PBE-PDF model is applied to investigate soot formation in the turbulent non-premixed Delft III flame. Here, the soot kinetics encompass acetylene-based rate expressions for nucleation and growth that were previously employed in the context of laminar diffusion flames. In addition, both species consumption by soot formation and radiation based on the assumption of optical thinness are accounted for. While the agreement of our model predictions with experimental measurements is not perfect, we indicate the benefits of the LES-PBE-PDF model and demonstrate its computational viability.
Franke LLC, Chatzopoulos AK, Rigopoulos S, 2017, Tabulation of combustion chemistry via Artificial Neural Networks (ANNs): methodology and application to LES-PDF simulation of Sydney flame L, Combustion and Flame, Vol: 185, Pages: 245-260, ISSN: 0010-2180
In this work, a methodology for the tabulation of combustion mechanisms via Artificial Neural Networks (ANNs) is presented. The objective of the methodology is to train the ANN using samples generated via an abstract problem, such that they span the composition space of a family of combustion problems. The abstract problem in this case is an ensemble of laminar flamelets with an artificial pilot in mixture fraction space to emulate ignition, of varying strain rate up to well into the extinction range. The composition space thus covered anticipates the regions visited in a typical simulation of a non-premixed flame. The ANN training consists of two-stage process: clustering of the composition space into subdomains using the Self-Organising Map (SOM) and regression within each subdomain via the multilayer Perceptron (MLP). The approach is then employed to tabulate a mechanism of CH4-air combustion, based on GRI 1.2 and reduced via Rate-Controlled Constrained Equilibrium (RCCE) and Computational Singular Perturbation (CSP). The mechanism is then applied to simulate the Sydney Flame L, a turbulent non-premixed flame that features significant levels of local extinction and re-ignition. The flow field is resolved through Large Eddy Simulation (LES), while the transported Probability Density Function (PDF) approach is employed for modelling the turbulence-chemistry interaction and solved numerically via the Stochastic Fields method. Results demonstrate reasonable agreement with experiments, indicating that the SOM-MLP approach provides a good representation of the composition space, while the great savings in CPU time allow for a simulation to be performed with a comprehensive combustion model, such as the LES-PDF, with modest CPU resources such as a workstation.
Sewerin F, Rigopoulos S, 2017, An LES-PBE-PDF approach for modeling particle formation in turbulent reacting flows, Physics of Fluids, Vol: 29, ISSN: 1070-6631
Many chemical and environmental processes involve the formation of a polydispersed particulate phase in a turbulent carrier flow. Frequently, the immersed particles are characterized by an intrinsic property such as the particle size, and the distribution of this property across a sample population is taken as an indicator for the quality of the particulate product or its environmental impact. In the present article, we propose a comprehensive model and an efficient numerical solution scheme for predicting the evolution of the property distribution associated with a polydispersed particulate phase forming in a turbulent reacting flow. Here, the particulate phase is described in terms of the particle number density whose evolution in both physical and particle property space is governed by the population balance equation (PBE). Based on the concept of large eddy simulation (LES), we augment the existing LES-transported probability density function (PDF) approach for fluid phase scalars by the particle number density and obtain a modeled evolution equation for the filtered PDF associated with the instantaneous fluid composition and particle property distribution. This LES-PBE-PDF approach allows us to predict the LES-filtered fluid composition and particle property distribution at each spatial location and point in time without any restriction on the chemical or particle formation kinetics. In view of a numerical solution, we apply the method of Eulerian stochastic fields, invoking an explicit adaptive grid technique in order to discretize the stochastic field equation for the number density in particle property space. In this way, sharp moving features of the particle property distribution can be accurately resolved at a significantly reduced computational cost. As a test case, we consider the condensation of an aerosol in a developed turbulent mixing layer. Our investigation not only demonstrates the predictive capabilities of the LES-PBE-PDF model but also indicate
Koniavitis P, Rigopoulos S, Jones WP, 2017, A methodology for derivation of RCCE-reduced mechanisms via CSP, Combustion and Flame, Vol: 183, Pages: 126-143, ISSN: 0010-2180
The development of reduced chemical mechanisms in a systematic way has emerged as a potential solution to the problem of incorporating the increasingly large chemical mechanisms into turbulent combustion CFD codes. In this work, a methodology is proposed for developing reduced mechanisms with Rate-Controlled Constrained Equilibrium (RCCE) via a Computational Singular Perturbation (CSP) analysis of counterflow non-premixed flamelets. An ordering of species for variable strain rates is derived by integrating over mixture fraction space a modified CSP pointer that depends on the timescale and mass fraction of each chemical species. Subsequently, a global set of kinetically controlled species is identified from weighting the local ordering for each strain rate. RCCE simulations with the derived reduced mechanisms for methane with 16 species and for propane with 27 species are compared with the integration of the detailed mechanisms GRI 1.2 and USC-Mech-II respectively. The applicability of the methodology is demonstrated in non-premixed flames for several strain rates, in non-premixed flames ignited with a pilot in order to test the dynamics and ignition of the reduced schemes, in premixed flames for different equivalence ratios and subsequently in perfectly stirred reactors for ignition delay times for varying temperature, pressure and equivalence ratio. Overall very good agreement is obtained, indicating that the methodology can produce reliable mechanisms for different fuels and for a wide range of conditions, including dynamical behaviour and conditions different from those employed for the derivation of the mechanism.
Sewerin F, Rigopoulos S, 2017, An explicit adaptive grid approach for the numerical solution of the population balance equation, Chemical Engineering Science, Vol: 168, Pages: 250-270, ISSN: 0009-2509
Many engineering applications, such as the formation of soot in hydrocarbon combustion or the precipitation of nanoparticles from aqueous solutions, encompass a polydispersed particulate phase that is immersed in a reacting carrier flow. From a Eulerian perspective, the evolution of the particulate phase both in physical and in particle property space can be described by the population balance equation (PBE). In this article, we present an explicit solution-adaptive numerical scheme for discretizing the spatially inhomogeneous and unsteady PBE along a one-dimensional particle property space. This scheme is based on a space and time dependent coordinate transformation which redistributes resolution in particle property space according to the shapes of recent solutions for the particle property distribution. In particular, the coordinate transformation is marched in time explicitly. In comparison to many existing moving or dynamic adaptive grid approaches, this has the advantage that the semi-discrete PBE does not need to be solved in conjunction with an additional system governing the movement of nodes in particle property space.By design, our adaptive grid technique is able to accurately capture sharp features such as peaks or near-discontinuities, while maintaining the semi-discrete system size and adhering to a uniform fixed grid discretization in transformed particle property space. This is particularly advantageous if the PBE is combined with a spatially and temporally fully resolved flow model and a standard Eulerian solution scheme is applied in physical space. In order to accommodate localized source terms and to control the grid stretching, we develop a robust scheme for modifying the coordinate transformation such that constraints on the resolution in physical particle property space are obeyed.As an example, we consider the precipitation of BaSO4 particles from an aqueous solution in a plug flow reactor. Our findings demonstrate that for a given accuracy o
Garcia Gonzalez CE, Sewerin F, Liu A, et al., 2017, Predicting and measuring soot formation and particle size distributions in a laminar diffusion flame, European Combustion Meeting 2017, Publisher: The Combustion Institute
We present the results from a joint experimental and modelling investigation of a laminar diffusion flame on a Santoroburner. The experimental techniques include laser diagnostic measurements and extractive thermophoretic sampling.In order to predict the spatial evolution of the primary soot particle size distribution throughout the flame, we employa detailed population balance model. From the model predictions, “modelled” laser diagnostic signals are obtainedwhich we directly compare with the experimental laser diagnostic images. This allows us to assess the validity ofthe model with reduced uncertainty by reducing the set of assumptions commonly made when recovering physicalmagnitudes from experimental signals.
Akridis P, Rigopoulos S, 2016, Modelling of soot formation in laminar diffusion flames using a comprehensive CFD-PBE model with detailed gas-phase chemistry, Combustion Theory and Modelling, Vol: 21, Pages: 35-48, ISSN: 1741-3559
A discretised population balance equation (PBE) is coupled with an in-house computational fluid dynamics (CFD) code in order to model soot formation in laminar diffusion flames. The unsteady Navier–Stokes, species and enthalpy transport equations and the spatially-distributed discretised PBE for the soot particles are solved in a coupled manner, together with comprehensive gas-phase chemistry and an optically thin radiation model, thus yielding the complete particle size distribution of the soot particles. Nucleation, surface growth and oxidation are incorporated into the PBE using an acetylene-based soot model. The potential of the proposed methodology is investigated by comparing with experimental results from the Santoro jet burner [Santoro, Semerjian and Dobbins, Soot particle measurements in diffusion flames, Combustion and Flame, Vol. 51 (1983), pp. 203–218; Santoro, Yeh, Horvath and Semerjian, The transport and growth of soot particles in laminar diffusion flames, Combustion Science and Technology, Vol. 53 (1987), pp. 89–115] for three laminar axisymmetric non-premixed ethylene flames: a non-smoking, an incipient smoking and a smoking flame. Overall, good agreement is observed between the numerical and the experimental results.
Elbahloul S, Rigopoulos S, 2015, Rate-Controlled Constrained Equilibrium (RCCE) simulations of turbulent partially premixed flames (Sandia D/E/F) and comparison with detailed chemistry, Combustion and Flame, Vol: 162, Pages: 2256-2271, ISSN: 1556-2921
This paper investigates the potential of the RCCE mechanism reduction approach for modelling turbulent flames within the framework of transported PDF methods. For this purpose, PDF simulations are performed with an RCCE-reduced mechanism via direct integration of the RCCE ODEs, without any tabulation, and comparison is made with both the experimental results and those from a PDF simulation with direct integration of the detailed mechanism. The flames simulated are the Sandia flames D/E/F and the simulations are carried out with a RANS approach and a Lagrangian particle method for solving the transported joint-scalar PDF equation. The detailed mechanism is the well known GRI 3.0 CH4 combustion mechanism. The turbulence closure employed is the k–ε model, while the micromixing closure in the PDF transport equation is the Interaction with the Mean (IEM) model. The RCCE-reduced mechanism incorporates 18 constraints, selected from the original 53 species based on laminar flamelet simulations. Excellent agreement was observed between the RCCE simulations and direct integration, indicating that the reduced mechanism can reproduce very well the features of the full mechanism. Agreement with experimental results is also very good, given the turbulence and mixing models employed.
Sewerin F, Rigopoulos S, 2015, A methodology for the integration of stiff chemical kinetics on GPUs, COMBUSTION AND FLAME, Vol: 162, Pages: 1375-1394, ISSN: 0010-2180
Akridis P, Rigopoulos S, 2015, Modelling of soot formation in a laminar coflow non-premixed flame with a detailed CFD-Population Balance model, 7th World Congress on Particle Technology (WCPT), Publisher: ELSEVIER SCIENCE BV, Pages: 1274-1283, ISSN: 1877-7058
Sewerin F, Rigopoulos SR, 2014, Integration of stiff chemical kinetics on a CPU-GPU pair - Application to a turbulent, non-premixed flame, Ninth Mediterranean Combustion Symposium
Chatzopoulos AK, Rigopoulos S, 2013, A chemistry tabulation approach via Rate-Controlled Constrained Equilibrium (RCCE) and Artificial Neural Networks (ANNs), with application to turbulent non-premixed CH4/H-2/N-2 flames, PROCEEDINGS OF THE COMBUSTION INSTITUTE, Vol: 34, Pages: 1465-1473, ISSN: 1540-7489
Navarro-Martinez S, Rigopoulos S, 2011, Large Eddy Simulation of a Turbulent Lifted Flame using Conditional Moment Closure and Rate-Controlled Constrained Equilibrium, FLOW TURBULENCE AND COMBUSTION, Vol: 87, Pages: 407-423, ISSN: 1386-6184
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