Machine Learning and Its Application to Reacting Flows

This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows. These two fields, ML and turbulent combustion, have large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the world’s total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML techniques to improve combustion sciences and technologies so that efficient and “greener” combustion systems that are friendlier to the environment can be designed. The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation

Population balance modelling of soot formation in laminar and turbulent flames

The reduction of soot emissions in combustion processes is a primary concern of combustion engineers due to the severe health impact of soot, and the prediction of the soot particle size distribution (PSD) has become important. The evolution of the PSD can be predicted by solving the population balance equation (PBE), and several approaches have been proposed for introducing soot morphology in the PBE. Furthermore, the PBE must be coupled with fluid dynamics, species transport and chemical kinetics in order to predict soot properties in laminar and turbulent flames. Finally, accurate and computationally efficient methods must be employed for solving the CFD-PBE approach. In the first part of this thesis, the recently developed conservative finite volume sectional method for the solution of the population balance equation (PBE) is extended to a two-PBE 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. The validation of the method is conducted by reproducing 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 application of the Santoro laminar non-premixed co-flow sooting flame. By using a comprehensive soot kinetic model, the deficiencies of the one-PBE approach are analysed, and the two-PBE approach is shown to provide a significant improvement in the description of soot morphology using a properly adjusted particle fusing rate. At present, the model parameters for the fusing of soot primary particles are based on sintering models from silica and titania nanoparticles due to the lack of experimental data for soot. Therefore, a comprehensive sensitivity analysis of the model parameters is conducted. The results show the predictive potential of both the one-PBE and two-PBE approaches. With the presently available experimental measurements, the results suggest that one-PBE method is a reasonable choice for the applications associated with turbulent flame. Subsequently in the second part, the one-PBE method is incorporated into the LES-PBE-PDF approach developed within the group for modelling soot formation in turbulent flames. For the first time, the LES-PBE-PDF approach provides a comprehensive physicochemical model accounting for nucleation, surface growth, oxidation, condensation, coalescence and aggregation. The interaction between chemistry, turbulence and soot particles are accounted for by resolving an evolution equation for the LES-filtered one-point, one-time, joint scalar-number density probability density function (PDF). The Eulerian stochastic field method is used for the solution of the joint-scalar-number density PDF. By using the same kinetics and model parameters as tested in the laminar flame case, the LES-PBE-PDF approach is applied to model soot formation in the Sandia turbulent non-premixed sooting flame. The predicted thermochemical conditions and soot volume fraction are in reasonably good agreement with experimental measurements. The analysis and findings demonstrate good predictive capability and computational feasibility of the complete LES-PBE-PDF approach. In summary, this thesis presents a systematic study for soot formation in the laminar and turbulent flames. In particular, the key adjustable model parameters, surface reactivity $\alpha$ and cut-off point $d_c$, are calibrated in the laminar flame and employed in the turbulent flame. Yet, some limitations should be pointed out. For soot study, the current methodology does not capture the composition of soot during its formation and growth, thus the surface reactivity model applied is rather primitive and needs some adjustments, and the work assumes a constant fractal dimension, whose impact should be further investigated. For turbulent sooting flame, future investigation regarding the micromixing model is warranted.Open Acces

Machine Learning and Its Application to Reacting Flows

This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows. These two fields, ML and turbulent combustion, have large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the world’s total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML techniques to improve combustion sciences and technologies so that efficient and “greener” combustion systems that are friendlier to the environment can be designed. The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation

Improving aircraft performance using machine learning: a review

This review covers the new developments in machine learning (ML) that are impacting the multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics (experimental and numerical), aerodynamics, acoustics, combustion and structural health monitoring. We review the state of the art, gathering the advantages and challenges of ML methods across different aerospace disciplines and provide our view on future opportunities. The basic concepts and the most relevant strategies for ML are presented together with the most relevant applications in aerospace engineering, revealing that ML is improving aircraft performance and that these techniques will have a large impact in the near future

Finite-Rate Chemistry Effects in Turbulent Premixed Combustion

In recent times significant public attention has been drawn to the topic of combustion. This has been due to the fact that combustion is the underlying mechanism of several key challenges to modern society: climate change, energy security (finite reserves of fossil fuels) and air pollution. The further development of combustion science is undoubtedly necessary to find improved solutions to manage these combustion science related challenges in the near and long term future. Combustion is essentially an exothermic process, this exothermicity or heat release essentially occurs at small scales, by small scales it meant these scales are small relative to the fluid length scales, for example heat release layer thicknesses in flames are typically much less than the fluid integral length scales. As heat release occurs at small scales this means that in turbulent combustion the small scales of the turbulence (which can be of the order of the heat release layer thickness) can possibly interact and influence the heat release and thus chemistry of the flame reaction zone. Premixed combustion is a combustion mode where the fuel and oxidiser are completely premixed prior to the flame reaction zone, this mode of combustion has been shown to be a promising method to maximise combustion efficiency and minimise pollutant formation. The continued and further application of premixed combustion to practical applications is limited by the current understanding of turbulent premixed combustion, these limitations in understanding are linked to the specific flame phenomena that can significantly influence premixed combustion in a combustion device, examples of such phenomena are: flame flashback, flame extinction and fuel consumption rate – all phenomena that are influenced by the interaction of the small scales of turbulence and chemistry. It is the study and investigation of the interaction of turbulence and chemistry at the small scales (termed finite-rate chemistry) in turbulent premixed flames that is the aim of this thesis which is titled “Finite-rate chemistry effects in turbulent premixed combustion”. Two very closely related experimental burner geometries have been developed in this thesis: the Piloted Premixed Jet Burner (PPJB) and the Premixed Jet Burner (PJB). Both feature an axisymmetric geometry and exhibit a parabolic like flow field. The PPJB and PJB feature a small 4mm diameter central jet from which a high velocity lean-premixed methane-air mixture issues. Surrounding the central jet in the PPJB is a 23.5mm diameter pilot of stoichiometric methane-air products, the major difference between the PPJB and the PJB is that the PJB does not feature a stoichiometric pilot. The pilot in the PPJB provides a rich source of combustion intermediates and enthalpy which promotes initial ignition of the central jet mixture. Surrounding both the central jet and pilot is a large diameter hot coflow of combustion products. It is possible to set the temperature of the hot coflow to the adiabatic flame temperature of the central jet mixture to simulate straining and mixing against and with combustion products without introducing complexities such as quenching and dilution from cold air. By parametrically increasing the central jet velocity in the PPJB it is possible to show that there is a transition from a thin conical flame brush to a flame that exhibits extinction and re-ignition effects. The flames that exhibit extinction and re-ignition effects have a luminous region near the jet exit termed the initial ignition region. This is followed by a region of reduced luminosity further downstream termed the extinction region. Further downstream the flame luminosity increases this region is termed the re-ignition region. For the flames that exhibit extinction and re-ignition it is proposed that intense turbulent mixing and high scalar dissipation rates drives the initial extinction process after the influence of the pilot has ceased (x/D>10). Re-ignition is proposed to occur downstream where turbulent mixing and scalar dissipation rates have decreased allowing robust combustion to continue. As the PJB does not feature a pilot, the flame stabilisation structure is quite different to the PPJB. The flame structure in the PJB is essentially a lifted purely premixed flame, which is an experimental configuration that is also quite unique. A suite of laser diagnostic measurements has been parametrically applied to flames in the PPJB and PJB. Laser Doppler Velocimetry (LDV) has been utilised to measure the mean and fluctuating radial and axial components of velocity at a point, with relevant time and length scale information being extracted from these measurements. One of the most interesting results from the LDV measurements is that in the PPJB the pilot delays the generation of high turbulence intensities, for flames that exhibit extinction the rapid increase of turbulence intensity after the pilot corresponds to the start of the extinction region. Using the LDV derived turbulence characteristics and laminar flame properties and plotting these flames on a traditional turbulent regime diagram indicates that all of the flames examined should fall in the so call distributed reaction regime. Planar imaging experiments have been conducted for flames using the PPJB and PJB to investigate the spatial structure of the temperature and selected minor species fields. Results from two different simultaneous 2D Rayleigh and OH PLIF experiments and a simultaneous 2D Rayleigh, OH PLIF and CH2O PLIF experiment are reported. For all of the flames examined in the PPJB and PJB a general trend of decreasing conditional mean temperature gradient with increasing turbulence intensity is observed. This indicates that a trend of so called flame front thickening with increased turbulence levels occurs for the flames examined. It is proposed that the mechanism for this flame front thickening is due to eddies penetrating and embedding in the instantaneous flame front. In the extinction region it is found that the OH concentration is significantly reduced compared to the initial ignition region. In the re-ignition region it is found that the OH level increases again indicating that an increase in the local reaction rate is occurring. In laminar premixed flames CH2O occurs in a thin layer in the reaction zone, it is found for all of the flames examined that the CH2O layer is significantly thicker than the laminar flame. For the high velocity flames beyond x/D=15, CH2O no longer exist in a distinct layer but rather in a near uniform field for the intermediate temperature regions. Examination of the product of CH2O and OH reveals that the heat release in the initial ignition region is high and rapidly decreases in the extinction region, an increase in the heat release further downstream is observed corresponding to the re-ignition region. This finding corresponds well with the initial hypothesis of an extinction region followed by a re-ignition region that was based on the mean chemiluminescence images. Detailed simultaneous measurement of major and minor species has been conducted using the line Raman-Rayleigh-LIF technique with CO LIF and crossed plane-OH PLIF at Sandia National Laboratories. By measuring all major species it is also possible to define a mixture fraction for all three streams of the PPJB. Using these three mixture fractions it was found that the influence of the pilot in the PPJB decays very rapidly for all but the lowest velocity flames. It was also found that for the high velocity flames exhibiting extinction, a significant proportion of the coflow fluid is entrained into the central jet combustion process at both the extinction region and re-ignition regions. The product of CO and OH conditional on temperature is shown to be proportion to the net production rate of CO2 for certain temperature ranges. By examining the product of CO and OH the hypothesis of an initial ignition region followed by an extinction region then a re-ignition region for certain PPJB flames has been further validated complementing the [CH2O][OH] imaging results. Numerical modelling results using the transported composition probability density function (TPDF) method coupled to a conventional Reynolds averaged Naiver Stokes (RANS) solver are shown in this thesis to successfully predict the occurrence of finite-rate chemistry effects for the PM1 PPJB flame series. To calculate the scalar variance and the degree of finite-rate chemistry effects correctly, it is found that a value of the mixing constant ( ) of approximately 8.0 is required. This value of is much larger than the standard excepted range of 1.5-2.3 for that has been established for non-premixed combustion. By examining the results of the RANS turbulence model in a non-reacting variable density jet, it is shown that the primary limitation of the predictive capability of the TPDF-RANS method is the RANS turbulence model when applied to variable density flows

Numerical simulation of combustion instability: flame thickening and boundary conditions

Combustion-driven instabilities are a significant barrier for progress for many avenues of immense practical relevance in engineering devices, such as next generation gas turbines geared towards minimising pollutant emissions being susceptible to thermoacoustic instabilities. Numerical simulations of such reactive systems must try to balance a dynamic interplay between cost, complexity, and retention of system physics. As such, new computational tools of relevance to Large Eddy Simulation (LES) of compressible, reactive flows are proposed and evaluated. High order flow solvers are susceptible to spurious noise generation at boundaries which can be very detrimental for combustion simulations. Therefore Navier-Stokes Characteristic Boundary conditions are also reviewed and an extension to axisymmetric configurations proposed. Limitations and lingering open questions in the field are highlighted. A modified Artificially Thickened Flame (ATF) model coupled with a novel dynamic formulation is shown to preserve flame-turbulence interaction across a wide range of canonical configurations. The approach does not require efficiency functions which can be difficult to determine, impact accuracy and have limited regimes of validity. The method is supplemented with novel reverse transforms and scaling laws for relevant post-processing from the thickened to unthickened state. This is implemented into a wider Adaptive Mesh Refinement (AMR) context to deliver a unified LES-AMR-ATF framework. The model is validated in a range of test case showing noticeable improvements over conventional LES alternatives. The proposed modifications allow meaningful inferences about flame structure that conventionally may have been restricted to the domain of Direct Numerical Simulation. This allows studying the changes in small-scale flow and scalar topologies during flame-flame interaction. The approach is applied to a dual flame burner setup, where simulations show inclusion of a neighbouring burner increases compressive flow topologies as compared to a lone flame. This may lead to favouring convex scalar structures that are potentially responsible for the increase in counter-normal flame-flame interactions observed in experiments.Open Acces