Conditional Source-term Estimation (CSE) is a closure technique for modelling turbulent combustion phenomena. CSE uses the Conditional Moment Closure (CMC) hypothesis for closing chemical source terms: conditionally averaged chemical source terms are closed by conditional averaged scalars, which are obtained by inverting an integral equation, instead of solving transport equations (as in CMC). Since CSE has been successfully applied to both premixed and non-premixed configurations, it represents an attractive method for dealing with the more general and complex case of partially premixed combustion. The objectives of the present study are to (i) consolidate the premixed formulation of CSE through numerical simulations of a turbulent bluff body premixed flame; (ii) formulate, implement and test the Doubly conditional CSE (DCSE) in the context of partially premixed combustion; (iii) compare the DCSE predictions with well documented turbulent partially premixed flames. The canonical example of partially premixed flames is represented by turbulent lifted flames. A series of lifted turbulent jet flames is investigated in RANS by using DCSE. The DCSE calculations are successful in predicting the lift-off heights at three different conditions and reproducing many aspects of the flame structure in agreement with the experimental observations. The current results show that important aspects of the stabilization mechanism can be reproduced by the DCSE combustion model. The applicability of DCSE is further evaluated by applying this approach to a series of turbulent V-shaped flames for which experimental data is available. Premixed and stratified conditions are investigated. Overall, the agreement between numerical results and experimental findings is good, demonstrating the capability of DCSE to deal with partially premixed combustion. Future work includes implementation of CSE in LES and investigation of different fuels such as propane and biofuels.

Conditional Source-term Estimation (CSE) is a turbulent combustion model which uses conditional averages to provide closure for the mean chemical source term and is based on the same ideas as the Conditional Moment Closure (CMC) approach. CSE applies first order closure for the conditional averages which are obtained by inverting an integral equation and has been used to simulate a range of premixed, non-premixed and partially premixed flames. In the present study, CSE is applied to investigate a high efficient, low emission combustion process called Moderate and Intense Low Oxygen Dilution (MILD) combustion. This work represents the first application of CSE for MILD combustion, the first application of a multi-stream CSE formulation and the first doubly-conditioned CSE formulation applied in the Large Eddy Simulation (LES) framework. The objectives of the present study are to i) investigate the CSE combustion model for turbulent non-premixed combustion, ii) develop a CSE formulation for MILD combustion problems, iii) implement CSE for MILD combustion problems in Reynolds-Averaged Navier-Stokes (RANS) and LES and iv) compare the CSE predictions to experimental and previous numerical results for well documented MILD combustion flames. Numerical simulations of a confined non-premixed methane flame are completed using the CSE non-premixed approach. This study investigates the sensitivity to various CSE model parameters and shows CSE is able to accurately predict non-premixed methane combustion. A detailed study of the inversion problem encountered in CSE is also investigated using the Bayesian framework. The origin of the perturbation seen in the unconditional mass fraction in CSE and the impact of a smoothing prior on the recovered solution and credible intervals are discussed. Different regularization methods are studied and it is shown that both zeroth and first order Tikhonov are promising regularization methods for CSE. In the present work, the non-premixed CSE formulation is extended to include the impact of radiation of the conditional reaction rates and is applied to a semi-industrial furnace. This study demonstrates that a RANS-CSE simulation is able to accurately predict the temperature and species concentration, including NOx, for large scale realistic furnace configurations. Finally, a multi-stream CSE formulation is developed and applied to the DJHC burners in the RANS and LES framework. This new CSE formulation is able to predict the temperature and velocity profiles in very good agreement with the experimental data. Further, the LES multi-stream CSE formulation is able to predict the time-dependent nature of the DHJC burners.

Based on the simulations developed in research groups over the past years, Introduction to Quasi-dimensional Simulation of Spark Ignition Engines provides a compilation of the main ingredients necessary to build up a quasi-dimensional computer simulation scheme. Quasi-dimensional computer simulation of spark ignition engines is a powerful but affordable tool which obtains realistic estimations of a wide variety of variables for a simulated engine keeping insight the basic physical and chemical processes involved in the real evolution of an automotive engine. With low computational costs, it can optimize the design and operation of spark ignition engines as well as it allows to analyze cycle-to-cycle fluctuations. Including details about the structure of a complete simulation scheme, information about what kind of information can be obtained, and comparisons of the simulation results with experiments, Introduction to Quasi-dimensional Simulation of Spark Ignition Engines offers a thorough guide of this technique. Advanced undergraduates and postgraduates as well as researchers in government and industry in all areas related to applied physics and mechanical and automotive engineering can apply these tools to simulate cyclic variability, potentially leading to new design and control alternatives for lowering emissions and expanding the actual operation limits of spark ignition engines

The book provides a comprehensive overview of combustion models used in different types of spark ignition engines. In the first generation of spark ignition (SI) engines, the turbulence is created by the shear flow passing through the intake valves, and significantly decays during the intake and compression strokes. The residual turbulence enhances the laminar flame velocity, which is characteristic of the fuel and increases the relative effectiveness of the engine. In this simple two-zone model, the turbulence is estimated empirically; the spherical flame propagation model considers ignition delay, thermodynamics, heat transfer and chemical equilibrium, to obtain the performance and emissions of an SI engine. The model is used extensively by designers and research engineers to handle the fuel-air mixture prepared in the inlet and different geometries of open combustion chambers. The empiricism of the combustion model was progressively dismantled over the years. New 3D models for ignition considering the flow near a spark plug and flame propagation in the bulk gases were developed by incorporating solutions to Reynolds-averaged Navier-Stokes (RANS) equations for the turbulent flow with chemical reactions in the intense computational fluid dynamics. The models became far less empirical and enabled treating new generation direct-injection spark-ignition (DISI) gasoline and gas engines. The more complex layout of DISI engines with passive or active prechamber is successfully handled by them. This book presents details of models of SI engine combustion progressively increasing in complexity, making them accessible to designers, researchers, and even mechanical engineers who are curious to explore the field. This book is a valuable resource for anyone interested in spark ignition combustion.