Academic literature on the topic 'Detailed chemistry solver'
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Journal articles on the topic "Detailed chemistry solver"
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Liang, Long, Song-Charng Kong, Chulhwa Jung, and Rolf D. Reitz. "Development of a Semi-implicit Solver for Detailed Chemistry in Internal Combustion Engine Simulations." Journal of Engineering for Gas Turbines and Power 129, no. 1 (February 28, 2006): 271–78. http://dx.doi.org/10.1115/1.2204979.
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An efficient semi-implicit numerical method is developed for solving the detailed chemical kinetic source terms in internal combustion (IC) engine simulations. The detailed chemistry system forms a group of coupled stiff ordinary differential equations (ODEs), which presents a very stringent time-step limitation when solved by standard explicit methods, and is computationally expensive when solved by iterative implicit methods. The present numerical solver uses a stiffly stable noniterative semi-implicit method. The formulation of numerical integration exploits the physical requirement that the species density and specific internal energy in the computational cells must be non-negative, so that the Lipschitz time-step constraint is not present and the computation time step can be orders of magnitude larger than that possible in standard explicit methods. The solver exploits the characteristics of the stiffness of the ODEs by using a sequential sort algorithm that ranks an approximation to the dominant eigenvalues of the system to achieve maximum accuracy. Subcycling within the chemistry solver routine is applied for each computational cell in engine simulations, where the subcycle time step is dynamically determined by monitoring the rate of change of concentration of key species, which have short characteristic time scales and are also important to the chemical heat release. The chemistry solver is applied in the KIVA-3V code to diesel engine simulations. Results are compared to those using the CHEMKIN package, which uses the VODE implicit solver. Good agreement was achieved for a wide range of engine operating conditions, and 40-70% CPU time savings were achieved by the present solver compared to the standard CHEMKIN.
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Matrisciano, Andrea, Tim Franken, Laura Catalina Gonzales Mestre, Anders Borg, and Fabian Mauss. "Development of a Computationally Efficient Tabulated Chemistry Solver for Internal Combustion Engine Optimization Using Stochastic Reactor Models." Applied Sciences 10, no. 24 (December 16, 2020): 8979. http://dx.doi.org/10.3390/app10248979.
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The use of chemical kinetic mechanisms in computer aided engineering tools for internal combustion engine simulations is of high importance for studying and predicting pollutant formation of conventional and alternative fuels. However, usage of complex reaction schemes is accompanied by high computational cost in 0-D, 1-D and 3-D computational fluid dynamics frameworks. The present work aims to address this challenge and allow broader deployment of detailed chemistry-based simulations, such as in multi-objective engine optimization campaigns. A fast-running tabulated chemistry solver coupled to a 0-D probability density function-based approach for the modelling of compression and spark ignition engine combustion is proposed. A stochastic reactor engine model has been extended with a progress variable-based framework, allowing the use of pre-calculated auto-ignition tables instead of solving the chemical reactions on-the-fly. As a first validation step, the tabulated chemistry-based solver is assessed against the online chemistry solver under constant pressure reactor conditions. Secondly, performance and accuracy targets of the progress variable-based solver are verified using stochastic reactor models under compression and spark ignition engine conditions. Detailed multicomponent mechanisms comprising up to 475 species are employed in both the tabulated and online chemistry simulation campaigns. The proposed progress variable-based solver proved to be in good agreement with the detailed online chemistry one in terms of combustion performance as well as engine-out emission predictions (CO, CO2, NO and unburned hydrocarbons). Concerning computational performances, the newly proposed solver delivers remarkable speed-ups (up to four orders of magnitude) when compared to the online chemistry simulations. In turn, the new solver allows the stochastic reactor model to be computationally competitive with much lower order modeling approaches (i.e., Vibe-based models). It also makes the stochastic reactor model a feasible computer aided engineering framework of choice for multi-objective engine optimization campaigns.
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Deepu, M., M. P. Dhrishit, and S. Shyji. "Numerical simulation of high speed reacting shear layers using AUSM+- up scheme-based unstructured finite volume method solver." International Journal of Modeling, Simulation, and Scientific Computing 08, no. 03 (September 2017): 1750020. http://dx.doi.org/10.1142/s1793962317500209.
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Development of an Advection Upstream Splitting Method (AUSM[Formula: see text]-up) scheme-based Unstructured Finite Volume (UFVM) solver for the simulation of two-dimensional axisymmetric/planar high speed compressible turbulent reacting shear layers is presented. The inviscid numerical flux is evaluated using AUSM[Formula: see text]-up upwind scheme. An eight-step hydrogen–oxygen finite rate chemistry model is used to model the development of chemical species in a supersonic reacting flow field. The chemical species terms are alone solved implicitly in this explicit flow solver by rescaling the equation in time. The turbulence modeling has been done using RNG-based [Formula: see text]–[Formula: see text] model. Three-stage Runge–Kutta method has been used for explicit time integration. The nonreacting two-dimensional Cartesian version of the same solver has been successfully validated against experimental and numerical results reported for the wall static pressure data in sonic slot injection to supersonic stream. Detailed validation studies for reacting flow solver has been done using experimental results reported for a coaxial supersonic combustor, in which species profile at various axial locations has been compared. Present numerical solver is useful in simulating combustors of high speed air-breathing propulsion devices.
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Zhou, Dezhi, Hongyuan Zhang, and Suo Yang. "A Robust Reacting Flow Solver with Computational Diagnostics Based on OpenFOAM and Cantera." Aerospace 9, no. 2 (February 14, 2022): 102. http://dx.doi.org/10.3390/aerospace9020102.
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In this study, we developed a new reacting flow solver based on OpenFOAM (OF) and Cantera, with the capabilities of (i) dealing with detailed species transport and chemistry, (ii) integration using a well-balanced splitting scheme, and (iii) two advanced computational diagnostic methods. First of all, a flaw of the original OF chemistry model to deal with pressure-dependent reactions is fixed. This solver then couples Cantera with OF so that the robust chemistry reader, chemical reaction rate calculations, ordinary differential equations (ODEs) solver, and species transport properties handled by Cantera can be accessed by OF. In this way, two transport models (mixture-averaged and constant Lewis number models) are implemented in the coupled solver. Finally, both the Strang splitting scheme and a well-balanced splitting scheme are implemented in this solver. The newly added features are then assessed and validated via a series of auto-ignition tests, a perfectly stirred reactor, a 1D unstretched laminar premixed flame, a 2D counter-flow laminar diffusion flame, and a 3D turbulent partially premixed flame (Sandia Flame D). It is shown that the well-balanced property is crucial for splitting schemes to accurately capture the ignition and extinction events. To facilitate the understanding on combustion modes and complex chemistry in large scale simulations, two computational diagnostic methods (conservative chemical explosive mode analysis, CCEMA, and global pathway analysis, GPA) are subsequently implemented in the current framework and used to study Sandia Flame D for the first time. It is shown that these two diagnostic methods can extract the flame structure, combustion modes, and controlling global reaction pathways from the simulation data.
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Myriokefalitakis, Stelios, Nikos Daskalakis, Angelos Gkouvousis, Andreas Hilboll, Twan van Noije, Jason E. Williams, Philippe Le Sager, et al. "Description and evaluation of a detailed gas-phase chemistry scheme in the TM5-MP global chemistry transport model (r112)." Geoscientific Model Development 13, no. 11 (November 12, 2020): 5507–48. http://dx.doi.org/10.5194/gmd-13-5507-2020.
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Abstract. This work documents and evaluates the tropospheric gas-phase chemical mechanism MOGUNTIA in the three-dimensional chemistry transport model TM5-MP. Compared to the modified CB05 (mCB05) chemical mechanism previously used in the model, MOGUNTIA includes a detailed representation of the light hydrocarbons (C1–C4) and isoprene, along with a simplified chemistry representation of terpenes and aromatics. Another feature implemented in TM5-MP for this work is the use of the Rosenbrock solver in the chemistry code, which can replace the classical Euler backward integration method of the model. Global budgets of ozone (O3), carbon monoxide (CO), hydroxyl radicals (OH), nitrogen oxides (NOx), and volatile organic compounds (VOCs) are analyzed, and their mixing ratios are compared with a series of surface, aircraft, and satellite observations for the year 2006. Both mechanisms appear to be able to satisfactorily represent observed mixing ratios of important trace gases, with the MOGUNTIA chemistry configuration yielding lower biases than mCB05 compared to measurements in most of the cases. However, the two chemical mechanisms fail to reproduce the observed mixing ratios of light VOCs, indicating insufficient primary emission source strengths, oxidation that is too fast, and/or a low bias in the secondary contribution to C2–C3 organics via VOC atmospheric oxidation. Relative computational memory and time requirements of the different model configurations are also compared and discussed. Overall, the MOGUNTIA scheme simulates a large suite of oxygenated VOCs that are observed in the atmosphere at significant levels. This significantly expands the possible applications of TM5-MP.
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Bigalli, Simone, Iacopo Catalani, Francesco Balduzzi, Nicola Matteazzi, Lorenzo Agostinelli, Michele De Luca, and Giovanni Ferrara. "Numerical Investigation on the Performance of a 4-Stroke Engine with Different Passive Pre-Chamber Geometries Using a Detailed Chemistry Solver." Energies 15, no. 14 (July 7, 2022): 4968. http://dx.doi.org/10.3390/en15144968.
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Pre-chamber turbulent jet ignition represents one of the most promising techniques to improve spark ignition engines efficiency and reduce pollutant emissions. This technique consists of igniting the air-fuel mixture in the main combustion chamber by means of several hot turbulent flame jets exiting a pre-chamber. In the present study, the combustion process of a 4-stroke, gasoline SI, PFI engine equipped with a passive pre-chamber has been investigated through three-dimensional CFD (Computational Fluid Dynamics) analysis. A detailed chemistry solver with a reduced reaction mechanism was employed to investigate ignition and flame propagation phenomena. Firstly, the combustion model was validated against experimental data for the baseline engine configuration (i.e., without pre-chamber). Eventually, the validated numerical model allowed for predictive simulations of the pre-chamber-equipped engine. By varying the shape of the pre-chamber body and the size of pre-chamber orifices, different pre-chamber configurations were studied. The influence of the geometrical features on the duration of the combustion process and the pressure trends inside both the pre-chamber and main chamber was assessed and discussed. Since the use of a pre-chamber can extend the air-fuel mixture ignition limits, an additional sensitivity on the air-fuel ratio was carried out, in order to investigate engine performance at lean conditions.
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Kawka, László, Gergely Juhász, Máté Papp, Tibor Nagy, István Gy Zsély, and Tamás Turányi. "Comparison of detailed reaction mechanisms for homogeneous ammonia combustion." Zeitschrift für Physikalische Chemie 234, no. 7-9 (August 27, 2020): 1329–57. http://dx.doi.org/10.1515/zpch-2020-1649.
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AbstractAmmonia is a potential fuel for the storage of thermal energy. Experimental data were collected for homogeneous ammonia combustion: ignition delay times measured in shock tubes (247 data points in 28 datasets from four publications) and species concentration measurements from flow reactors (194/22/4). The measurements cover wide ranges of temperature T, pressure p, equivalence ratio φ and dilution. The experimental data were encoded in ReSpecTh Kinetics Data Format version 2.2 XML files. The standard deviations of the experimental datasets used were determined based on the experimental errors reported in the publications and also on error estimations obtained using program MinimalSplineFit. Simulations were carried out with eight recently published mechanisms at the conditions of these experiments using the Optima++ framework code, and the FlameMaster and OpenSmoke++ solver packages. The performance of the mechanisms was compared using a sum-of-square error function to quantify the agreement between the simulations and the experimental data. Ignition delay times were well reproduced by five mechanisms, the best ones were Glarborg-2018 and Shrestha-2018. None of the mechanisms were able to reproduce well the profiles of NO, N2O and NH3 concentrations measured in flow reactors.
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Arrighetti, Cinzio, Stefano Cordiner, and Vincenzo Mulone. "Heat and Mass Transfer Evaluation in the Channels of an Automotive Catalytic Converter by Detailed Fluid-Dynamic and Chemical Simulation." Journal of Heat Transfer 129, no. 4 (July 12, 2006): 536–47. http://dx.doi.org/10.1115/1.2709657.
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The role of numerical simulation to drive the catalytic converter development becomes more important as more efficient spark ignition engines after-treatment devices are required. The use of simplified approaches using rather simple correlations for heat and mass transfer in a channel has been widely used to obtain computational simplicity and sufficient accuracy. However, these approaches always require specific experimental tuning so reducing their predictive capabilities. The feasibility of a computational fluid dynamics three-dimensional (3D) model coupled to a surface chemistry solver is evaluated in this paper as a tool to increase model predictivity then allowing the detailed study of the performance of a catalytic converter under widely varying operating conditions. The model is based on FLUENT to solve the steady-state 3D transport of mass, momentum and energy for a gas mixture channel flow, and it is coupled to a powerful surface chemistry tool (CANTERA). Checked with respect to literature available experimental data, this approach has proved its predictive capabilities not requiring an ad hoc tuning of the parameter set. Heat and mass transfer characteristics of channels with different section shapes (sinusoidal, hexagonal, and squared) have then been analyzed. Results mainly indicate that a significant influence of operating temperature can be observed on Nusselt and Sherwood profiles and that traditional correlations, as well as the use of heat/mass transfer analogy, may give remarkable errors (up to 30% along one-third of the whole channel during light-off conditions) in the evaluation of the converter performance. The proposed approach represents an appropriate tool to generate local heat and mass transfer correlations for less accurate, but more comprehensive, 1D models, either directly during the calculation or off-line, to build a proper data base.
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Pala, M. G., and G. Iannaccone. "A three-dimensional solver of the Schrödinger equation in momentum space for the detailed simulation of nanostructures." Nanotechnology 13, no. 3 (May 24, 2002): 369–72. http://dx.doi.org/10.1088/0957-4484/13/3/325.
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Mallet, V., and B. Sportisse. "3-D chemistry-transport model Polair: numerical issues, validation and automatic-differentiation strategy." Atmospheric Chemistry and Physics Discussions 4, no. 2 (March 8, 2004): 1371–92. http://dx.doi.org/10.5194/acpd-4-1371-2004.
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Abstract. We briefly present in this short paper some issues related to the development and the validation of the three-dimensional chemistry-transport model Polair. Numerical studies have been performed in order to let Polair be an efficient and robust solver. This paper summarizes and comments choices that were made in this respect. Simulations of relevant photochemical episodes were led to assess the validity of the model. The results can be considered as a validation, which allows next studies to focus on fine modeling issues. A major feature of Polair is the availability of a tangent linear mode and an adjoint mode entirely generated by automatic differentiation. Tangent linear and adjoint modes grant the opportunity to perform detailed sensitivity analyses and data assimilation. This paper shows how inverse modeling is achieved with Polair.
Dissertations / Theses on the topic "Detailed chemistry solver"
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Meyer, Michael Peter. "The application of detailed and systematically reduced chemistry to transient laminar flames." Thesis, Imperial College London, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.248801.
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Bigalli, Simone. "CFD analysis of the combustion process in a 4-stroke engine equipped with different passive prechamber using a detailed chemistry solver." Doctoral thesis, 2021. http://hdl.handle.net/2158/1245179.
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The combustion process of a 4-stroke PFI gasoline engine equipped with a passive prechamber has been investigated through three dimensional CFD analysis. The goal was to analyse the behaviour of the flame front during the entire combustion process and to evaluate the improvements in terms of both combustion speed and ignitability of lean mixtures. The trade-off between the accuracy and complexity of the numerical approach and computational costs was assessed by adopting two different combustion models, with different detail level, for the simulation of the engine cycle: a detailed chemistry model and a flame surface density model.
Books on the topic "Detailed chemistry solver"
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GRE Chemistry Guide with Practice Book: NEW GRE Chemistry Questions and Solution, Chemistry Exam Strategy - Tips, GRE Chemistry All Problems Solved Step by Step, All Questions with Detailed Explanations. Independently Published, 2021.
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Henriksen, Niels E., and Flemming Y. Hansen. Theories of Molecular Reaction Dynamics. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805014.001.0001.
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This book deals with a central topic at the interface of chemistry and physics—the understanding of how the transformation of matter takes place at the atomic level. Building on the laws of physics, the book focuses on the theoretical framework for predicting the outcome of chemical reactions. The style is highly systematic with attention to basic concepts and clarity of presentation. Molecular reaction dynamics is about the detailed atomic-level description of chemical reactions. Based on quantum mechanics and statistical mechanics or, as an approximation, classical mechanics, the dynamics of uni- and bimolecular elementary reactions are described. The first part of the book is on gas-phase dynamics and it features a detailed presentation of reaction cross-sections and their relation to a quasi-classical as well as a quantum mechanical description of the reaction dynamics on a potential energy surface. Direct approaches to the calculation of the rate constant that bypasses the detailed state-to-state reaction cross-sections are presented, including transition-state theory, which plays an important role in practice. The second part gives a comprehensive discussion of basic theories of reaction dynamics in condensed phases, including Kramers and Grote–Hynes theory for dynamical solvent effects. Examples and end-of-chapter problems are included in order to illustrate the theory and its connection to chemical problems. The book has ten appendices with useful details, for example, on adiabatic and non-adiabatic electron-nuclear dynamics, statistical mechanics including the Boltzmann distribution, quantum mechanics, stochastic dynamics and various coordinate transformations including normal-mode and Jacobi coordinates.
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Flarend, Alice, and Robert Hilborn. Quantum Computing: From Alice to Bob. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780192857972.001.0001.
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Quantum Computing: From Alice to Bob provides a distinctive and accessible introduction to the rapidly growing fields of quantum information science (QIS) and quantum computing (QC). The book is designed for undergraduate students and upper-level secondary school students with little or no background in physics, computer science, or mathematics beyond secondary school algebra and trigonometry. While broadly accessible, the book provides a solid conceptual and formal understanding of quantum states and entanglement—the key ingredients in quantum computing. The authors give detailed treatments of many of the classic quantum algorithms that demonstrate how and when QC has an advantage over classical computers. The book provides a solid explanation of the physics of QC and QIS and then weds that knowledge to the mathematics of QC algorithms and how those algorithms deploy the principles of quantum physics to solve the problem. This book connects the physics concepts, the computer science vocabulary, and the mathematics, providing a complete picture of how QIS and QC work. The authors give multiple representations of the concept—textual, graphical, and symbolic (state vectors, matrices, and Dirac notation)—which are the lingua franca of QIS and QC. Those multiple representations allow the readers to develop a broader and deeper understanding of the fundamental concepts and their applications. In addition, the book provides examples of recent experimental demonstrations of quantum teleportation and the applications of quantum computational chemistry. The last chapter connects to the growing commercial world of QC and QIS and provides recommendations for further study.
Book chapters on the topic "Detailed chemistry solver"
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Paxion, S., R. Baron, A. Gordner, N. Neuss, P. Bastian, D. Thévenin, and G. Wittum. "Development of a Parallel Unstructured Multigrid Solver for Laminar Flame Simulations with Detailed Chemistry and Transport." In Numerical Flow Simulation II, 181–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-540-44567-8_11.
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Hale, Robert C., Meredith E. Seeley, Ashley E. King, and Lehuan H. Yu. "Analytical Chemistry of Plastic Debris: Sampling, Methods, and Instrumentation." In Microplastic in the Environment: Pattern and Process, 17–67. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78627-4_2.
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AbstractApproaches for the collection and analysis of plastic debris in environmental matrices are rapidly evolving. Such plastics span a continuum of sizes, encompassing large (macro-), medium (micro-, typically defined as particles between 1 μm and 5 mm), and smaller (nano-) plastics. All are of environmental relevance. Particle sizes are dynamic. Large plastics may fragment over time, while smaller particles may agglomerate in the field. The diverse morphologies (fragment, fiber, sphere) and chemical compositions of microplastics further complicate their characterization. Fibers are of growing interest and present particular analytical challenges due to their narrow profiles. Compositional classes of emerging concern include tire wear, paint chips, semisynthetics (e.g., rayon), and bioplastics. Plastics commonly contain chemical additives and fillers, which may alter their toxicological potency, behavior (e.g., buoyancy), or detector response (e.g., yield fluorescence) during analysis. Field sampling methods often focus on >20 μm and even >300 μm sized particles and will thus not capture smaller microplastics (which may be most abundant and bioavailable). Analysis of a limited subgroup (selected polymer types, particle sizes, or shapes) of microplastics, while often operationally necessary, can result in an underestimation of actual sample content. These shortcomings complicate calls for toxicological studies of microplastics to be based on “environmentally relevant concentrations.” Sample matrices of interest include water (including wastewater, ice, snow), sediment (soil, dust, wastewater sludge), air, and biota. Properties of the environment, and of the particles themselves, may concentrate plastic debris in select zones (e.g., gyres, shorelines, polar ice, wastewater sludge). Sampling designs should consider such patchy distributions. Episodic releases due to weather and anthropogenic discharges should also be considered. While water grab samples and sieving are commonplace, novel techniques for microplastic isolation, such as continuous flow centrifugation, show promise. The abundance of nonplastic particulates (e.g., clay, detritus, biological material) in samples interferes with microplastic detection and characterization. Their removal is typically accomplished using a combination of gravity separation and oxidative digestion (including strong bases, peroxide, enzymes); unfortunately, aggressive treatments may damage more labile plastics. Microscope-based infrared or Raman detection is often applied to provide polymer chemistry and morphological data for individual microplastic particles. However, the sheer number of particles in many samples presents logistical hurdles. In response, instruments have been developed that employ detector arrays and rapid scanning lasers. The addition of dyes to stain particulates may facilitate spectroscopic detection of some polymer types. Most researchers provide microplastic data in the form of the abundances of polymer types within particle size, polymer, and morphology classes. Polymer mass data in samples remain rare but are essential to elucidating fate. Rather than characterizing individual particles in samples, solvent extraction (following initial sample prep, such as sediment size class sorting), combined with techniques such as thermoanalysis (e.g., pyrolysis), has been used to generate microplastic mass data. However, this may obviate the acquisition of individual particle morphology and compositional information. Alternatively, some techniques (e.g., electron and atomic force microscopy and matrix-assisted laser desorption mass spectrometry) are adept at providing highly detailed data on the size, morphology, composition, and surface chemistry of select particles. Ultimately, the analyst must select the approach best suited for their study goals. Robust quality control elements are also critical to evaluate the accuracy and precision of the sampling and analysis techniques. Further, improved efforts are required to assess and control possible sample contamination due to the ubiquitous distribution of microplastics, especially in indoor environments where samples are processed.
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Noskov, M., and M. D. Smooke. "Primitive variable solver for modeling steady-state and time-dependent laminar flames with detailed chemistry and transport properties." In Computational Fluid and Solid Mechanics, 1338–41. Elsevier, 2001. http://dx.doi.org/10.1016/b978-008043944-0/50910-0.
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Arshad, Muzammil. "Numerical Simulations and Validation of Engine Performance Parameters Using Chemical Kinetics." In Numerical Simulation [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.106536.
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Use of detailed chemistry augments the combustion model of a three-dimensional unsteady compressible turbulent Navier–Stokes solver with liquid spray injection when coupled with fluid mechanics solution with detailed kinetic reactions. Reduced chemical reaction mechanisms help in the reducing the simulations time to study of the engine performance parameters, such as, in-cylinder pressure in spark ignition engines. Sensitivity analysis must be performed to reduce the reaction mechanism for the compression and power strokes utilizing computational singular perturbation (CSP) method. To study a suitable well-established surrogate fuel, an interface between fluid dynamics and chemical kinetics codes must be used. A mesh independent study must be followed to validate results obtained from numerical simulations against the experimental data. To obtain comprehensive results, a detailed study should be performed for all ranges of equivalence ratios as well as stoichiometric condition. This gives rise to the development of a reduced mechanism that has the capability to validate engine performance parameters from stoichiometric to rich mixtures in a spark ignition engine. The above-mentioned detailed methodology was developed and implemented in the present study for premixed and direct injection spark ignition engines which resulted in a single reduced reaction mechanism that validated the engine performance parameters for both engine configurations.
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Yung, Yuk L., and William B. DeMore. "Jovian Planets." In Photochemistry of Planetary Atmospheres. Oxford University Press, 1999. http://dx.doi.org/10.1093/oso/9780195105018.003.0008.
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The four giant planets in the outer solar system, Jupiter, Saturn, Uranus, and Neptune, are a distinct group by themselves. The essential astronomical and atmospheric aspects of these planets are summarized in table 5.1. The significance of this group in the chemistry of the solar system is briefly pointed out in chapter 4. These planets are composed primarily of the lightest elements, hydrogen and helium, which were captured from the solar nebula during formation. The planets have rocky cores made of heavier elements. In the case of Jupiter and Saturn the mass of the gas greatly exceeds that of the core, whereas for Uranus and Neptune the masses of gas and core are comparable. Due to the enormous gravity of the giant planets, little mass has escaped from their atmospheres. Hence, the bulk composition of these planets provides a good measure of the initial composition of the solar nebula from which they were derived. Of all planetary bodies in the solar system, the constituents of giant planets are the closest to the cosmic abundances of the elements. The chemistry of the atmospheres of the giant planets is interesting for the following reasons:… 1. chemistry in a dominantly reducing atmosphere 2. interplay between photochemistry and equilibrium chemistry 3. ion chemistry in polar auroral regions 4. heterogeneous chemistry of aerosols 5. chemistry of meteoritic debris 6. lack of a planetary "surface"… We briefly comment on these reasons in this section. Each topic will receive a more detailed treatment in later sections. First of all, the atmospheres of the Jovian planets are more than 90% hydrogen and helium. Since helium is inert, the atmospheric chemistry is dominated by hydrogen. Therefore, we would expect the most stable compounds of carbon, oxygen, nitrogen, and phosphorus to be CH4, H2O, NHa, and PHs. This is in fact confirmed by the available observed composition of the bulk atmospheres of these planets. However, in the upper atmospheres of these planets, the composition is controlled by photochemistry.
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Enoki, Toshiaki, Morinobu Endo, and Masatsugu Suzuki. "Synthesis and Intercalation Chemistry." In Graphite Intercalation Compounds and Applications. Oxford University Press, 2003. http://dx.doi.org/10.1093/oso/9780195128277.003.0004.
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Alkali metal GICs are the best known donor type GICs, since they are easily prepared and their brilliant gold color for stage-1 GICs has attracted scientists working in intercalation chemistry. They have therefore been targets of intensive and detailed studies of their solid-state properties on the basis of the employment of highly oriented pyrolytic graphite (HOPG). There are several intercalation methods, which are classified basically into vapor-phase reaction, reaction of the mixture of graphite and alkali metal, high pressure reaction, electrochemical reaction, and reaction in a solvent. Among these methods, vapor-phase intercalation reaction is the most popular. The two-zone method can easily give alkali metal GICs with well-defined single-stage phases. The vapor pressure of the alkali metal becomes high enough to obtain a satisfactory reaction rate for intercalation reaction in the temperature range 200-550°C, at which we can use a Pyrex glass tube as a reaction chamber. Figure 2.1 shows a typical two-zone method, where graphite and alkali metal are maintained at different temperatures, TG and TI, respectively, in a vacuum-sealed glass tube placed in a two-zone furnace. Changing TI controls the vapor pressure of the alkali metal. Figure 2.2 presents the conditions of intercalation reaction with potassium, where single-stage phase samples with stages 1 to 8 are obtained by changing the temperature difference TG — TK (Nishitani et al., 1983). Typical experimental conditions are given in Table 2.1 for the preparation of K, Rb, and Cs GICs (Dresselhaus and Dresselhaus, 1981). The intercalation reaction is again carried out by heating a mixture of graphite and alkali metal in a vacuum-sealed glass tube. In this case, the reaction becomes considerably more rapid owing to direct contact of molten alkali metal with graphite, although the reaction takes place in a similar manner to the vapor-phase reaction. A stainless steel tube is used for the intercalation of lithium since lithium vapor degrades a glass tube because of its high chemical activity. Alkali metal can be intercalated into graphite when the alkali metal is solvated in liquid ammonia or an organic solvent such as dimethylsulphoxide (DMSO).
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Kang, Rira, Tae-ho Jeong, and Byunghong Lee. "Lead-Free Perovskite and Improved Processes and Techniques for Creating Future Photovoltaic Cell to Aid Green Mobility." In Recent Advances in Multifunctional Perovskite Materials [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.106256.
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Perovskites material is in the spotlight as photovoltaic device due to their optical and physical properties. In a short period of time, this organic-inorganic pevskite can achieve about energy conversion efficiencies of 25.6% by anti-solvent and spin-coating based process. In addition, ambipolar carrier transport properties of perovskite materials open up new directions for the high-efficiency thin-film solar cells. Despite its attractive properties in solar cell application, concerned about device stability and the use of lead compounds (APbX3, A = a cation X = halide) with toxicity cause the potential risk for the human body and environment issue. Therefore, the use of a new classed strucutral materials with intrinsic stability and beneficial optoelectronic properties can be considered as a start of the next chapter in pervoksite device. This chapter is structured into two major parts: In section 1, we introduce more stable class of perovskite, A2SnX6, where Sn is in the 4+ oxidation state. A detailed discussion on the ramifications of material structure and chemistry-related challenges is presented for solution processing, along with careful characterization. In section 2, we talk about the direction of development for perovksite materials to be a next chapter of energy source for a green mobility.
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"The Chemistry of a Single Firearm Cartridge." In The Chemists' War: 1914–1918, 78–92. The Royal Society of Chemistry, 2014. http://dx.doi.org/10.1039/bk9781849739894-00078.
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Machine guns andrifles, and the snipers and soldiers who wielded them, played a significant role in the First World War; machine gun and rifle fire accounted for some 39% of the 2.9 million British casualties. Every bulletthat killed, maimed or missed a soldier, was a product of chemistry, and every round relied on chemical powders and chemical processes to propel that bullet from the barrel of the gun towards its victim. This chapter details the chemicals and methods involved in producing firearm and artillery cartridges, as well as their use and effectiveness in battle.
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Hota, Lopamudra, and Prasant Kumar Dash. "A Taxonomy of Quantum Computing Algorithms." In Advances in Systems Analysis, Software Engineering, and High Performance Computing, 36–56. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-9183-3.ch004.
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Quantum computing exploits quantum-mechanical principles such as entanglement and superposition to offer significant computational advantages over conventional classical computing. Many complex and computationally challenging problems are expected to be solved by quantum computing in a number of fields, such as data science, industrial chemistry, smart energy, finance, secure communications, and many others. In order to understand the current status of quantum computing and identify its challenges, a systematic review of the existing literature will be valuable. An overview of quantum computing literature and its taxonomy is presented in this chapter. Further, the proposed taxonomy aims to identify research gaps by mapping various related studies. There is a detailed analysis of quantum technologies with the most current state of the art. Finally, the chapter presents a highlight of open challenges and future research directions.
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Calvert, Jack, Abdelwahid Mellouki, John Orlando, Michael Pilling, and Timothy Wallington. "The Influence of Oxygenates on the Atmospheric Chemistry of Urban, Rural, and Global Environments." In Mechanisms of Atmospheric Oxidation of the Oxygenates. Oxford University Press, 2011. http://dx.doi.org/10.1093/oso/9780199767076.003.0013.
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One cannot overestimate the importance of oxygenated organic compounds in atmospheric chemistry. As discussed in the previous chapters of this book and elsewhere (e.g., Wayne, 1991; Seinfeld and Pandis, 1998; Brasseur et al., 1999; Finlayson-Pitts and Pitts, 2000; Calvert et al., 2000, 2002, 2008) the atmosphere is an oxidizing environment and all organic compounds emitted into the atmosphere are converted into oxygenated organic compounds. The first-generation products are oxidized further. As an example, the oxidation of ethane gives CH3CHO, C2H5OH, and C2H5OOH as first-generation products and CH3OH, CH3OOH, CH2O, and HC(O)OH as second-generation products. An understanding of the chemistry of oxygenated organic compounds is central to unraveling the complex processes in the atmosphere. In this chapter we discuss the representation of oxygenates in atmospheric models, their participation in secondary organic aerosol formation, contribution to HOx chemistry in the upper troposphere, role in the transport of pollutants, and use as proxies for volatile organic compound (VOC) emissions. A major application of the chemical kinetics and mechanisms of VOC oxidation is the development of an understanding of the chemistry occurring in the troposphere and the use of that understanding to predict and develop strategies which help to mitigate adverse changes in air quality and climate change. Such applications depend on the development of models that assess chemical impacts; chemical mechanisms lie at the heart of such models. The mechanisms can be very detailed, often termed explicit, in models where the aim is to understand the chemistry occurring in a small volume of air, for example, in an analysis of processes determining radical concentrations in field measurements. Such a mechanistic approach can also be used, with increased computer resources, when a trajectory approach is used to assess the coupled impacts of atmospheric transport and chemistry. An Eulerian approach to modeling both regional and global processes presents greater problems, because the chemical rate equations have to be solved for each species at each spatial grid point in the model; this severely limits the number of chemical species that can be incorporated realistically in the model.
Conference papers on the topic "Detailed chemistry solver"
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Kundu, Prithwish, Muhsin M. Ameen, Chao Xu, Umesh Unnikrishnan, Tianfeng Lu, and Sibendu Som. "Implementation of Detailed Chemistry Mechanisms in Engine Simulations." In ASME 2017 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/icef2017-3596.
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The stiffness of large chemistry mechanisms has been proved to be a major hurdle towards predictive engine simulations. As a result, detailed chemistry mechanisms with a few thousand species need to be reduced based on target conditions so that they can be accommodated within the available computational resources. The computational cost of simulations typically increase super-linearly with the number of species and reactions. This work aims to bring detailed chemistry mechanisms within the realm of engine simulations by coupling the framework of unsteady flamelets and fast chemistry solvers. A previously developed Tabulated Flamelet Model (TFM) framework for non-premixed combustion was used in this study. The flamelet solver consists of the traditional operator-splitting scheme with VODE (Variable coefficient ODE solver) and a numerical Jacobian for solving the chemistry. In order to use detailed mechanisms with thousands of species, a new framework with the LSODES (Livermore Solver for ODEs in Sparse form) chemistry solver and an analytical Jacobian was implemented in this work. Results from 1D simulations show that with the new framework, the computational cost is linearly proportional to the number of species in a given chemistry mechanism. As a result, the new framework is 2–3 orders of magnitude faster than the conventional VODE solver for large chemistry mechanisms. This new framework was used to generate unsteady flamelet libraries for n-dodecane using a detailed chemistry mechanism with 2,755 species and 11,173 reactions. The Engine Combustion Network (ECN) Spray A experiments which consist of an igniting n-dodecane spray in turbulent, high-pressure engine conditions are simulated using large eddy simulations (LES) coupled with detailed mechanisms. A grid with 0.06 mm minimum cell size and 22 million peak cell count was implemented. The framework is validated across a range of ambient temperatures against ignition delay and liftoff lengths. Qualitative results from the simulations were compared against experimental OH and CH2O PLIF data. The models are able to capture the spatial and temporal trends in species compared to those observed in the experiments. Quantitative and qualitative comparisons between the predictions of the reduced and detailed mechanisms are presented in detail. The main goal of this study is to demonstrate that detailed reaction mechanisms (∼1000 species) can now be used in engine simulations with a linear increase in computation cost with number of species during the tabulation process and a small increase in the 3D simulation cost.
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Liang, Long, Chulhwa Jung, Song-Charng Kong, and Rolf D. Reitz. "Development of a Semi-Implicit Solver for Detailed Chemistry in I.C. Engine Simulations." In ASME 2005 Internal Combustion Engine Division Spring Technical Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/ices2005-1005.
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An efficient semi-implicit numerical method is developed for solving the detailed chemical kinetic source terms in I.C. engine simulations. The detailed chemistry system is a group of coupled extremely stiff O.D.E.s, which presents a very stringent timestep limitation when solved by standard explicit methods, and is computationally expensive when solved by iterative implicit methods. The present numerical solver uses a stiffly-stable noniterative semi-implicit method, in which the numerical solution to the stiff O.D.E.s never blows up for arbitrary large timestep. The formulation of numerical integration exploits the physical requirement that the species density and specific internal energy in the computational cells must be nonnegative, so that the Lipschitz timestep constraint is not present [1,2], and the computation timestep can be orders of magnitude larger than that possible in standard explicit methods and can be formulated to be of high formal order of accuracy. The solver exploits the characteristics of the stiffness of the O.D.E.s by using a sequential sort algorithm that ranks an approximation to the dominant eigenvalues of the system to achieve maximum accuracy. Subcycling within the chemistry solver routine is applied for each computational cell in engine simulations, where the subcycle timestep is dynamically determined by monitoring the rate of change of concentration of key species which have short characteristic time scales and are also important to the chemical heat release. The chemistry solver is applied in the KIVA-3V code to diesel engine simulations. Results are compared with those using the CHEMKIN package which uses the VODE implicit solver. Very good agreement was achieved for a wide range of engine operating conditions, and 40∼70% CPU time savings were achieved by the present solver compared to CHEMKIN.
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Wang, David H., Michael J. Bockelie, Marc A. Cremer, and J. Y. Chen. "A Newton-Krylov Based Solver for Modeling Finite Rate Chemistry." In ASME 2002 Pressure Vessels and Piping Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/pvp2002-1542.
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To date, computational fluid dynamics (CFD) codes aimed at solving practical engineering problems involving chemically reacting flow have incorporated relatively simple descriptions of the chemical mechanisms involved. Techniques are now available to create reduced mechanisms that faithfully represent detailed chemical descriptions over an appropriate range of conditions using many fewer species. However, including reduced mechanisms into a CFD analysis typically leads to numerical difficulties. In a recent project, a new modeling tool was created that utilizes a combination of state-of-the-art techniques used by Reaction Engineering International (REI) for modeling finite rate chemistry in chemically reacting flows using reduced mechanisms with emerging Newton-Krylov methods for solving systems of non-linear equations. For tests problems ranging from geometrically simple combustion problems to full-scale utility boiler simulations, the Newton-Krylov solver has reduced the CPU time to achieve a solution by up to 60% compared to our traditional Picard iteration method. This paper discusses the implementation of the Newton-Krylov solver into the REI combustion code, the impact of parameters on the performance of the Newton-Krylov solver for solving problems using reduced mechanisms, and demonstration of the Newton-Krylov solver on full-scale utility boiler NOx simulations.
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Luo, Zhaoyu, Parvez Sukheswalla, Scott A. Drennan, Mingjie Wang, and P. K. Senecal. "3D Numerical Simulations of Selective Catalytic Reduction of NOx With Detailed Surface Chemistry." In ASME 2017 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/icef2017-3658.
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Environmental regulations have put stringent requirements on NOx emissions in the transportation industry, essentially requiring the use of exhaust after-treatment on diesel fueled light and heavy-duty vehicles. Urea-Water-Solution (UWS) based Selective Catalytic Reduction (SCR) for NOx is one the most widely adopted methods for achieving these NOx emissions requirements. Improved understanding and optimization of SCR after-treatment systems is therefore vital, and numerical investigations can be employed to facilitate this process. For this purpose, detailed and numerically accurate models are desired for in-cylinder combustion and exhaust after-treatment. The present paper reports on 3-D numerical modeling of the Urea-Water-Solution SCR system using Computational Fluid Dynamics (CFD). The entire process of Urea injection, evaporation, NH3 formation and NOx reduction is numerically investigated. The simulation makes use of a detailed kinetic surface chemistry mechanism to describe the catalytic reactions. A multi-component spray model is applied to account for the urea evaporation and decomposition process. The CFD approach also employs an automatic meshing technique using Adaptive Mesh Refinement (AMR) to refine the mesh in regions of high gradients. The detailed surface chemistry NOx reduction mechanism validated by Olsson et al. (2008) is applied in the SCR region. The simulations are run using both transient and steady-state CFD solvers. While transient simulations are necessary to reveal sufficient details to simulate catalytic oxidation during transient engine processes or under cyclic variations, the steady-state solver offers fast and accurate emission solutions. The simulation results are compared to available experimental data, and good agreement between experimental data and model results is observed.
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Zhou, Dezhi, Shufan Zou, and Suo Yang. "An OpenFOAM-based fully compressible reacting flow solver with detailed transport and chemistry for high-speed combustion simulations." In AIAA Scitech 2020 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2020. http://dx.doi.org/10.2514/6.2020-0872.
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Gao, Jian, Ronald O. Grover, Venkatesh Gopalakrishnan, Ramachandra Diwakar, Wael Elwasif, K. Dean Edwards, Charles E. A. Finney, and Russell Whitesides. "Steady-State Calibration of a Diesel Engine in CFD Using a GPU-Based Chemistry Solver." In ASME 2017 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/icef2017-3631.
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The prospect of analysis-driven pre-calibration of a modern diesel engine is extremely valuable in order to significantly reduce hardware investments and accelerate engine designs compliant with stricter EPA fuel economy regulations. Advanced modeling tools, such as CFD, are often used with the goal of streamlining significant portions of the calibration process. The success of the methodology largely relies on the accuracy of analytical predictions, especially engine-out emissions. However, the effectiveness of CFD simulation tools for in-cylinder engine combustion is often compromised by the complexity, accuracy, and computational overhead of detailed chemical kinetics necessary for combustion calculations. The standard approach has been to use skeletal kinetic mechanisms (∼50 species) which consume acceptable computational time but with degraded accuracy. In this work, a comprehensive demonstration and validation of the analytical pre-calibration process is presented for a passenger car diesel engine using CFD simulations with CONVERGE™ and a GPU-based chemical kinetics solver (Zero-RK, developed at Lawrence Livermore National Laboratory) on high performance computing resources to enable the use of detailed kinetic mechanisms. Diesel engine combustion computations have been conducted over 600 operating points spanning in-vehicle speed-load map, using massively parallel ensemble simulation sets on the Titan supercomputer located at the Oak Ridge Leadership Computing Facility. The results with different mesh resolutions have been analyzed to compare differences in combustion and emissions (NOx, Carbon Monoxide CO, Unburned Hydrocarbons UHC, and Smoke) with actual engine measurements. The results show improved agreement in combustion and NOx predictions with a large n-heptane mechanism consisting of 144 species and 900 reactions with refined mesh resolution; however; agreement in CO, UHC and Smoke remain a challenge.
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Menon, Sachin, Thijs Bouten, Jan Withag, Sikke Klein, and Arvind Gangoli Rao. "Numerical Investigation of 100% Premixed Hydrogen Combustor at Gas Turbines Conditions Using Detailed Chemistry." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-16134.
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Abstract The combustion properties of hydrogen make premixed hydrogen-air flames prone to flashback. Several combustor concepts have been proposed and studied in the past few years to tackle the problem of flame flashback in premixed high hydrogen fuel combustors. This study looks at one of the concepts which uses the Aerodynamically Trapped Vortex to stabilize the flame. Burner concepts based on trapped vortex flame stabilization have a higher resistance towards flame blowout than conventional swirl stabilized burners. This work looks at the flow and flame behavior in the proposed Aerodynamically Trapped Vortex Combustor for 100% premixed hydrogen operation. Numerical simulations for the analysis were performed with the commercial CFD simulation package AVL FIRE™. The flow field characterization was focused on the investigation of the influence of both the inlet velocity and inlet turbulence intensity on the mean velocity, wall velocity gradient and turbulence intensity in the combustor. To study the flame stabilization mechanism, reactive simulations were performed at two fuel equivalence ratios. The combustion regime of the flame, turbulent flame speed and temperature distribution in the combustor were quantified from the simulation results. Combustion is modelled using a detailed chemistry solver with the k–ε turbulence model to resolve turbulence. No additional turbulence-chemistry interaction model is used in the current research. To reduce chemistry computational time, the multi-zone method is employed. To capture the effect of preferential diffusion, two approaches were used to quantify the diffusion coefficient of each species. The diffusion coefficients were calculated using both mixture averaged approach and the multi component diffusion approach. The proposed design for the Aero-dynamically Trapped Vortex combustor was able to stabilize a 100% premixed hydrogen flame without flashback for the simulated conditions.
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Zhou, Dezhi, and Suo Yang. "A robust reacting flow solver with detailed transport, chemistry, and steady-state preserving splitting schemes based on OpenFOAM and Cantera." In AIAA Scitech 2020 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2020. http://dx.doi.org/10.2514/6.2020-2139.
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Wan, Kaidi, Zhihua Wang, Luc Vervisch, Jun Xia, Yingzu Liu, Yong He, and Kefa Cen. "Large-Eddy Simulation of Alkali Metal Reacting Dynamics in a Preheated Pulverized-Coal Jet Flame Using Tabulated Chemistry." In ASME 2017 Power Conference Joint With ICOPE-17 collocated with the ASME 2017 11th International Conference on Energy Sustainability, the ASME 2017 15th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2017 Nuclear Forum. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/power-icope2017-3212.
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This paper proposed an approach to modeling alkali metal reacting dynamics in turbulent pulverized-coal combustion (PCC) using tabulated sodium chemistry. With tabulation, detailed sodium chemistry can be incorporated in large-eddy simulation (LES), but the expenses of solving stiff Arrhenius equations can be avoided. The sodium release rate from a pulverized-coal particle is assumed to be proportional to the pyrolysis rate, as a simplification. The chemical forms of released sodium is assumed to be atomic sodium Na, because atomic sodium is predicted to be the favoured species in a flame environment. A detailed sodium chemistry mechanism including 5 sodium species, i.e., Na, NaO, NaO2, NaOH and Na2O2H2, and 24 elementary reactions is tabulated. The sodium chemistry table contains four coordinates, i.e., the equivalence ratio, the mass fraction of the sodium element, the gas-phase temperature, and the progress variable. Apart from the reactions of sodium species, hydrocarbon volatile combustion has been modeled by a partially stirred reactor concept. Since the magnitude of sodium species is very small, i.e., at the ppm level, and the reactions of sodium species are slower than volatile combustion, one-way coupling is used for the interaction between the sodium reactions and volatile combustion, i.e., the former having no influence on the latter. A verification study has been performed to compare the predictions on sodium species evolutions in zero-dimensional simulations using the chemistry table against directly using the detailed sodium mechanism under various initial conditions, and their agreement is always good. The PCC-LES solver used in the present study is validated on a pulverized-coal jet flame ignited by a preheated gas flow. Good agreements between the experimental measurements and the LES results have been achieved on gas temperature, coal burnout and lift-off height. Finally, the sodium chemistry table is incorporated into the LES solver to model sodium reacting dynamics in turbulent pulverized-coal combustion. Properties of Loy Yang brown coal, for which sodium data are available, are used. Characteristics of the reacting dynamics of the 5 sodium species in a pulverized-coal jet flame are then obtained. The results show that Na and NaOH are the two major sodium species in the pulverized-coal jet flame. Na, the atomic sodium, has a high concentration in fuel-rich regions; while the highest NaOH concentration is found in regions close to the stoichiometric condition. It should be pointed out that the proposed chemistry tabulation approach can be extended to modeling potassium reacting dynamics in turbulent multiphase biomass combustion. (CSPE)
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Arshad, Muzammil. "Numerical Simulations and Validation of Engine Performance Parameter in Direct Injection Spark Ignition (DISI) Engines Using Chemical Kinetics." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-24683.
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Abstract Experimental studies have been augmented by computer modelling and simulations for the development and optimization of future fuels and automotive engines. Traditional reliance on the simplified global reactions for combustion simulations reduces the credibility of the prediction of combustion and engine performance parameters, such as in-cylinder pressure, heat release and pollutant formation. The study of engine performance parameters helps in improving the performance as well as the reduction of emissions in the engines. The present study has used detailed chemistry by augmenting the combustion model of a three-dimensional unsteady compressible turbulent Navier-Stokes solver with liquid spray injection by coupling its fluid mechanics solution with detailed kinetic reactions solved by a commercial chemistry solver. A skeletal reaction mechanism was reduced to study the in-cylinder pressure in a direct injection spark ignition (DISI) engine. Sensitivity analysis was performed to reduce the reaction mechanism for the compression and power strokes utilizing computational singular perturbation (CSP) method. An interface was developed between fluid dynamics and chemical kinetics codes to study iso-octane that is a well-established surrogate fuel for gasoline. Gasoline is a complex mixture of various compounds and hydrocarbons. The study used 90% iso-octane and 10% n-heptane as surrogate fuel because this combination best modelled the results. A mesh independent study was performed at stoichiometric conditions that validated and showed a good agreement of peak in-cylinder pressure against the experimental data for a direct injection spark ignition (DISI) engine. This study has been comprehensive as it includes a detailed study performed for premixed case at ϕ = 0.98 and 1.3 as well as stoichiometric condition in a direct injection spark ignition (DISI) engine, that resulted in the development of a reduced mechanism that has the capability to validate in-cylinder pressure and heat release rate from stoichiometric to rich mixtures for premixed cases in a spark ignition engine. The study concludes that it is imperative to establish a library of reduced mechanisms for various spark ignition engines as well as other combustion systems.