GQL-RedChem: A MatLAB-based tool for the model reduction for chemical kinetics based on the Global Quasi-linearisation (GQL) approach

The Global Quasi-linearization (GQL) approach has been developed for the dimension reduction of the chemical kinetics, which aim at speeding up the numerical simulation of reacting flows. GQL-RedChem is a MatLAB-based package that integrates the homogeneous reacting systems, formulated mathematically as a system of Ordinary Differential Equations (ODEs). The package provides with an approximation of the fast/slow decomposition linear basis, describing a reacting source term by a system of Differential Algebraic Equations (DAEs). The GQL method can be applied for reacting systems with any complexity, and the GQL decomposition basis can be generated in a generic and automatic manner

REDIM based model reduction of the decomposition of urea-water-solutions in films and droplets

Selective catalytic reduction (SCR) process with urea-water solution (UWS) is often used in automotive industry to decrease emissions of nitric oxides (NO x) in the exhaust gas. In this process the urea from UWS decomposes to isocyanic acid and ammonia, where the latter is needed to increase the efficiency of the NO xreduction on the catalyst surface. Along with the advantages of using UWS several drawbacks reduce the performance of a SCR system. Incomplete decomposition of urea leads to a formation of residuals affecting the efficiency of the exhaust gas systems. Therefore, the complete decomposition of urea and homogeneous distribution of the resulting ammonia in front of the SCR catalyst represent main challenges in improving the SCR technology. In order to investigate the process of the urea decomposition a detailed chemical kinetic mechanism in the liquid phase is employed. The results are compared with a commonly used approach to model urea decomposition as an evaporation with a following decomposition reaction in the gas phase. It is shown that by using such a mechanism, the decomposition of urea and the gas phase composition with the urea decomposition products can be described more accurately. However, implementing these mechanisms in computations (in CFD approaches) requires a large amount of computational (CPU) time and memory. The method of Reaction Diffusion Manifolds (REDIMs) is implemented for the reduction of the detailed chemical kinetics in the stage of urea decomposition such that the distribution of products of the urea decomposition can be captured accurately in the gas phase with only two reduced variables instead of the 7 gas phase species of the original model

REDIM based model reduction of the decomposition of urea-water-solutions in films and droplets

Selective catalytic reduction (SCR) process with urea-water solution (UWS) is often used in automotive industry to decrease emissions of nitric oxides (NO x) in the exhaust gas. In this process the urea from UWS decomposes to isocyanic acid and ammonia, where the latter is needed to increase the efficiency of the NO xreduction on the catalyst surface. Along with the advantages of using UWS several drawbacks reduce the performance of a SCR system. Incomplete decomposition of urea leads to a formation of residuals affecting the efficiency of the exhaust gas systems. Therefore, the complete decomposition of urea and homogeneous distribution of the resulting ammonia in front of the SCR catalyst represent main challenges in improving the SCR technology. In order to investigate the process of the urea decomposition a detailed chemical kinetic mechanism in the liquid phase is employed. The results are compared with a commonly used approach to model urea decomposition as an evaporation with a following decomposition reaction in the gas phase. It is shown that by using such a mechanism, the decomposition of urea and the gas phase composition with the urea decomposition products can be described more accurately. However, implementing these mechanisms in computations (in CFD approaches) requires a large amount of computational (CPU) time and memory. The method of Reaction Diffusion Manifolds (REDIMs) is implemented for the reduction of the detailed chemical kinetics in the stage of urea decomposition such that the distribution of products of the urea decomposition can be captured accurately in the gas phase with only two reduced variables instead of the 7 gas phase species of the original model

Activation Energy of Hydrogen–Methane Mixtures

In this work, the overall activation energy of the combustion of lean hydrogen–methane–air mixtures (equivalence ratio = 0.7−1.0 and hydrogen fraction in methane =0, 2, 4) is experimentally determined using thin-filament pyrometry of flames stabilised on a flat porous burner under normal conditions (=1 bar, T = 20 °C). The experimental data are compared with numerical calculations within the detailed reaction mechanism GRI3.0 and both approaches confirm the linear correlation between mass flow rate and inverse flame temperature predicted in the theory. An analysis of the numerical and experimental data shows that, in the limit of lean hydrogen–methane–air mixtures, the activation energy approaches a constant value, which is not sensitive to the addition of hydrogen to methane. The mass flow rate for a freely propagating flame and, thus, the laminar burning velocity, are measured for mixtures with different hydrogen contents. This mass flow rate, scaled over the characteristic temperature dependence of the laminar burning velocity for a one-step reaction mechanism, is found and it can also be used in order to estimate the parameters of the overall reaction mechanisms. Such reaction mechanisms will find implementation in the numerical simulation of practical combustion devices with complex flows and geometries

Theoretical backgrounds of educational and training technology

This article presents an overview of the most popular theoretical approaches to developing computer tools for organising and supporting cognition, learning and teaching in Eastern European countries. Such theoretical approaches as the theory of activity, problem solving modelling, problem-based teaching, constructivism, theories of meta-cognitive processes are described in detail. Its function is to clarify underlying fundamental views on the learning and teaching process the authors used in their papers

Hierarchical structure of slow manifolds of reacting flows

Nowadays the mathematical description of chemically reacting flows uses very often reaction mechanisms with far above hundred or even thousand chemical species (and, therefore, a large number of partial differential equations must be solved), which possibly react within more than a thousand of elementary reactions. These chemical kinetic processes cover time scales from nanoseconds to seconds. An analogous scaling problem arises for the length scales. Due to these scaling problems the detailed simulation of three-dimensional turbulent flows in practical systems is beyond the capacity of even today's super-computers. Using simplified sub-models is a way out of this problem. The question arising in mathematical modeling of reacting flows is then: How detailed, or down to which scale has each process to be resolved (chemical reaction, chemistry-turbulence-interaction, molecular transport processes) in order to allow a reliable description of the entire process. Both the chemical source term and the transport term have one important property, namely, they cause the existence of low-dimensional attractors in composition space. When these manifolds can be constructed (described) and parametrized by a small number of variables, it can be used to reformulate and reduce the mathematical description for modeling reacting flows. In this work the hierarchical nature of these low-dimensional manifolds of slow motions is discussed. It is demonstrated how this important feature of reacting flows is accounted for by the standard model reduction methods (like e.g. PEA and QSSA methods) as well as by recently developed concepts of model reduction. The use of the hierarchical nature for identification of the low-dimensional manifolds to devise hierarchical modeling concepts (e.g. for turbulent reacting flows) is additionally discussed