The Eddy Dissipation Concept (EDC) is common in modeling turbulent combustion. Several model improvements have been proposed in literature; recent modifications aim to extend its validity to Moderate or Intense Low oxygen Dilution (MILD) conditions. In general, the EDC divides a fluid into a reacting and a non-reacting part. The reacting part is modeled as perfectly stirred reactor (PSR) or plug flow reactor (PFR). EDC theory suggests PSR treatment, while PFR treatment provides numerical advantages. Literature lacks a thorough evaluation of the consequences of employing the PFR fine structure treatment. Therefore, these consequences were evaluated by employing tests to isolate the effects of the EDC variations and fine structure treatment and by conducting a Sandia Flame D modeling study. Species concentration as well as EDC species consumption/production rates were evaluated. The isolated tests revealed an influence of the EDC improvements on the EDC rates, which is prominent at low shares of the reacting fluid. In contrast, PSR and PFR differences increase at large fine fraction shares. The modeling study revealed significant differences in the EDC rates of intermediate species. Summarizing, the PFR fine structure treatment might be chosen for schematic investigations, but for detailed investigations a careful evaluation is necessary.Energies 2018, 11, 1902 2 of 21 mixing rate only, and an infinitely fast chemistry assumption is possible. However, if turbulence and turbulent mixing decrease, the reaction progress can be limited by either mixing or chemistry. In this regime, finite rate chemistry is necessary to accurately describe the turbulence-chemistry interaction [7,12,13]. When using detailed chemistry with the EDC, the fine structures are typically treated as perfectly stirred reactors (PSRs), since educts are mixed on a molecular scale and mass is exchanged with the surroundings [4]. The fine structure state is determined by solving the PSR to steady-state, which is numerically expensive due to the strong nonlinearity in the reaction source terms. Some EDC implementations, therefore, treat the fine structures as plug flow reactors (PFR) [7,[16][17][18][19]. These PFRs are solved for the fine structure residence time, implying that the fine structures are spatially isolated structures in the fluid only evolving in time. Since fine structure residence times are typically small (approx. O 10 −7 to O 10 −3 seconds) for classical turbulent combustion, the numerical effort to solve the detailed chemistry in a PFR is significantly reduced. However, the latter approach is not in line with the EDC theory. Although the PFR fine structure treatment was employed in many published research works, e.g., [16][17][18][19][20][21], only De et al. [17], Li et al. [16], and Lewandowski and Ertesvaag [18] commented on the consequences of the PFR simplification. However, none of them performed an in-depth analysis of species profiles and species consumption rates.De et al. [17] state that the PSR and PFR results are only sim...

The chemical time scale can be used to characterize a reactive system ('s behavior). In addition, various dimensionless numbers (e.g. Damköhler number) rely on a characteristic chemical time scale. The inverse eigenvalues of a system are regarded as the system's time scales. This means, the number of time scales is equal the numbers of eigenvalues. A formulation for a single characteristic time scale is required for the system characterization and to calculate dimensionless numbers. Recently proposed modifications of the Eddy Dissipation Concept (a turbulence-chemistry interaction model) also incorporate the Damköhler number in their formulation. Besides accuracy, the numerical efficiency is important, since the chemical time scale needs to be computed in each cell at every time step. We present different chemical time scale definitions found in literature, evaluate them on simple test problems and use them for flame simulations in conjunction with the modified Eddy Dissipation Concept. For the simple test case, most formulations give satisfactory results. The complexity of the chemical reaction mechanism greatly impacts the calculated time scale values. Therefore, we suggest to use a simple global mechanism for the calculation of chemical time scales to ensure reproducibility and consistency of the results.

Heat transfer is a crucial aspect of thermochemical conversion of pulverized fuels. Over-predicting the heat transfer during heat-up leads to under-estimation of the ignition time, while under-predicting the heat loss during the char conversion leads to an over-estimation of the burnout rates. This effect is relevant for dense particle jets injected from dense-phase pneumatic conveying. Heat fluxes characteristic of such dense jets can significantly differ from single particles, although a single, representative particle commonly models them in Euler–Lagrange models. Particle-resolved direct numerical simulations revealed that common representative particles approaches fail to reproduce the dense-jet characteristics. They also confirm that dense clusters behave similar to larger, porous particles, while the single particle characteristic prevails for sparse clusters. Hydrodynamics causes this effect for convective heat transfer since dense clusters deflect the inflowing fluid and shield the center. Reduced view factors cause reduced radiative heat fluxes for dense clusters. Furthermore, convection is less sensitive to cluster shape than radiative heat transfer. New heat transfer models were derived from particle resolved simulations of particle clusters. Heat transfer increases at higher void fractions and vice versa, which is contrary to most existing models. Although derived from regular particle clusters, the new convective heat transfer models reasonably handle random clusters. Contrary, the developed correction for the radiative heat flux over-predicts shading effects for random clusters because of the used cluster shape. In unresolved Euler–Lagrange models, the new heat transfer models can significantly improve dense particle jets’ heat-up or thermochemical conversion modeling.

Identifying coals suitable for blast furnace injection has become increasingly important due to rising injection rates. This review of traditional pulverised coal reactivity testing equipment reveals that no agreed-upon evaluation standard exists and that different reactor types are employed for testing. Therefore, reference blast furnace conversion conditions are defined, followed by a discussion of their influence on the coal conversion process as illustrated by conceptual conversion models. Critical process parameters are temperature, heating rate and pressure, while other effects can be calibrated. Evaluating the currently employed test equipment with regard to these process parameters shows that only specially designed drop-tube furnaces and flow reactors provide conversion conditions near to blast furnace conditions. For consistent injection coal testing, special reactors complying with the previously defined critical process parameters must be established.

The separation of immiscible liquids is critical in many industrial processes, such as water treatment, different extraction processes, the petroleum industry, food production, and medicine. This work provides an overview of present research on the separation of liquid mixtures. A brief summary of the thermodynamic basis is provided, covering phase equilibrium, phase diagrams, and thermodynamic properties of phases. Additionally, the fundamentals of dispersion, necessary for discussing liquid–liquid separation, are presented. Subsequently, different liquid–liquid separation methods are discussed, highlighting their advantages and limitations. These methods include decanters, coalescers, centrifugal separators, membranes and electro-coalescers for liquid–liquid separation. Phase properties, dispersion formation, and time and space constraints specify the most efficient separation method. Phase recycling is also briefly discussed as a method to reduce the environmental impact of liquid–liquid extraction with subsequent phase separation. In summary, liquid–liquid separation methods are compared and future perspectives of liquid–liquid separation are discussed.