Computational fluid dynamics (CFD) has become a reference tool for the investigation of pollutant emission and dispersion in urban areas, and for the assessment of the associated risk. In this framework, specific focus is given to the estimation of the downwind and ground level concentration of air pollutants coming from emission sources such as vehicular traffic, industrial plants or accidental events. Pollutant dispersion in the Atmospheric Boundary Layer (ABL) is strongly impacted by the turbulence. This leads to a complex coupled problem, considering the reciprocal influence of the two phenomena. A key role in pollutant dispersion is played by the turbulent Schmidt number Sc t which directly affects the turbulent dispersion coefficient and, consequently, the concentration field. No universally-accepted formulation for the turbulent Schmidt number exists in the literature, although its impact on the prediction of pollutant dispersion is recognised. Stemming from a brief review of the existing literature and knowledge on the topic, this paper aims to propose a novel approach for the optimal determination of Sc t , also through the use of uncertainty quantification. The proposed Sc t is based on the local turbulece level, and is validated on different idealized test cases, representative of typical urban configurations.
A numerical and experimental
investigation of a quasi-industrial
furnace operating in moderate or intense low-oxygen dilution combustion
regime, and fed with natural gas, is presented. The study analyzes
the effect of various parameters, including the combustion model [eddy
dissipation concept (EDC) and partially stirred reactor (PaSR)], the
definition of the chemical and mixing time scale, the turbulence model,
and the choice of the kinetic mechanism. The numerical results are
validated against in-flame temperature profiles, pollutant emission,
and OH* chemiluminescence images. It was found that EDC fails in providing
a reasonable estimation of the ignition region, while improved predictions
can be obtained using the PaSR model. A sensitivity analysis was carried
out to determine the optimal mixing time scale formulation for the
PaSR model. Indeed, a static time scale approach, based on defining
a prescribed fraction of the integral time scale, was compared to
a dynamic mixing time scale formulation, based on the ratio between
the variance of the mixture fraction and its dissipation rate. Results
indicate the need to modify the coefficients appearing in the scalar
dissipation rate transport equation, as the latter was originally
derived for homogeneous turbulence and two-dimensional configurations.
Results obtained with an optimized set of transport equation coefficients
are in good agreement with the experimental data and in line with
those obtained calibrating the mixing constant, C
mix, in the static approach.
The present paper investigates the role of combustion models and kinetic mechanisms on the prediction of NO x emissions in a turbulent combustion system where conventional and unconventional routes are equally important for NO x formation. To this end, a lab-scale combustion system working in Moderate and Intense Low-oxygen Dilution (MILD) conditions, namely the Adelaide Jet in Hot Co-flow (JHC) burner, is targeted. The Eddy Dissipation Concept (EDC) and
Ammonia/hydrogen-fueled combustion represents a very promising solution for the future energy scenario. This study aims to shed light and understand the behavior of ammonia/hydrogen blends under flameless conditions. A first-of-its-kind experimental campaign was conducted to test fuel flexibility for different ammonia/hydrogen blends in a flameless burner, varying the air injector and the equivalence ratio. NO emissions increased drastically after injecting a small amount of NH3 in pure hydrogen (10% by volume). An optimum trade-off between NOx emission and ammonia slip was found when working sufficiently close to stoichiometric conditions (ϕ = 0.95). In general, a larger air injector (ID25) reduces the emissions, especially at ϕ = 0.8. A well-stirred reactor network with exhaust recirculation was developed exchanging information with computational fluid dynamics (CFD) simulations, to model chemistry in diluted conditions. Such a simplified system was then used in two ways: 1) to explain the experimental trends of NOx emissions varying the ammonia molar fraction within the fuel blend and 2) to perform an uncertainty quantification study. A sensitivity study coupled with latin hypercube sampling (LHS) was used to evaluate the impact of kinetic uncertainties on NOx prediction in a well-stirred reactor network model. The influence of the identified uncertainties was then tested in more complex numerical models, such as Reynolds-averaged Navier–Stokes (RANS) simulations of the furnace. The major over-predictions of existing kinetic scheme was then alleviated significantly, confirming the crucial role of detailed kinetic mechanisms for accurate predictive simulations of NH3/H2 mixtures in flameless regime.
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