Turbulent Schmidt Number Measurements Over Three-Dimensional Cubic Arrays

Bernardino, Annalisa Di; Monti, Paolo; Leuzzi, Giovanni; Querzoli, Giorgio

doi:10.1007/s10546-019-00482-z

Cited by 20 publications

(20 citation statements)

References 68 publications

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“…When dealing with CFD dispersion simulation, a relevant role is played by Sc t which expresses the ratio of turbulent viscosity to mass diffusivity. The relevance of this parameter in affecting the concentration field is undoubted (Di Bernardino et al, 2019;Gualtieri et al, 2017) and is further demonstrated in the works of different authors (Di Sabatino et al, 2004;Gorlé et al, 2010;Longo et al, 2019). When dealing with atmospheric flows, typical values of Sc t range between 0.2 and 1.3 (Tominaga et al, 2008).…”

Section: Methodsmentioning

confidence: 95%

“…The literature tends to prescribe this parameter as a constant quantity, without reporting a precise and definitive guideline for its specification (Li et al, 2018a;Longo et al, 2019). However, the variable nature of Sc t has been repeatedly demonstrated (Di Bernardino et al, 2019;Gorlé et al, 2010;Gualtieri et al, 2017;Longo et al, 2019), also referring to a number of experiments (Reynolds, 1975) and to direct numerical simulations (DNS) (Donzis et al, 2014).…”

Section: Methodsmentioning

confidence: 99%

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Application of Improved CFD Modeling for Prediction and Mitigation of Traffic-Related Air Pollution Hotspots in a Realistic Urban Street

Lauriks

Longo

Baetens

et al. 2021

Atmospheric Environment

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The correct prediction of air pollutants dispersed in urban areas is of paramount importance to safety, public health and a sustainable environment. Vehicular traffic is one of the main sources of nitrogen oxides (NO x ) and particulate matter (PM), strongly related to human morbidity and mortality. In this study, the pollutant level and distribution in a section of one of the main road arteries of Antwerp (Belgium, Europe) are analyzed. The assessment is performed through computational fluid dynamics (CFD), acknowledged as a powerful tool to predict and study dispersion phenomena in complex atmospheric environments. The two main traffic lanes are modeled as emitting sources and the surrounding area is explicitly depicted. A Reynolds-averaged Navier-Stokes (RANS) approach specific for Atmospheric Boundary Layer (ABL) simulations is employed. After a validation on a wind tunnel urban canyon test case, the dispersion within the canopy of two relevant urban pollutants, nitrogen dioxide (NO 2 ) and particulate matter with an aerodynamic diameter smaller than 10 µm (PM 10 ), is studied. An experimental field campaign led to the availability of wind velocity and direction data, as well as PM 10 concentrations in some key locations within the urban canyon. To accurately predict the concentration field, a relevant dispersion parameter, the turbulent

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Section: Methodsmentioning

confidence: 95%

Section: Methodsmentioning

confidence: 99%

Application of Improved CFD Modeling for Prediction and Mitigation of Traffic-Related Air Pollution Hotspots in a Realistic Urban Street

Lauriks

Longo

Baetens

et al. 2021

Atmospheric Environment

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“…Other recent works on urban-like geometries include the already cited study of Marucci and Carpentieri (2020) and that of Di Bernardino et al (2019) who, however, mainly focused on the determination of the turbulent Schmidt number rather than the concentration fluctuations.…”

Section: Urban Mock-upmentioning

confidence: 99%

Concentration Fluctuations from Localized Atmospheric Releases

Cassiani

Bertagni

Marro

et al. 2020

Boundary-Layer Meteorol

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We review the efforts made by the scientific community in more than seventy years to elucidate the behaviour of concentration fluctuations arising from localized atmospheric releases of dynamically passive and non-reactive scalars. Concentration fluctuations are relevant in many fields including the evaluation of toxicity, flammability, and odour nuisance. Characterizing concentration fluctuations requires not just the mean concentration but also at least the variance of the concentration in the location of interest. However, for most purposes the characterization of the concentration fluctuations requires knowledge of the concentration probability density function (PDF) in the point of interest and even the time evolution of the concentration. We firstly review the experimental works made both in the field and in the laboratory, and cover both point sources and line sources. Regarding modelling approaches, we cover analytical, semi-analytical, and numerical methods. For clarity of presentation we subdivide the models in two groups, models linked to a transport equation, which usually require a numerical resolution, and models mainly based on phenomenological aspects of dispersion, often providing analytical or semi-analytical relations. The former group includes: large-eddy simulations, Reynolds-averaged Navier–Stokes methods, two-particle Lagrangian stochastic models, PDF transport equation methods, and heuristic Lagrangian single-particle methods. The latter group includes: fluctuating plume models, semi-empirical models for the concentration moments, analytical models for the concentration PDF, and concentration time-series models. We close the review with a brief discussion highlighting possible useful additions to experiments and improvements to models.

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“…Finally, it is clear that for a correct estimate of indoor concentrations it is essential to know the ventilation of the environment or the AER, and at the same time, the knowledge of outdoor concentrations cannot be ignored. These, among other things, are strongly dependent on the external wind field, the building geometry, the intensity and position of the pollutant sources [37][38][39][40].…”

Section: Comparison Of Sampled and Simulated Voc Concentrationmentioning

confidence: 99%

Modelling VOC Emissions from Building Materials for Healthy Building Design

et al. 2020

Self Cite

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The profound qualitative changes of indoor air and the progressive increase in the absolute number of pollutants, combined with the scientific awareness of the health impacts deriving from spending more than 90% of one’s time inside confined spaces, have increased the attention onto the needs of well-being, hygiene, and the health of users. This scientific attention has produced studies and analyses useful for evidence-based insights into building performance. Among the main pollutants in the indoor environment, Volatile Organic Compounds (VOCs) play a central role, and the use of box-models using the mass balance approach and Computational Fluid Dynamics (CFD) models are now consolidated to study their concentrations in an indoor environment. This paper presents the use of both types of modelling for the prediction of the VOC concentration in the indoor environment and the proposal of a guide value for the Indoor Air Quality (IAQ)-oriented building design, specifically related to the indoor VOC concentration due to building materials. Methodologically, the topic is addressed through environmental sampling, the definition of the parameters necessary for the numerical models, the simulations with the box-model and the CFD, and the comparison between the results. They show a good correspondence between the modelling tools used, highlighting the central role of ventilation and allowing a discussion of the relationship between regulatory limits of emissivity of materials and Indoor Air Guide Values for the concentration of pollutants.

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Turbulent Schmidt Number Measurements Over Three-Dimensional Cubic Arrays

Cited by 20 publications

References 68 publications

Application of Improved CFD Modeling for Prediction and Mitigation of Traffic-Related Air Pollution Hotspots in a Realistic Urban Street

Application of Improved CFD Modeling for Prediction and Mitigation of Traffic-Related Air Pollution Hotspots in a Realistic Urban Street

Concentration Fluctuations from Localized Atmospheric Releases

Modelling VOC Emissions from Building Materials for Healthy Building Design

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