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Andronopoulos, S.; Grigoriadis, D.G.E.; Robins, Alan; Venetsanos, A.G.; Rafailidis, Stilianos; Bartzis, John G.

doi:10.1023/a:1015705615846

Cited by 40 publications

(6 citation statements)

References 20 publications

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“…Galperin (1986) [77] showed that the dissipation time scale grows linearly with time, and, if we consider the dissipation time scale as the life-time of the fluctuations, it should be smaller close to the source where the intense mixing causes rapid development and dissipation of the fluctuations. Proportionality between t d and the Lagrangian integral time scale was proposed by Bèguier et al (1978) [78] and Warhaft and Lumley (1978) [79], and used by Andronopoulos et al (2002) [80] and Milliez and Carissimo (2008) [81]. A similar relationship can be found in Yee et al (2009) [63].…”

Section: Variance Dissipation Time Scalementioning

confidence: 81%

Concentration Fluctuations and Odor Dispersion in Lagrangian Models

et al. 2019

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In this paper, a review of the Lagrangian stochastic models developed in the last decades for the simulation of the concentration–fluctuation dispersion is presented. The main approaches available in the literature are described and their ability in reproducing the higher order moments of the probability density function is discussed. Then, the Lagrangian approaches for evaluating of the odor annoyance are presented. It is worth to notice that, while Lagrangian stochastic models for mean concentrations are well-known and their ability in correctly reproducing the observation is well assessed, concerning concentration fluctuations the approaches are often new and unknown for most of the scientific community.

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Section: Variance Dissipation Time Scalementioning

confidence: 81%

Concentration Fluctuations and Odor Dispersion in Lagrangian Models

et al. 2019

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“…is the SGS KE. It can be shown that the transport equation for the time-averaged resolved KE of the flow takes the following form: 32 (11). As such, the pressure diffusion, viscous dissipation, and SGS diffusion terms shown in the budget balance in these figures are…”

Section: Budget Of the Resolved Kinetic Energymentioning

confidence: 99%

“…Similar to the function of the SGS dissipation term τ * i jS i j in Eq. (11) for the transport of the resolved KE, the SGS dissipation term 2h j ∂c ∂x j reflects the local SE flux between the resolved and subgrid scale motions. As shown in Figs.…”

Section: F Spectra and Scalar Energy Of The Concentration Fieldmentioning

confidence: 99%

“…In RANS approaches, use of numerical models has been primarily focused on prediction of the first-and second-order concentration statistics for urban pollutant plumes. Andronopoulos et al 11 investigated the dispersion field at the cross-junction of two street canyons by explicitly solving the transport equation for the concentration variance and used the so-called gradient transfer assumption for closing the concentration variance equation. Milliez and Carissimo 12 introduced an algebraic model for closure of the concentration variance equation and validated their model performance by comparing the obtained results against MUST measurement data.…”

Section: Introductionmentioning

confidence: 99%

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Large-eddy simulation of turbulent flow and dispersion over a matrix of wall-mounted cubes

Saeedi

Wang

2015

Physics of Fluids

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“…The use of a transport equation for the concentration variance was first adopted in [26]. Of particular interest for the present paper is the calculation of concentration fluctuations in dispersion in urban environments or in the vicinity of buildings [27][28][29][30][31][32][33][34][35][36][37][38][39]. Several experimental studies of concentration fluctuations of plume (continuous release) dispersion in urban areas or in the vicinity of buildings in real scale or in the wind tunnel have also been reported in the literature [40][41][42][43][44].…”

Section: Introductionmentioning

confidence: 99%

Modelling Exposure from Airborne Hazardous Short-Duration Releases in Urban Environments

2021

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When considering accidental or/and deliberate releases of airborne hazardous substances the release duration is often short and in most cases not precisely known. The downstream exposure in those cases is stochastic due to ambient turbulence and strongly dependent on the release duration. Depending on the adopted modelling approach, a relatively large number of dispersion simulations may be required to assess exposure and its statistical behaviour. The present study introduces a novel approach aiming to replace the large number of the abovementioned simulation scenarios by only one simulation of a corresponding continuous release scenario and to derive the exposure-related quantities for each finite-duration release scenario by simple relationships. The present analysis was concentrated on dosages and peak concentrations as the primary parameters of concern for human health. The experimental and theoretical analysis supports the hypothesis that the dosage statistics for short releases can be correlated with the corresponding continuous release concentration statistics. The analysis shows also that the peak concentration statistics for short-duration releases in terms of ensemble average and standard deviation are well correlated with the corresponding dosage statistics. However, for more reliable quantification of the associated correlation coefficients further experimental and theoretical research is needed. The probability/cumulative density function for dosage and peak concentration can be approximated by the beta function proposed in an earlier work by the authors for continuous releases.

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Untitled

Cited by 40 publications

References 20 publications

Concentration Fluctuations and Odor Dispersion in Lagrangian Models

Concentration Fluctuations and Odor Dispersion in Lagrangian Models

Large-eddy simulation of turbulent flow and dispersion over a matrix of wall-mounted cubes

Modelling Exposure from Airborne Hazardous Short-Duration Releases in Urban Environments

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