Pasquale Franzese

Evaluations of CALPUFF, HPAC, and VLSTRACK with Two Mesoscale Field Datasets

Abstract Results of evaluations of transport and dispersion models with field data are summarized. The California Puff (CALPUFF), Hazard Prediction and Assessment Capability (HPAC), and Chemical/Biological Agent Vapor, Liquid, and Solid Tracking (VLSTRACK) models were compared using two recent mesoscale field datasets—the Dipole Pride 26 (DP26) and the Overland Along-wind Dispersion (OLAD). Both field experiments involved instantaneous releases of sulfur hexafluoride tracer gas in a mesoscale region with desert basins and mountains. DP26 involved point sources, and OLAD involved line sources. Networks of surface wind observations and special radiosonde and pilot balloon soundings were available, and tracer concentrations were observed along lines of whole-air samplers and some fast-response instruments at distances up to 20 km. The models were evaluated using the maximum 3-h dosage (concentration integrated over time) along a sampling line. It was found that the solutions were highly dependent upon the di...

Lagrangian stochastic modeling of a fluctuating plume in the convective boundary layer

A Lagrangian stochastic model of dispersion in the atmospheric convective boundary layer is derived. The turbulence is assumed to be non-homogeneous and non-Gaussian in the vertical direction, homogeneous and Gaussian in the horizontal directions. The model describes the evolution of an airborne contaminant in terms of motion of its centroid and diffusion of particles relative to the centroid. The vertical motion of the centroid is simulated using non-stationary Lagrangian stochastic equations incorporating a time-dependent filter for the turbulent energy. The filtering procedure removes the contribution of turbulent eddies smaller than the cloud instantaneous size to the meandering. The instantaneous dispersion of particles relative to the centroid is parameterized using inertial range similarity formulae. The model is applied to the case of continuous stationary releases and the crosswind dispersion is calculated according to Taylors theory. The model satisfies the well-mixed condition and is capable of calculating all moments of concentration. Mean concentration and concentration fluctuations for several source heights are simulated and compared with laboratory observations.

Use of Salt Lake City URBAN 2000 Field Data to Evaluate the Urban Hazard Prediction Assessment Capability (HPAC) Dispersion Model

After the terrorist incidents on 11 September 2001, there is a greatly heightened concern about the potential impacts of acts of terrorism involving the atmospheric release of chemical, biological, radiological, and nuclear (CBRN) materials in urban areas. In response to the need for an urban CBRN model, the Urban Hazard Prediction Assessment Capability (Urban HPAC) transport and dispersion model has been developed. Because HPAC is widely used by the Department of Defense community for planning, training, and operational and tactical purposes, it is of great importance that the new model be adequately evaluated with urban datasets to demonstrate its accuracy. This paper describes evaluations of Urban HPAC using the “URBAN 2000” urban tracer and meteorological field experiment data from Salt Lake City, Utah. Four Urban HPAC model configuration options and five plausible meteorological input data options—ranging from data-sparse to data-rich scenarios—were considered in the study, thus leading to a total of 20 possible model combinations. For the maximum concentrations along each sampling arc for each intensive operating period (IOP), the 20 Urban HPAC model combinations gave consistent mean overpredictions of about 50%, with a range over the 20 model combinations from no overprediction to a factor-of-4 overprediction in the mean. The median of the random scatter for the 20 model combinations was about a factor of 3 of the mean, with a range over the 20 model combinations between a factor of about 2 and 9. These performance measures satisfy previously established acceptance criteria for dispersion models.

Measurements of Turbulence and Dispersion in Three Idealized Urban Canopies with Different Aspect Ratios and Comparisons with a Gaussian Plume Model

Water-tunnel measurements of velocity, turbulence and scalar concentration for three model urban canopies with aspect ratios Ar of building height-to-width of 0.25, 1 and 3 are presented. The measurements for the canopies with Ar = 1 and 3 are new, while the measurements for Ar = 0.25 were previously published. A passive scalar was continuously released from a near-ground point source, and the concentration was measured at several distances from the source and at different heights above the ground. Plume spreads, concentration and distance from the source were non-dimensionalized using length, time and velocity scales reflecting the geometry of the buildings. The scaling collapses the data for all aspect ratios and is valid when the vertical extent of the plume is smaller than the canopy height. The observed plume spreads are compared with analytical relations, which predict linear growth in both transverse and vertical directions. The observed mean concentration is compared with a Gaussian dispersion model that predicts a −2 power-law decay with distance from the source.

Monte Carlo source detection of atmospheric emissions and error functions analysis

A Monte Carlo algorithm is iteratively run to identify candidate sources for atmospheric releases. The values of the ground measurements of concentration are synthetically generated by a benchmark simulation of a Gaussian dispersion model. At each iteration, a Gaussian reflected plume model is applied to compute the dispersion from a candidate source, and the resulting concentrations are compared with the measurements at fixed points on the ground. Iterative algorithms for detection of atmospheric release sources are based on the optimization of an error function between numerical simulations and observations. However, the definition of error between observations and simulations by an atmospheric dispersion model is not univocal. In this paper, the comparisons are made using various error functions. The characteristics of different error functions between model predictions and sensor measurements are investigated, with a statistical analysis of the results. Sensitivity to domain size and addition of random noise to the measurements are also investigated.

A non-hybrid method for the PDF equations of turbulent flows on unstructured grids

In probability density function (PDF) methods of turbulent flows, the joint PDF of several flow variables is computed by numerically integrating a system of stochastic differential equations for Lagrangian particles. A set of parallel algorithms is proposed to provide an efficient solution of the PDF transport equation modeling the joint PDF of turbulent velocity, frequency and concentration of a passive scalar in geometrically complex configurations. In the vicinity of walls the flow is resolved by an elliptic relaxation technique down to the viscous sublayer, explicitly modeling the high anisotropy and inhomogeneity of the low-Reynolds-number wall region without damping or wall-functions. An unstructured Eulerian grid is employed to extract Eulerian statistics, to solve for quantities represented at fixed locations of the domain (i.e., the mean pressure and the elliptic relaxation tensor) and to track particles. All three aspects regarding the grid make use of the finite element method employing the simplest linear shapefunctions. To model the small-scale mixing of the transported scalar, the interaction by exchange with the conditional mean (IECM) model is adopted. An adaptive algorithm to compute the velocity-conditioned scalar mean is proposed that homogenizes the statistical error over the sample space with no assumption on the shape of the underlying velocity PDF. Compared to other hybrid particle-in-cell approaches for the PDF equations, the current methodology is consistent without the need for consistency conditions. The algorithm is tested by computing the dispersion of passive scalars released from concentrated sources in two different turbulent flows: the fully developed turbulent channel flow and a street canyon (or cavity) flow. Algorithmic details on estimating conditional and unconditional statistics, particle tracking and particle-number control are presented in detail. Relevant aspects of performance and parallelism on cache-based shared memory machines are discussed.

Probability density function modeling of scalar mixing from concentrated sources in turbulent channel flow

Dispersion of a passive scalar from concentrated sources in fully developed turbulent channel flow is studied with the probability density function (PDF) method. The joint PDF of velocity, turbulent frequency and scalar concentration is represented by a large number of Lagrangian particles. A stochastic near-wall PDF model combines the generalized Langevin model of Haworth and Pope [Phys. Fluids 29, 387 (1986)] with Durbins [J. Fluid Mech. 249, 465 (1993)] method of elliptic relaxation to provide a mathematically exact treatment of convective and viscous transport with a nonlocal representation of the near-wall Reynolds stress anisotropy. The presence of walls is incorporated through the imposition of no-slip and impermeability conditions on particles without the use of damping or wall-functions. Information on the turbulent time scale is supplied by the gamma-distribution model of van Slooten et al. [Phys. Fluids 10, 246 (1998)]. Two different micromixing models are compared that incorporate the effect ...

A Simple Relative Dispersion Model for Concentration Fluctuations in Contaminant Clouds

The relative dispersion process for clouds of contaminant in generic atmospheric flow is considered. The properties of the separation distance for pairs of particles are simplified by implicitly averaging over the spatial domain of the dispersing cloud. Representative statistics and simplified sets of measurements for characterizing two-particle dispersion in complex flows are identified. A Lagrangian stochastic model of relative dispersion equivalent to processes in homogeneous and isotropic turbulence at high Reynolds numbers is derived. The model uses a new formulation for parameterizing the acceleration of separation, satisfies the criterion of conserving a well-mixed distribution of particle separations, and accounts explicitly for non-Gaussian statistics of the turbulence velocity differences. The results are in very good agreement with similarity theory in the inertial range and are consistent with uncorrelated velocities at length scales larger than the turbulence integral scale. The model is applied to the estimation of fluctuating concentration fields, which is relevant for representing the relative dispersion part of popular meandering plume and puff approaches. The dependence of mean-square concentration and concentration fluctuations on the source size is eliminated via a new scaling law for the time, which in fact determines a universal behavior for the concentration field. Simple formulas are derived that are consistent with previous theories, and they are successfully tested against numerical simulations.

Joint PDF Modelling of Turbulent Flow and Dispersion in an Urban Street Canyon

The joint probability density function (PDF) of turbulent velocity and concentration of a passive scalar in an urban street canyon is computed using a newly developed particle-in-cell Monte Carlo method. Compared to moment closures, the PDF methodology provides the full one-point one-time PDF of the underlying fields containing all higher moments and correlations. The small-scale mixing of the scalar released from a concentrated source at the street level is modelled by the interaction by exchange with the conditional mean (IECM) model, with a micro-mixing time scale designed for geometrically complex settings. The boundary layer along no-slip walls (building sides and tops) is fully resolved using an elliptic relaxation technique, which captures the high anisotropy and inhomogeneity of the Reynolds stress tensor in these regions. A less computationally intensive technique based on wall functions to represent the boundary layers and its effect on the solution are also explored. The calculated statistics are compared to experimental data and large-eddy simulation. The present work can be considered as the first example of computation of the full joint PDF of velocity and a transported passive scalar in an urban setting. The methodology proves successful in providing high level statistical information on the turbulence and pollutant concentration fields in complex urban scenarios.

Source Term Estimation for the 2011 Fukushima Nuclear Accident

A new methodology is presented for the reconstruction of an unsteady release rate of an atmospheric contaminant, based on atmospheric transport and dispersion models, concentration measurements, and stochastic search techniques. The methodology is applied to reconstruct the radiation release rate for the March 2011 Fukushima nuclear accident.The observed radiation data were retrieved from 218 stations located in 17 Japanese prefectures. The dispersion simulations are performed using the SCIPUFF model, using model vertical profiles and ground meteorological data. The non-stationary time-series of the Fukushima release rate is determined for a period of 5 days with a 2-h resolution.