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Roseane A.S. Albani

Bio: Roseane A.S. Albani is an academic researcher from Federal University of Rio de Janeiro. The author has contributed to research in topics: Markov chain Monte Carlo & Medicine. The author has an hindex of 1, co-authored 1 publications receiving 17 citations.

Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors presented a numerical model to study pollutant dispersion in the atmospheric boundary layer (ABL) by accounting for the mechanisms of advection by the mean wind in the horizontal direction, turbulent diffusion in the vertical direction to ground surface, dry deposition, and radioactive decay.

20 citations

Posted ContentDOI
TL;DR: In this paper , a parsimonious, yet effective, susceptible-exposed-infected-removed-type model that incorporates the time change in the transmission and death rates was proposed.
Abstract: We propose a parsimonious, yet effective, susceptible–exposed–infected–removed-type model that incorporates the time change in the transmission and death rates. The model is calibrated by Tikhonov-type regularization from official reports from New York City (NYC), Chicago, the State of São Paulo, in Brazil and British Columbia, in Canada. To forecast, we propose different ways to extend the transmission parameter, considering its estimated values. The forecast accuracy is then evaluated using real data from the above referred places. All the techniques accurately provided forecast scenarios for periods 15 days long. One of the models effectively predicted the magnitude of the four waves of infections in NYC, including the one caused by the Omicron variant for periods of 45 days using out-of-sample data.

3 citations

Journal ArticleDOI
TL;DR: In this paper , the authors presented a methodology to identify multiple pollutant sources in the atmosphere that combines a data-driven dispersion model with Bayesian inference and uncertainty quantification.

1 citations

Journal ArticleDOI
TL;DR: In this paper , a time-dependent model was proposed to estimate the source parameters of multiple point releases using an adaptive Monte Carlo Markov Chain (MCMC) algorithm and a Fourier series that best fits the wind field time series of experimental data.
Abstract: . Source identification methodologies use inverse problems techniques combined with a dispersion model and observational data to estimate relevant source parameters. This work proposes a time-dependent model to estimate source parameters of multiple point releases. The forward problem or dispersion model accounts for the time variation of the wind field using a Fourier series that best fits the wind field time series of the experimental data. The source parameters are estimated by an adaptive Monte Carlo Markov Chain algorithm.

Cited by
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Journal ArticleDOI
TL;DR: In this article, a new method is proposed for estimating the rate of fugitive emissions of particulate matter from multiple time-dependent sources via measurements of deposition and concentration, and a forward model based on a Gaussian plume solution is used.

27 citations

Journal ArticleDOI
TL;DR: The second stage of the field tests conducted by a joint venture between the University of Sao Paulo and the Universitat Politecnica de Catalunya was established to investigate the performance of CFD tools when analyzing cloud dispersion of hazardous substances by means of ad hoc experimentation as discussed by the authors.
Abstract: Dispersion of hazardous gas releases represents a major threat to health and to the environment; therefore, the prediction of the dispersion features raises great interest. In recent years, with the increase in computational capacity, the interest in Computational Fluid Dynamics (CFD) tools to evaluate dispersion analysis has increased. With the growing use of CFD tools to perform dispersion analysis in different scenarios, it is imperative to amplify the availability of experimental data in order to allow validations studies to contribute to understanding the real capacity of CFD tools to properly represent real cases. The second stage of the field tests conducted by a joint venture between the University of Sao Paulo and the Universitat Politecnica de Catalunya was established to investigate the performance of CFD tools when analyzing cloud dispersion of hazardous substances by means of ad-hoc experimentation. The experiments consisted of CO2 clouds formation and dispersion tracking of releases of up to 0.85 kg s−1 of about 40 s of duration in a 600-m2discharge area. We provide a description of the tests and the main results of the simulation using the FLACS software; the peak concentrations for 51 sensors placed at the dispersion cloud path are provided here and compared with CFD simulations. In general terms, the CFD simulator presented good performance; all the statistical performance measures were well within the acceptable range. However, the simulator performance presented sensitivity to the wind profile, especially when cross wind occurs.

17 citations

Journal ArticleDOI
TL;DR: In this paper, a large commercial installation scale atmospheric ion generator based on corona plasma discharges, experimental monitoring and numerical modeling of the parameters and range of the atmospheric ions, and application of the generated ions to produce charged aerosols and induce precipitation at a scale of a large cloud chamber.
Abstract: . Artificial rain is explored as a remedy to climate change caused farmland drought and bushfires. Increasing the ion density in the open air is an efficient way to generate charged nuclei from atmospheric aerosols and induce precipitation or eliminate fog. Here we report on the development of the large commercial installation scale atmospheric ion generator based on corona plasma discharges, experimental monitoring and numerical modeling of the parameters and range of the atmospheric ions, and application of the generated ions to produce charged aerosols and induce precipitation at a scale of a large cloud chamber. The coverage area of the ions generated by the large corona discharge installation with the 7.2 km long wire electrode and applied voltage of −90 kV is studied under prevailing weather conditions including wind direction and speed. By synergizing over 300 000 localized corona discharge points, we demonstrate a substantial decrease of the decay of ions compared to a single corona discharge point in the open air, leading to a large-scale (30 m × 23 m × 90 m) ion coverage. Once aerosols combine with the generated ions, charged nuclei are produced. The higher wind speed has led to the larger areas covered by the plasma generated ions. The cloud chamber experiments (relative humidity 130 ± 10 %) suggest that the charged aerosols generated by ions with the density of ~ 104/cm3 can accelerate the settlement of moisture by 38 %. These results are promising for the development of large-scale installations for the effective localized control of atmospheric phenomena.

12 citations

Journal ArticleDOI
TL;DR: A methodology to estimate single and multiple emission sources of atmospheric contaminants by combining hybrid metaheuristic/gradient-descent optimization techniques and Tikhonov-type regularization, which is highly versatile and presents accurate results under different contexts with a competitive computational cost.

11 citations

Journal ArticleDOI
TL;DR: In this paper, a hybrid unsteady Reynolds averaged Navier Stokes (RANS) and large eddy simulation (LES) numerical approach is applied with a new mixed scale sub-grid parameterization technique in the commercial ANSYS Fluent software in order to simulate the buoyant plume behavior in a turbulent crossflow.

9 citations