Formulation and analysis of a diffusion-velocity particle model for transport-dispersion equations

The modelling of diffusive terms in particle methods is a delicate matter and several models were proposed in the literature to take such terms into account. The diffusion velocity method (DVM), originally designed for the diffusion of passive scalars, turns diffusive terms into convective ones by expressing them as a divergence involving a so-called diffusion velocity. In this paper, DVM is extended to the diffusion of vectorial quantities in the three-dimensional Navier–Stokes equations, in their incompressible, velocity–vorticity formulation. The integration of a large eddy simulation (LES) turbulence model is investigated and a DVM general formulation is proposed. Either with or without LES, a novel expression of the diffusion velocity is derived, which makes it easier to approximate and which highlights the analogy with the original formulation for scalar transport. From this statement, DVM is then analysed in one dimension, both analytically and numerically on test cases to point out its good behaviour.

Simulations of droplet dispersion in the wakes of cylinders and icing tunnel spray bars

Simulations of droplet dispersion behind cylinder wakes and downstream of icing tunnel spray bars were conducted. In both cases, a range of droplet sizes were investigated numerically with a Lagrangian particle trajectory approach while the turbulent air flow was investigated with a hybrid Reynolds-Averaged Navier-Stokes/Large-Eddy Simulations approach scheme. In the first study, droplets were injected downstream of a cylinder at sub-critical conditions (i.e. with laminar boundary layer separation). A stochastic continuous random walk (CRW) turbulence model was used to capture the effects of sub-grid turbulence. Small inertia droplets (characterized by small Stokes numbers) were affected by both the large-scale and small-scale vortex structures and closely followed the air flow, while exhibiting a dispersion consistent with that of a scalar flow field. Droplets with intermediate Stokes numbers were centrifuged by the vortices to the outer edges of the wake, yielding an increased dispersion. Large Stokes number droplets were found to be less responsive to the vortex structures and exhibited the least dispersion. Particle concentration was also correlated with vorticity distribution which yielded preferential bias effects as a function of different particle sizes. This trend was qualitatively similar to results seen in homogenous isotropic turbulence, though the influence of particle inertia was less pronounced for the cylinder wake case. A similar study was completed for droplet dispersion within the Icing Research Tunnel (IRT) at the NASA Glenn Research Center, where it is important to obtain a nearly uniform liquid water content (LWC) distribution in the test section (to recreate atmospheric icing conditions).. For this goal, droplets are diffused by the mean and turbulent flow generated from the nozzle air jets, from the upstream spray bars, and from the vertical strut wakes. To understand the influence of these three components, a set of simulations was conducted with a sequential inclusion of these components. Firstly, a jet in an otherwise quiescent airflow was simulated to capture the impact of the air jet on flow turbulence and droplet distribution, and the predictions compared well with experimental results. The effects of the spray bar wake and vertical strut wake were then included with two more simulation conditions, for which it was found that the air jets were the primary driving force for droplet dispersion, i.e. that the spray bar and vertical strut wake effects were secondary.

In situ characterization of sediment oxygen demand across the spectrum of non-resuspension to full resuspension with varying bed shear stress

Sediment oxygen demand (SOD) can be a significant oxygen sink in various types of water bodies, particularly slow-moving waters with substantial organic sediment accumulation. In most settings where SOD is a concern, the prevailing hydraulic conditions are such that the impact of sediment resuspension on SOD is not considered. However, in the case of Bubbly Creek in Chicago, Illinois, the prevailing slack water conditions are interrupted by infrequent intervals of very high flow rates associated with pumped combined sewer overflow (CSO) during intense hydrologic events. These events can cause resuspension of the highly organic, nutrient-rich bottom sediments, resulting in precipitous drawdown of dissolved oxygen (DO) in the water column. While many past studies have addressed the dependence of SOD on near-bed velocity and bed shear stress prior to the point of sediment resuspension, there has been limited research that has attempted to characterize the complex and dynamic phenomenon of resuspended-sediment oxygen demand. To address this issue, a new in situ experimental apparatus referred to as the U of I Hydrodynamic SOD Sampler was designed to achieve a broad range of velocities and associated bed shear stresses. This allowed SOD to be analyzed across the spectrum of no sediment resuspension associated with low velocity/ bed shear stress through full sediment resuspension associated with high velocity / bed shear stress. The current study split SOD into two separate components: (1) SODNR is the sediment oxygen demand associated with non-resuspension conditions and is a surface sink calculated using traditional methods to yield a value with units (g/m2/day); and (2) SODR is the oxygen demand associated with resuspension conditions, which is a volumetric sink most accurately characterized using non-traditional methods and units that reflect suspension in the water column (mg/L/day). In the case of resuspension, the suspended sediment concentration was analyzed as a function of bed shear stress, and a formulation was developed to characterize SODR as a function of suspended sediment concentration in a form similar to first-order biochemical oxygen demand (BOD) kinetics with Monod DO term. The results obtained are intended to be implemented into a numerical model containing hydrodynamic, sediment transport, and water quality components to yield oxygen demand varying in both space and time for specific flow events. Such implementation will allow evaluation of proposed Bubbly Creek water quality improvement alternatives which take into account the impact of SOD under various flow conditions. Although the findings were based on experiments specific to the conditions in Bubbly Creek, the techniques and formulations developed in this study should be applicable to similar sites.

MDP periodically time-varying convolutional codes

In this paper we use some classical ideas from linear systems theory to analyse convolutional codes. In particular, we exploit input-state-output representations of periodic linear systems to study periodically time-varying convolutional codes. In this preliminary work we focus on the column distance of these codes and derive explicit necessary and sufficient conditions for an (n, 2, 1) periodically time-varying convolutional code to have Maximum Distance Profile (MDP).

Heat dissipation from carbon nano-electronics

The incorporation of graphitic compounds such as carbon nanotubes (CNTs) and graphene into nano-electronic device packaging holds much promise for waste heat management given their high thermal conductivities. However, as these graphitic materials must be used in together with other semiconductor/insulator materials, it is not known how thermal transport is affected by the interaction. Using different simulation techniques, in this thesis, we evaluate the thermal transport properties - thermal boundary conductance (TBC) and thermal conductivity - of CNTs and single-layer graphene in contact with an amorphous SiO2 (a-SiO2) substrate. First, the theoretical methodologies and concepts used in our simulations are presented. In particular, two concepts are described in detail as they are necessary for the understanding of the subsequent chapters. The first is the linear response Green-Kubo (GK) theory of thermal boundary conductance (TBC), which we develop in this thesis, and the second is the spectral energy density method, which we use to directly compute the phonon lifetimes and thermal transport coefficients. After we set the conceptual foundations, the TBC of the CNT-SiO2 interface is computed using non- equilibrium molecular dynamics (MD) simulations and the new Green-Kubo method that we have developed. Its dependence on temperature, the strength of the interaction with the substrate, and tube diameter are evaluated. To gain further insight into the phonon dynamics in supported CNTs, the scattering rates are computed using the spectral energy density (SED) method. With this method, we are able to distinguish the different scattering mechanisms (boundary and CNT-substrate phonon-phonon) and rates. The phonon lifetimes in supported CNTs are found to be reduced by contact with the substrate and we use that lifetime reduction to determine the change in CNT thermal conductivity. Next, we examine thermal transport in graphene supported on SiO2. The phonon contribution to the TBC of the graphene-SiO2 interface is computed from MD simulations and found to agree well with experimentally measured values. We derive the theory of remote phonon scattering of graphene electrons and compute the heat transfer coefficient dependence on doping level and temperature. The thermal boundary conductance from remote phonon scattering is found to be an order of magnitude smaller than that of the phonon contribution. The in-plane thermal conductivity of supported graphene is calculated from MD simulations. The experimentally measured order of magnitude reduction in thermal conductivity is reproduced in our simulations. We show that this reduction is due to the damping of the flexural (ZA) modes. By varying the interaction between graphene and the substrate, the ZA modes hybridize with the substrate Rayleigh modes and the dispersion of the hybridized modes is found to linearize in the strong coupling limit, leading to an increased thermal conductance in the composite structure.

Toxin and Growth Responses of the Neurotoxic Dinoflagellate Vulcanodinium rugosum to Varying Temperature and Salinity

Vulcanodinium rugosum, a recently described species, produces pinnatoxins. The IFR-VRU-01 strain, isolated from a French Mediterranean lagoon in 2010 and identified as the causative dinoflagellate contaminating mussels in the Ingril Lagoon (French Mediterranean) with pinnatoxin-G, was grown in an enriched natural seawater medium. We tested the effect of temperature and salinity on growth, pinnatoxin-G production and chlorophyll a levels of this dinoflagellate. These factors were tested in combinations of five temperatures (15, 20, 25, 30 and 35 °C) and five salinities (20, 25, 30, 35 and 40) at an irradiance of 100 µmol photon m−2 s−1. V. rugosum can grow at temperatures and salinities ranging from 20 °C to 30 °C and 20 to 40, respectively. The optimal combination for growth (0.39 ± 0.11 d−1) was a temperature of 25 °C and a salinity of 40. Results suggest that V. rugosum is euryhaline and thermophile which could explain why this dinoflagellate develops in situ only from June to September. V. rugosum growth rate and pinnatoxin-G production were highest at temperatures ranging between 25 and 30 °C. This suggests that the dinoflagellate may give rise to extensive blooms in the coming decades caused by the climate change-related increases in temperature expected in the Mediterranean coasts.

Characterisation and quantification of changes in odorants from litter headspace of meat chickens fed diets varying in protein levels and additives

The effect of dietary crude protein (CP) and additives on odor flux from meat chicken litter was investigated using 180 day-old Ross 308 male chicks randomly allocated to five dietary treatments with three replicates of 12 birds each. A 5 × 3 factorial arrangement of treatments was employed. Factors were: diet (low CP, high CP, high CP+antibiotic, high CP+probiotic, high CP+saponin) and age (15, 29, 35 days). The antibiotic used was Zn bacitracin, the probiotic was a blend of three Bacillus subtilis strains and the saponin came from a blend of Yucca and Quillaja. Odorants were collected from litter headspace with a flux hood and measured using selective ion flow tube mass spectrometry (SIFT-MS). Litter moisture, water activity (Aw), and litter headspace odorant concentrations were correlated. The results showed that low CP group produced lower flux of dimethyl amine, trimethyl amine, H2S, NH3, and phenol in litter compared to high CP group (P < 0.05). Similarly, high CP+probiotic group produced lower flux of H2S (P < 0.05) and high CP+saponin group produced lower flux of trimethylamine and phenol in litter compared to high CP group (P < 0.05). The dietary treatments tended (P = 0.065) to have higher flux of methanethiol in high CP group compared to others. There was a diet × age interaction for litter flux of diacetyl, 3-hydroxy-2-butanone (acetoin), 3-methyl-1-butanol, 3-methylbutanal, ethanethiol, propionic acid, and hexane (P < 0.05). Concentrations of diacetyl, acetoin, propionic acid, and hexane in litter were higher from low CP group compared to all other treatments on d 35 (P < 0.05) but not on d 15 and 29. A high litter moisture increased water activity (P < 0.01) and favored the emissions of methyl mercaptan, hydrogen sulfide, dimethyl sulfide, ammonia, trimethyl amine, phenol, indole, and 3-methylindole over others. Thus, the low CP diet, Bacillus subtilis based probiotic and the blend of Yucca/Quillaja saponin were effective in reducing the emissions of some key odorants from meat chicken litter.

Quantification of air quality in space and time and its effects on health

The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.

Different Multimorbidity Measures Result in Varying Estimated Levels of Physical Quality of Life in Individuals with Multimorbidity: A Cross-Sectional Study in the General Population

International audience

Analysis of the four wave mixing effect (FWM) in a dispersion decreasing fiber (DDF) for a WDM system

We did a numerical investigation of the propagation of short light pulses in the region of 1.55 mu m and the conversion efficiency (CE) for the four wave mixing generation (FWM) of ordinary and dispersion decreasing fibers for use in wavelength division multiplexing (WDM) systems, Our simulations studies three different profiles, linear, hyperbolic. and constant, One conclude that for all the profiles there is decrease of the conversion efficiency with the increase in the channel separation. The hyperbolic profile present a higher efficiency of around 1000 above in magnitude compared with the others profiles at 0.2 nm of channel separation. We calculate the conversion efficiency versus the fiber length for the three profiles. The conversion efficiency for the hyperbolic profile is higher when compared to the constant and linear profiles. The other interesting point of the hyperbolic profile is that the increase of the CE in the beginning of the fiber does not show my oscillation in the CE value (log eta), which was observed for the constant and linear profiles. For all the profiles there is an increase of the conversion efficiency with the increase of the pump power. The compression factor C-i for the generated FWM signal at omega(3) was measured along the DDF's and the constant profile fibers. One can conclude that with the use of decreasing dispersion profile (DDF) fibers one can have a control of the (CE) conversion efficiency and the compression factor of the four wave mixing (FWM) generation in WDM systems. (c) 2005 Elsevier B.V. All rights reserved.

Aperture effects on the oxygen abundance determinations from Califa data

This paper aims to provide aperture corrections for emission lines in a sample of spiral galaxies from the Calar Alto Legacy Integral Field Area Survey (CALIFA) database. In particular, we explore the behavior of the log([O III] λ5007/Hβ)/([N II] λ6583/Hα) (O3N2) and log[N II] lambda 6583/Hα (N2) flux ratios since they are closely connected to different empirical calibrations of the oxygen abundances in star-forming galaxies. We compute the median growth curves of Hα, Hα/Hβ, O3N2, and N-2 up to 2.5R(50) and 1.5 disk R-eff. These distances cover most of the optical spatial extent of the CALIFA galaxies. The growth curves simulate the effect of observing galaxies through apertures of varying radii. We split these growth curves by morphological types and stellar masses to check if there is any dependence on these properties. The median growth curve of the Hα flux shows a monotonous increase with radius with no strong dependence on galaxy inclination, morphological type, and stellar mass. The median growth curve of the Hα/HβH ratio monotonically decreases from the center toward larger radii, showing for small apertures a maximum value of ≈10% larger than the integrated one. It does not show any dependence on inclination, morphological type, and stellar mass. The median growth curve of N-2 shows a similar behavior, decreasing from the center toward larger radii. No strong dependence is seen on the inclination, morphological type, and stellar mass. Finally, the median growth curve of O3N2 increases monotonically with radius, and it does not show dependence on the inclination. However, at small radii it shows systematically higher values for galaxies of earlier morphological types and for high stellar mass galaxies. Applying our aperture corrections to a sample of galaxies from the SDSS survey at 0.02 ≤ z ≤ 0.3 shows that the average difference between fiber-based and aperture-corrected oxygen abundances, for different galaxy stellar mass and redshift ranges, reaches typically to ≈11%, depending on the abundance calibration used. This average difference is found to be systematically biased, though still within the typical uncertainties of oxygen abundances derived from empirical calibrations. Caution must be exercised when using observations of galaxies for small radii (e.g., below 0.5 R_eff) given the high dispersion shown around the median growth curves. Thus, the application of these median aperture corrections to derive abundances for individual galaxies is not recommended when their fluxes come from radii much smaller than either R_50 or R_eff.

Motion compensation with minimal residue dispersion matching criteria

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnoloigia, 2016.

Rheological Properties of a Sodium Bentonite and Lactose Aqueous Dispersion

Aim of this paper is show the viscosity measure of a sodium bentonite-water-lactose mixture and your rheological behaviour. This analysis showed the formation of tridimensional structure type and formation of stratified silicate/lactose, this occurred due to different concentrations of organic products into mixture and due to a difference of rotation during viscosity measument. Formation of networks is a consequence of the attraction between the silicate layers in water-lactose mixture. In the present work aqueous solutions of lactose with concentration of 7%, 5%, 3%, 1% and 0% (wt %) were used.

Dynamics and Heterogeneity of Pb(II) Binding by SiO2 Nanoparticles in an Aqueous Dispersion

Pb(II) binding by SiO2 nanoparticles in an aqueous dispersion was investigated under conditions where the concentrations of Pb2+ ions and nanoparticles are of similar magnitude. Conditional stability constants (log K) obtained at different values of pH and ionic strength varied from 4.4 at pH 5.5 and I = 0.1 M to 6.4 at pH 6.5 and I = 0.0015 M. In the range of metal to nanoparticle ratios from 1.6 to 0.3, log K strongly increases, which is shown to be due to heterogeneity in Pb(II) binding. For an ionic strength of 0.1 M the Pb2+/SiO2 nanoparticle system is labile, whereas for lower ionic strengths there is loss of lability with increasing pH and decreasing ionic strength. Theoretical calculations on the basis of Eigen-type complex formation kinetics seem to support the loss of lability. This is related to the nanoparticulate nature of the system, where complexation rate constants become increasingly diffusion controlled. The ion binding heterogeneity and chemodynamics of oxidic nanoparticles clearly need further detailed research.