Hydrodynamic numerical simulation at the mouths of the Parana and Uruguay rivers and the upper Rio de la Plata estuary: A realistic boundary condition

A hydrodynamic numerical study at the mouths of the Paraná and Uruguay rivers and the upper Río de la Plata is presented in this paper. Water Quality Mapping numerical model was implemented and realistic and very simple boundary conditions were specially developed for this complex estuarial system. A set of numerical experiments were carried out using different constant discharges for the Paraná and Uruguay rivers but unrealistic currents were generated. In order to obtain more realistic results, a set of numerical simulations were carried out imposing water level timeseries at the open boundaries. M₂, S₂, K₁ and O₁ harmonic constants were used to generate water levels at Zárate (Paraná river), Nueva Palmira (Uruguay river) and the eastern boundary of the domain (La Plata–Colonia). A mean water level equal to zero was set between La Plata and Colonia. Positive mean water levels (0.3–0.4 m) were imposed at Zárate and Nueva Palmira to simulate the hydraulic slope of both rivers and, consequently, to generate realistic and unsteady discharges. These boundary conditions, built by means of the addition of a mean water level and the astronomical tide, significantly improve the simulated currents at the northernmost region of the RDP estuary.     

Investigations of shear free turbulent diffusion in a rotating frame

We reconsider the problem of shear free turbulent diffusion in a rotating frame, rotating about x₁. Shear free turbulence is generated at a vibrating grid in the x₂–x₃ plane and diffuses away from the grid in x₁ direction. An important property of this flow case is that there is no mean flow‐velocity. With the help of Lie‐group methods Reynolds‐stress transport models can be analyzed for this kind of flow in a rotating frame. From the analysis it can be found, that the turbulent diffusion only influences a finite domain. Implicating this solution in the model equations shows that even fully nonlinear Reynolds‐stress transport models (non‐linear in the Reynolds‐stresses for the pressure‐strain model) are insensitive to rotation for this type of flow. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

The effects of bed form roughness on total suspended load via the Lattice Boltzmann Method

Bed forms in natural rivers and man-made channels provide the dominant contribution to overall flow resistance and hence significantly affect sediment transport rate. Many laboratory experiments and field observations have been conducted on bed forms, and it was found that theoretical flat-bed assumptions do not give the correct estimation for the total suspended load (TSL). In this study, we present a systematic numerical investigation of turbulent open-channel flows over bed forms using the Lattice Boltzmann Method (LBM). A static Smagorinsky model is incorporated into LBM to account for turbulence, and the dynamic interface between fluid and air is captured by a free-surface model. The time-averaged flow velocity, turbulence intensity and Reynolds shear stress in LBM simulations show an excellent agreement with the available experimental data. In addition, the coherent flow structures induced by the bed forms qualitatively agree with previous numerical results from Large Eddy Simulations based the Navier–Stokes equations. We then proceed to investigate the effects of bed form roughness, quantified by the total friction factor f_T, on sediment transport. It is found that the prediction of the TSL based on the theoretical flat-bed assumptions may lead to an overestimation of up to 30%, depending on the bed form roughness. In addition, the normalized TSL is linearly proportional to f_T and nearly inversely proportional to the ratio of downward settling velocity and upward turbulence induced diffusion. Our work proposes a general law linking these quantities to estimate the TSL, which has the potential for a more efficient and accurate engineering design of man-made channels and improved river management.     

Survey of mathematical programming models in air pollution management

This paper surveys the current state of the literature in management science/operations research approaches to air pollution management. After introducing suitable background we provide some of the institutional and legal framework needed to understand the continuing regulatory efforts in United States. Attention is then turned to mathematical programming models ranging from fairly simple deterministic linear programs to quite sophisticated stochastic models which have appeared in the literature dealing with these topics. This is followed by extensions reflecting some of the work we have undertaken in association with the Texas Natural Resource Conservation Commission, a regulatory agency in Texas. Application and potential use of models is the central theme of this survey. Issues for future research are presented at the end and an extensive list of publications is provided in the references at the end of the article.Principal air quality issues of local, national, and international concern are listed below in increasing order of difficulty based on the number of different types of pollutants and problems in quantification of the risks the pollutants pose:

• 1.1. Stratospheric ozone depletion: one relatively easily controllable class of trace gases - ozone depleting chemicals, or ODCs, principally chloroflurocarbons (CFCs) — with relatively well quantified risks;
• 2.2. Criteria pollutants: six common pollutants — ozone (O₃), carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), lead (Pb), and particulate matter less than 10 microns in size (PM10) — regulated since 1970 in the U.S. and presenting relatively well quantified risks;
• 3.3. Acid precipitation: two relatively easily controllable classes of trace gases — oxides of nitrogen (NO_x) and oxides of sulfur (SO_x) with relatively well quantified risks;
• 4.4. Global warming/climate change: a few difficult to control trace gases — principally carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O), and CFCs — with highly uncertain risks;
• 5.5. Toxics or HAPS (hazardous air pollutants): hundreds of types of gaseous chemicals and particles with uncertain risks;
• 6.6. Somewhat dated, but nevertheless useful, is the following reference: Glossary on Air Pollution (Copenhagen, World Health Organization, 1980).

     

Forward and reverse representations for Markov chains

In this paper we carry over the concept of reverse probabilistic representations developed in Milstein, Schoenmakers, Spokoiny [G.N. Milstein, J.G.M. Schoenmakers, V. Spokoiny, Transition density estimation for stochastic differential equations via forward–reverse representations, Bernoulli 10 (2) (2004) 281–312] for diffusion processes, to discrete time Markov chains. We outline the construction of reverse chains in several situations and apply this to processes which are connected with jump–diffusion models and finite state Markov chains. By combining forward and reverse representations we then construct transition density estimators for chains which have root-N$N$ accuracy in any dimension and consider some applications.     

One-step Taylor–Galerkin methods for convection–diffusion problems

Third and fourth order Taylor–Galerkin schemes have shown to be efficient finite element schemes for the numerical simulation of time-dependent convective transport problems. By contrast, the application of higher-order Taylor–Galerkin schemes to mixed problems describing transient transport by both convection and diffusion appears to be much more difficult. In this paper we develop two new Taylor–Galerkin schemes maintaining the accuracy properties and improving the stability restrictions in convection–diffusion. We also present an efficient algorithm for solving the resulting system of the finite element method. Finally we present two numerical simulations that confirm the properties of the methods.     

CFD of turbulent transport of particles behind a backward-facing step using a new model—k-ε-Sp

The k-ε-S_p model, describing two-dimensional gas–solid two-phase turbulent flow, has been developed. In this model, the diffusion flux and slip velocity of solid particles are introduced to represent the particle motion in two-phase flow. Based on this model, the gas–solid two-phase turbulent flow behind a vertical backward-facing step is simulated numerically and the turbulent transport velocities of solid particles with high density behind the step are predicted. The numerical simulation is validated by comparing the results of the numerical calculation with two other two-phase turbulent flow models (k-ε-A_p, k-ε-k_p) by Laslandes and the experimental measurements. This model, not only has the same virtues of predicting the longitudinal transport of the solid particles as the present practical two-phase flow models, but also can predict the lateral transport of the solid particles correctly.     

On the derivation of fractional diffusion equation with an absorbent term and a linear external force

Recently, the generalized fractional reaction–diffusion equation subject to an external linear force field has been proposed to describe the transport processes in disordered systems. The solution of this generalized model can be formally expressed in closed form through the Fox function. For the sack of completeness, we dedicate this work to construct a neatly derivation of the generalized fractional reaction–diffusion equation. Remarkably, such derivation could in general offer some novel and inspiring inspection to the phenomena of anomalous transport. For instance, there is a strong evidence that the fractional calculus offers some physical insight into the origin of fractional dynamics for a systems which exhibit multiple trapping.     

Three-dimensional modelling of NOx and particulate traps using CFD: A porous medium approach

Lean burn after-treatment systems are the current focus for reducing emissions from diesel exhaust. The trend is for commercial CFD packages to use a single channel modelling approach. Due to computational demands, this necessitates specification of representative channels for modelling, implying prior knowledge of the flow field. This paper investigates a methodology for applying the porous medium approach to lean burn after-treatment systems. This approach has proved successful for three-way catalysis modelling and has the advantage that the flow field is predicted. Chemical kinetic rates for NO_x trapping and regeneration in the model are based on information available in the open literature. Similarly, filtration information based on mass accumulation and soot combustion kinetics are also readily available. Modification of the source terms in a commercial CFD package enables prediction of trapping and release of NO_x. This is an effective way to model a NO_x trap after-treatment system and provides simultaneous 3D modelling of the flow field. With diesel, particulate filtration is required. In the case of particulate traps, however, because of channel geometry, some assumptions are necessary for use of the porous medium approach and these are discussed in this paper. Both models produce qualitatively correct output and have parameters that can be tuned to conform to experimental data. Data to validate the NO_x trap model is to be measured. The particulate trap model, on the other hand, is a feasibility study for modelling the complete diesel after-treatment system using the porous medium approach.     

The unique solvability of a complex 3D heat transfer problem

Conductive–convective–radiative heat transfer in a scattering and absorbing medium with reflecting and radiating boundaries is considered. The P₁${}_1$ approximation (diffusion model) is used for the simplification of the original problem. The existence of bounded states of the diffusion model is proved. The uniqueness of solutions is established under certain assumptions.     

Stability analysis of impulsive Cohen–Grossberg neural networks with distributed delays and reaction–diffusion terms

In this paper, we investigate a class of impulsive Cohen–Grossberg neural networks with distributed delays and reaction–diffusion terms. By establishing an integro-differential inequality with impulsive initial conditions and applying M-matrix theory, we find some sufficient conditions ensuring the existence, uniqueness, global exponential stability and global robust exponential stability of equilibrium point for impulsive Cohen–Grossberg neural networks with distributed delays and reaction–diffusion terms. An example is given to illustrate the results obtained here.     

Solving the car sequencing problem via Branch & Bound

In a mixed-model assembly line, varying models of the same basic product are to be produced in a facultative sequence. This results to a short-term planning problem where a sequence of models is sought which minimizes station overloads. In practice – e.g. the final assembly of cars – special sequencing rules are enforced which restrict the number of models possessing a certain optional feature k to r_k within a subsequence of s_k successive models. This problem is known as car sequencing. So far, employed solution techniques stem mainly from the field of Logic and Constraint Logic Programming. In this work, a special Branch & Bound algorithm is developed, which exploits the problem structure in order to reduce combinatorial complexity.     

Existence and uniqueness of solutions to nonlinear evolution equations with locally monotone operators

In this paper we establish the existence and uniqueness of solutions for nonlinear evolution equations on a Banach space with locally monotone operators, which is a generalization of the classical result for monotone operators. In particular, we show that local monotonicity implies pseudo-monotonicity. The main results are applied to PDE of various types such as porous medium equations, reaction–diffusion equations, the generalized Burgers equation, the Navier–Stokes equation, the 3D Leray-α model and the p-Laplace equation with non-monotone perturbations.     

SEIQRS model for the transmission of malicious objects in computer network

Susceptible (S) – exposed (E) – infectious (I) – quarantined (Q) – recovered (R) model for the transmission of malicious objects in computer network is formulated. Thresholds, equilibria, and their stability are also found with cyber mass action incidence. Threshold R_cq determines the outcome of the disease. If R_cq ? 1, the infected fraction of the nodes disappear so the disease die out, while if R_cq > 1, the infected fraction persists and the feasible region is an asymptotic stability region for the endemic equilibrium state. Numerical methods are employed to solve and simulate the system of equations developed. The effect of quarantine on recovered nodes is analyzed. We have also analyzed the behavior of the susceptible, exposed, infected, quarantine, and recovered nodes in the computer network.     

Existence of periodic travelling wave solutions of non-autonomous reaction–diffusion equations with lambda–omega type

Periodic travelling wave solutions of reaction–diffusion equations were studied by many authors. The λ–ω$\lambda \text{–}\omega$ type reaction–diffusion system is a notable special model that admits explicit periodic travelling wave solutions and was introduced by Kopell and Howard in 1973. There are now similar systems which are investigated by means of autonomous dynamics. In contrast, there are few papers which are concerned with non-autonomous cases. For this reason, we apply Mawhin’s continuation theorem to derive the existence of periodic travelling wave solutions for non-autonomous λ–ω$\lambda \text{–}\omega$ systems, and we describe the ‘disappearance’ of periodic travelling wave solutions under special situations. Our main result is also illustrated by examples.     

Numerical simulation of cavitation dynamics using a cavitation-induced-momentum-defect (CIMD) correction approach

A new unsteady cavitation event tracking model is developed for predicting vapor dynamics occurring in multi-dimensional incompressible flows. The procedure solves incompressible Navier–Stokes equations for the liquid phase supplemented with an additional vapor transport equation for the vapor phase. The novel cavitation-induced-momentum-defect (CIMD) correction methodology developed in this study accounts for cavitation inception and collapse events as relevant momentum-source terms in the liquid phase momentum equations. The model tracks cavitation zones and applies compressibility effects, employing homogeneous equilibrium model (HEM) assumptions, in constructing the source term of the vapor transport model. Effects of vapor phase accumulation and diffusion are incorporated by detailed relaxation models. A modified RNG k–ε model, including the effects of compressibility in the vapor regions, is employed for modeling turbulence effects. Numerical simulations are carried out using a finite volume methodology available within the framework of commercial CFD software code Fluent v.6.2. Simulation results are in good qualitative agreement with experiments for unsteady cloud cavitation behavior in planar nozzle flows. Multitude of mechanisms such as formation of vortex cavities, vapor cluster shedding and coalescence, cavity pinch off are sharply captured by the CIMD approach. Our results indicate the profound influence of re-entrant jet motion and adverse pressure gradients on the cavitation dynamics.     

On duality and fractionality of multicommodity flows in directed networks

In this paper we address a topological approach to multiflow (multicommodity flow) problems in directed networks. Given a terminal weight μ, we define a metrized polyhedral complex, called the directed tight span T_μ, and prove that the dual of the μ-weighted maximum multiflow problem reduces to a facility location problem on T_μ. Also, in case where the network is Eulerian, it further reduces to a facility location problem on the tropical polytope spanned by μ. By utilizing this duality, we establish the classifications of terminal weights admitting a combinatorial min–max relation (i) for every network and (ii) for every Eulerian network. Our result includes the Lomonosov–Frank theorem for directed free multiflows and Ibaraki–Karzanov–Nagamochi’s directed multiflow locking theorem as special cases.     

A note on the long time behavior for the drift-diffusion-Poisson system

In this note we analyze the long time behavior of a drift-diffusion-Poisson system with a symmetric definite positive diffusion matrix, subject to Dirichlet boundary conditions. This system models the transport of electrons in semiconductor or plasma devices. By using a quadratic relative entropy obtained by keeping the lowest order term of the logarithmic relative entropy, we prove the exponential convergence to the equilibrium. To cite this article: N. Ben Abdallah et al., C. R. Acad. Sci. Paris, Ser. I 339 (2004).     

Numerical simulation of UV disinfection reactors: Evaluation of alternative turbulence models

Six turbulence models, including standard k–ε, k–ε RNG, k–ω (88), revised k–ω (98), Reynolds stress transport model (RSTM), and two-fluid model (TFM), were applied to the simulation of a closed conduit polychromatic UV reactor. Predicted flow field and turbulent kinetic energy were compared with the experimental data from a digital particle image velocimetry (DPIV). All of the predicted flow fields were combined with a multiple segment source summation (MSSS) fluence rate model and three different microbial response kinetic models to simulate the disinfection process at two UV lamp power conditions. Microbial transport was simulated using the Lagrangian particle tracking method. The results show that the fluence distributions and the effluent inactivation levels were sensitive to the turbulence model selection. The level of sensitivity was a function of the operating conditions and the UV response kinetics of the microorganisms. Simulations with operating conditions that produced higher log inactivation or utilized microorganisms with higher UV sensitivity showed greater sensitivity to the turbulence model selection. In addition, a broader fluence distribution was found with turbulence models that predicted a larger wake region behind the lamps.     

Development of an energy-emission model using fuzzy sets

In searching for cost-efficient strategies to reduce emissions from energy conversion, most western countries use energy-emission models. In these models, the whole energy conversion chain and possible future options for energy supply and emission reduction are mapped into a network of energy flows. Total discounted cost of energy supply and emission reduction is minimized under the restriction of maximum allowed emissions of SO₂, NO _x , or CO₂. The present paper extends one of these models to allow for fuzzy parameters. Such an extension appears to be useful when the data situation is weak. In this paper, a fuzzy linear program is developed, which has been applied to an energy-emission model of Lithuania.