Large Eeddy Simulation of cavitation effects on reacting spray flames using FGM and a new dispersion model with multiple realizations

The paper deals with the mass transfer in a liquid on a plate with mobile packing. A procedure has been suggested which enables estimation of the mass transfer coefficients from experimental data considering the dispersion flow of the liquid. The results obtained from the desorption of CO2 from water are presented graphically and in the form of empirical equation.

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Certain Problems with the Application of Stochastic Diffusion Processes for the Description of Chemical Engineering Phenomena. Stochastic Model of Non-Isothermal Flow Chemical Reactor

Collection of Czechoslovak Chemical Communications ◽

10.1135/cccc19960242 ◽

1996 ◽

Vol 61 (2) ◽

pp. 242-258 ◽

Cited By ~ 2

Author(s):

Vladimír Kudrna ◽

Libor Vejmola ◽

Pavel Hasal

Keyword(s):

Stochastic Model ◽

Chemical Engineering ◽

Diffusion Processes ◽

Dispersion Model ◽

Chemical Reactor ◽

Segregation Index ◽

One Dimensional ◽

A Value ◽

Isothermal Case ◽

Flow Through

Recently developed stochastic model of a one-dimensional flow-through chemical reactor is extended in this paper also to the non-isothermal case. The model enables the evaluation of concentration and temperature profiles along the reactor. The results are compared with the commonly used one-dimensional dispersion model with Danckwerts' boundary conditions. The stochastic model also enables to evaluate a value of the segregation index.

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Mass Transport Modelling in Porous Media Using Delay Differential Equations

Defect and Diffusion Forum ◽

10.4028/www.scientific.net/ddf.258-260.586 ◽

2006 ◽

Vol 258-260 ◽

pp. 586-591

Author(s):

António Martins ◽

Paulo Laranjeira ◽

Madalena Dias ◽

José Lopes

Keyword(s):

Porous Media ◽

Differential Equations ◽

Mass Transport ◽

Delay Differential Equations ◽

Dispersion Model ◽

Flow Characteristics ◽

Convective Transport ◽

Transport Modelling ◽

Flow Field Characteristics ◽

Delay Differential

In this work the application of delay differential equations to the modelling of mass transport in porous media, where the convective transport of mass, is presented and discussed. The differences and advantages when compared with the Dispersion Model are highlighted. Using simplified models of the local structure of a porous media, in particular a network model made up by combining two different types of network elements, channels and chambers, the mass transport under transient conditions is described and related to the local geometrical characteristics. The delay differential equations system that describe the flow, arise from the combination of the mass balance equations for both the network elements, and after taking into account their flow characteristics. The solution is obtained using a time marching method, and the results show that the model is capable of describing the qualitative behaviour observed experimentally, allowing the analysis of the influence of the local geometrical and flow field characteristics on the mass transport.

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Qualitative Properties of Autocatalytic Reactions Occurring in a Flow System

Zeitschrift für Naturforschung A ◽

10.1515/zna-1985-0715 ◽

1985 ◽

Vol 40 (7) ◽

pp. 736-747

Author(s):

Sang H. Kim ◽

Vladimir Hlavacek

Keyword(s):

Chaotic Behavior ◽

Flow System ◽

Cell Model ◽

Dispersion Model ◽

Travelling Waves ◽

Continuous Model ◽

Product Inhibition ◽

Stable Node ◽

Qualitative Properties ◽

Intermediate Value

The dynamic behavior of an autocatalytic reaction with a product inhibition term is studied in a flow system. A unique steady state exists in the continuous tank reactor. Linear stability analysis predicts either a stable node, a focus or an unstable saddle-focus. Sustained oscillations around the unstable focus can occur for high values of the Damköhler number (Da). In the distributed system, travelling, standing or complex oscillatory waves are detected. For a low value of Da, travelling waves with a pseudo-constant pattern are observed. With an intermediate value of Da, single or multiple standing waves are obtained. The temporal behavior indicates also the appearance of retriggering or echo waves. For a high value of Da, both single peak and complex multipeak oscillations are found. In the cell model, both regular oscillations near the inlet and chaotic behavior downstream are observed. In the dispersion model, higher Peclet numbers (Pe) eliminate the oscillations. The spatial profile shows a train of pulsating waves for the discrete model and a single pulsating or solitary wave for the continuous model.

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Development of a Line Source Dispersion Model for Gaseous Pollutants by Incorporating Wind Shear near the Ground under Stable Atmospheric Conditions

Environmental Sciences Proceedings ◽

10.3390/ecas2020-08154 ◽

2020 ◽

Vol 4 (1) ◽

pp. 17

Author(s):

Saisantosh Vamshi Harsha Madiraju ◽

Ashok Kumar

Keyword(s):

Air Pollution ◽

Urban Areas ◽

Wind Shear ◽

Dispersion Model ◽

Near Field ◽

Ground Level ◽

Gaseous Pollutants ◽

Air Pollution Control ◽

Mobile Sources ◽

Input Variables

Transportation sources are a major contributor to air pollution in urban areas. The role of air quality modeling is vital in the formulation of air pollution control and management strategies. Many models have appeared in the literature to estimate near-field ground level concentrations from mobile sources moving on a highway. However, current models do not account explicitly for the effect of wind shear (magnitude) near the ground while computing the ground level concentrations near highways from mobile sources. This study presents an analytical model based on the solution of the convective-diffusion equation by incorporating the wind shear near the ground for gaseous pollutants. The model input includes emission rate, wind speed, wind direction, turbulence, and terrain features. The dispersion coefficients are based on the near field parameterization. The sensitivity of the model to compute ground level concentrations for different inputs is presented for three different downwind distances. In general, the model shows Type III sensitivity (i.e., the errors in the input will show a corresponding change in the computed ground level concentrations) for most of the input variables. However, the model equations should be re-examined for three input variables (wind velocity at the reference height and two variables related to the vertical spread of the plume) to make sure that that the model is valid for computing ground level concentrations.

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