Turbulence Models and Their Application: Efficient Numerical Methods With Computer Programs


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In this way, an analysis of turbulence models and their applications in mixing characterization and the adequacy of these models to the reactor configuration and operating conditions is carried out.


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Mention is also made of the experiences around the study of turbulence in mixing tanks. The use of biodigesters offers great advantages in energy production. The purpose of anaerobic digestion AD is the destruction of volatile solids by microorganisms in the absence of oxygen [ 1 ]. The AD is a common process to stabilize and reduce excesses or wastes of a different nature. For example, in a wastewater treatment plant and agricultural holdings, the AD allows a better treatment of animal or vegetable waste, by extracting much of the energy they contain. Besides, the use of biogas to generate electricity gives an additional value to the utilization of bioreactors in agricultural enterprises.

The process of anaerobic digestion has several implications, and its effectiveness is based on aspects such as source, pH, temperature, reduction potential, hydraulic retention time HRT and mixing characteristics [ 2 ]. Mixing is one of the critical activities in the transformation process, a uniform mixture reduces the stratification, allows a better substrate dispersion, and if the mixture is not adequate, the digestion efficiency is reduced [ 3 , 4 ].

When designing an anaerobic digestion system, the volume to be removed should be considered in relation to pump capacity, hydraulic retention time, sludge inflow rate, velocity gradient which relates the pump power, tank volume and sludge viscosity [ 1 , 5 ]. Despite the technological advances in organic waste treatment, established mechanisms for design and operation require even more research.

The AD is based on a combination of complex processes in which different residues are transformed mainly into a mixture composed of CH 4 , CO 2 and H 2 , which is called biogas [ 6 ].

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Hydrodynamic performance of bioreactors is determined by the flow patterns inside. Consequently, biogas production is also conditioned by the reactor design, mainly referred to device dimensions and arrangement inside to favor the fluid movement and thereby generate the desired product [ 7 ]. Several models that allow relatively stable operation and provide desirable results have emerged. However, the punctual analysis of fluid movement inside the bioreactor is a complex issue mainly for the fluid characteristics, and of course by the geometry.

Understanding the Turbulence Models available in Autodesk Simulation CFD

This problem has been investigated using numerical methods, specifically computational fluid dynamics CFD. Digester design process involves several stages. A part is based on the calculation of organic loading rate as a function of temperature and input intensity. However, factors such as sedimentation, biogas, and sludge accumulation can influence on system hydrodynamic behavior and therefore on its removal efficiency.

Computational fluid dynamics

Generally, the predominance of mixed flows inside the reactor and its highly complex description is presumed, reason why a numerical discretization is attempted using CFD. The evaluation and optimization of designs currently made with CFD allows to reduce the costs of prototype development [ 8 ]. Different studies have been conducted on improving hydrodynamic configurations using CFD [ 9 , 10 ]. The use of CFD has allowed to understand that mixing is one of the most important activities for total solids reduction and biogas production.

Despite the low speeds occurring inside a biodigester, it is advisable that the materials be completely mixed, so it is desirable to produce turbulence, which will be a function of rheological characteristics of fluid, flow rate, and dimensions and geometry of bioreactor.

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Phenomena involving fluid movement at high velocities or in chaotic patterns can be inferred by turbulence models. Currently, robust turbulence models applicable to most physical processes have been developed. This is shown by the comparison of numerical solutions against experimental results. With the addition of rheological properties of reaction materials, an appropriate turbulence model application for simulation becomes more complicated, since it is usual to find materials that do not present linear stress-strain behavior when flowing, that is, non-Newtonian fluids [ 11 ]. Flow dynamics of mixing process in anaerobic digesters has been analyzed from different standpoints.

Holdings : Modeling and computation of boundary-layer flows : | York University Libraries

In waste degradation for energy generation, there are advances indicating the relevance of mixing process. Although good mixing can favor the material homogenization and exchange process between microorganisms and their environment, excessive mixing may also disrupt biological activities such as trophic processes [ 12 , 13 ]. Studies on geometry influence in the mixing process include not only the container shape but also the shape of elements to generate movement inside the reactors.

Agitation inside the anaerobic digestion containers is carried out mainly in the following three ways: 1 mechanical agitation with impellers, 2 pumped circulation and 3 gas recirculation [ 4 ]. The main type of reactor used in anaerobic digestion is the Continuous Stirred Tank Reactor CSTR , from which various geometry investigations have been carried out, of flat bottom, conical, spherical or even egg-shaped reactors [ 14 , 15 ]. Such reactors are used to exploit the methane production potential of animal waste. In these reactors, methane emission rates may vary depending on the covered lagoon area [ 17 ].

Total solids concentration in digestion fluids, besides having effects on degradation rate of organic matter, also has direct effects on rheological properties [ 14 ].

get link The study of fluid rheology entails the adjustment of CFD models to more real conditions [ 18 , 19 ]. The time-independent flow behavior is classified as Newtonian and non-Newtonian shear thinning, shear thickening and yield stress [ 11 ]. The rheological properties of non-Newtonian fluids greatly affect flow patterns, differing from those obtained with Newtonian fluids [ 19 ].

The description of nonlinear deformation of non-Newtonian fluids is characterized by generating rheological models, which must match experimental data that help obtain the value of model variables to be used. The rheological model application will depend on behavior and trend of experimental data, as well as the speed ranges achieved by the mixing equipment. The power law model Eq.

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Commercial CFD programs incorporate the power law model function for viscosity of non-Newtonian fluids. Skickas inom vardagar. After a brief review of the more popular turbulence models, the author presents and discusses accurate and efficient numerical methods for solving the boundary-layer equations with turbulence models based on algebraic formulas mixing length, eddy viscosity or partial-differential transport equations. A computer program employing the Cebeci-Smith model and the k-e model for obtaining the solution of two-dimensional incompressible turbulent flows without separation is discussed in detail and is presented in the accompanying CD.

Passar bra ihop. Ladda ned. Skickas inom vardagar. After a brief review of the more popular turbulence models, the author presents and discusses accurate and efficient numerical methods for solving the boundary-layer equations with turbulence models based on algebraic formulas mixing length, eddy viscosity or partial-differential transport equations.


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A computer program employing the Cebeci-Smith model and the k-e model for obtaining the solution of two-dimensional incompressible turbulent flows without separation is discussed in detail and is presented in the accompanying CD. Passar bra ihop.

Ladda ned.

Turbulence Models and Their Application: Efficient Numerical Methods With Computer Programs Turbulence Models and Their Application: Efficient Numerical Methods With Computer Programs
Turbulence Models and Their Application: Efficient Numerical Methods With Computer Programs Turbulence Models and Their Application: Efficient Numerical Methods With Computer Programs
Turbulence Models and Their Application: Efficient Numerical Methods With Computer Programs Turbulence Models and Their Application: Efficient Numerical Methods With Computer Programs
Turbulence Models and Their Application: Efficient Numerical Methods With Computer Programs Turbulence Models and Their Application: Efficient Numerical Methods With Computer Programs
Turbulence Models and Their Application: Efficient Numerical Methods With Computer Programs Turbulence Models and Their Application: Efficient Numerical Methods With Computer Programs

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