A Comparison of Convergence and Error Estimates for the Monte Carlo and Discrete Transfer Methods

Versteeg, Hendrik K.; Henson, Jonathan C.; Malalasekera, Weeratunge

doi:10.1615/ichmt.2001.radiationsymp.100

Cited by 5 publications

(7 citation statements)

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“…Hence, the renormalization group (RNG) model systematically removes scales of motion from the governing equations by expressing their effects in terms of larger-scale motions and a modified viscosity. However, the standard ( k – ε) model uses the small eddies in defining the large eddies scale, which, in turn, reduces the efficiency of this model at high Reynolds numbers (i.e., high superficial gas velocity). , Therefore, the standard ( k – ε) model is restricted to the flow without internal geometrics inside the simulated field. Accordingly, the RNG ( k – ε) model is recommended as long as the current work aims to study the effect of internals at the churn turbulent flow regime.…”

Section: Resultsmentioning

confidence: 99%

3D CFD Simulation of a Bubble Column with Internals: Validation of Interfacial Forces and Internal Effects for Local Gas Holdup Predictions

Al-Naseri,

Schlegel,

Al-Dahhan

2023

Ind. Eng. Chem. Res.

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Section: Resultsmentioning

confidence: 99%

3D CFD Simulation of a Bubble Column with Internals: Validation of Interfacial Forces and Internal Effects for Local Gas Holdup Predictions

Al-Naseri,

Schlegel,

Al-Dahhan

2023

Ind. Eng. Chem. Res.

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“…For example, the model developed here may be extended to simulate mixing and solid–liquid flows in FO as crystallizers . To illustrate such potential applications, we simulated the solid–liquid flow in FO using a two-way coupling discrete particle modeling (DPM) − , approach in base case geometry. Inert particles having the density of Paracetamol ( ρ p = 1260 kg/m 3 ), and particles of a constant size of 200 μm were injected from the inlet surface.…”

Section: Resultsmentioning

confidence: 99%

“…The model equations for other turbulence models are given in Table S2 of the Supporting Information. Additional information on these equations can be found in any standard textbook − and Ansys Fluent theory guide …”

Section: Computational Modelingmentioning

confidence: 99%

Jet Oscillations and Mixing in Fluidic Oscillators: Influence of Geometric Configuration and Scale

Madane

Ranade

2023

Ind. Eng. Chem. Res.

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Fluidic oscillators (FOs) harness inherently oscillating jets for improving mixing, heat, and mass transfer and offer an attractive device platform for a wide range of applications. Despite several promising applications of FOs, the influence of their design and scale on the resulting jet oscillations and mixing has not been systematically studied. In this work, we investigated the influence of geometric configuration and device scale on jet oscillation frequency, flow, mixing, and residence time distribution (RTD). Initially, flow in FO was simulated using a two-dimensional computational fluid dynamics (CFD) model for exploring a wider parameter space. These simulations indicated that the distance of the backflow limb from the inlet and device scale are the most important design parameters influencing the jet oscillation frequency. Detailed three-dimensional CFD simulations were then carried out for the shortlisted configurations of the FO. The shortlisted configurations were fabricated, and experimental measurements of jet oscillations were carried out. The jet oscillation frequency was measured using acquired pressure fluctuation data and fast Fourier transforms. The simulated results were compared with the experimental data. The validated CFD model was then used to evaluate various flow features of FO, mixing, and liquid and solid RTD considering potential applications. The presented results will be useful for identifying suitable design and operating parameters of the FO for a variety of processes and applications.

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“…A number of investigators have published comparisons of performance of different monochromatic or gray radiative transfer models using test cases or experimental data (Viskanta and Mengüç 1987;Carvalho and Farias, 1998;Coelho, 2002;Liu et al, 1998;Rivière et al, 1994;Soufiani and Taine, 1997;Liu, 1999;Coelho et al, 1995;Helbig et al, 2001;Versteeg et al, 2001). A comparison of different methods for predicting radiative transfer in 2D rectangular (Viskanta and Mengüç 1987;Carvalho and Farias, 1998;Coelho et al, 1995) and axisymmetric (Viskanta and Mengüç 1987;Carvalho and Farias, 1998) as well as 3D rectangular (Carvalho and Farias, 1998;Versteeg et al, 2001) enclosures has been reported, and the discussions will not be repeated. Suffice it to state that it is difficult to generalize the findings as the results depend on the choice of the radiation property model for the participating medium, the radiation characteristics of the walls and the geometry considered.…”

Section: Comparison Of Rte Solution Methodsmentioning

confidence: 99%

Computation of radiative transfer in combustion systems

Viskanta

2008

International Journal of Numerical Methods for Heat &Amp; Fluid Flow

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Purpose -This paper seeks to review the literature on methods for solving the radiative transfer equation (RTE) and integrating the radiant energy quantities over the spectrum required to predict the flow, the flame and the thermal structures in chemically reacting and radiating combustion systems. Design/methodology/approach -The focus is on methods that are fast and compatible with the numerical algorithms for solving the transport equations using the computational fluid dynamics techniques. In the methods discussed, the interaction of turbulence and radiation is ignored. Findings -The overview is limited to four methods (differential approximation, discrete ordinates, discrete transfer, and finite volume) for predicting radiative transfer in multidimensional geometries that meet the desired requirements. Greater detail in the radiative transfer model is required to predict the local flame structure and transport quantities than the global (total) radiation heat transfer rate at the walls of the combustion chamber.Research limitations/implications -The RTE solution methods and integration of radiant energy quantities over the spectrum are assessed for combustion systems containing only the infra-red radiating gases and gas particle mixtures. For strongly radiating (i.e. highly sooting) and turbulent flows the neglect of turbulence/radiation interaction may not be justified. Practical implications -Methods of choice for solving the RTE and obtaining total radiant energy quantities for practical combustion devices are discussed. Originality/value -The paper has identified relevant references that describe methods capable of accounting for radiative transfer to simulate processes arising in combustion systems.

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A Comparison of Convergence and Error Estimates for the Monte Carlo and Discrete Transfer Methods

Cited by 5 publications

References 0 publications

3D CFD Simulation of a Bubble Column with Internals: Validation of Interfacial Forces and Internal Effects for Local Gas Holdup Predictions

3D CFD Simulation of a Bubble Column with Internals: Validation of Interfacial Forces and Internal Effects for Local Gas Holdup Predictions

Jet Oscillations and Mixing in Fluidic Oscillators: Influence of Geometric Configuration and Scale

Computation of radiative transfer in combustion systems

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