Effects of mesh grid and turbulence models on heat transfer coefficient in a convergent–divergent nozzle

Zhalehrajabi, Ehsan; Rahmanian, Nejat; Hasan, Nurul

doi:10.1002/apj.1767

Cited by 13 publications

(5 citation statements)

References 10 publications

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“…Ronier 4 reservoir is divided into three single layers. After the layering of the single layer, the planar grid scaling in Block Ronier 4 is performed (Witt et al 2007;Zhalehrajabi et al 2014). The longitudinal grid scaling is divided as 0.3 m according to the minimum single sand body thickness of various sedimentary units (Ishak et al 2018;Khan et al 2001).…”

Section: Computational Methodologymentioning

confidence: 99%

Geological modeling and upscaling of the Ronier 4 block in Bongor basin, Chad

Zene

Hasan

Jiang

et al. 2019

J Petrol Explor Prod Technol

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The study focuses on building a 3D-dimensional model for using well log data of 3 wells to enable a better understanding of the reservoir characteristics and evaluation of the hydrocarbon potential in the field of Ronier in the Bongor Basin, Chad. These data are used to build a Lithofacies model, property model, the permeability model and the saturation model which are the parameters that describe the reservoir. Indeed, the accuracy to quantify the geological reserve of Ronier 4 reservoir block depends on the estimation of these values. The result of geological modeling and upscaling of the Ronier 4 block of Ronier oilfield is presented systematically. In this work, a Sequential Gaussian Simulation (SGS) algorithm under the phase control based on the collocated co-Kriging is adopted and the models of porosity, permeability and saturation are established. Lithofacies model has sand (0) content of 66.69% mostly the first layer, while the code (2) shale content 12.15% mostly concentrated in the center, north and south. Finally, the code (3) sand content is 21.16%. The NTG distribution is highly concentrated in the north, center and south (1) and 0.7 on average, while the lowest range is 0.1. The study shows a good permeability range between 460 to 1200 and 500 mD on average. The porosity distribution mainly distributed between 17 to 27 and 19% on average. These indicate that it has good reservoir properties. The 3D developed geological model provides the basis for calculating the Oil Initially in Place (OIIP) volumes of hydrocarbons.

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Section: Computational Methodologymentioning

confidence: 99%

Geological modeling and upscaling of the Ronier 4 block in Bongor basin, Chad

Zene

Hasan

Jiang

et al. 2019

J Petrol Explor Prod Technol

Self Cite

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“…A series of verification 26 tests were performed before proceeding for validations as in literature. 27,28 The ultimate setting is shown in Table 1.…”

Section: Computational Modelsmentioning

confidence: 99%

Liquid water film on the outer surface of a half-submerged rotating drum

Trang¹,

Ahmed

Kaosar

2019

Journal of Plastic Film & Sheeting

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In this study, a two-dimensional computational model describing the rise and development of thin liquid water film on a rotating drum is presented. The liquid water flow is predicted by solving the Navier–Stoke equation using computational fluid dynamics neglecting the end effects of the rotating drum side wall along width. The liquid film on a half-submerged rotating drum was modeled by volume of fluid to determine the thickness and quality of the liquid film on a rotating drum. Computational results show that the liquid film on the rising side is smooth, whereas the film on the plunging point is complex. For a 300 r/min of 75 mm rotating drum, it takes ∼300 ms to develop the film from the rising point to fall to the plunging point. Air is entrained in plunging side by the falling film from the rising side.

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“…They also reported that the placement of the first cell near the wall strongly affects heat transfer prediction. A similar study by Zhalehrajabi 12 compared the effect of a number of grids and a turbulence model. They reported that heat flux estimation is grid sensitive, and results obtained using the k-ε turbulence model 13 are close to the experimental data than the k-ω SST [14][15] turbulence model.…”

Section: Introductionmentioning

confidence: 99%

Numerical Estimation of Convective Heat Transfer Coefficient and Heat Flux for a Supersonic Rocket Nozzle

Makhija,

Bodi,

Chakraborty

2024

Def. Sc. J.

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Rocket nozzles are often cooled by passing liquid propellants through channels in the nozzle walls. Estimating heat transfer to the wall from the hot gases in the nozzle is essential in deciding on the coolant flow requirements. The present work examines the computational estimation of convection heat transfer to the nozzle walls for compressible turbulent flows. Computations were performed using the rhoPimpleFoam solver in OpenFOAM® with two different turbulence models. We simulate the supersonic flow over a flat plate and validate the heat flux calculation method and turbulence model characteristics. We compare two methods of calculating convection heat transfer in the context of the nozzle flow case presented by Back & Massier. We find that the realizablek-ε turbulence model works well in estimating the heat transfer coefficient.

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Effects of mesh grid and turbulence models on heat transfer coefficient in a convergent–divergent nozzle

Cited by 13 publications

References 10 publications

Geological modeling and upscaling of the Ronier 4 block in Bongor basin, Chad

Geological modeling and upscaling of the Ronier 4 block in Bongor basin, Chad

Liquid water film on the outer surface of a half-submerged rotating drum

Numerical Estimation of Convective Heat Transfer Coefficient and Heat Flux for a Supersonic Rocket Nozzle

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