A parametric study to simulate the non‐Newtonian turbulent flow in spiral tubes

Valizadeh, Kamran; Farahbakhsh, Soroush; Bateni, Amir; Zargarian, Amirhossein; Davarpanah, Afshin; Alizadeh, Araz; Zarei, Mojtaba

doi:10.1002/ese3.514

Cited by 43 publications

(32 citation statements)

References 36 publications

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“…First, velocity distribution changes considerably as fluid flows near the junction of the cone and the tube or the outlet . Second, friction head loss is caused by the viscosity of the fluid because the inner surface of the Marsh funnel is not perfectly slippery . Lastly, the changes in momentum are due to the mixing of viscous fluid molecules .…”

Section: Mathematical Models For Flow Fieldmentioning

confidence: 99%

Rheological analysis of Newtonian and non‐Newtonian fluids using Marsh funnel: Experimental study and computational fluid dynamics modeling

Zheng

Huang

2020

Energy Science & Engineering

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In the drilling industry, Marsh funnel viscosity is only a dynamic viscosity and cannot characterize actual rheology. Thus, measuring rheology using a Marsh funnel has been drawing considerable attention. In this study, we develop simplified mathematical models for wall shear rate, wall shear stress, and their consistency plots. Moreover, we propose mathematical models for the rheological parameters of Newtonian and non‐Newtonian fluids. We compare the results of the present model with those of a ZNN‐6 viscometer, a computational fluid dynamics (CFD) model, and other analytical models. According to the quantitative analysis results, the average systematic error of the Newtonian, apparent, and plastic viscosities between the present model and the ZNN‐6 viscometer measurements is 1.35%, 8.18%, and 5.42%, respectively. The average systematic error of the yield stress is 21.43%, which is under the controllable scope. Meanwhile, results of the qualitative analysis reveal that the present model for the wall shear rate and stress agrees with the CFD model. Moreover, the flow field inside the Marsh funnel is axisymmetric and has a component velocity in the horizontal direction. In summary, the proposed model is accurate, concise, available for field applications, and beneficial for a successful and safe drilling operation. Furthermore, the CFD approach is a necessary complement to exploring the actual field flow inside the Marsh funnel.

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Section: Mathematical Models For Flow Fieldmentioning

confidence: 99%

Rheological analysis of Newtonian and non‐Newtonian fluids using Marsh funnel: Experimental study and computational fluid dynamics modeling

Zheng

Huang

2020

Energy Science & Engineering

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“…Since the governing Equations (6) and (7) are highly coupled and nonlinear, to the best of our information, it is difficult to find their analytical solutions based on the current theory. Some numerical methods, and the calculation software have been applied as an effective tool to simulate the flow of non-Newtonian fluids [31][32][33]. In this section, the numerical solutions of governing Equations (6) and 7are obtained by an effective finite difference method.…”

Section: The Numerical Techniquementioning

confidence: 99%

Numerical Solutions of Unsteady Boundary Layer Flow with a Time-Space Fractional Constitutive Relationship

et al. 2020

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In this paper, we develop a new time-space fractional constitution relation to study the unsteady boundary layer flow over a stretching sheet. For the convenience of calculation, the boundary layer flow is simulated as a symmetrical rectangular area. The implicit difference method combined with an L1-algorithm and shift Grünwald scheme is used to obtain the numerical solutions of the fractional governing equation. The validity and solvability of the present numerical method are analyzed systematically. The numerical results show that the thickness of the velocity boundary layer increases with an increase in the space fractional parameter γ. For a different stress fractional parameter α, the viscoelastic fluid will exhibit viscous or elastic behavior, respectively. Furthermore, the numerical method in this study is validated and can be extended to other time-space fractional boundary layer models.

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“…Geothermal energy is heat from the inner part of the earth that is present in rocks and water in cracks and pores within the rock of the earth's crust. The temperature normally increases with depth, although not in a constant manner [1][2][3][4]. The benefits of geothermal energy include reduced pollution and avoidance of change in ecosystems' reliability and renewability.…”

Section: Introductionmentioning

confidence: 99%

“…Heberle et al [2] studied an ORC with geothermal sources. A combination of heat and power generation for the geothermal sources was proposed at a temperature below 450 K. The results showed that the best choice of working fluid is R227a.…”

Section: Introductionmentioning

confidence: 99%

Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages

et al. 2020

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Due to the harmful effects and depletion of non-renewable energy resources, the major concerns are focused on using renewable energy resources. Among them, the geothermal energy has a high potential in volcano regions such as the Middle East. The optimization of an organic Rankine cycle with a geothermal heat source is investigated based on a genetic algorithm having two stages. In the first stage, the optimal variables are the depth of the well and the extraction flow rate of the geothermal fluid mass. The optimal value of the depth of the well, extraction mass flow rate, and the geothermal fluid temperature is found to be 2100 m, 15 kg/s, and 150 °C. In the second stage, the efficiency and output power of the power plant are optimized. To achieve maximum output power as well as cycle efficiency, the optimization variable is the maximum organic fluid pressure in the high-temperature heat exchanger. The optimum values of energy efficiency and cycle power production are equal to 0.433 MW and 14.1%, respectively.

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A parametric study to simulate the non‐Newtonian turbulent flow in spiral tubes

Cited by 43 publications

References 36 publications

Rheological analysis of Newtonian and non‐Newtonian fluids using Marsh funnel: Experimental study and computational fluid dynamics modeling

Rheological analysis of Newtonian and non‐Newtonian fluids using Marsh funnel: Experimental study and computational fluid dynamics modeling

Numerical Solutions of Unsteady Boundary Layer Flow with a Time-Space Fractional Constitutive Relationship

Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages

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