A Study on the Mechanism of Convective Heat Transfer Enhancement Based on Heat Convection Velocity Analysis

Xiao, Hui; Dong, Zhimin; Long, Rui; Yang, Kun; Fang, Yuan

doi:10.3390/en12214175

Cited by 13 publications

(6 citation statements)

References 47 publications

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“…ρ wi , C pwi and k wi are the density of ice-water mixture flow (kg/m 3 ), constant pressure heat capacity (J/(kg•K)) and thermal conductivity (W/(m•K)), respectively, and Nu is a dimensionless Nusselt number that represents the degree of convective heat transfer. It can be expressed as a function of the dimensionless Reynolds number Re and the dimensionless Prandtl number Pr related to the hydraulic characteristics according to the experimental data [22,23], as shown in Equation (4).…”

Section: Water Flow Temperature Calculation Modelmentioning

confidence: 99%

A Horizontal Distribution Model of Static Ice Cover Generated by Static and Dynamic Water Considering the Heat Transfer of Riverbanks

Xue,

Wang,

Liu

et al. 2023

Water

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The thermal factor is the main reason for winter ice cover with a low Froude number flow, and the heat transfer to narrow and deep river banks accelerates ice cover formation and ice thickness change. The freezing of water flow to freezing thickening is a nonisothermal-flow phase transition process coupled with the water flow temperature, environment and riverbank. Here, the Nusselt number and viscous dissipation are used to consider the flow velocity influence on icing, and a thermodynamic model of static ice cover horizontal distribution considering riverbed heat transfer is established. The initial ice time, freezing time and static ice cover thickness formed by static and dynamic water calculated by the model were consistent with measured data. The model reflects the horizontal growth process of the static ice cover, which was significant for narrow and deep channels. The horizontal distribution of the static ice cover was thin in the center and thick on both sides. The maximum horizontal thickness difference of −20 °C indoor freezing for 24 h reached 15% of the central ice thickness. Compared with the degree-day method for calculating ice thickness, the numerical model and dimensionless formula better reflect the growth law and horizontal distribution characteristics of static ice cover and provide a theoretical basis for safe water conveyance under ice cover in winter and ice cover formation in reservoirs and lakes in cold regions.

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Section: Water Flow Temperature Calculation Modelmentioning

confidence: 99%

A Horizontal Distribution Model of Static Ice Cover Generated by Static and Dynamic Water Considering the Heat Transfer of Riverbanks

Xue,

Wang,

Liu

et al. 2023

Water

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“…c 1 is the most critical parameter in the SSA algorithm. Because c 1 , shown in Equation (21), determines the balancing of exploration and exploitation [31].…”

Section: Salp Swarm Optimization Algorithm (Sso)mentioning

confidence: 99%

“…I in Equation (21) shows the current iteration, and L is the maximum iteration. The parameters c 2 , c 3 are random numbers in the [0, 1] range.…”

Section: Salp Swarm Optimization Algorithm (Sso)mentioning

confidence: 99%

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Optimization of Laminar Boundary Layers in Flow over a Flat Plate Using Recent Metaheuristic Algorithms

2022

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Heat transfer is one of the most fundamental engineering subjects and is found in every moment of life. Heat transfer problems, such as heating and cooling, where the transfer of heat between regions is calculated, are problems that can give exact solutions with parametric equations, many of which were obtained by solving differential equations in the past. Today, the fact that heat transfer problems have a more complex structure has led to the emergence of multivariate models, and problems that are very difficult to solve with differential equations have emerged. Optimization techniques, which are also the subject of computer science, are frequently used to solve complex problems. In this study, laminar thermal boundary layers in flow over a flat plate, a sub-problem of heat transfer, is solved with recent metaheuristic algorithms. Teaching learning-based optimization (TLBO), sine cosine optimization (SCO), gray wolf optimization (GWO), whale optimization (WO), salp swarm optimization (SSO), and Harris hawk optimization (HHO) algorithms are used in the study. In the optimization problem, the laminar boundary layer thickness, heat flow, and distance from the leading edge are determined. These three models’ minimum, maximum, and target values are found under the specified design variables and constraints. In the study, 540 optimization models are run, and it is seen that HHO is the most suitable optimization technique for heat transfer problems. Additionally, SSO and WO algorithms gave results close to HHO. Other algorithms also set model targets with an average of less than 0.07% and acceptable error rates. In addition, the average problem solution time of all optimization algorithms and all models was 0.9 s. To conclude, the recent metaheuristic algorithms are found to be powerful and fast in solving heat transfer problems.

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“…They found that better field synergy between velocity and heat flux will improve heat transfer intensity under the same boundary conditions. Since then, much attention has been given to improving the overall heat exchanger performance, and the synergetic effect on heat transfer enhancement was found to be strongly related to the flow resistance [18].…”

Section: Introductionmentioning

confidence: 99%

Numerical Research of Pump-as-Turbine Performance with Synergy Analysis

et al. 2021

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The wide use of pumps and turbines has significant value in energy conservation and utilization. In this work, a three-dimensional Computational Fluid Dynamics (CFD) model and a one-dimensional theoretical model of a Pump as Turbine (PAT) were established. On this basis, the correlation between pressure and velocity was quantitatively investigated by a proposed sensitivity index (SPV). A synergy field analysis was then applied to evaluate the flow characteristics of a pump and PAT, providing a perspective from the mechanism of the energy transfer enhancement for hydraulic devices. Moreover, the hydraulic and synergy performances of PAT were studied under various operating conditions. The results show that the minimum SPV is obtained in the impeller. With increasing flow rate, the SPV of the PAT generally increases, and the synergy angle of the impeller surface increases as well. A strong disordered synergy field is observed in regions of the blade leading edge, trailing edge, and volute tongue. The variations in efficiency and head with flow rate showed similar trends, respectively, with the synergy angle of the outlet and the mid-plane. This study provides an analytical method for quantitative evaluation of flow synergy characteristics, and it supplies a basis for further design improvement of the pump and PAT.

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A Study on the Mechanism of Convective Heat Transfer Enhancement Based on Heat Convection Velocity Analysis

Cited by 13 publications

References 47 publications

A Horizontal Distribution Model of Static Ice Cover Generated by Static and Dynamic Water Considering the Heat Transfer of Riverbanks

A Horizontal Distribution Model of Static Ice Cover Generated by Static and Dynamic Water Considering the Heat Transfer of Riverbanks

Optimization of Laminar Boundary Layers in Flow over a Flat Plate Using Recent Metaheuristic Algorithms

Numerical Research of Pump-as-Turbine Performance with Synergy Analysis

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