A Petrov–Galerkin finite element approach for the unsteady boundary layer upper-convected rotating Maxwell fluid flow and heat transfer analysis

Khan, Raja Mehmood; Imran, Naveed; Mehmood, Zaffar; Sohail, Muhammad

doi:10.1080/17455030.2022.2055201

Cited by 12 publications

(4 citation statements)

References 22 publications

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“…In order to solve the multiobjective optimization problem (12), the multiobjective optimization algorithm (NSGA-II) is applied. Tis algorithm was proposed by Kalyanmoy Deb [28].…”

Section: Optimization Equation Solution Through Nsga-iimentioning

confidence: 99%

“…It can be seen from the above research studies that the extrusion process parameters have signifcant infuences on the size characteristics of the microtube cross section, and the desired results can be obtained by a large number of extrusion experiments, but it will take a lot of time and consume a lot of experimental materials. In recent years, the efciency of microtubule forming process parameter design has been continuously improved with the improvement of computing power and the gradual application of numerical simulation methods in extrusion expansion simulation [11][12][13][14]. However, the nonlinear relationship between extrusion process parameters and tube size characteristics is rarely reported, especially in the optimization of the extrusion process for multiobjective characteristics.…”

Section: Introductionmentioning

confidence: 99%

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Multiobjective Optimization System of Extrusion Process Parameters for Targeted Microtubes Based on RSM and NSGA-II

Zhang

Jin

Dai

2022

Advances in Materials Science and Engineering

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An optimization system of extrusion process parameters was designed to rapidly extrude a microtube with a target diameter and wall thickness for forming medical balloons with personalized size characteristics. Firstly, the double convected pom-pom (DCPP) model was selected for the numerical simulation of the tube extrusion process, and different parameter combinations and their corresponding simulation results were extracted based on orthogonal experiments. Secondly, the nonlinear functional relationships between microtube diameter and wall thickness with extrusion parameters were established based on the response surface model (RSM). Finally, the nondominated sorting genetic algorithm II (NSGA-II) and response surface model (RSM) were mixed to find the optimal parameters of the tube extrusion. The extrusion experiment results, taking three microtubes with different target size characteristics (1, 0.15), (1, 0.2), and (1.5, 0.2) as examples, show that the average error between the actual and predicted values of diameter and wall thickness of three microtubes is 6.53%, where the average diameter error is 7.3%, the wall thickness error is 5.77%, the maximum value is 9%, and the minimum value is only 1.3%.

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“…In order to solve the multiobjective optimization problem (12), the multiobjective optimization algorithm (NSGA-II) is applied. Tis algorithm was proposed by Kalyanmoy Deb [28].…”

Section: Optimization Equation Solution Through Nsga-iimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multiobjective Optimization System of Extrusion Process Parameters for Targeted Microtubes Based on RSM and NSGA-II

Zhang

Jin

Dai

2022

Advances in Materials Science and Engineering

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“…Qayyum et al 3 examined the blood fluid properties for suspension of MWCNTs via stretching disk. Khan et al 4 exclusively determined the Maxwell nanofluid thermal effects for boosting the heating capacitance. The reaction consequences for wavy surface with nanofluid flow was identified by Javed et al 5 .…”

Section: Introductionmentioning

confidence: 99%

Entropy generation analysis for mixed convection flow of nanofluid due to vertical plate with chemical reaction effects

Abdelhameed

2023

Sci Rep

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The analysis have been presented to observe the optimized flow of Casson nanofluid conveying the applications of external heat generation and mixed convection features. The problem is further influenced by chemical reactive species with order one. The significant of Bejan number is evaluated. A vertically moving with convective heat phenomenon endorsed the flow. The modeled problem is reflected in terms PDE’s which are further simplifies with dimensionless form. The analytical outcomes have been established with implementation of Laplace technique. The graphical impact conveying the different parameters is assessed. The insight of skin friction and Nusselt number is observed via various curves. It is observed that entropy generation enhanced due to porosity parameter and magnetic number. With increasing Casson fluid parameter, the entropy generation decrease. Moreover, the Bejan number decreases for chemical reaction constant.

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“…G-FEM was also used by Hatami and Ghasemi to compute the thermophoresis and Brownian diffusion for two-phase nanofluid flow through a porous vertical cone [37]. G-FEM has been widely used by researchers, for instance, Al-Kouz et al [38], Khan et al [39], Abbas et al [40], Qureshi et al [41], and Asmadi et al [42]. Ibrahim and Gadisa [43] reported the numerically calculated values of the local skin friction coefficient and the local Nusselt value correlate with those previously published in the literature.…”

Section: Introductionmentioning

confidence: 99%

Galerkin Finite Element Process for Entropy Production and Thermal Evaluation of Third-Grade Fluid Flow: A Thermal Case Study

et al. 2022

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A fluid’s moving class improves its heat transmission capability, as well as its rigidity, owing to multivariate molecule suspension. In this way, nanofluids are superior to common fluids. In this study, we evaluated the features of ease and heat transfer. Furthermore, we investigated permeable media, heat source, variable heat conductivity, and warm irradiation results. A mathematical technique known as the Galerkin finite element (G-FEM) approach was used to solve the supervising conditions. Third-grade nanofluid (TGNF), which consists of two types of nanoparticles (NPs), single-walled carbon nanotubes (SWCNT), and multi-walled carbon nanotubes (MWCNTs) distributed in a base liquid of carboxymethyl cellulose (CMC) water, was used for this examination. The main conclusion of this study is that MWCNT-CMC nanofluid has a higher heat transfer velocity than SWCNT-CMC nanofluid. The entropy of the framework can be increased by adjusting the thermal conductivity. Additionally, we found that increasing the main volume section decreases the speed but increases the dispersion of atomic energy. In order to separately account for the development properties of inertial forces and shallow heat dispersion forces, Reynolds and Brinkman values can be used to accelerate the entropy rate of the heating framework.

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A Petrov–Galerkin finite element approach for the unsteady boundary layer upper-convected rotating Maxwell fluid flow and heat transfer analysis

Cited by 12 publications

References 22 publications

Multiobjective Optimization System of Extrusion Process Parameters for Targeted Microtubes Based on RSM and NSGA-II

Multiobjective Optimization System of Extrusion Process Parameters for Targeted Microtubes Based on RSM and NSGA-II

Entropy generation analysis for mixed convection flow of nanofluid due to vertical plate with chemical reaction effects

Galerkin Finite Element Process for Entropy Production and Thermal Evaluation of Third-Grade Fluid Flow: A Thermal Case Study

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