Geometric optimization of a highly conductive insert intruding an annular fin

Hajmohammadi, M.R.; Rasouli, Erfan; Elmi, Mojgan

doi:10.1016/j.ijheatmasstransfer.2019.118910

Cited by 37 publications

(6 citation statements)

References 29 publications

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“…The solid fraction of the finned system also includes the interior release of thermal energy at a rate of qnormal″normal′false(W⋅m−3false). The fin base ( r = r i ) is subjected to a finite temperature ( T b (K)) whereas its tip condition ( r = r e ) is maintained under an adiabatic condition. 4,31 The ambient temperature is T ∞ (K) and acceleration due to gravity is denoted by g (m·s −2 ). With respect to Figure 1, the applicable energy balance for computing the local temperature field ( T (K)) corresponding to any small region along the fin radius can be represented as mentioned below: where σ(W·m −2 ·K −4 ) denotes the Stefan–Boltzmann constant, K (m 2 ) denotes the permeability, ρf (kg·m −3 ) denotes the fluid’s density, χf (K −1 ) denotes the volumetric thermal expansion coefficient of the fluid medium, νf (m 2 ·s −1 ) denotes the kinematic viscosity and cp,f(J·kg −1 ·K −1 ) denotes the fluid heat capacity per unit mass.…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…The fin base (r = r i ) is subjected to a finite temperature (T b (K)) whereas its tip condition (r = r e ) is maintained under an adiabatic condition. 4,31 The ambient temperature is T ∞ (K) and acceleration due to gravity is denoted by g (m•s −2 ). With respect to Figure 1, the applicable energy balance for computing the local temperature field (T (K)) corresponding to any small region along the fin radius can be represented as mentioned below:…”

Section: Mathematical Formulationmentioning

confidence: 99%

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Quantification of thermal energy generation in annular hyperbolic porous-finned heat sinks using inverse optimization

Pal

Das

2021

Proceedings of the Institution of Mechanical Engineers, Part E:

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The present paper introduces an accurate numerical procedure to assess the internal thermal energy generation in an annular porous-finned heat sink from the sole assessment of surface temperature profile using the golden section search technique. All possible heat transfer modes and temperature dependence of all thermal parameters are accounted for in the present nonlinear model. At first, the direct problem is numerically solved using the Runge–Kutta method, whereas for predicting the prevailing heat generation within a given generalized fin domain an inverse method is used with the aid of the golden section search technique. After simplifications, the proposed scheme is credibly verified with other methodologies reported in the existing literature. Numerical predictions are performed under different levels of Gaussian noise from which accurate reconstructions are observed for measurement error up to 20%. The sensitivity study deciphers that the surface temperature field in itself is a strong function of the surface porosity, and the same is controlled through a joint trade-off among heat generation and other thermo-geometrical parameters. The present results acquired from the golden section search technique-assisted inverse method are proposed to be suitable for designing effective and robust porous fin heat sinks in order to deliver safe and enhanced heat transfer along with significant weight reduction with respect to the conventionally used systems. The present inverse estimation technique is proposed to be robust as it can be easily tailored to analyse all possible geometries manufactured from any material in a more accurate manner by taking into account all feasible heat transfer modes.

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Section: Mathematical Formulationmentioning

confidence: 99%

Section: Mathematical Formulationmentioning

confidence: 99%

Quantification of thermal energy generation in annular hyperbolic porous-finned heat sinks using inverse optimization

Pal

Das

2021

Proceedings of the Institution of Mechanical Engineers, Part E:

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“…The results in the case of different straight fin profiles including rectangular, exponentially decaying, and exponentially growing were compared. Hajmohammadi et al [5] have carried out a geometric optimization to attain maximum cooling performance of an annular fin with a highly conductive insert intruded. The objective of their optimization study was to obtain the minimum peak temperature of the fin where uniform heat flux is applied at its base.…”

Section: Introductionmentioning

confidence: 99%

Ansys Mechanical Automation using Python for the Steady State Thermal Analysis of Fins

Shaimi¹,

Khatyr²,

Naciri³

2022

Proceedings of the 8th World Congress on Mechanical, Chemical, and Material Engineering

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A numerical investigation of the heat transfer enhancement through fins using the Ansys Mechanical solver is presented. Results are given for a uniform fin with elliptical cross-sections and uniform heat flux applied on its base while heat is dissipated to its surroundings by convection from both its lateral surface and tip. The peak temperature at the base of the fin is used to evaluate the thermal performance. Ansys Mechanical solver is automated using Python scripting to run 792 simulations for various materials, fin lengths, and ratios between the minor and major axes of the elliptical cross-sectional shape for both cases of natural and forced convection. The use of the original automated numerical procedure significantly decreases the computational time and the user intervention. It was found that the thermal performance is improved by increasing the length of the fin, using a material with higher thermal conductivity, or having a ratio between the minor and major axes of the ellipse that is farther from unity. Forced convection gives better thermal performance compared to natural convection.

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“…Konan and Cetkin [30] experimented with constructal design of snowflake-shaped HTCC, and found that the optimal constructal design of the HTCC with minimum MTD is very close to the natural snowflake shape. Hajmohammadi et al [31] devised a model in which HTCCs are embedded in annular fins to assist heat dissipation, and achieved constructal design of HTCCs with minimum MTD. Li and Feng [32] proposed a quadrilateral HGB model with embedded vein-like HTCCs, and obtained optimal constructal design of this model by with the objective of minimizing the MTD.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Constructal Design for Square Heat-Generation Body with “Arrow-Shaped” High-Thermal-Conductivity Channel

Zhu

Chen

et al. 2022

Energies

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Based on the square heat-generation body (HGB) with “arrow-shaped” high-thermal-conductivity channel (HTCC) model established in the previous literature, we performed multi-objective optimization (MOO) with maximum temperature difference (MTD) minimization and entropy-generation rate (EGR) minimization as optimization objectives for its performance. Pareto frontiers with optimal set were obtained based on NSGA-II. TOPSIS, LINMAP, and Shannon entropy decision methods were used to select the optimal results in Pareto frontiers, and the deviation index was used to compare and analyze advantages and disadvantages of the optimal results for each decision method. At the same time, multi-objective constructal designs of the “arrow-shaped” HTCC were carried out through optimization of single degree of freedom (DOF), two DOF, and three DOF, respectively, and the thermal performance of the square heat-generation body under optimizations of different DOF were compared. The results show that constructal design with the MOO method can achieve the best compromise between the maximum thermal resistance and the irreversible loss of heat transfer of the square heat-generation body, thereby improving the comprehensive thermal performance of the square heat-generation body. The MOO results vary with different DOF, and optimization with increasing DOF can further improve the comprehensive thermal performance of square HGBs.

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Geometric optimization of a highly conductive insert intruding an annular fin

Cited by 37 publications

References 29 publications

Quantification of thermal energy generation in annular hyperbolic porous-finned heat sinks using inverse optimization

Quantification of thermal energy generation in annular hyperbolic porous-finned heat sinks using inverse optimization

Ansys Mechanical Automation using Python for the Steady State Thermal Analysis of Fins

Multi-Objective Constructal Design for Square Heat-Generation Body with “Arrow-Shaped” High-Thermal-Conductivity Channel

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