Micropin-fin Heat Sink Research Articles

Neural network-based regression for effective parametric study of micro-pin fin heat sinks

Neural network-based regression for effective parametric study of micro-pin fin heat sinks

Multi‐objective optimization of a Fibonacci phyllotaxis micro pin‐fin heat sink

AbstractThere are still significant technical challenges associated with thermal management of electronic devices such as microprocessors. To improve heat dissipation performance of integrated circuits, a new Fibonacci phyllotaxis design of circular micropin fin heat sinks has been developed. To minimize both chip temperature and pumping power, a multi‐objective optimization technique was employed. The effect of design parameters such as phyllotaxis coefficient, pin fin diameter, and pin fin height on response parameters was numerically investigated using the full factorial design of the experiment. Artificial neural network was coupled with MO‐Jaya, to arrive at a Pareto frontier of optimal compromise solutions. The optimal set of design variables were found to be a height of 300 μm, a diameter of 122.6 μm, and a phyllotaxis coefficient of 130 μm with an inlet velocity of coolant 2.263 m/s. The selected optimum design was then investigated numerically, and the outcomes were compared to those predicted by the MO‐Jaya algorithm. The final confirmed response variables were a maximum temperature of 51.6°C and a pumping power of 0.191 W. The results show that the Fibonacci phyllotaxis structure of the micro pin fin heat sink has better heat‐dissipating performance.

Multimodal machine learning for predicting heat transfer characteristics in micro-pin fin heat sinks

As three-dimensional integrated circuit (3D-IC) chip technology advances, thermal management has become increasingly important because of increasing heat flux from thermal stacking. Micro-pin fin-embedded cooling has emerged as a promising solution for 3D-ICs, offering better thermal and hydraulic performance than conventional microchannel heat sinks. It is also easy to integrate into existing 3D-IC structures, such as through-silicon vias between stacks. The utilization of two-phase flow in micro-pin fins further enhances temperature uniformity and improves the heat transfer coefficient by leveraging latent heat. Nevertheless, predicting thermal performance in micro-pin fin heat sinks under boiling conditions remains challenging owing to intricate geometric shapes and diverse operating conditions. The present lack of correlation or theoretical models poses a significant obstacle. To address this problem, our study employed a Multimodal machine-learning (ML) approach, combining image data capturing boiling patterns of two-phase flow and information about geometric shape and operating conditions, to predict heat transfer characteristics in micro-pin fin heat sinks. We utilized experimental data comprising 155 types of boiling heat transfer data with the dielectric fluid FC-72 in two micro-fin shapes directly etched on Si. Four ML algorithms (XGBoost, LightGBM, Multilayer perceptron (MLP), and Multimodal ML) were employed to predict thermal performance. The correlation coefficient analysis before learning revealed the influence of each type of measurement data on the heater surface temperature during two-phase flow. Prediction accuracy was measured using mean absolute percent error (MAPE), and the results were compared in terms of maximum and average temperature depending on the characteristics of each ML algorithm. Overall, the Multimodal approach demonstrated superior capability in predicting temperature distributions with spatial details, surpassing conventional decision-tree algorithms and MLP in performance. When trained with boiling images, the Multimodal ML model achieved remarkable precision, evidenced by a MAPE of 1.81% for the maximum temperature and 0.84% for the average temperature, highlighting its exceptional accuracy in mapping the heated surface temperature profile. By contrast, the traditional MLP model, which lacked training on boiling images, showed diminished accuracy, with a MAPE of 2.54% for the maximum temperature and 1.77% for the average temperature, indicating a comparative shortfall against the Multimodal model results.

Two-Phase Liquid Cooling for High-Power Microelectronics via Embedded Micro-Pin Fin Heat Sink

Two-Phase Liquid Cooling for High-Power Microelectronics via Embedded Micro-Pin Fin Heat Sink

Thermal-hydraulic performance enhancement of modified hexagonal micro-Pin fin heat sinks using rotational configurations

Nowadays, micro-pin fin heat sinks (MPFHSs) have shown promising performance in removing high heat fluxes in small dimensions and are widely used in electronic cooling applications. Among various techniques for thermal–hydraulic enhancement of MPFHSs, geometric design modification has been emphasized in this study, which focuses on investigating the orientation of the micro-pin fins (MPFs) as an overlooked but crucial parameter. To this end, rotational configurations of modified hexagonal MPFs, including co-rotation, alternating rotation, and counter-rotation have been investigated at rotation angles ranging from 0 to 60 degrees. In the numerical study, the copper MPFHS with a heat flux of 50 W/cm2 is cooled using water within the Reynolds number (Re) range of 400 to 1000. The results revealed that the rotation angle of MPFs governs the flow behavior around them. In general, counter-rotation configurations exhibited better thermal performance by providing the possibility of increased fluid mixing and contraction of low-velocity recirculation zones. However, the considerable increase in pressure drop in this configuration may limit its usability in higher Re regimes. By considering the compromise between pressure drop and heat transfer, the counter-rotation configuration with a 30-degree angle was selected as the optimal design. The optimized design results in an increase of approximately 50 % in Nusselt number (Nu) and up to 26.7 % in performance evaluation criteria (PEC). Furthermore, a supplementary experimental study confirmed the numerical results. It demonstrated the remarkable performance of the proposed design in removing heat fluxes ranging from 125 to 250 W/cm2, within the range of Re under investigation.

The study of heat characteristics for micro pin-fin heat sinks with different structures

Heat flux in electronic devices has increased dramatically with the development of advanced IC technology, facing the demand for effective thermal management technology. Micro pin-fin heat sink (MPFHS) has been demonstrated to be capable of improving the heat transfer capability and suppressing temperature rise effectively. In order to elaborate the discrepancy of heat dissipation of the MPFHS due to the cross-section shapes of pin-fin structures a set of heat sink samples with four different shapes, including the circle-MPFHS, the square-MPFHS, the crisscross- MPFHS, and the octagon-MPFHS, are fabricated with micromachining technology. Then, the thermal characteristics are tested by integrating the heat sinks with a Pt film resistor chip as the heating source, and nucleate boiling phenomenon was observed with a high-speed camera. Results showed that concave corners in pin-fin structures increased the specific surface area, but generated low velocity vortexes in back flow regions, reducing the heat transfer capability. The heat transfer coefficients of the octagon-MPFHS, the crisscross-MPFHS, and the circle- MPFHS was increased by 161.9 %, 152.4%, and 85.7 %, respectively, relative to the square-MPFHS at the flow rate of 147 kg/m2s. The heat transfer coefficients of the octagon-MPFHS, the crisscross-MPFHS, the circle-MPFHS, and the square- MPFHS was increased by 7.27%, 11.32%, 2.56%, and 4.76% when the mass-flow rate was increased from 147 kg/m2s to 295 kg/m2s. The nucleate boiling phenome-non in the crisscross-MPFHS showed periodicity and positive feedback effect, resulting in local dry-out and consequent heat transfer capability deterioration. This study will contribute to the design and modification of MPFHS.

Heat transfer enhancement in multijet micropin fin heat sink

The thermal performance of tiny heat sinks with liquid cooling is being studied in order to solve the issue of electronics cooling. Increasing thermal performance while lowering pressure drop and maintaining a constant substrate temperature is a difficult task. The purpose of this study is to harvest the useful features of combination of microjet and micropin fins and explore the influence of geometrical features on fluid structures and heat transfer. To comprehend and assess the performance of a multijet heat sink with a micropin fin, three-dimensional numerical simulation is used in this inquiry. The three parameters under consideration are, the ratio of the jet diameter to the pin fin diameter (α), which ranges from 1.5 to 6.0; the ratio of the jet diameter to the jet standoff distance (β), which ranges from 0.75 to 1.5; and the pin fin pitch is determined by the ratio of the pin fin diameter to the pitch length (λ), which ranges from 0.1 to 0.8. The grid independence test is done to ensure accuracy in numerical results. The numerical scheme is validated by comparing numerical results with that of experimental results from literature. The results obtained from numerical simulation are analyzed. It has been found that improving heat transfer is not just caused by expanding the contact surface area; fluid structure vortex generation also affects overall thermal performance. Better overall performance is produced at lower values of α, β and higher values of λ. The ideal design parameters are α = 1.99, β = 1.431, and λ = 0.699, according to the optimization of geometrical parameters using a radial basis neural network surrogate model and particle swarm optimization. The jet Reynolds number is found to have no significant impact on the overall performance.

Hydraulic and thermal performances of micro pin fin heat sink with increasing pin fin height

This study investigates numerically the impacts of pin fins (PF) with varying height on the pressure drop ΔP, the bottom average temperature Tbw, the Nusselt number Nu and the thermal performance factor η of a micro pin fin heat sink (MPFHS). Three groups of PF structure characterized by a different height increase mode are introduced: Case 1: structure with constant height step, Case 2: structure with increasing height step, and Case 3: structure with decreasing height step. The findings in this work show that ΔP and Nu increase but Tbw decreases with the increasing height step for Case 1 and with the increasing increment of the height step for Case 2 and Case 3. When comparing their thermal and hydraulic performances, Case 2 demonstrates the best thermal performances, whereas Case 3 has the best hydraulic performance when the total height steps of PFs in all three kinds of heat sink are kept constant. Furthermore, this study finds that the PF with increasing height can always enhance η of the MPFHS compared to PF with uniform height. This finding validates the performance advantage of the PF with increasing height and offers the potential technique for the optimization design of MPFHS.

Multi-Objective Optimization of Air-Cooled Perforated Micro-Pin Fin Heat Sink Via an Artificial Neural Network Surrogate Model Coupled With NSGA-II

Abstract This research aims to create an artificial neural network (ANN) regression model for predicting the performance parameters of the perforated micro-pin fin (MPF) heat sinks for various geometric parameters and inflow conditions. A three-dimensional computational fluid dynamics (CFD) simulation system is developed to generate dataset samples under different operational conditions, which are specified using Latin hypercube sampling (LHS). An ANN model is first obtained by optimizing the model hyper-parameters, which are then deployed to learn from the input feature space that consists of perforation diameter, perforation location, and inflow velocity. For accurate training of the ANN, the model is trained over a range of uniformly distributed data points in the input feature space. The developed multi-layer model predicted Nusselt number and friction factor with the mean absolute percentage error of 4.45% and 1.80%, respectively. Subsequently, the developed surrogate model is used in the optimization study to demonstrate the application of the surrogate model. A multi-objective non-dominated sorting genetic algorithm (NSGA-II) is used to perform the optimization of the perforation location, diameter, and inflow conditions. Negative of the Nusselt number and friction factor are chosen as objectives to minimize. A Pareto front is obtained from the optimization study that shows a set of optimal solutions. Thermal performance of the perforated MPF is increased between 11.5% and 39.77%. The optimizer selected a significantly smaller hole diameter at a higher location and a faster speed to maximize the Nusselt number and minimize the friction factor.

Modified hexagonal pin fins for enhanced thermal-hydraulic performance of micro-pin fin heat sinks

PurposeThis numerical study aims to investigate the modification of the hexagonal pin fin geometry to enhance both the thermal and hydraulic performance of the copper micropin fin heat sink with single-phase water coolant in a laminar regime. The heat sink performance evaluation criteria have been investigated for the parametric effects of vertex angle θ (10–120) and relative length (RL) (0.25–9) of hexagonal pin fins.Design/methodology/approachTo carry out research and reduce the computational cost, only one heat sink unit is simulated and analyzed using periodic boundary conditions on the side walls and includes a hexagonal pin fin and half channel on both sides to reflect the structural characteristics completely. The governing equations are also solved using finite volume method.FindingsThe results reveal that θ = 60 and RL = 1 yield the optimum thermal performance and heat sink performance is significantly influenced by the vertex angle and RL. The modified hexagon geometry improves fluid flow behavior by reducing the volume of the recirculation region behind the pin fin, preventing its effects on the downstream pin fins and restricting the thermal boundary layer development on its straight side. At Re = 1,000, the modified geometry enhances the average Nusselt number by 24.46% and the thermal performance factor by 23.89%, demonstrating the potential of modified hexagonal pin fins to enhance micropin fin heat sink performance.Originality/valuePrior studies suggest using the pin fins with a regular hexagonal cross-section to obtain better thermal performance. However, this comes with a higher pressure drop penalty. The modification of the hexagonal pin fin geometry has been investigated in this numerical study to enhance both the thermal and hydraulic performance of the micropin fin heat sink. Because little attention has been paid to the modification of the regular hexagonal pin fins, as a geometry inspired by natural honeycomb structures, its design optimization is relatively scarce, and a gap was felt in this field.

Experimental investigations of the flow boiling characteristics of green refrigerants in a novel petaloid micropin-fin heat sink

Although micropin-fin heat sinks (MPFHSs) are widely regarded as an effective way to dissipate heat in microelectronic equipment, the pin fin structure has not changed much over the years. Inspired by the flower of Clematis montana, a novel petaloid structure was designed. The flow boiling characteristics of green refrigerants, including R1234ze(E) and R1234yf, in the petaloid MPFHS were investigated under mass fluxes of 100–200 kg/m2 s, heat fluxes of 20–40 kW/m2 and saturation pressures of 0.4–0.6 MPa and compared with those of R134a. In the nucleate boiling zone, the heat transfer coefficient (HTC) rises with saturation pressure, vapor quality, and heat flux; in the convective boiling region, it rises with mass flux. With mass flux and vapor quality, the frictional pressure drop (FPD) rises; with saturation pressure, it falls; with heat flux, it keeps constant. R1234ze(E) shows the largest HTC and the smallest FPD, and R1234yf and R134a have similar HTC and FPD. Specific bubbles, slugs, confined slugs and liquid films yielded by the petaloid micropin fins are identified, and the flow behaviors, including coalescence and separation of bubbles/slugs, are described. Comparing the existing empirical correlations for flow boiling HTC and FPD in plain and micropin-fin channels with the experimental data yields unsatisfactory mean absolute deviations (MADs). Hence, new correlations for petaloid MPFHS are developed, which yield satisfactory MADs of 12.6% and 9.9% for HTC and FPD, respectively.

Experimental and numerical investigations of the thermal–hydraulic characteristics of novel micropin-fin heat sinks

Micropin-fin heat sinks (MPFHSs) have great potential to dissipate heat from microelectronic equipment. However, explorations of MPFHSs with novel pin fins are still rare. By drawing on the flower of Clematis montana and the skin of Squalus acanthias, two micropin-fin structures, termed petaloid and placoid, were designed. The thermal–hydraulic characteristics of water flowing in MPFHSs were investigated with inlet temperatures of 10 and 20 °C, Reynolds number (Re) values of approximately 300–1500, and heat fluxes of 80–120 kW/m2. The heat transfer coefficient, Nusselt number (Nu), pressure drop and friction factor (f) of the MPFHS with petaloid pin fins were the largest, and those of the MPFHS with placoid pin fins were the smallest. The values increased with increasing Re except for the f, changed slightly with heat flux, and decreased with inlet temperature except for the f due to variation in physical properties. The temperature and velocity fields of MPFHSs were affected by pin fins. The water temperature was higher near the tail of the pin fins than in areas farther from the pin fins. Vortices generated by petaloid pin fins were the most plentiful and largest, while those generated by placoid pin fins were the least plentiful and smallest. For MPFHSs with different pin fins, the transition from laminar to turbulent flow was different; the transition Re was approximately 900 for petaloid and circular pin fins and larger than 1500 for placoid pin fins. The comprehensive performances of MPFHSs were evaluated by different indicators. For indicators emphasizing heat transfer, petaloid pin fins performed better than circular pin fins at small Re, and placoid pin fins performed worst in the whole Re range. For indicators emphasizing flow resistance, petaloid pin fins performed worst, and placoid pin fins performed best. New correlations of the Nu and f for MPFHSs with different pin fins were proposed with mean absolute deviations less than 2.0 and 4.5%, respectively.

Thermo-hydraulic investigation of two stepped micro pin fin heat sink having variable step size

To achieve enhanced flux dissipation, microchannels heat sink are being effectively implemented in various engineering processes. Here, a numerical analysis is to be carried out on an open stepped micro pin fin heat sink (MPFHS) with different step size. The stepped pin fin heat sink (PFHS) having varied fin height in an array of two fins having inline arrangement. For the simulation purpose, a single-phase water was used as working fluid with variable thermophysical properties. The present configuration has operated for Reynolds number =100-500, heat flux of 500 kW/m2. The step variation of 100 µm, 200 µm and 300 µm has been considered. It was observed that with increase in step size, the heat transfer augmentation also increases. However, at higher Reynold number, the present studies does not provide effective results in terms of sustainability.

Numerical investigation of CPU cooling with micro-pin–fin heat sink in different shapes

Numerical investigation of CPU cooling with micro-pin–fin heat sink in different shapes

A machine learning approach for predicting heat transfer characteristics in micro-pin fin heat sinks

Micro-pin fin heat sinks are receiving attention for their use in the thermal management of high-heat-flux electronics systems since they can help to enhance heat transfer characteristics (owing to their large extended surface area) and flow mixing while requiring relatively low pumping power compared with conventional microchannel heat sinks. Although many studies have determined the thermal performance of micro-pin fin heat sinks over the past several decades, a universal model for predicting the thermal performance of micro-pin fin heat sinks with various geometries and under different operating conditions has not been developed. In this study, we developed universal machine learning models for predicting the thermal performance of micro-pin fin heat sinks of various shapes and under different operating conditions beyond the limits of existing correlations by using power law regression. The database for these models comprised 906 data points amassed from 15 studies. Three machine learning models and a newly proposed regression model were compared with the conventional regression models. The prediction accuracies of each model and complex relations between the geometric shape, operating conditions, and heat transfer performance are discussed by comparing the three machine learning models and the regression model. The machine learning models had mean absolute errors (MAEs) of 7.5–10.9%, representing an approximately fivefold enhancement in the prediction accuracy compared with existing regression correlations. Their MAEs were lower than that of the regression model. Moreover, the machine learning models provided high accuracies for rare geometric shapes and operating conditions, such as a triangular pin shape or the use of R134A as a working fluid. These results showed the superiority of the machine learning models over traditional correlations in terms of the prediction accuracy for the thermal performance of micro-pin fin heat sinks over a wide range of geometric and operating conditions.

Numerical analysis of heat transfer evacuation from a cavity confining coated micro-pin fin heat sink using lattice Boltzmann approach

Numerical analysis of heat transfer evacuation from a cavity confining coated micro-pin fin heat sink using lattice Boltzmann approach

Numerical study of the effects of pin geometry and configuration in micro-pin-fin heat sinks for turbulent flows

This study numerically investigates a micro-pin-fin heat sink (MPFHS) to improve cooling capability and productivity of MPFHS. It was assumed that the flow is turbulent, steady, and incompressible. Turbulence was modeled using the k−ε turbulence model. For this purpose, the effects of different pin-fin configurations, including RS, ET, and ES, height, fluid velocity, in terms of heat transfer, pressure drop, as well as temperature variation between the inlet and outlet were studied in detail. Moreover, a comparison investigation with experimental results was carried out. Finally, it is found that the RS configuration possessed maximum heat transfer while yielding the maximum pressure drop. Smaller distances between the pins improved heat transfer but enhanced the convective heat transfer coefficient and increased pressure drop. Contrarily, an increased pin length and diameter enhanced pressure drop and heat transfer for all the configurations. This was more obvious in the RS configuration.

Thermal design and management of micro-pin fin heat sinks for energy-efficient three-dimensional stacked integrated circuits

Three-dimensional stacked electronics have substantially improved the electrical performance of integrated circuits. However, given the geometrical complexity and high pressure drop they entail, thermal management difficulties and energy requirements are exacerbated owing to the inapplicability of thermal management schemes. In this study, the thermal and hydrodynamic characteristics of various micro-pin fin arrays were investigated to maximize heat dissipation while minimizing the energy consumption. Specifically, a 10 × 10 mm2 micro-pin fin array was fabricated on an eight-inch silicon wafer via microfabrication. A Pyrex cover was bonded anodically with the top side of the micro-pin fins to prevent leakage, and a titanium/gold thin film serpentine heater was used to supply uniform heat flux on the backside of the micro-pin fin array. Subsequently, the heat transfer and pressure drop in the micro-pin fin heat sinks were obtained experimentally with various micro-pin fin geometries having pin diameter Df = 38–100 µm, transverse pin spacing ST = 74–301 µm, longitudinal pin spacing SL = 74–301 µm and pin height Hf = 90–207 µm. Thereafter, the geometrical and operational effects on heat transfer and pressure drop were investigated based on a consolidated database cumulated from the literature. Altogether, 256 data points from 21 geometrical combinations were explored from existing relevant studies to obtain optimized geometric and operating conditions in the micro-pin fin arrays over a wide range of geometrical and operating conditions: Reynolds number Re = 35–491.3, heat flux q" = 0–114 W/cm2, pin diameter Df = 38–559 µm, pin spacing S = 74–800 µm, and pin height Hf = 90–845 µm. Subsequently, new empirical correlations based on the consolidated database were formulated to describe the Nusselt number and fanning friction factor in the micro-pin fin arrays. These correlations provide suitable predictions in comparison with those based on extant correlations.

An artificial neural network model for predicting frictional pressure drop in micro-pin fin heat sink

Abstract This study is part of two studies conducted for developing artificial neural-network-based tools for predicting the thermal and hydraulic performance of micro-pin fin heat sinks used for high-heat-flux electronic devices. The thermal design of high-heat-flux electronics requires a strong understanding of both pressure drop and heat transfer coefficient. Increasing the pressure drop in a cooling system significantly increases the required pumping power and decreases the system energy efficiency, in addition to considerably increasing temperature nonuniformity and causing reliability issues. Micro-pin fin heat sinks can help in the thermal management of high-heat-flux electronic systems owing to their effective heat transfer characteristics, namely, a large surface area and passage flow turbulence generation, and the requirement of lower pumping power compared with the microchannel heat sink. Studies conducted over the past decade have revealed that the thermal and hydraulic performance of micro-pin fin heat sinks are highly dependent on their geometric and operational parameters. However, a universal approach to predicting the frictional pressure drop, which influences the amount of power required, in pin fin arrays for various operating conditions and geometric shapes has not been developed so far. In this study, a trained artificial neural network (ANN) was used to develop a universal model for predicting the friction factor of micro-pin fin arrays. The friction factor correlation was predicted from 1,651 experimentally determined friction factor data points obtained from 22 studies. The relationship between a wide range of geometric and operating conditions and the hydraulic performance was investigated for accurately training the ANN. Furthermore, the universal model was analyzed by comparing values predicted by it with values obtained in other experimental studies. The model was found to show superior performance compared with other regression-method-based correlations.

Computational modeling of thermal characteristics of hybrid nanofluid in micro-pin fin heat sink for electronic cooling

ABSTRACT Emerging technology in the electronic industry has led to miniaturization of electronic devices such as iPhones and laptops. Heat dissipation is required to maintain high performance and long-term reliability of these devices. Micro heat sinks and novel working fluids such as nanofluids are becoming popular. Until recent times the full potential of hybrid nanofluid in heat transfer has not yet been exploited. In order to address the lack of adequate modeling data in this field, the aim of this study is to systematically model and investigate computational heat transfer characteristics of Al2O3-Cu/water hybrid nanofluid in micro heat sink. Volume concentration in the range of 0.1%-0.5% was used for the working fluid. Hexagonal micro-pin fin heat sink with staggered arrangement was simulated in ANSYS Fluent. Reliable experimental result from literature was used to validate the accuracy of the results. The most obvious finding to emerge from this study is that the Nusselt number increases with increase in Reynolds number and this observation is consistently the same at different concentrations and pin spacing. Lower transverse pitch was observed to dominate the enhancement of Nusselt number. There was a 10% increase in heat transfer coefficient at 0.5% nanofluid concentration when compared to 0.1%. This phenomenon is highly influenced by the transition of the Re into turbulent situation which eventually enhances the heat transfer characteristics. Also, lower transverse pitch promotes swirling flow situation. At 0.5% hybrid nanofluid concentration, it was observed that the Nusselt number increased from 14.00 at transverse pitch of 3.81 mm to 17.00 at a transverse pitch of 1.81 mm and this corresponds to 16.05% enhancement of Nusselt number. The pressure drop penalty of the working fluid is a result of increase in viscous effect of the hybrid nanofluid, especially at high concentration.