Search Results (39)

The escalating heat flux densities in high-performance electronics necessitate superior thermal management. This study enhanced pool-boiling heat transfer, a method offering high heat removal capacity, by leveraging Binder Jetting 3D Printing (BJ3DP) to create complex porous copper structures without the need for chemical treatments. This approach enables a reliable utilization of phenomena like capillarity for improved performance. Three types of porous copper structures, namely Large Lattice, Small Lattice, and Staggered, were fabricated on pure copper substrates and tested via pool boiling of de-ionized and de-gassed water at atmospheric pressure. Compared to a plain polished copper surface, which exhibited a critical heat flux (CHF) of 782 kW/m² at a wall superheat of 18 K, the 3D-printed porous copper surfaces showed significantly improved heat transfer performance. The Staggered surface achieved a conventional CHF of 2342.4 kW/m² (a 199.7% enhancement) at a wall superheat of 24.6 K. Notably, the Large Lattice and Small Lattice structures demonstrated exceptionally stable boiling without reaching the typical catastrophic CHF within the experimental parameters. These geometries continued to increase in heat flux, reaching maximums of 2397.7 kW/m² (206.8% higher at a wall superheat of 55.6 K) and 2577.2 kW/m² (229.7% higher at a wall superheat of 39.5 K), respectively. Subsequently, a gradual decline in heat flux was observed with an increasing wall superheat, demonstrating an outstanding resistance to the boiling crisis. These improvements are attributed to the formation of distinct vapor–liquid pathways within the porous structures, which promotes the efficient rewetting of the heated surface through capillary action. This mechanism supports a highly efficient, self-sustaining boiling configuration, emphasizing the superior rewetting and vapor management capabilities of these 3D-printed porous structures, which extend the boundaries of sustained high heat flux performance. The porous surfaces also demonstrated a higher heat transfer coefficient (HTC), particularly at lower heat fluxes (≤750 kW/m²). High-speed digital camera visualization provided further insight into the boiling phenomenon. Overall, the findings demonstrate that these BJ3DP structured surfaces produce optimized vapor–liquid pathways and capillary-enhanced rewetting, offering significantly superior heat transfer performance compared to smooth surfaces and highlighting their potential for advanced thermal management. Full article

Boiling heat transfer, utilizing latent heat during phase change, has widely been used due to its high thermal efficiency and plays an important role in existing and next-generation cooling technologies. The most critical parameter in boiling heat transfer is critical heat flux (CHF), which represents the maximum heat flux a heated surface can sustain during boiling. CHF is primarily influenced by the wicking performance, which governs liquid supply to the surface. This study experimentally and numerically analyzed the wicking performance of micropillar structures at various temperatures (20–95 °C) using distilled water as the working fluid to provide fundamental data for CHF prediction. Infrared (IR) visualization was used to extract the wicking coefficient, and the experimental data were compared with computational fluid dynamics (CFD) simulations for validation. At room temperature (20 °C), the wicking coefficient increased with larger pillar diameters (D) and smaller gaps (G). Specifically, the highest roughness factor sample (D04G10, r = 2.51) exhibited a 117% higher wicking coefficient than the lowest roughness factor sample (D04G20, r = 1.51), attributed to enhanced capillary pressure and improved liquid supply. Additionally, for the same surface roughness factor, the wicking coefficient increased with temperature, showing a 49% rise at 95 °C compared to 20 °C due to reduced viscous resistance. CFD simulations showed strong agreement with experiments, with error within ±10%. These results confirm that the proposed numerical methodology is a reliable tool for predicting wicking performance near boiling temperatures. Full article

This article presents an exhaustive and comprehensive review of research endeavors conducted in China over the past three decades focusing on critical heat flux—a thermal–hydraulic phenomenon of paramount importance in nuclear engineering. CHF represents the ultimate threshold of heat transfer capability, governed by fundamental physical principles, and serves as a cornerstone in the design of reactor cores, fundamentally delineating the reactor’s capacity for safe heat dissipation. In this study, we undertake a meticulous analysis of 60+ research papers published in Chinese by a diverse array of Chinese research institutions spanning the last three decades, encompassing both experimental and numerical simulation investigations. The experimental research is systematically reviewed. The experimental setups and test sections are examined in detail. Then, the experimental parameters and conclusions are analyzed comprehensively. This examination elucidates the achievements attained and the challenges encountered in the experimental domain. In the realm of numerical simulation research, this review consolidates the prevailing hypotheses regarding inherent mechanisms, modeling methodologies, and their validations against experimental data. Building upon the existing research accomplishments and acknowledging the emerging trends in fluid mechanics research, particularly the integration of next-generation measurement technologies and artificial intelligence, a strategic and forward-looking research trajectory is proposed. This trajectory aims to guide and inspire future endeavors in this crucial and intricate field, fostering a deeper understanding and enhanced performance of nuclear reactors through innovative and rigorous research. Full article

This paper introduces a novel hyperparameter optimization framework for regression tasks called the Combined-Sampling Algorithm to Search the Optimized Hyperparameters (CASOH). Our approach enables hyperparameter tuning for deep learning models with two hidden layers and multiple types of hyperparameters, enhancing the model’s capacity to work with complex optimization problems. The primary goal is to improve hyperparameter tuning performance in deep learning models compared to conventional methods such as Bayesian Optimization and Random Search. Furthermore, CASOH is evaluated alongside the state-of-the-art hyperparameter reinforcement learning (Hyp-RL) framework to ensure a comprehensive assessment. The CASOH framework integrates the Metropolis-Hastings algorithm with a uniform random sampling approach, increasing the likelihood of identifying promising hyperparameter configurations. Specifically, we developed a correlation between the objective function and samples, allowing subsequent samples to be strongly correlated with the current sample by applying an acceptance probability in our sampling algorithm. The effectiveness of our proposed method was examined using regression datasets such as Boston Housing, Critical heat flux (CHF), Concrete compressive strength, Combined Cycle Power Plant, Gas Turbine CO, and NOx Emission, as well as an ‘in-house’ dataset of lattice-physics parameters generated from a Monte Carlo code for nuclear fuel assembly simulation. One of the primary goals of this study is to construct an optimized deep-learning model capable of accurately predicting lattice-physics parameters for future applications of machine learning in nuclear reactor analysis. Our results indicate that this framework achieves competitive accuracy compared to conventional random search and Bayesian optimization methods. The most significant enhancement was observed in the lattice-physics dataset, achieving a 56.6% improvement in prediction accuracy, compared to improvements of 53.2% by Hyp-RL, 44.9% by Bayesian optimization, and 38.8% by random search relative to the nominal prediction. While the results are promising, further empirical validation across a broader range of datasets would be helpful to better assess the framework’s suitability for optimizing hyperparameters in complex problems involving high-dimensional parameters, highly non-linear systems, and multi-objective optimization tasks. Full article

The nucleation and growth of bubbles on homogeneous wetting surfaces have been extensively studied, but the intricate dynamics on hybrid wetting surfaces remain under-explored. This research aims to elucidate the impact of hybrid wettability on pool boiling heat transfer efficiency, specifically under downward-facing heating conditions. To this end, a series of hybrid wettability surfaces with varying hydrophilic and hydrophobic configurations are meticulously fabricated and analyzed. The study reveals distinctive interfacial phenomena occurring at the boundary between hydrophilic and hydrophobic regions during the boiling process. Experimental results indicate that surfaces with a higher proportion of hydrophilic to hydrophobic interfaces exhibit reduced superheat requirements and enhanced boiling heat transfer coefficients for equivalent heat flux densities. Furthermore, the rewetting characteristics of hybrid wettability surfaces are identified as pivotal factors in determining their critical heat flux (CHF). This investigation underscores the potential of hybrid wettability surfaces to optimize pool boiling heat transfer, offering valuable insights for the design and en-hancement of heat exchangers and other thermal management systems. Full article

This study represents the development and optimization of a micro-baffle design to enhance heat transfer in film boiling. Numerical simulations are performed using an open-source computational fluid dynamics (CFD) model, which incorporates the Lee model for momentum source associated with the phase change, and the Volume of Fluid (VOF) method to capture bubble dynamics. A comparison of the numerical results with the previous numerical and experimental data confirmed the validity of the numerical model. The influence of key design parameters was systematically investigated. The results revealed that a vertical baffle provided the maximum performance. The optimal baffle design achieved a 57.4% improvement in the Nusselt number and a 66.4% increase in critical heat flux (CHF). Furthermore, the proposed design facilitated continuous bubble formation, even with a reduced temperature difference between the heated surface and the subcooled liquid, which is crucial for energy-efficient thermal management in engineering systems. Ultimately, this study demonstrates the potential of micro-baffle designs in controlling bubble dynamics and improving heat transfer in film boiling, thereby aiding the design of efficient thermal systems. Full article

Utilizing pool boiling as a cooling method holds significant importance within power plant industries due to its ability to effectively manage temperature differentials amidst high heat flux conditions. This study delves into the impact of surface modifications on the pool boiling process by conducting experiments on four distinct boiling surfaces under various conditions. An experimental setup tailored for this investigation is meticulously designed and implemented. The primary objective is to discern the optimal surface configuration capable of efficiently absorbing maximum heat flux while minimizing temperature differentials. In addition, this study scrutinizes bubble dynamics, pivotal in nucleation processes. Notably, surfaces polished unidirectionally (ROD), exhibiting lower roughness, demonstrate superior performance in critical heat flux (CHF) compared to surfaces with circular roughness (RCD). Moreover, the integration of bubble liquid separation methodology along with the introduction of a bubble micro-layer yields a microchannel surface. Remarkably, this modification results in a noteworthy enhancement of 131% in CHF and a substantial 211% increase in the heat transfer coefficient (HTC) without resorting to particle incorporation onto the surface. This indicates promising avenues for enhancing cooling efficiency through surface engineering without additional additives. Full article

The rapid progress of electronic devices has necessitated efficient heat dissipation within boiling cooling systems, underscoring the need for improvements in boiling heat transfer coefficient (HTC) and critical heat flux (CHF). While different approaches for micropillar fabrication on copper or silicon substrates have been developed and have shown significant boiling performance improvements, such enhancement approaches on aluminum surfaces are not broadly investigated, despite their industrial applicability. This study introduces a scalable approach to engineering hierarchical micro-nano structures on aluminum surfaces, aiming to simultaneously increase HTC and CHF. One set of samples was produced using a combination of nanosecond laser texturing and chemical etching in hydrochloric acid, while another set underwent an additional laser texturing step. Three distinct micropillar patterns were tested under saturated pool boiling conditions using water at atmospheric pressure. Our findings reveal that microcavities created atop pillars successfully facilitate nucleation and micropillars representing nucleation site areas on a microscale, leading to an enhanced HTC up to 242 kW m⁻² K⁻¹. At the same time, the combination of the surrounding hydrophilic porous area enables increased wicking and pillar patterning, defining the vapor–liquid pathways on a macroscale, which leads to an increase in CHF of up to 2609 kW m⁻². Full article

Boiling with downflow in vertical channels is involved in many applications such as boilers, nuclear reactors, chemical processing, etc. Accurate prediction of CHF (Critical Heat Flux) is important to ensure their safe design. While numerous experimental studies have been done on CHF during upflow and reliable methods for predicting it have been developed, there have been only a few experimental studies on CHF during downflow. Some researchers have reported no difference in CHF between up- and downflow, while some have reported that CHF in downflow is lower or higher than that in upflow. Only a few correlations have been published that are stated to be applicable to CHF during downflow. No comprehensive comparison of correlations with test data has been published. In the present research, literature on CHF during downflow in fully heated channels was reviewed. A database for CHF in downflow was compiled. The data included round tubes and rectangular channels, hydraulic diameters 2.4 mm to 15.9 mm, reduced pressure 0.0045 to 0.6251, flow rates from 15 to 21,761 kg/m²s, and several fluids with diverse properties (water, nitrogen, refrigerants). This database was compared to a number of correlations for upflow and downflow CHF. The results of this comparison are presented and discussed. Design recommendations are provided. Full article

It is widely established that flow boiling, being a direct cooling technique also employing the latent heat of the fluid, has the potential to be more efficient than being useful in single-phase conventional cooling methods. This results in considerable potential for thermal management in many fields like microelectronics, space technology, thermal power plants, etc. The increasing demand for heat dissipation, consequent to component miniaturization, has pushed the development of new strategies for enhancing heat transfer efficiency, such as employment of functionalized surfaces. This review aims to describe in detail the current status of technology related to flow boiling heat transfer enhancement via micro/nanoscale surface functionalization. Key objectives are an increased nucleation site density and enhanced bubble dynamics. The vast majority of findings show favorable heat transfer performance, evidenced by an earlier onset of boiling (ONB), an improved flow boiling heat transfer coefficient (HTC), and an ameliorated critical heat flux (CHF). Increased pressure drop is a serious concern in certain application cases. Nanoscale textures mainly enhance capillary wicking to nucleation sites, thus being more effective in combination with microscale textures that define fixed nucleation sites. Degradation effects need to be more thoroughly and systematically characterized for application cases. Extra effects related to the manufacturing process can be easily overlooked, but one should be aware of their possible existence when drawing conclusions. Finally, the implementation of enhanced surfaces in mainstream applications is hindered by the absence of general predictive design tools for different channel configurations/materials, fluids, and operating conditions. A more universal understanding of the basic mechanisms involving texture geometry is needed in this aspect. Full article

The effects of the anisotropic properties (wettability and roughness) of microgrooved surfaces on heat transfer were experimentally investigated during pool boiling using Novec-7100 as a working fluid. The idea for introducing the concept of anisotropic wettability in boiling experiments draws inspiration from biphilic surfaces. The investigation is also motivated by two-phase immersion cooling, which involves phase-change heat transfer, using a dielectric liquid as a working fluid. Very few studies have focused on the effects of surfaces with anisotropic properties on boiling performance. Thus, this study aims to examine the pool-boiling heat transfer performance on surfaces with microgroove-induced anisotropic properties under the saturation condition. A femtosecond-laser texturing method was employed to create microgrooved surfaces with different groove spacings. The results indicated that anisotropic properties affected the heat transfer coefficient and critical heat flux. Relative to the plain surface, microgrooved surfaces enhanced the heat transfer performance due to the increased number of bubble nucleation sites and higher bubble detachment frequency. An analysis of bubble dynamics under different surface conditions was conducted with the assistance of high-speed images. The microgrooved surface with a groove spacing of 100 μm maximally increased the BHTC by 37% compared with that of the plain surface. Finally, the CHF results derived from experiments were compared with related empirical correlations. Good agreement was achieved between the results and the prediction correlation. Full article

This study reports an experimental investigation of pool boiling (PB) heat transfer performance of hybrid (two types of particles) and mono (single-particle) nanofluids consisting of Boron nitride (BN) and Silicon dioxide (SiO₂) nanoparticles (NPs). While hybrid nanofluids (HNFs) were prepared in a total particle concentration of 0.05 vol.% with four different percentages of these two types of NPs (are 0.01/0.04, 0.02/ 0.03, 0.03/0.02, and 0.04/0.01 (BN vol.%/SiO₂ vol.%)), two mono nanofluids (MNFs) of BN and SiO₂ nanoparticles were prepared at the same total concentration of 0.05 vol.% for each NP type. Both nanofluids (NFs) were prepared in the base fluid (BF), which is the mixture of 15 vol.% of ethylene glycol (EG) and 85 vol.% of distilled water (DW). Then, the boiling heat transfer performance of these MNFs and HNFs was assessed by experimentation in a pool boiling test rig. The obtained results demonstrated good improvements in critical heat flux (CHF) and burnout heat flux (BHF) of both types of NFs. The CHF increased by up to 80% for BN-based MNF and up to 69% for HNF at 0.04 vol.% BN, which is the maximum percentage of BN into HNF, while the lowest improvement in CHF was 48% for the SiO₂-based MNF compared to the BF. Similarly, the BHF was found to increase with the increasing in the loading of BN nanoparticles and a maximum enhancement of BHF of 103% for BN-based MNF was observed. These HNFs and MNFs exhibited significantly improved pool boiling heat transfer performance compared to this BF, and it became lower by increasing the percentage of SiO₂ NPs in the HNFs. Full article

Nanofluid (NF) pool boiling experiments have been conducted widely in the past two decades to study and understand how nanoparticles (NP) affect boiling heat transfer and critical heat flux (CHF). However, the physical mechanisms related to the improvements in CHF in NF pool boiling are still not conclusive due to the coupling effects of the surface characteristics and the complexity of the experimental data. In addition, the current models for pool boiling CHF prediction, which consider surface microstructure characteristics, show limited agreement with the experimental data and do not represent NF pool boiling CHF. In this scenario, artificial intelligence tools, such as machine learning (ML) regressor models, are a very promising means of solving this nonlinear problem. This study focuses on creating a new model to provide more accurate NF pool boiling CHF predictions based on pressure, substrate thermal effusivity, and NP size, concentration, and effusivity. Three ML models (supporting vector regressor—SVR, multi-layer perceptron—MLP, and random forest—RF) were constructed and showed good agreement with an experimental database built from the literature, with MLP presenting the highest mean R² score and the lowest variability. A systematic methodology for optimizing the ML models is proposed in this work. Full article

This paper presents an experimental characterization of liquid nitrogen (LN₂) flow boiling in additively manufactured minichannels. There is a pressing need of concerted efforts from the space exploration and thermal transport communities to design high-performance rocket engine cooling channels. A close observation of the literature gaps warrants a systematic cryogenic flow boiling characterization of asymmetrically heated small (<3 mm) non-circular channels fabricated with advanced manufacturing technologies at mass flux > 3000 kg/m²s and pressure > 1 MPa. As such, this work presents the LN₂ flow boiling results for three asymmetrically heated additively manufactured GR-Cop42 channels of 1.8 mm, 2.3 mm, and 2.5 mm hydraulic diameters. Twenty different tests have been performed at mass flux~3805–14,295 kg/m²s, pressures~1.38 and 1.59 MPa, and subcooling~0 and 5 K. A maximum departure from nucleate boiling (DNB)-type critical heat flux (CHF) of 768 kW/m² has been achieved for the 1.8 mm channel. The experimental results show that CHF increases with increasing LN₂ flow rate (337–459 kW/m² at 25–57 cm³/s for 2.3 mm channel) and decreasing channel size (307–768 kW/m² for 2.5–1.8 mm channel). Finally, an experimental DNB correlation has been developed with 10.68% mean absolute error. Full article

Aluminum vapor chambers have become an important component used to solve heat dissipation problems in lightweight applications due to their low density and good heat transfer characteristics. In this paper, a new sintered aluminum powder wick is provided for an aluminum vapor chamber. An aluminum porous wick was sintered using liquid phase sintering technology. Using acetone as the working medium, the influence of the structural parameters of the aluminum wick on its boiling heat transfer performance was studied. The influence of thickness on the boiling heat transfer performance of a sintered porous wick is particularly significant. Thinner, porous wicks have better critical heat flux (CHF). The porosity and particle diameter mainly affect the heat transfer coefficient (HTC). At a low heat flux, the sintered wick with low porosity and a small particle diameter has a higher HTC. The HTC of porous wicks, with a larger particle diameter and porosity, decreases slower. The optimal porosity ranges from 46.4 ± 2.5% to 51.8 ± 2.5%. Compared with the polished aluminum plate, the CHF is increased by 1.7 times, and the HTC is increased by about 4.6 times under the same heat flux. Full article