International Communications in Heat and Mass Transfer最新文献

{"title":"Flow behavior in parallel heated pipes: The role of pipe inclination","authors":"Ron Rene Hayat ,&nbsp;Dvora Barnea ,&nbsp;Yehuda Taitel","doi":"10.1016/j.icheatmasstransfer.2025.108841","DOIUrl":"10.1016/j.icheatmasstransfer.2025.108841","url":null,"abstract":"<div><div>This study theoretically investigates the impact of pipe inclination, ranging from vertical upward to vertical downward, on evaporating flow in parallel pipes with shared inlet and outlet headers.</div><div>The first step in analyzing the flow behavior of multiple parallel pipes is to obtain the characteristic curve of pressure difference versus flow rate for a single heated pipe. Momentum and energy balances are iteratively solved, incorporating the local instantaneous flow pattern.</div><div>By utilizing the inclination dependent characteristic curves of individual pipes within an array of parallel inclined pipes all possible steady-state solutions for pressure difference and flow rate distribution can be determined as functions of the inlet flow rate for various inclination angles. Furthermore, time-dependent equations have been introduced for a system of parallel inclined pipes, and transient simulations have been conducted.</div><div>The study reveals that, depending on the inclination angle, pipe's diameter and heating power, three types of characteristic curves can be obtained for a single pipe. In the case of two parallel pipes, the effect of the inclination angle on the flow rate distributions and the system pressure drop has been shown. Three flow distribution patterns are identified: equal flow rate distribution, maldistribution, and maldistribution with oscillations.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"164 ","pages":"Article 108841"},"PeriodicalIF":6.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards robust predictions: Ensemble machine learning framework for entrainment fraction with uncertainty in annular flow regime","authors":"Anadi Mondal,&nbsp;Subash L. Sharma","doi":"10.1016/j.icheatmasstransfer.2025.108813","DOIUrl":"10.1016/j.icheatmasstransfer.2025.108813","url":null,"abstract":"<div><div>Entrainment fraction measures the fraction of liquid that is entrained as droplets into the gas core in gas-liquid annular flow. It directly impacts heat transfer characteristics, pressure drop, and flow stability in systems with an annular flow regime. Given its significance in industrial processes, many experiments have been carried out, leading to the proposal of various empirical and semi-empirical correlations. However, these correlations are often limited to specific operating conditions or gas-liquid combinations, making them unsuitable for robust prediction. Additionally, some correlations require many input parameters and iterative methods for predicting the entrainment fraction. This paper proposes two ensemble machine learning models—Random Forest (RF) and Gradient Boosting Regression (GBR)—for robust entrainment prediction in annular flow, applicable to varying operating conditions as well as gas-liquid combinations. The proposed models can learn complex correlations among 5 dimensionless input parameters—liquid and gas Reynolds number (<em>Re</em>_<em>L</em> and <em>Re</em>_<em>g</em>), Weber (gas) number (<em>We</em>_<em>g</em>), density ratio of liquid to gas(<em>ρ</em>_<em>l</em><em>/ρ</em>_<em>g</em>), and viscosity ratio of liquid to gas (μ_<em>l</em><em>/</em>μ_<em>g</em>)—to predict the entrainment fraction. A dataset of about 1628 data points on liquid entrainment from 11 authors was used to train (1302 data points—80 % of the data) and test (326 data points—20 % of the data) the models. The developed models were further validated on 140 completely raw(unseen) data points (not used for training and testing, but in the range of training dataset) and 153 extrapolated (outside of training range or flow configuration) data points from varying operating conditions. The performance of these two models was compared to five correlations and three other algorithms—Linear Regression (LR), K-nearest neighbors (KNN), and Support Vector Regression (SVR). Four evaluation metrics—Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Coefficient of Determination (R²)—were utilized for performance evaluation. The results indicate that the ensemble models outperformed both empirical correlations and other machine learning models, achieving the lowest RMSE, MAE, and MAPE values, along with the highest R² on test and unseen data points. Only 15.7 % and 20 % of unseen data points were outside the ±30 % limit for the RF and GBR models, respectively, compared to at least 22.1 % for the empirical models and 22.8 % for the other machine-learning models. Moreover, predictions on extrapolated data points, along with uncertainty quantification and the effect of experimental parameters on prediction accuracy for unseen data points, have also been conducted here.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"164 ","pages":"Article 108813"},"PeriodicalIF":6.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heat transfer mechanism of spray cooling under vibrational conditions: Effects of spray volume flow rate and nozzle inclination angle","authors":"Meng Zhang ,&nbsp;Xinwen Chen ,&nbsp;Kun Liang ,&nbsp;Zhaohua Li ,&nbsp;Xiang Wang ,&nbsp;Jinzuo Huang ,&nbsp;Yuqi Qian ,&nbsp;Hang Zhou","doi":"10.1016/j.icheatmasstransfer.2025.108820","DOIUrl":"10.1016/j.icheatmasstransfer.2025.108820","url":null,"abstract":"<div><div>Spray volume flow rate and nozzle inclination angle are key parameters affecting the heat transfer performance in spray cooling. However, under complex vibration conditions, the effects of spray volume flow rate and nozzle inclination angle on spray cooling heat transfer performance remain unclear. This study employs experimental research to systematically investigate the effects of different spray volume flow rates and nozzle inclination angles on spray cooling heat transfer performance under vibration conditions. Experimental results show that under vibration conditions, the heat transfer performance of spray cooling improves with an increase in spray volume flow rate. However, excessive flow rates increase droplet splashing, reducing the amount of coolant effectively involved in heat exchange, thus decreasing cooling efficiency. Under vibration conditions (amplitude of 2 mm, frequency of 25 Hz), when the nozzle inclination angle is 0°, and the spray volume flow rate is 3.2 × 10⁻² m³/m²·s, the cooling efficiency is 18 %, which is 27 % lower compared to the cooling efficiency at a spray volume flow rate of 2.0 × 10⁻² m³/m²·s. Moreover, appropriately increasing the nozzle inclination angle under vibration conditions can effectively suppress droplet splashing, thereby enhancing heat transfer performance. However, when the nozzle inclination angle is too large, the force of the droplets penetrating the liquid film is significantly reduced, thereby hindering direct heat exchange between the droplets and the heated surface. Under vibration conditions (amplitude of 2 mm, frequency of 25 Hz), when the spray volume flow rate is 2.0 × 10⁻² m³/m²·s, the optimal nozzle inclination angle is 15°, with a critical heat flux of 57.5 W/cm², which is 5 % and 11 % higher compared to the nozzle inclination angles of 0° and 30°, respectively. This study reveals the effects of spray volume flow rate and nozzle inclination angle on the heat transfer performance of spray cooling under vibration conditions, providing theoretical guidance for optimizing thermal management of high heat flux electronic devices.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"164 ","pages":"Article 108820"},"PeriodicalIF":6.4,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heat source field inversion and detection based on physics-informed deep learning","authors":"Yimeng Chi,&nbsp;Mingliang Li,&nbsp;Rui Long,&nbsp;Zhichun Liu,&nbsp;Wei Liu","doi":"10.1016/j.icheatmasstransfer.2025.108824","DOIUrl":"10.1016/j.icheatmasstransfer.2025.108824","url":null,"abstract":"<div><div>Heat source field inversion and detection (HSFID) has drawn increasing attention as the exponentially growing application for integrated circuits, which offers promising way for determining the system's unnormal operation condition. In the HSFID, embodying the physical constraints in the neural networks could significantly reduce the data demand for training and offer higher reconstruction accuracy. In present study, the physics-informed neural network (PINN) is employed to achieve the goal of HSFID. The problem of reconstructing the heat source field is transformed into the challenge of temperature field reconstruction. The PINN is employed to conduct the HSFID with various locations, shapes, sizes and power densities under multi-heat source configurations. For the two-source configuration, the heat source shape and position similarity (HSSPS) for detecting triangular heat sources is 98.9 %, meanwhile for four heat source configurations, the HSSPS is 93.5 %. In complex heat source systems where the location, shape, size and power density change randomly and simultaneously, the maximum temperature mean absolute error (TMAE) value is around 0.003 K, the maximum value of the temperature absolute error (M-TAE) value fluctuates in the range of 0.02 K, and the HSSPS is not less than 92 %.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"164 ","pages":"Article 108824"},"PeriodicalIF":6.4,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel lattice Boltzmann - phase field model of dendritic growth and sedimentation with melt flows","authors":"Yafang Wu,&nbsp;Shilin Mao,&nbsp;Jinyi Wu,&nbsp;Dongke Sun","doi":"10.1016/j.icheatmasstransfer.2025.108741","DOIUrl":"10.1016/j.icheatmasstransfer.2025.108741","url":null,"abstract":"<div><div>The dendrites growing anisotropically during alloy solidification exhibit different crystallographic orientations, accompanied by the sedimentation and collision of free equiaxed dendrites. In this study, a novel lattice Boltzmann - phase field (LB-PF) scheme is developed for modeling simultaneous dendritic growth and motion in the melt of binary alloys. Unit quaternions are employed to handle anisotropy dependent on local crystallographic orientation. The LB method is applied to solve the PF model and melt flow, while the finite volume method is adopted to discretize the solute field. The model is validated by examining the preservation of equiaxed dendrite shapes after rotation and the sedimentation of solid particles in fluid. Using the present scheme, the evolution of solidification microstructures with different preferred crystalline orientations and the sedimentation of free equiaxed dendrites above the stationary columnar dendrites under varying gravity levels are numerically investigated. The preferred orientation significantly affects the transition from planar crystals to columnar dendrites. Motion and melt convection promote dendritic growth along the flow direction and alter its orientation. This work demonstrates the applicability of the LB-PF scheme with quaternions to simulate dendritic growth and sedimentation in both two and three dimensions.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"164 ","pages":"Article 108741"},"PeriodicalIF":6.4,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical modeling for freezing of aircraft anti-icing fluids","authors":"Igor A. Usachev ,&nbsp;Dmitry Kolomenskiy ,&nbsp;Oleg A. Rogozin ,&nbsp;Viktor G. Grishaev ,&nbsp;Alidad Amirfazli ,&nbsp;Vladimir P. Drachev","doi":"10.1016/j.icheatmasstransfer.2025.108803","DOIUrl":"10.1016/j.icheatmasstransfer.2025.108803","url":null,"abstract":"<div><div>The on-ground icing is a major concern for aircraft safety. De/anti-icing fluid treatment is widely used to delay the onset of freezing. A fast and reliable method for predicting the performance of de/anti-icing fluids is needed. A simplified continuum model of fluid freezing (the SAE Type II and IV fluids) based on the Navier–Stokes equations coupled with the diffusion and enthalpy equations is developed and validated against experimental data. The discrepancy between the experimental and numerical results is about 10% after 5% surface freezing, indicating a fairly good predictive ability of the model. The model can quickly monitor fluid performance before testing. It can also help in developing new types of fluids.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"164 ","pages":"Article 108803"},"PeriodicalIF":6.4,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a high-accuracy temperature sensor for meteorological observations based on computational fluid dynamics and neural networks","authors":"Wei Jin ,&nbsp;Xin Hong ,&nbsp;Jie Yang ,&nbsp;Qingquan Liu ,&nbsp;Zhenyu Li ,&nbsp;Qin Ding ,&nbsp;Haque M. Amdadul","doi":"10.1016/j.icheatmasstransfer.2025.108801","DOIUrl":"10.1016/j.icheatmasstransfer.2025.108801","url":null,"abstract":"<div><div>Global temperatures are rising at approximately 0.1 °<span><math><mi>C</mi></math></span> per decade. Existing air temperature observation sensors often measure temperatures higher than the actual values due to solar radiation effects, leading to errors of up to 1 °<span><math><mi>C</mi></math></span>, which significantly affects the accuracy of meteorological observations. Traditional naturally ventilated temperature sensors exhibit significant limitations in reducing radiation errors, making it challenging to meet the precision requirements of 0.05 °<span><math><mi>C</mi></math></span> or even higher in atmospheric science research. To address this challenge, this paper proposes and designs a novel naturally ventilated temperature sensor. The core sensing element of the sensor employs a Pt100 thin-film platinum resistor, and its performance is optimized through computational fluid dynamics (CFD) methods and a multi-layer perceptron (MLP) network to reduce radiation errors. External field comparative experiments with the 076B artificially ventilated temperature monitoring device, using its measurements as temperature references, have validated the effectiveness of the new sensor in reducing radiation errors. Experimental results indicate that the new sensor has a root mean square error (<span><math><mrow><mi>R</mi><mi>M</mi><mi>S</mi><mi>E</mi></mrow></math></span>) of 0.047 °<span><math><mi>C</mi></math></span>, a mean absolute error (<span><math><mrow><mi>M</mi><mi>A</mi><mi>E</mi></mrow></math></span>) of 0.039 °<span><math><mi>C</mi></math></span>, and a correlation coefficient (<span><math><mi>r</mi></math></span>) of 0.999. The average radiation error of the calibrated sensor is 0.03 °<span><math><mi>C</mi></math></span>. These findings fully demonstrate the significant advantages of this sensor in improving the accuracy of temperature measurements.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"164 ","pages":"Article 108801"},"PeriodicalIF":6.4,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An artificial intelligence – Finite element study of magnetohydrodynamic heat transfer of a nano-encapsulated phase change material suspension in a cylindrical enclosure with partial heated walls","authors":"Hakim S. Sultan Aljibori ,&nbsp;Mohammed Hasan Ali ,&nbsp;Zehba Raizah ,&nbsp;Ahmad Hajjar ,&nbsp;Jana Shafi ,&nbsp;Faisal Alresheedi ,&nbsp;Ahmed Elhassanein ,&nbsp;Mohammad Edalatifar ,&nbsp;Mohammad Ghalambaz","doi":"10.1016/j.icheatmasstransfer.2025.108812","DOIUrl":"10.1016/j.icheatmasstransfer.2025.108812","url":null,"abstract":"<div><div>The present study delivers an exhaustive exploration into the mechanisms governing heat and mass transfer within an enclosure filled with Nano-Encapsulated Phase Change Material (NEPCM) and subject to magnetic fields. Leveraging a set of governing partial differential equations, the research investigates the intricacies of natural convection, convective heat transfer, and conjugate heat transfer within solid walls. The entropy generation in the NEPCM suspension was addressed. The finite element method was used for the numerical solution. A dataset was generated from simulations and was utilized to train an artificial neural network. Subsequently, the trained neural network was employed to analyze the effects of model parameters on heat transfer and entropy generation. The results show the pivotal role of the magnetic source's position in manipulating heat transfer. Increasing the magnetic number slightly elevates Nu_Avg and significantly boosts total entropy generation. An increment in thermal conductivity ratio from 1 to 100 at <em>Ra</em> = 100,000 elevates Nu_Avg from 2 to 4.5, signifying a 56 % improvement. Additionally, elevating nanoparticle concentration enhances Nu_L, owing to increased thermal conductivity. The study reveals that regions of high entropy generation are universally close to the magnetic source, regardless of its specific location.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"164 ","pages":"Article 108812"},"PeriodicalIF":6.4,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of liquid injector pressure on gas flow characteristics and evaporation rates: A combined Eulerian-Lagrangian approach and PSO-optimized XGBoost model","authors":"Hossein Ali Kamali","doi":"10.1016/j.icheatmasstransfer.2025.108822","DOIUrl":"10.1016/j.icheatmasstransfer.2025.108822","url":null,"abstract":"<div><div>In this study, the effect of increasing the pressure of liquid jet spray nozzles on the quantity of hot gas flow inside the cylinder and the evaporation rate of the sprayed liquid has been numerically investigated using the Eulerian-Lagrangian method. Additionally, the molar ratio of water vapor along the geometry has been predicted using an optimized machine learning model. Liquid water with a temperature of 300 K is injected into the cylinder containing a high-speed gas flow with a temperature of 2500 K by an arrangement of 5 injectors under different pressures. In this study, changes in static quantities and total flow such as pressure, temperature, mach number, evaporation rate, mole fraction and flow rate changes before and after liquid injection into the cylinder and also the effect of increasing injector pressure from 10 MPa to 50 MPa on this quantity have been investigated. Finally, the hyperparameters of the XGBoost model were optimized using the Particle Swarm Optimization (PSO) algorithm to predict the average molar ratio of water vapor under various conditions, resulting in the development of a combined PSO-XGBoost model. The results show that initially increasing the pressure of the liquid injectors causes significant changes in the gas flow quantities, but increasing the pressure from a certain range does not have a significant effect on the changes in the flow parameters. Increasing the liquid injector pressure up to about 20 MPa has a significant effect on the pressure and Mach number and up to about 30 MPa on the total temperature, increasing the evaporation rate and mass flow rate, but increasing the injector pressure more than these values does not have much effect on the flow characteristics. Also, the results obtained from predicting the molar ratio of water vapor using the PSO-XGBoost model demonstrated a strong correlation with the results from the numerical solutions, highlighting the model accuracy in predicting the molar ratio of water vapor under the complex flow conditions examined.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"164 ","pages":"Article 108822"},"PeriodicalIF":6.4,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental study on flow boiling heat transfer of HFE-7100 in minichannel heat sinks for professional-grade server chips cooling","authors":"Huiqing Shang,&nbsp;Guodong Xia,&nbsp;Ran Li,&nbsp;Shanshan Miao","doi":"10.1016/j.icheatmasstransfer.2025.108825","DOIUrl":"10.1016/j.icheatmasstransfer.2025.108825","url":null,"abstract":"<div><div>Micro/mini-channel heat sinks play a crucial role in the heat dissipation of electronic components, such as server chips. In this study, the minichannel heat sinks were designed by 6061‑aluminum alloy to investigate their heat dissipation capabilities. Flow boiling experiments with low flow velocities in minichannels were conducted in the smooth parallel minichannel (SPMC) and porous parallel minichannel (PPMC) heat sinks at conditions of high power and low heat flux. The mass fluxes varied from 121.0 to 241.9 kg/(m²s), and the effective heat fluxes varied from 0 to 9.1 W/cm². The effects of mass flux, heat flux, inlet temperature, and surface structure on heat transfer and flow pattern transition during flow boiling of HFE-7100 were discussed. The research indicates that at the room-temperature condition, the maximum decrease in wall temperature is 2.39 % between them under a mass flux is 181.4 kg/(m²s) and a heat flux is about 7 W/cm². The wall temperature can be maintained below 75 °C, while the pressure drop is consistently below 0.6 kPa at all conditions. With the increase in effective heat fluxes, the boundary of flow pattern transition becomes less distinct, slug flow and churn flow are the main flow patterns in the mid/downstream of minichannels.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"164 ","pages":"Article 108825"},"PeriodicalIF":6.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}