International Communications in Heat and Mass Transfer最新文献

{"title":"Comparative review of flow characteristics and thermal efficiency in wall-attachment self-excited oscillating jets: From cavity jets to fluidic oscillators","authors":"Seyed Mohammad Jaafarian ,&nbsp;Amir Omidvar ,&nbsp;Seyed Alireza Zolfaghari","doi":"10.1016/j.icheatmasstransfer.2025.110243","DOIUrl":"10.1016/j.icheatmasstransfer.2025.110243","url":null,"abstract":"<div><div>This review investigates three configurations of wall-attachment, self-excited oscillating jets, cavity jets, single-feedback fluidic oscillators, and double-feedback fluidic oscillators, and evaluates their flow behavior and thermal performance. The study synthesizes a broad range of research to identify the governing parameters that control jet hydrodynamics and heat-transfer characteristics, emphasizing dimensionless results that enable meaningful comparison across different geometries. The analysis demonstrates that internal jet geometry is the dominant factor in establishing oscillatory flow, while inlet conditions and thermal boundary constraints strongly influence flow stability and thermal enhancement. Cavity jets generally fail to generate oscillations at Reynolds numbers below 2000, yet they exhibit superior thermal performance relative to other configurations when <span><math><mi>Re</mi><mo>&lt;</mo><mn>55,000</mn></math></span>. In contrast, double-feedback fluidic oscillators can produce oscillatory flow at significantly lower Reynolds numbers, around Re ≈ 220, making them attractive for low-flow applications. The review also highlights the roles of feedback-loop design, nozzle structure, and cavity resonance in shaping jet behavior. By integrating experimental and numerical findings, the study clarifies performance trade-offs, identifies unresolved challenges such as turbulence modeling and transient flow characterization, and provides guidance for developing geometry-optimized oscillating jet systems suitable for advanced cooling and thermal-management applications across a wide range of modern engineering domains today.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"172 ","pages":"Article 110243"},"PeriodicalIF":6.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145734204","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 analysis of heat transfer by natural convection of a nano-encapsulated phase-change materials in a porous cavity with heated cylinders","authors":"Abdelhak Daiz ,&nbsp;Rachid Hidki ,&nbsp;Ahmed Bahlaoui ,&nbsp;Ismail Arroub","doi":"10.1016/j.icheatmasstransfer.2025.110262","DOIUrl":"10.1016/j.icheatmasstransfer.2025.110262","url":null,"abstract":"<div><div>This article proposes a comprehensive computational investigation of natural convection-driven heat transport within a porous square enclosure containing a nanofluid incorporating nano-encapsulated phase change materials (NEPCMs). The arrangement consists of nine heated hollow cylinders symmetrically arranged, each having a conductive strip of different materials around it. The nonlinear flow and heat transfer governing equations are numerically solved using the finite element approach to examine the effect of various dimensionless parameters, i.e., Darcy number <span><math><mfenced><mi>Da</mi></mfenced></math></span>, NEPCM volume fraction <span><math><mfenced><mi>φ</mi></mfenced></math></span>, reduced melting temperature <span><math><mfenced><msub><mi>θ</mi><mi>f</mi></msub></mfenced></math></span> and Stefan number <span><math><mfenced><mi>Ste</mi></mfenced></math></span>, regarding the system's thermal behavior and performance. The results indicate that low Darcy number values correspond to heat transfer dominated by conduction due to the limited permeability of the medium, while high values favor the formation of convection cells, leading to an increase in the average Nusselt number. Increasing the concentration of NEPCM significantly improves the heat transfer and storage, particularly for large Rayleigh numbers, because of the effect of latent heat. An optimum behavior is observed for <span><math><msub><mi>θ</mi><mi>f</mi></msub><mo>≈</mo><mn>0.5</mn></math></span>, for which the partial melting of the particles increases the heat exchange. Small values of the <span><math><mi>Ste</mi></math></span> also improve the latent heat-associated effects, thereby enhancing the phase change process effectiveness. Finally, the thermal conductivity of the material enclosing the cylinders plays a deciding role: materials with high thermal conductivity (such as copper or aluminum) increase the heat exchange, while insulating materials (such as glass or plastic) decrease it. These results sanction the excellent prospect of NEPCMs in compact thermal storage devices, particularly when embedded in porous structures under complex thermal conditions.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"172 ","pages":"Article 110262"},"PeriodicalIF":6.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145734295","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":"Novel application of COMBI learning models and multi-objective Lichtenberg algorithm in HVAC system design","authors":"Abdulilah Mohammad Mayet","doi":"10.1016/j.icheatmasstransfer.2025.110210","DOIUrl":"10.1016/j.icheatmasstransfer.2025.110210","url":null,"abstract":"<div><div>The growing demand for energy-efficient and comfort-oriented indoor environments highlights the need for advanced decision-support frameworks for task/ambient conditioning (TAC) systems. Traditional approaches often fall short in simultaneously capturing complex system behavior, quantifying energy–comfort trade-offs, and providing actionable design guidance. To address this challenge, the present study introduces a novel four-stage AI-based framework that integrates CFD data analysis, surrogate machine learning modeling, multi-objective optimization, and multi-criteria decision-making. Specifically, CFD-based simulations first generate system dataset, which are then modeled using the COMBI regression technique to construct predictive surrogates. These models feed into a Pareto-based optimization process using the multi-objective Lichtenberg algorithm (MOLA), benchmarked against NSGA-II, while final solution ranking is achieved through the VIKOR method. The results demonstrate the robustness of the COMBI models, achieving R² values of 0.999, confirming high predictive fidelity without overfitting. Both MOLA and NSGA-II produced smooth, overlapping Pareto fronts, ensuring reliable exploration of energy–comfort trade-offs. Analysis revealed that supply air temperature consistently converged to 26 °C, while airflow rate governed system performance, with optimal solutions ranging from energy-saving (10 L/s, Q_C ≈ 30.5 W, PMV ≈ 0.7) to comfort-maximizing (32.25 L/s, Q_C ≈ 49 W, PMV ≈ 0.0). Finally, VIKOR ranking highlighted seven representative scenarios reflecting diverse design priorities, from energy-focused to comfort-oriented settings. Overall, the proposed hybrid methodology offers a robust, flexible, and practical pathway for optimizing TAC systems, bridging methodological gaps and supporting stakeholder-driven decision-making in building energy management.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"172 ","pages":"Article 110210"},"PeriodicalIF":6.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145734296","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":"Control of double diffusive flow field of nanoenhanced phase change material via small satellite body around square heater in a lid-driven cavity with machine learning integration","authors":"Shafqat Hussain ,&nbsp;Hakan F.Öztop ,&nbsp;Awatef Abidi ,&nbsp;Fatih Ertam","doi":"10.1016/j.icheatmasstransfer.2025.110293","DOIUrl":"10.1016/j.icheatmasstransfer.2025.110293","url":null,"abstract":"<div><div>This study presents a comprehensive numerical investigation of double-diffusive natural convection in a lid-driven square cavity filled with a nanoencapsulated phase change material (NEPCM) suspension. The cavity incorporates a central heated and solutally enriched square obstacle alongside a small adiabatic circular satellite obstacle. The present paper also proposes a comprehensive mathematical framework for the application of machine learning algorithms to predict concentration and temperature fields in flows characterized by varying Richardson numbers. The governing equations, formulated under the assumptions of laminar, incompressible, steady-state, Newtonian flow with the Boussinesq approximation, are solved using a Galerkin-based finite element method, enabling accurate treatment of complex geometries and boundary conditions. The study elucidates the effects of the satellite obstacle’s angular position, the Lewis number, the Reynolds number, and the magnetic field strength on the flow structure, temperature and concentration distributions, and overall transport characteristics. Quantitative analyses of dimensionless parameters, including the average Nusselt and Sherwood numbers as well as mean kinetic energy, provide insights into the interplay between convective and diffusive transport phenomena in NEPCM-laden fluids. The findings demonstrate that machine learning algorithms, particularly Random Forest, can attain nearly perfect predictive accuracy (<span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> <span><math><mo>&gt;</mo></math></span> 0.9996 for both concentration and temperature fields across a range of Richardson number regimes. Furthermore, the location of the satellite obstacle can be used as a control parameter for regulating the calculated values inside the cavity. The results reveal critical interactions between obstacle placement and flow behavior, offering design guidance for enhanced thermal and solutal management in advanced energy and microfluidic applications.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"172 ","pages":"Article 110293"},"PeriodicalIF":6.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145734305","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":"Parametric analysis of flow and heat transfer during R1234yf/R1336mzz condensation in microchannels","authors":"Hang Zhou ,&nbsp;SiJing Zhang ,&nbsp;Jian Liu ,&nbsp;XiaoSong Zhang","doi":"10.1016/j.icheatmasstransfer.2025.110278","DOIUrl":"10.1016/j.icheatmasstransfer.2025.110278","url":null,"abstract":"<div><div>Zeotropic mixtures are gaining attention as working fluids for high-temperature heat pumps and Organic Rankine Cycle (ORC) systems due to their favorable thermophysical properties and low global warming potential. However, their condensation behavior remains insufficiently studied, especially under microscale conditions. This study conducts a parametric numerical investigation of R1234yf/R1336mzz condensation in microchannels. A transient multiphase heat and mass transfer model was developed based on the quasi-equilibrium theory, incorporating a two-dimensional transient volume-of-fluid (VOF) approach, species transport equations, and a modified interfacial mass transfer source term.The model was validated against experiments, showing good predictive accuracy and applicability. Simulations captured the evolution of typical flow regimes and identified injection flow as a transitional pattern unique to microscale channels. Interfacial dynamics were governed by shear stress and surface tension. The effects of key parameters—including mass flux, wall subcooling, and component mass fraction—on local heat transfer, film thickness, velocity, and temperature fields were evaluated. Results show that increasing mass flux markedly enhances interfacial shear and disturbance intensity, leading to thinner liquid films and up to a 210.75 % improvement in condensation heat transfer. Wall subcooling has a relatively limited effect, while a higher R1234yf mass fraction effectively reduces heat and mass transfer resistance, further increasing the average heat transfer coefficient by about 42.77 %.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"172 ","pages":"Article 110278"},"PeriodicalIF":6.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145734306","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":"Optimization of multi-orifice synthetic jet configuration using flow and heat transfer characteristics coupled with machine learning","authors":"Rajat Kumar ,&nbsp;Dnyanesh Mirikar ,&nbsp;Mohammad Zia Ur Rehman ,&nbsp;Anukriti Bhatnagar ,&nbsp;Nagendra Kumar ,&nbsp;Harekrishna Yadav","doi":"10.1016/j.icheatmasstransfer.2025.110160","DOIUrl":"10.1016/j.icheatmasstransfer.2025.110160","url":null,"abstract":"<div><div>This study investigates the heat transfer and flow characteristics of multi-orifice synthetic jet (SJ) to identify the most efficient configuration for enhanced cooling, particularly in regions where conventional single-orifice jets are limited by recirculation effects. The heat transfer characteristics are evaluated using infrared thermography, while flow behavior is analyzed through hot-wire anemometry and smoke-wire flow visualization. A total of 23 orifice configurations, including single, two, three, four, and eight-satellite arrangements, are examined while maintaining a constant total orifice area. Results indicate that the two, three, and four-satellite configurations exhibit enhancements of 19.8 %, 27.25 %, and 26.63 %, respectively, over the single-orifice configuration at Z/D = 2, while the eight-satellite configuration shows no significant improvement. The peak heat transfer rate is observed for the two-satellite configuration at Z/D = 4, which is 13.75 % higher than that of the single-orifice configuration. At larger jet-to-surface spacings, the single-orifice configuration demonstrates superior performance due to the formation of more coherent and stable vortex structures. Hot-wire anemometry measurements reveal that differences in the velocity ratio between the central and satellite jets strongly affect flow interaction and vortex formation, thereby influencing the heat transfer rate. Furthermore, flow visualization confirms that smaller central orifices reduce flow recirculation and promote enhanced near-wall mixing, supporting the observed heat transfer trends. An artificial neural network (ANN) model developed to predict the heat transfer behavior of SJ impingement achieves a maximum prediction error of 6.14 % and an R² value of 0.99. Overall, the findings provide valuable insights for optimizing multi-orifice synthetic jet configurations to achieve efficient cooling in compact thermal management systems.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"172 ","pages":"Article 110160"},"PeriodicalIF":6.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145683259","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":"Thermophysical property prediction of R32, R1234yf, and R454B refrigerants using artificial neural networks","authors":"Hai-peng Lu ,&nbsp;Xu-Li Zhou ,&nbsp;Soheil Salahshour ,&nbsp;Mokhtar Hamedinia ,&nbsp;Yasmin Khairy ,&nbsp;Mauricio Vásquez-Carbonell ,&nbsp;José Escorcia-Gutierrez","doi":"10.1016/j.icheatmasstransfer.2025.110123","DOIUrl":"10.1016/j.icheatmasstransfer.2025.110123","url":null,"abstract":"<div><div>Accurate prediction of the thermophysical properties of next-generation refrigerants is essential to improving the energy efficiency and environmental compatibility of cooling systems. Therefore, this paper developed an artificial neural network-based data-driven framework for the prediction of the density and viscosity of R32, R1234yf, and R454B at a wide range of temperatures (Ts) and pressures (Ps). Extensive datasets, validated by high-accuracy experimental measurements, were used to train and validate multilayer feedforward networks developed to provide nonlinear thermodynamic dependency features. The resulting models displayed good quantitative accuracy on all refrigerants. The root mean square errors regarding R32 were found to be 40.70 kg/m³ density and 0.0237 mPa·s viscosity, while the coefficients of determination of 0.98031 and 0.97195 were achieved for density and viscosity, respectively. In the case of R1234yf, the foregoing errors were 51.07 kg/m³ and 0.0256 mPa·s. Meanwhile, the coefficients were given as 0.96488 and 0.97983. The R454B model achieved the Maximum (Max) performance with 22.01 kg/m³ errors concerning density and 0.0044 mPa·s concerning viscosity, while attaining correlation coefficients of 0.99895 and 0.9937, respectively. Relative error analysis showed that all refrigerants had Maximum and mean deviations below 8 % and 25 %, respectively, for density and viscosity. That trend in predictions confirmed that density increased as T gradually increased, remaining nearly P-independent, while viscosity decreased nonlinearly with increasing T. The viscosity sets themselves showed little sensitivity to P. These results could validate the highly accurate and computationally efficient capabilities of artificial neural networks to replicate complex thermophysical behavior, as above, and hence serve as a rigorous alternative to empirical correlations for predictive design of sustainable refrigeration and air-conditioning systems.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"172 ","pages":"Article 110123"},"PeriodicalIF":6.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145683182","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":"Analytical investigation of thermo-hydraulic performance of a double-pass solar air collector with transverse rib roughness","authors":"Selcuk Darici ,&nbsp;Ahmet Emre Ozer","doi":"10.1016/j.icheatmasstransfer.2026.110505","DOIUrl":"10.1016/j.icheatmasstransfer.2026.110505","url":null,"abstract":"<div><div>Hot air generation for applications like crop drying and space heating is commonly achieved using solar air collectors. However, the formation of a viscous sublayer at the absorber–air interface reduces the convective heat transfer coefficient and overall thermal efficiency. To overcome this limitation, this study analytically investigates the thermo-hydraulic performance of a two-glass, double-pass solar air collector equipped with continuous transverse wire roughness beneath the absorber plate. An iterative MATLAB-based computational program was developed using the Nusselt number (<em>Nu</em>) and friction factor (f) correlations available in the literature for similar roughened surfaces to solve the governing energy equations. An analytical model was developed to evaluate the thermal and flow resistance characteristics while varying relative roughness pitch (p/e = 10–40), relative roughness height (e/Dₕ = 0.011–0.030), and Reynolds number (<em>Re</em> = 5000–20,000). The proposed analytical formulation enables direct prediction of thermo-hydraulic performance without reliance on empirical correlations. Results indicate that the use of transverse ribs significantly enhances heat transfer with a moderate increase in friction losses. The configuration at p/e = 10, e/Dₕ = 0.030, and <em>Re</em> = 5000 demonstrates the highest thermal hydraulic performance, achieving a THPP value of 1.25. This study provides analytical insight into the optimal roughness configuration for improving the performance of double-pass solar air collectors.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"172 ","pages":"Article 110505"},"PeriodicalIF":6.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145972739","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":"Hematocrit and Plasma proteins influenced dispersion in a tumor microvessel during magnetic drug targeting using Walburn–Schneck fluid model","authors":"Lazaro Revocatus Mashiku ,&nbsp;Sachin Shaw","doi":"10.1016/j.icheatmasstransfer.2026.110526","DOIUrl":"10.1016/j.icheatmasstransfer.2026.110526","url":null,"abstract":"<div><div>Hematocrit levels and plasma protein concentrations are key determinants of blood viscosity and nanoparticle dispersion, but their combined influence under magnetic drug targeting (MDT) remains unclear. This study mathematically investigates their impact on MNP transport under MDT, alongside other physical parameters. A two-fluid model of unsteady blood flow in porous media was employed, using the Walburn–Schneck non-Newtonian constitutive equation to relate shear stress to hematocrit, plasma protein, and shear rate. The Brinkman model simulated the flow in the plasma layer. Velocities were computed analytically, and a numerical scheme of backward time-centered space solved the advection–diffusion equation for the dispersion of solute. Interestingly, the results reveal that lower hematocrit levels suppress the dispersion of MNP, contrary to the commonly held assumption, while elevated plasma protein concentrations enhance the dispersion. By incorporating variable diffusivity influenced by hematocrit, plasma protein, and local shear conditions, the model demonstrates improved predictive accuracy in drug transport and distribution patterns within the tumor microenvironment. The reduced slip velocity increases wall shear stress and intravascular resistance, while a larger nanoparticle size and enhanced magnetic properties improve pharmacokinetics. Stress jump, permeability, and plasma layer thickness significantly influence drug dispersion. The findings contribute to a deeper understanding of nanoparticle transport, aiding the optimization of MNP-based drug delivery systems for improved cancer therapy.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"172 ","pages":"Article 110526"},"PeriodicalIF":6.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145972744","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":"Augmentation of convection heat transfer in bioinspired corrugated channels using CFD and machine learning approaches","authors":"Arup Das ,&nbsp;Syeda Tanjila Sarwar ,&nbsp;Neloy Kumar Das ,&nbsp;Nabil Mohammad Chowdhury ,&nbsp;Ashfaq Uddin Musanna ,&nbsp;Abdul Quader Jony ,&nbsp;Mohammad Rejaul Haque","doi":"10.1016/j.icheatmasstransfer.2026.110512","DOIUrl":"10.1016/j.icheatmasstransfer.2026.110512","url":null,"abstract":"<div><div>The integration of bio-inspired configurations, leveraging natural insights for industrial advancements, has transformed heat transfer technologies. This study examines the impact of bio-inspired designs, such as shark fin and bird wing shapes, on convective transmission of heat in corrugated tubes under laminar flow (<em>Re</em> = 350–750). Validation against numerical and experimental data shows a maximum deviation of 3.86%. The optimized shark fin design (pattern 100, width-height 2 mm × 2 mm) demonstrates the best performance, achieving a Nu of 10.239 at Re = 750 with a corresponding 10.76 Pa pressure drop, representing a 146.62% improvement over the baseline case. A uniform heat flux of 1000 W/m² has been applied in the corrugated portion, where all configurations outperformed the base case. A Hydro-Thermal Performance Factor (HTPF) of 2.49 was achieved. Machine learning models ANN, MLR, XGBR were employed to predict Nusselt number, pressure drop, and HTPF. XGBR demonstrated superior accuracy, achieving R²_test = 0.953, MRE (%) = 4.23, and rRMSE = 4.76% for Nusselt number prediction, and R²_test = 0.959, MRE (%) = 2.24, and rRMSE = 3.02% for HTPF. While ANN provided reliable predictions for HTPF (R²_test = 0.922, rRMSE = 4.19%), its higher MRE suggests overfitting. XGBR proved most effective overall.</div></div>","PeriodicalId":332,"journal":{"name":"International Communications in Heat and Mass Transfer","volume":"172 ","pages":"Article 110512"},"PeriodicalIF":6.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145972743","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}