Heat Conduction Research Articles

Elasto-Thermodiffusion in a Slim Strip Revisited with New Definition of Nonlocal Heat Conduction

Elasto-Thermodiffusion in a Slim Strip Revisited with New Definition of Nonlocal Heat Conduction

Research on laser brazing diamond coating process based on temperature field finite element simulation and machine learning

The temperature of laser brazing diamond seriously affects the quality and service life of diamond tools. In this study, a finite element model of laser brazing diamond was established to achieve digital control of the temperature field during the brazing process. It was determined that the main energy of diamond warming comes from the heat conduction of the molten pool. The maximum temperature value within the brazing layer was proposed as an important indicator of the quality of diamond coating formation. The correlation and local sensitivity of each process parameter to the maximum value of temperature were calculated by a neural network-based machine learning method, and the influence of process parameters on the temperature field was explored. The result of the theoretical analys was finally verified by the coating wear-resistance experiments, and the wear-resistance of the diamond coatings was significantly better than that of other cases when the maximum temperature value in the brazing process was in the range of 1100 °C–1130 °C.

Deep learning-based topology optimization for multi-axis machining

This paper presents a novel framework that integrates topology optimization (TO) and deep learning (DL) to generate high-performance structures suitable for multi-axis machining. Within the proposed framework, DL is built on the pix2pix network, with the conditional channel used to determine the tool shape and feed direction in multi-axis machining. This DL model will be trained using our own generated dataset on TO for multi-axis machining. Then, users can customize tool dimensions and machining orientations of the multi-axis machining operation and specify the design boundary and loading conditions as input. The DL model will rapidly generate a near-optimized structure, which subsequently serves as the starting point for further optimization. Ultimately, a topology-optimized structure that meets the tailored requirements is apt for multi-axis machining and can be finalized with only a few iterations. 2D and 3D numerical examples for heat conduction problems are studied to prove the effectiveness of the proposed method, validating improved structural performance and optimization efficiency compared to conventional TO for multi-axis machining.

Experimental analysis of a radiant floor system incorporating phase change materials: Thermal performance and energy efficiency

The incorporation of Phase Change Materials (PCMs) in radiant floors has the potential to improve the thermal and energy performance of the system. PCMs can act as thermal batteries, providing additional thermal energy storage capacity to Radiant Floor Systems (RFS). However, in the case of wet construction, when PCMs are incorporated into the enveloping mortar surrounding the RFS water pipes, the resulting specific heat and thermal conductivity can pose a challenge to system performance. The objective of this paper is to evaluate the impact that the incorporation of microencapsulated PCM (mPCM) in the RFS mortar has on the thermal and energy performance of the system. To tackle this objective, an experimental setup was constructed consisting of two RFS specimens: one reference and the other with mPCM within an innovative mortar. The two specimens were then tested under different heating strategies controlled by: i) timer, and ii) floor surface temperature setpoint. The thermal performance of the PCM-RFS and operating time were compared with the reference RFS. Timer-controlled intermittent heating has proven beneficial when the heating strategy is established to combine renewable solar energy and off-peak electricity tariffs. Thermal fluctuation was reduced and the PCM phase change process was mobilized twice in 24 h, maintaining surface floor temperatures of the PCM-RFS within comfort levels throughout the test period. When the heat source is controlled by floor surface temperature setpoint, the thermophysical properties of the PCM-RFS led to longer operating times, however mitigating high intermittency of the heat source activations, resulting in more regular operation mode, easier control and avoiding peak heating loads.

Experimental investigations on strength and microstructural characteristics of air-cell impregnated light weight concrete

Concrete structures have high massive building materials than steel structures and possess very low thermal conductivity and high specific heat capacity. However, an efficient approach to reducing high production cost and structural weight of concrete elements without impacting their strength evolve as a growing necessity that leads to innovation in the Light weight concrete (LWC) fields such as aerated concrete and foamed concrete. Those large bubbles seem highly likely to get a break, move upwards through buoyancy and may get lost, while concrete has been mixed, transported, placed and vibrated. Hence to prevent increased bubble spacing, and air loss and to increase concrete durability, a sort of micron-sized air-cells could be generated in aerosol form, by passing out compressed air to dense form generating surfactants. Therefore to circumvent certain drawbacks of conventional LWC, the study delineated to bring out an innovative air-cell impregnated concrete (AIC) material, with homogenous mixing of cement, sand, water and uniformly distributed micron-sized air-cells wherein course-aggregates were replaced with air-cells. This uniform air-cell distribution creates durable concrete with unique feature characteristics since the micron-sized air-cells will be stable and does not collapse. The suitable surfactant towards contributing the strength and durability of proposed AIC structure are assessed, based on results.

Thermal reaction based mesoscale ablation model for phase degradation and pyrolysis of needle-punched composite

Needle-punched composites are highly valued for their exceptional resistance to interlaminar properties, ablation, and design flexibility, making them increasingly popular in aerospace thermal protection systems. This work investigates the mesoscale structural characteristics and thermophysical properties of needle-punched composites in ablation process. Oxyacetylene ablation experiments were carried out at different temperatures, and a mesoscopic needle-punched structure model was established based on the results of CT characterization. Further, Abaqus custom subroutine was used to reveal the ablation evolution mechanism of carbon fiber reinforced phenolic resin-based needle-punched composites. The results show that, at mesoscopic scale, the acicular fiber bundle perpendicular to the ablative surface accelerates the heat conduction to the interior of the material and promotes the thermal damage and performance degradation of the composite.

Paradigm on Levenberg–Marquardt neural algorithm analysis of heat conduction optimization for ternary hybrid nanofluid with entropy generation

AbstractThe significance of the present article is to enhance the thermal management and energy efficiency of complex engineering infrastructures such as energy storage systems, modern electric vehicles, thermal insulations, heavy‐duty machinery, and production units. This research aims to understand the intricate relationship between the thermal conductivity performance of ternary () hybrid nanomaterial and entropy generation to optimize material design and efficacy. A synergetic combination of three distinct nanomaterials silicon dioxide, ferric oxide, and titanium oxide with ethylene glycol and water in the ratio 3:2 as a base solvent is comprised of contributing unique thermophysical properties. To elucidate the impact of this hybrid composition on thermal conductivity, various factors are analyzed. The advanced computational technique of Artificial intelligent feed‐forward neural network (AIFFNN) is utilized. The problem governed the system of PDEs, which is transformed into ODEs by dimensionless similarity. Adams method provided the dataset which is filtered and embedded into Marquardt–Levenberg Algorithm (LMA). The study examines the role of nanomaterial constituents, morphology, and boundary conditions on thermal performance and entropy generation. Graphical analysis of velocity, temperature, and entropy is provided with respect to varying parameters, including surface absorption (λ), magnetic strength (Tesla M), radiation parameter (Rd), Brownian motion (Br), and Eckert number (Ec). The findings have practical significance for optimizing material design in engineering and industrial applications.

Application of inverse heat transfer to fatigue fracture

Cyclic actuation tends to cause self-heating in the material as the structure experiences fatigue, where the movement and coalescence of defects lead to crack formation, propagation, and eventual fracture. This study explores the modeling aspects of the self-heating phenomenon using a one-dimensional inverse heat problem to analyze heat generation and dissipation to quantify the plastic work rates needed for predicting fatigue life. The approach is based on analyzing the surface thermography obtained using an infrared camera and numerically solving an inverse Fourier heat conduction equation. Formulation of the inverse problem via constrained optimization and method of solution for analyzing the fatigue behavior of CS 1018 flat dog bone specimens subjected to fully reversed bending fatigue are presented. The proposed model demonstrates superior accuracy in predicting the location of maximum heat generation and identifying potential fracture zones compared to traditional methods.

Significant improving magnetic properties and thermal conductivity of FeBSiPCNbCu nanocrystalline powder cores by designing novel ZnO insulating layer

As the application scenarios of soft magnetic composites (SMCs) tend to be high frequency, reducing their high-frequency core loss (Pcv) and improve the heat-sinking capability to avoiding thermal failure of electronic system are still greatly challenging. In present work, we successfully designed and prepared novel ZnO insulating layers on the surface of FeBSiPCNbCu nanocrystalline powders and discussed their growth processes. In addition, we investigated the effects of the ZnO insulating layers on the magnetic properties and heat-sinking capability of the FeBSiPCNbCu nanocrystalline magnetic powder cores (NMPCs) and explored the related mechanisms. The experimental results show that the hydrolysis of 1.75 wt% zinc acetate dihydrate under the coupling of 1 wt% polyvinylpyrrolidone forms uniform and thin ZnO insulating layers on the powders surface. The FeBSiPCNbCu@ZnO NMPCs annealed at 510 °C for 60 min exhibit excellent magnetic properties and superior heat-sinking capability with a low core loss of 698.4 mW/cm3 (20 mT, 2 MHz), high DC bias permeability of 68.3% (100 Oe) and heat conductivity coefficient of 2.22 W/(m•K) as compared with those of 859.8 mW/cm3, 57.1% and 1.86 W/(m•K), respectively, for the NMPCs without ZnO insulating layer.

Bio-inspired chemistry for developing micro/nano structured nanofiber membranes for membrane distillation

Membrane distillation (MD) holds significant promise for effluent purification to mitigate the global water shortage. However, the existing petroleum-based MD membranes suffer from high costs, limited sustainability, and wetting issues. Herein, we employed biosynthetic bacterial cellulose (BC) as the substrate and successfully achieved a uniform and stable dispersion of ZnO nanoflowers onto the BC nanofibers through in-situ synthesis technology. After undergoing a fluorination process, a superhydrophobic membrane was prepared by the synergistic effect of micro/nano structures and low surface energy. The resulting membrane exhibited exceptional properties, including a remarkable contact angle of 151.7°, a substantial liquid entry pressure of 2.5 bar, and exhibiting structural integrity and high hydrophobicity even under harsh conditions. Furthermore, this strategy ensured exceptional membrane porosity (∼94.9 %), increased the permeation flux and reduced conductive heat transfer, thereby enhancing the thermal efficiency of the membrane. Furthermore, the membrane demonstrated effective bactericidal activity and self-cleaning capability, facilitating easy cleaning and extending service life. These properties endow the membrane with an impressive durability. After 96 h of continuous operation, the membrane maintained a stable permeation flux of 10.29 L m−2 h−1 and an extraordinary salt rejection rate exceeding 99.9 %. Notably, even with the addition of sodium dodecyl sulfate to the feed, the membrane exhibited stable permeation flux and outstanding antiwetting properties. In summary, the MD membrane fabricated using the bio-inspired chemistry demonstrated a promising potential for long-term applications in direct contact MD operations.

Bernoulli Distillation System (BDS) for Bioethanol Sorghum Stalk Purification

Sorghum is a plant that produces syrup, forage and animal feed silage. The utilization of sorghum stalk as fuel oil (bioethanol) is an energy increasingly needed by the depletion of deposits of fossil fuel oil. Thus, tools and methods are needed to produce sorghum stem bioethanol, which has a certain purity level. This study aims to increase the purity of bioethanol from sorghum stems using the Bernoulli Distillation System (BDS) by experimentally testing the purification of sorghum stem bioethanol. In the bioethanol purification stage, heat transfer in the reactor and condenser was analyzed, and the performance of the ejector was analyzed with a vacuum pressure (-55 cmHg), temperature 71°C, test time of 1800, 3600, 5400 and 7200 seconds with a test material of 28% capacity 20 liters. The results of the analysis of the highest conduction heat transfer on the water jacket wall are 14757.72 Joules, the reactor tank is 962.1 Joules, the bottom of the reactor tank is 765.05 Joules and convection in the reactor fluid is 2.09 Joules. The highest heat transfer energy in the condenser is 72683.1 Joules. While the efficiency of the water jet ejector is 65.4%, the highest increase in bioethanol content is 51% in 3600 seconds, as much as 745 ml. The characteristics of the bioethanol obtained included a calorific value test of 1389.48 cal/gram, a viscosity of 1.02044, a flash point of 32.5°C, and a density of 0.934 g/cm3. Thus, the Bernoulli Distillation System’s purification process can increase bioethanol levels effectively and efficiently.

Numerical simulation of thermal and stress fields for multilayer and multi-pass weaving WAAM of magnesium alloy

Purpose A 3D finite element (FE) model based on the double ellipsoidal heat source was developed to investigate the evolution of temperature and stress fields during the multilayer and multi-pass wire and arc additive manufacturing (WAAM) process. This paper aims to investigate the evolution of temperature and stress fields during the multilayer and multi-pass wire and arc additive manufacturing (WAAM) process by developing a 3D finite element (FE) model based on the double ellipsoidal heat source. Design/methodology/approach Experimental thermal cycle curves and residual stresses were obtained by thermocouples and X-ray diffraction, respectively. The validity of the model was verified by the corresponding experimental results. Findings The deposition process of the upper pass led to the partial remelting of the lower deposited pass. The thermal process of the current-deposited pass alleviated the stress concentration in the previous-formed passes. A more uniform temperature distribution could be obtained by using the reciprocating deposition path. Compared to the reciprocating deposition path, the peak values of the transverse and longitudinal tensile residual stresses of the deposited sample under the unidirectional deposition path were reduced by 15 MPa and increased by 13 MPa, respectively. The heat conduction in the deposited passes could be improved by extending the inter-pass cooling time appropriately. With an increase in the inter-pass cooling time, the longitudinal residual stress in the middle region of sample along longitudinal and transverse directions showed increase and decrease–increase trends, respectively, while the transverse residual stress exhibited decrease trend. Originality/value This study enhances the understanding of temperature and stress fields evolution during the multilayer and multi-pass cold metal transfer-WAAM processes of magnesium alloy and provides the reference for parameter optimization.

An innovative subdivision collocation algorithm for heat conduction equation with non-uniform thermal diffusivity.

This paper presents a subdivision collocation algorithm for numerically solving the heat conduction equation with non-uniform thermal diffusivity, considering both initial and boundary conditions. The algorithm involves transforming the differential form of the heat conduction equation into a system of equations and discretizing the time variable using the finite difference formula. The numerical solution of the system of heat conduction equations is then obtained. The feasibility of the algorithm is verified through theoretical and numerical analyses. Additionally, numerical and graphical representations of the obtained numerical solutions are provided, along with a comparison to existing methods. The results demonstrate that our proposed method outperforms the existing methods in terms of accuracy.

Research on surface integrity of titanium alloy in V-groove micro-textured ball-end milling cutter

In order to realize chip guiding control in titanium alloy machining, reduce the negative influence of unstable chip flow direction on the milling environment, and improve the performance and reliability of parts, this article adopts the V-groove micro-texture carbide tool as the research object and takes the laser preparation of the V-groove micro-texture as a breakthrough point, analyzes the influence of laser parameters on the aspect ratio of V-groove micro-texture, and optimizes the laser parameters. The titanium alloy milling test platform was built to analyze the influence of the micro-texture parameters of the V-groove on the surface integrity of the workpiece, reveal the action mechanism, and optimize the relevant parameters based on the artificial bee colony algorithm. The results show that laser power has the largest influence on the aspect ratio of the groove. The power determines the melt content in the groove and influences the width and depth of the micro-texture. The optimized laser combination parameters are: laser power 42.5 W, scanning speed 10 mm/s scanning times nine times, scanning frequency 30 kHz, and spot diameter 30 μm. The V-groove micro-texture on the tool surface can change the chip flow direction, reduce the contact area of the chip, accommodate the cutting particles, and improve heat conduction, reducing cutting resistance and friction, thereby optimizing cutting control distance, thereby improving the surface integrity of the workpiece becomes. The optimized V-groove micro-texture parameters are as follows: V-groove angle X = 46.2°, V-groove height H = 175 μm, radial spacing L = 259.4 μm, circumferential angle J = 2.1°, and distance from the edge K = 120 μm.

Efficient ecological function analysis and multi-objective optimizations for an endoreversible simple air refrigerator cycle

Abstract Combining finite time thermodynamics and exergetic analysis, analogous to the definition of ecological efficient power for heat engines, this paper proposes a unified performance indicator for various cycles, exergy-based efficient ecological function (E ɛ ) which is defined as product of exergy-based ecological function and coefficient of performance, and introduces it into performance optimization of endoreversible simple air refrigerator cycle coupled to constant-temperature heat reservoirs. Relations among E ɛ , pressure ratio (π) and heat conductance distribution ratio (u) are derived by using numerical method. The cycle performance indicators which include cooling load (R), coefficient of performance (ɛ), and exergetic loss rate (E out/T 0) under the different maximum objective criteria are compared. Taking π as optimal variable, and taking R, ɛ, cooling load density (r), E ɛ and their combinations as optimization objectives, multi-objective optimizations, totally 15 optimization combinations, are performed by using NASG-II algorithm. The results demonstrate that, the maximum E ɛ criteria can better reflect the compromise among R, ɛ and E out/T 0. The Pareto solution sets are majorly distributed in 2.5–20 when quadru-objective optimizations are performed. The option selected by LINMAP decision-making method is closer to ideal solution when bi-objective optimization of ɛ and r is carried out.

Enhancing directional thermal conductivity in hexagonal boron nitride reinforced epoxy composites through robust interfacial bonding

AbstractEstablishing a robust interfacial bond between hexagonal boron nitride (h‐BN) plates and the epoxy matrix is essential for enhancing heat transfer, which is difficult because of h‐BN's low‐surface energy, tendency to clump together, and the chemical inertness of the epoxy matrix. This research shows different techniques for treating the surface of h‐BN fillers by applying acids and thermal processes to activate the surface. The silanization process was used to increase the silane content on the surface of activated h‐BN in order to make it more compatible with the epoxy matrix. X‐ray photoelectron spectroscopy analysis revealed silicon peaks (Si2s peak at 150.1 eV and Si2p peak at 100.3 eV) in the spectrum of silane‐treated samples. Heat treatment resulted in the production of more oxygen molecules on the shell of h‐BN compared to the acid treatment. Here, the primary focus was on examining how surface treatment affects thermal conductivity (TC) performance in both in‐plane and through‐thickness paths. There was an increase in the epoxy's TC perpendicular to the plane, going from 0.21 to 0.47 (W/mK), showing a remarkable 123.8% enhancement by adding 10 wt% of silane‐modified‐thermal treated h‐BN particles. The improvement resulted from effectively silanizing the exterior boundary of h‐BN particles, enhancing connection and distribution in the epoxy matrix. Surface modification of h‐BN‐epoxy composites improves TC, leading to better heat conduction in thermal management systems, benefiting industries like aerospace, automotive, and energy systems.Highlights Silanization of h‐BN for better filler‐matrix bonding leading to improved heat transfer Boosting thermal conductivity in the through‐thickness direction with surface‐modified h‐BN Significant improvement in through‐thickness thermal conductivity with treated h‐BN. Thermal treatment of h‐BN produced better oxygenation than acid treatment. Application in aerospace and automotive through improved heat transfer.

Chaotic self-beating of left ventricle modeled by liquid crystal elastomer

Self-vibration systems using active materials generate sustained vibrations spontaneously through synergistic actions between internal structure and external environment. Therefore, the self-vibration systems have a wide application prospect in bionic design and soft robots. Inspired by the human left ventricle, a novel chaotic self-beating system modeled by an electrothermal responsive liquid crystal elastomer balloon is proposed. To study the self-beating characteristics of the liquid crystal elastomer left ventricle, a simplified theoretical framework is formed by combining the electric joule heat conduction model, the left ventricle circulatory system model and the dynamic principle. The numerical results show that the left ventricle has two typical self-beating modes: periodic beating and chaotic beating. The mechanisms of periodic beating and chaotic beating are elucidated by analyzing the balance between the work done by each force on the left ventricle. In addition, the effects of key system parameters on self-beating behavior are investigated in detail. This research will promote the application of chaotic dynamics in artificial hearts and medical devices, while providing a new perspective for the study of chaotic behavior and mechanism in biology.

Enhanced Thermoelectric Performance of Bi0.5Sb1.5Te3 through Precise Pb Doping: Analysis Using the Single Parabolic Band Model

This study investigates the thermoelectric properties of Pb-doped p-type Bi0.5Sb1.5Te3 alloys using the Single Parabolic Band (SPB) model, focusing on optimizing room-temperature performance. We systematically analyze the effects of Pb doping (0, 0.49, 0.65, 0.81, 0.97, and 1.3 at%) on key parameters including density-of-states effective mass (md *), non-degenerate mobility (μ0), weighted mobility (μw), and the thermoelectric quality factor (B-factor) at 323 K. The results reveal that md * reaches a maximum of 1.37 me at 0.97 at% Pb doping, representing a 22.25 % increase over the pristine sample. The highest μ0 of 234.5 cm2 V-1 s-1 is achieved at 0.65 at% Pb, highlighting the complex relationship between doping and carrier mobility. Notably, 0.97 at% Pb doping optimizes thermoelectric performance, yielding the highest μw, power factor, and B-factor. This composition also minimizes lattice thermal conductivity (k1) by 44.93 % compared to the undoped sample, significantly reducing phonon heat conduction. The Callaway-von Baeyer model corroborates these findings, indicating maximized point defect scattering at 0.97 at% Pb. A theoretical peak figure-of-merit (zT) of 1.74 is thus predicted at this doping level, demonstrating a possible substantial enhancement in thermoelectric efficiency upon appropriate carrier concentration tuning. The observed trends in Seebeck coefficient, Hall carrier concentration, and Hall mobility with increasing Pb content provide insights into the underlying mechanisms of performance enhancement. This comprehensive study highlights the critical role of precise Pb doping in optimizing the thermoelectric properties of Bi0.5Sb1.5Te3 alloys for room-temperature applications and establishes a framework for future investigations into similar material systems.

Natural convection and variable fluid properties of tangent hyperbolic nanofluid flow with Cattaneo-Christov theories and heat generation

The main aim behind this work is that we have to determine the enhancement that happens in thermal conductivity by using the Buongiorno model of nanofluid when the nanofluid particles are added to the tangent hyperbolic base fluid moving above the stretched surface. The viscosity of tangent hyperbolic nanofluid is assumed to be temperature-dependent. The modified form of the Fourier law of heat conduction motivated us; therefore, the Cattaneo-Christov heat and mass flux model is considered to observe its significance for heat and mass transport. The chemical reaction and heat generation are also considered to determine their influence on temperature and concentration gradients. This study is crucial because of its application in industrial manufacturing processes such as the coating of wire, the thinning of copper, the production of paper, photographic films, hot rolling, and the purification of crude oil. In electronic cooling systems, the efficient dissipation of heat in smartphones, computers, and data centers is critical to preventing overheating. Nanofluids, with their enhanced thermal properties, can significantly improve heat transfer rates, ensuring better performance, stability, and energy savings. The partial governing equations arising from fluid flow, mass, and heat transfer are transformed into ordinary differential equations via appropriate similarity variables. The obtained ordinary differential equations are solved numerically by using the Runge-Kutta Fehlberg method in the MATLAB software. The effects of the emerging parameters are represented through graphs. According to the results, the velocity profile upsurges due to the natural convection parameters and curvature parameter, while the power law index declines the velocity profile. As the Brownian motion coefficient rises, the concentration profile diminishes while the temperature profile increases. Both the concentration and temperature profiles increase for larger values of the thermophoresis parameter. The concentration profile declines for larger values of chemical reaction parameters, and enhancement happens in the temperature region.

Impact of Acoustic and Optical Phonons on the Anisotropic Heat Conduction in Novel C-Based Superlattices.

C-based XC binary materials and their (XC)m/(YC)n (X, Y ≡ Si, Ge and Sn) superlattices (SLs) have recently gained considerable interest as valuable alternatives to Si for designing and/or exploiting nanostructured electronic devices (NEDs) in the growing high-power application needs. In commercial NEDs, heat dissipation and thermal management have been and still are crucial issues. The concept of phonon engineering is important for manipulating thermal transport in low-dimensional heterostructures to study their lattice dynamical features. By adopting a realistic rigid-ion-model, we reported results of phonon dispersions ωjSLk→ of novel short-period XCm/(YC)n001 SLs, for m, n = 2, 3, 4 by varying phonon wavevectors k→SL along the growth k|| ([001]), and in-plane k⟂ ([100], [010]) directions. The SL phonon dispersions displayed flattening of modes, especially at high-symmetry critical points Γ, Z and M. Miniband formation and anti-crossings in ωjSLk→ lead to the reduction in phonon conductivity κz along the growth direction by an order of magnitude relative to the bulk materials. Due to zone-folding effects, the in-plane phonons in SLs exhibited a strong mixture of XC-like and YC-like low-energy ωTA, ωLA modes with the emergence of stop bands at certain k→SL. For thermal transport applications, the results demonstrate modifications in thermal conductivities via changes in group velocities, specific heat, and density of states.