Search Results (219)

Calcium niobate ceramics were synthesized by the solid-state reaction of seashell-derived CaCO₃ and Nb₂O₅ at a molar ratio of 4:1 over the temperature range of 800–1200 °C for 8 h. This work provides a correlated structural, morphological, and thermophysical characterization of the resulting calcium niobate phases. X-ray diffraction coupled with Rietveld refinement revealed a temperature-dependent phase transformation from a CaNb₂O₆-rich composition at lower synthesis temperatures to a Ca₄Nb₂O₉-rich material at higher temperatures. At 1200 °C, Ca₄Nb₂O₉ was obtained as the predominant phase (96.16 ± 1.81%), with only a minor Ca₂Nb₂O₇ contribution. This phase evolution was accompanied by an increase in the Ca₄Nb₂O₉ crystallite size from 39.49 ± 0.19 nm at 1000 °C to 50.38 ± 0.24 nm at 1200 °C. SEM analysis showed a concurrent morphological transformation from agglomerated and irregular particles to well-defined elongated and platelet-like particles, indicating enhanced crystallization and grain growth. Thermophysical properties were determined using open photoacoustic cell and laser-flash techniques. Thermal diffusivity ranged from 1.86 to 3.12 × 10⁻⁷ m² s⁻¹, heat capacity from 0.79 to 1.30 × 10⁴ JK⁻¹ m⁻³, thermal conductivity from 0.15 to 0.41 Wm⁻¹ K⁻¹, and thermal effusivity from 0.36 to 0.73 kWs^1/2 m⁻² K⁻¹. The combined results establish a clear synthesis–structure–property relationship and identify the Ca₄Nb₂O₉-rich ceramic obtained at 1200 °C as a promising low-thermal-conductivity material. The use of seashell waste additionally provides a renewable calcium precursor for the synthesis. Full article

Electrical discharge machining (EDM) demonstrates significant advantages in machining difficult-to-cut materials, particularly those with high hardness and brittleness, owing to its thermally driven material removal mechanism in which the arc plasma serves as the heat source. However, machining performance varies markedly across different workpiece materials. Such differences are likely attributable to the coupled effects of arc plasma characteristics, which may vary with tool–workpiece material combinations, and the thermophysical properties of the workpiece. Nevertheless, the mechanisms underlying this coupling remain poorly understood. In this study, arc plasma characteristics and material removal behavior under different material combinations were investigated using arc plasma and thermo-hydrodynamic simulation models. Under positive polarity, a copper tool electrode was paired with 304 stainless steel, Ti-6Al-4V, and Inconel 718 workpieces, while copper and tungsten electrodes were compared using a 304 stainless steel workpiece. Simulation results show that material combinations significantly affect anode heat flux and energy distribution, with 304 stainless steel exhibiting the highest heat flux and Inconel 718 receiving the largest energy distribution ratio. Crater depth correlates strongly with heat flux magnitude, while crater diameter is jointly determined by heat flux radius and melt flow dynamics, with the selected cathode material exerting only minor influence. High-speed imaging and crater morphology measurements validate the simulation results, confirming model reliability. These findings provide theoretical guidance for process optimization in EDM. Full article

Boiling is one of the most effective mechanisms for heat transfer enhancement and is therefore widely applied in high-performance cooling systems for electronic devices, power electronics, and compact heat exchangers. A comprehensive understanding of the relationship between surface microstructure geometry and boiling dynamics enables the design of advanced surfaces with improved thermal performance and enhanced operational stability. This study presents an experimental investigation into the effect of inclined microchannel geometry on the pool boiling characteristics of FC-72 and ethanol, two working fluids with significantly different thermophysical properties. The experiments were conducted on copper surfaces with parallel microchannels of various widths, depths, and inclination angles, with the obtained results compared with those for a technically smooth reference surface. The experiments were performed under atmospheric pressure conditions with a gradually increasing heat flux. Boiling curves, heat transfer coefficients (HTCs), and critical heat flux (CHF) values were determined. The results demonstrate that properly designed microchannel geometries can significantly enhance boiling heat transfer by increasing the number of active nucleation sites and modifying the conditions of vapor bubble growth and departure. The most favorable thermal performance was achieved for surfaces with the smallest channel width, confirming the important role of microstructure geometry in governing boiling heat transfer mechanisms. For FC-72, the HTC increased by more than 200% compared with the reference surface, whereas ethanol exhibited higher HTC values and a more stable nucleate boiling regime over the entire investigated heat flux range. The results confirm that optimization of inclined microchannel geometry provides an effective strategy for designing surfaces dedicated to enhanced boiling cooling, while the effectiveness of surface modification depends on both microstructure characteristics and the thermophysical properties of the working fluid. Full article

In this study, the cooling performances of various nanofluids were compared under the operating conditions of a real automobile radiator, based on an internal combustion engine vehicle cooling system whose experiments had been previously completed. In the analyses, the radiator inlet fluid temperature was fixed at 70 °C, air inlet velocities were set to 6, 8, and 10 m/s, and fluid flow rates were taken as 17, 19, and 21 L/min. Under these conditions, the cooling capacities were evaluated for three different working fluids whose thermophysical properties were experimentally determined: 100% pure water, water-based 0.3% ZnO nanofluid, and water-based 0.3% ZnO + CuO hybrid nanofluid. Within the scope of this study, a Computational Fluid Dynamics (CFD) model was developed based on the aforementioned experimental parameters and validated with a maximum deviation of 6%. Using the validated model, additional CFD analyses were performed for water-based 0.3% Al₂O₃ and TiO₂ nanofluids, whose thermophysical properties were also experimentally determined, and their cooling performances were assessed. Based on the experimental and numerical results obtained, the highest cooling capacity was determined to be 20.8 kW in the 0.3% TiO₂ nanofluid, representing a 69.1% increase in cooling capacity compared to pure water. These findings clearly demonstrate that the use of nanofluids significantly enhances heat transfer performance in automotive cooling systems. Full article

This study presents a comparative evaluation of geopolymer foams incorporating either commercially available shape-stabilized phase change materials (PCMs) or laboratory-developed diatomite–paraffin PCM granules with controlled particle size fractions ranging from <1.6 mm to >2.5 mm. All PCM variants were incorporated at a constant dosage of 7.5 wt.% to isolate the influence of PCM type on the properties of the resulting composites. The commercial materials comprised PX-4, PX15, and PX20 (Rubitherm Technologies GmbH), whereas the laboratory-developed PCM consisted of paraffin immobilized within a porous diatomite matrix to produce granular shape-stabilized composites. The experimental program included the determination of bulk density, total porosity, pore size distribution, thermal conductivity (λ), thermal resistance (R), specific heat capacity (Cp), and compressive strength. The pore structure was characterized by mercury intrusion porosimetry (MIP), while the morphology and dispersion of PCM particles within the geopolymer matrix were investigated using scanning electron microscopy (SEM). All mixtures were produced using the same alkali-activated matrix and identical curing conditions, with the PCM content maintained at 7.5 wt.%. The results demonstrated that the type of PCM significantly affected the microstructure and thermophysical performance of the geopolymer foams. The laboratory-developed diatomite–paraffin PCM provided the most favorable thermal insulation performance, exhibiting the lowest thermal conductivity (0.095 W/m·K) together with the highest thermal resistance (0.278 m²·K/W). In contrast, the commercial PX15 and PX20 materials exhibited the highest specific heat capacities (1.740 and 1.778 kJ/kg·K, respectively), indicating superior thermal energy storage capability. In addition, the estimated production cost of the laboratory-developed PCM (2.5–4.0 EUR/kg) was substantially lower than that of the commercial PX materials (approximately 20 EUR/kg), highlighting its potential as a cost-effective alternative for sustainable, energy-efficient building materials. These findings demonstrate that both commercial and laboratory-developed PCM systems can effectively enhance the functionality of geopolymer foams, although they provide different balances between thermal insulation, heat storage capacity, and production cost. Full article

This study experimentally investigates the mixed convection heat transfer performance of CuZnFe₂O₄–water-based magnetic nanofluids in a cylindrical minichannel under the influence of external magnetic fields. Nanofluids with three different volumetric concentrations (0.25%, 0.50%, and 0.75%) were synthesized and characterized in terms of thermophysical properties. The experiments were conducted within the Richardson number range of 0.1–10 to ensure mixed convection conditions, while magnetic field intensities of 220 G, 300 G, and 380 G were applied using custom-built electromagnets. Results show that suspending CuZnFe₂O₄ nanoparticles significantly enhances the heat transfer rate compared to pure water, mainly due to increased thermal conductivity and particle–fluid interactions. The application of a magnetic field further augments the Nusselt number by disturbing the thermal boundary layer and intensifying particle motion, leading to up to 64.4% improvement compared with pure water at similar Reynolds numbers. In addition, Analysis of Variance (ANOVA) and Response Surface Methodology (RSM) were employed to determine the most influential parameters on heat transfer performance and to develop a predictive correlation for the Nusselt number as a function of Reynolds number, nanoparticle concentration, and magnetic field intensity. The findings highlight the combined effects of nanoparticle suspension and magnetic field application as a promising approach for enhancing heat transfer in low-flow mixed convection regimes, offering valuable insights for thermal management in miniaturized cooling systems. Full article

The dilution of lubricating oil with diesel oil (DO) is a significant operational problem in piston combustion engines, as it degrades lubrication conditions and may accelerate the wear of interacting components. This study aimed to evaluate the usefulness of selected thermophysical and electrical properties of lubricating oil for determining the degree of its dilution with diesel oil. The tests were conducted on mixtures of SAE 30 or SAE 40 lubricating oil with diesel oil over a concentration range of 0–100% m/m of the latter material. Changes in thermal conductivity, thermal effusivity, and breakdown voltage were examined as a function of the mixture’s fuel content. The thermal conductivity and effusivity of the tested oils were measured using the MTPS (Modified Transient Plane Source) transient method, while the breakdown voltage of the tested oils was measured at mains frequency using an apparatus in which the oil sample was exposed to an increasing electric field by gradually increasing the alternating voltage at a constant frequency until electrical breakdown occurred. An increase in the proportion of diesel oil caused a systematic linear decrease in thermal conductivity and thermal effusivity. A decreasing trend was also observed for breakdown voltage; however, this parameter exhibited significantly greater variation in results. The results indicate that thermal conductivity and thermal effusivity are more useful for assessing the degree of dilution of lubricating oil with DO than breakdown voltage. Full article

The push for higher energy density in electric vehicles has resulted in large-sized lithium-ion batteries, but their geometric upscaling exacts a heavy thermal price. Under high-rate discharge, these massive cells become heat traps, risking thermal runaway. To tame this instability, this paper engineered a hybrid management strategy fusing liquid cooling, Phase Change Materials (PCMs), and flow deflectors. With a primary focus on the structural optimization of the cooling channel, a three-dimensional numerical model, calibrated using experimentally determined thermophysical properties, was developed to overcome the thermal bottlenecks of conventional cooling architectures. Results indicated that the initial channel optimization effectively reduced the maximum temperature to 327.7 K, but it still remained near the safety threshold. Integrating PCM radically altered the thermal landscape, slashing the outlet temperature differential by 41.67% (from 2.76 K to 1.61 K) compared to pure liquid cooling and blunting peak thermal spikes. Furthermore, to overcome laminar stagnation, strategic deflector baffles were introduced to agitate the coolant, enhancing heat dissipation. Specifically, the optimal half-coverage (L = 1/2) baffle configuration successfully lowered the maximum temperature to 322.42 K while substantially reducing the system pressure drop from 948.16 Pa to 627.57 Pa, achieving a 33.33% reduction compared to the full-coverage scheme. Finally, a multi-variable sensitivity analysis confirmed the extraordinary engineering robustness of the optimized configuration, demonstrating a negligible maximum temperature fluctuation of less than 0.5% despite ±10% operational and material uncertainties. This synergistic system actively stabilizes the thermal envelope, offering a robust engineering blueprint for next-generation high-power battery packs. Full article

Improving the energy efficiency of the building envelope is critical for global decarbonization, yet a gap remains in the comprehensive thermophysical characterization of carbon-enhanced Expanded Polystyrene (EPS). This study evaluates the impact of expansion ratios and moisture content on the thermal behavior of two commercial EPS grades, EPS-A (12.7 ± 0.5 kg/m³) and EPS-B (16.0 ± 1.1 kg/m³), investigating the counterintuitive role of graphite (1.4–1.8 wt.%) in enhancing the thermal insulation properties. Thermal conductivity and diffusivity were independently determined via Transient Plane Source (TPS) and Heat Flow Meter (HFM) methods across a 10–50 °C range, while specific heat capacity (c_p) was analyzed using HFM and Differential Scanning Calorimetry (DSC) through the sapphire comparison method and Temperature-Modulated DSC (TOPEM^®). Methodologically, it was found that standard HFM protocols are unsuitable for c_p determination in low-density foams, yielding an average relative error of ±29%; conversely, the sapphire comparison method provided the most reliable results in agreement with theoretical expectations. Results indicate that the efficacy of graphite as a radiative shield is closely coupled with cellular morphology, proving significantly more effective in the higher expansion grade (EPS-A, 70 wt.% open porosity) than in the denser EPS-B. Furthermore, 30-day water immersion tests revealed that the higher open porosity of EPS-A facilitates increased water uptake of 144 ± 17 wt.% (compared to 97 ± 7 wt.% for EPS-B), causing the geometric densities of the two grades to converge and fundamentally altering thermal transport mechanisms. The study concludes that accurate thermal modeling of carbon-enhanced insulation requires careful selection of testing parameters, particularly when accounting for moisture-induced degradation in high-porosity systems. Full article

The evaluation of building energy performance under dynamic conditions requires reliable estimates of the thermophysical properties of envelope components. In existing buildings, however, the properties of multilayer walls are often unknown or uncertain, limiting the applicability of detailed physical models. To address this issue, this study proposes an inverse modeling framework for identifying the equivalent thermophysical parameters of a multilayer wall through a simplified homogeneous one-dimensional conduction model. The equivalent parameters are determined by matching the inner-side dynamic thermal response of the homogeneous model to that of the actual multilayer structure under the same external excitation. The approach explicitly accounts for the role of inner boundary conditions, which govern both the identifiability of the equivalent parameters and the formulation of the inverse problem. Adiabatic, isothermal, and more general inner boundary conditions are analyzed to determine how many independent parameters can be reliably identified and which response variables should be used in the objective function. Synthetic datasets, generated via numerical simulations driven by real weather data, are first employed to assess the method and to quantify the effect of transient initialization. The framework is then applied to experimental measurements collected from a full-scale test room. The results show that, under adiabatic conditions, the wall dynamics can be accurately reproduced by identifying a single equivalent thermal diffusivity, whereas isothermal and near-isothermal conditions require the simultaneous estimation of thermal conductivity and volumetric heat capacity. Moreover, the analysis demonstrates that inverse formulations based on inner heat flux are significantly more robust than temperature-based formulations, particularly when the inner-surface temperature is weakly varying or tightly controlled, as commonly occurs in real buildings. In a nearly isothermal experimental case, the inverse identification failed (${EF}_T=-5.76$) when based on the inner-surface temperature, while it resulted in a better match (${EF}_q=0.63$) when based on the inner heat flux. Overall, the proposed framework provides a physically consistent and practically robust methodology for the dynamic thermal characterization of multilayer building walls using equivalent homogeneous models. Full article

The applications of nanofluids are widely beneficial in heat transmission and cooling systems. Nanofluid viscosity and thermal conductivity have a substantial effect on heat transfer applications and on devices such as solar and geothermal systems. Machine learning models enable faster, less expensive modeling of nanofluid thermophysical properties. These models are secure for future studies and in the development of nanotechnology. In this review, shape, size, temperature, and volume concentration are considered as inputs to develop several machine learning methods, such as artificial neural networks, support vector regression, decision trees, and random forests. These models were analyzed by comparing their R² values, and the results indicated that machine learning-based models generally exhibited more reliable performance than the other approaches. The observation in this review was that thermal conductivity increases with temperature and volume fractions, whereas viscosity decreases with size, temperature, and volume fractions. To determine the optimal nanoparticle type, size, and concentration for specific applications such as data center cooling and high-heat-flux electronics, future research may employ ML-based optimization techniques. Full article

Desalination is an increasingly important element in the sustainable supply of potable water. To accurately predict costs, the efficiency of such systems requires accurate knowledge of seawater’s thermodynamic properties. Four models have been proposed for determining the thermophysical properties of salt water, pure water, an ideal mixture, and an aqueous sodium chloride solution, and empirical correlations, as would be expected, provide the precision necessary for accurate exergy calculations. This research began with a study of the most recent and accurate empirical investigations of the thermodynamic properties of seawater. It then employed AI techniques to develop a simpler, more accurate model for density, Gibbs free energy, specific enthalpy, and specific entropy for pressures extending up to 12 MPa, salinities from 0 to 80 g/kg, and the temperature range of 10 °C to 120 °C. The AI-based correlations achieved absolute errors of 1.5 kg/m³ for density, 0.185 kJ/kg for specific enthalpy, 0.005 kJ/kg·K for specific entropy, and 0.214 kJ/kg for Gibbs free energy. These values demonstrated at least equivalent, and even superior, accuracy to the existing state-of-the-art formulations, with the advantage of significantly reduced computational complexity, enhanced computational efficiency, and a more user-friendly implementation. Validation against experimental data demonstrated the exceptional accuracy of the predicted values for all the stated thermodynamic properties. In addition, an exergy-based assessment was conducted of the performance of a recently commissioned desalination plant in Kuwait. This was a large-scale multi-effect distillation plant with thermal vapour compression (MED-TVC), showing a second-law efficiency of 8.9%, with the primary source of exergy destruction identified as the evaporator units. Comparative assessment with a more conventional approach showed differences of less than 0.4% in total exergy destruction and less than 5% in exergetic efficiency. This is taken as a validation of the accuracy, reliability, and practical usefulness of the proposed AI framework for the performance evaluation of desalination systems. Full article

While traditional equations of state can determine thermophysical properties, they are computationally demanding, as most formulations are implicit and require iterative solutions. Dynamic simulation of complex energy systems involves various components defined by mathematical equations. Incorporating equations of state for refrigerant properties adds complexity, slowing down the computation. Moreover, studies have demonstrated that calculations of refrigerant thermophysical properties have the most significant impact on computational speed. Therefore, this work develops fast, accurate, and explicit thermodynamic formulations for thermophysical properties of propane, a widely used natural refrigerant for the new generation of heat pumps. The developed set of formulations yielded a mean absolute relative deviation of less than 1% for most of the formulations across the saturated lines and the different phase regions. The results show that using the explicit formulations for dynamic simulation of an air-source heat pump cycle achieves up to a 117× speedup compared to CoolProp, with a maximum relative error around 1% for the COP. This level of accuracy is suitable for applications such as vapor-compression cycle simulations, where accuracy is sacrificed in favor of computational speed. In addition, they offer greater flexibility for modelling and optimizing complex energy systems. Full article

The homogeneity of methane hydrates in marine sediments plays a significant role in determining the efficiency of gas production during exploitation processes. Revealing their distribution mechanisms is crucial for optimizing the development of gas hydrates. This work systematically investigates the evolution patterns of effective thermal conductivity (ETC) during the formation and dissociation of methane hydrate in marine sediments, focusing on their major mineral components, such as quartz sand, illite, and montmorillonite. The results reveal the influence of thermal conductivity (TC) characteristics in porous media on hydrate phase transition behavior and spatial distribution. Key findings demonstrate that the TC characteristics of porous media are one of the dominant factors controlling hydrate formation rates. High-conductivity porous media significantly accelerate hydrate formation through efficient heat transfer. The swelling characteristics of montmorillonite and its coupling effects with salt ions impair heat transfer pathways, thereby inhibiting hydrate formation. Further analysis reveals that the spatial heterogeneity in reservoir TC is the primary intrinsic mechanism responsible for the macroscopic heterogeneous distribution of hydrates. Additionally, the hydrate dissociation process disrupts solid-state thermal bridging and generates gaseous thermal barriers, causing irreversible attenuation of reservoir TC. This phenomenon exacerbates the non-uniformity of the front during dissociation and increases the risk of secondary formation during exploitation. From a novel perspective of reservoir TC heterogeneity, this study establishes mechanistic links between the thermophysical properties of porous media and the spatial distribution patterns of hydrates. This provides significant theoretical guidance for resource exploration and the safe, efficient exploitation of marine gas hydrate reservoirs. Full article

The properties of chemically bonded core sands strongly depend on the reactivity of phenol-formaldehyde resole binders and on the granulometry of the sand matrix. This study presents an evaluation of the mechanical, technological, thermomechanical, and thermophysical properties of core sands prepared using two resole binders with different reactivity levels (Resin 1—lower reactivity; Resin 2—higher reactivity) and two fractions of quartz sand (BK 40 and BK 45). The investigations included the kinetics of strength development (1–48 h), friability, permeability, thermal deformation (DMA), and the determination of thermophysical coefficients (λ₂, a₂, b₂) based on temperature field registration during the solidification of a copper plate. The results indicate that sands containing the higher-reactivity binder exhibit a faster early strength increase (≈0.42–0.45 MPa after 1–3 h), whereas sands bonded with the lower-reactivity resin reach higher tensile strength after 24–48 h (≈0.58–0.62 MPa). Specimens based on BK 45 quartz sand achieved higher tensile strength; however, the finer grain fraction resulted in increased friability (up to ≈3.97%) and a reduction in permeability by 30–40%. DMA analysis confirmed that sands based on BK 40 exhibit delayed and more stable thermal deformation. Thermophysical parameters revealed that BK 45 provides significantly higher thermal insulation, extending the solidification time of the Cu plate from 71–73 s to 89–92 s compared with BK 40. Overall, the results indicate that the combination of BK 40 quartz sand and a lower-reactivity resin offers an optimal balance between thermal conductivity and thermal stability, promoting improved technological performance in casting processes. The determined thermophysical coefficients can be directly applied as input data for foundry process simulations. Full article