Search Results (163)

This study proposes an innovative Thermodynamic Activity Controlled Homogeneous Charge Compression Ignition (TAC-HCCI) strategy for diesel–natural gas dual-fuel engines, aiming to achieve high thermal efficiency while maintaining low emissions. By employing numerical simulation methods, the effects of the intake pressure, intake temperature, EGR rate, intake valve closing timing, diesel injection timing, diesel injection pressure, and diesel injection quantity on engine combustion, energy distribution, and emission characteristics were systematically investigated. Through a comprehensive analysis of optimized operating conditions, a high-efficiency and low-emission TAC-HCCI combustion technology for dual-fuel engines was developed. The core mechanism of TAC-HCCI combustion control was elucidated through an analysis of the equivalence ratio and temperature distribution of the in-cylinder mixture. The results indicate that under the constraints of PCP ≤ 30 ± 1 MPa and RI ≤ 5 ± 0.5 MW/m², the TAC-HCCI technology achieves a gross indicated mean effective pressure (IMEPg) of 24.0 bar, a gross indicated thermal efficiency (ITEg) of up to 52.0%, and indicated specific NOx emissions (ISNOx) as low as 1.0 g/kW∙h. To achieve low combustion loss, reduced heat transfer loss, and high thermal efficiency, it is essential to ensure the complete combustion of the mixture while maintaining low combustion temperatures. Moreover, a reduced diesel injection quantity combined with a high injection pressure can effectively suppress NOx emissions. Full article

The presented research examines the performance characteristics of Brazed Plate Heat Exchangers through computational fluid dynamics (CFD), focusing on pressure drop calculations for single-phase flow within full channels of plates featuring dimpled corrugation. This work aims to bridge gaps in the literature, particularly regarding the underexplored behavior near the ports for the studied technology and establishing a framework for future conjugate heat transfer studies. A methodology for the domain generation was developed, integrating a preliminary forming simulation to reproduce the complex plate geometry. Comprehensive sensitivity analyses were conducted to evaluate the influence of different parameters and identify the optimal settings for obtaining reliable results. The findings indicate that the $k-\epsilon$ realizable turbulence model with enhanced wall treatment offers superior accuracy in predicting pressure drops, with errors within ±4.4%. Additionally, leveraging the information derived from CFD, a strategy to estimate contributions from different channel sections without a direct reliance on those simulations was developed, offering practical implications for plate design. Full article

This study compares the heat transfer and pressure drop of three cell structures, namely Kelvin cells (KCs), ellipsoidal Kelvin cells (EKCs), and body-centered cubic (BCC) structures, at the cell scale in order to identify the superior configuration. Then, we conducted numerical simulations on the heat exchangers based on porous media, and evaluate their comprehensive performance. It is shown that KCs have a superior heat transfer. Their volumetric heat transfer coefficient (h_V) is more than 50% higher than that of EKCs and more than 100% higher than that of BCC structures. EKCs exhibit a lower pressure drop. In the heat exchanger performance optimization study, the Kelvin structure demonstrated significant heat transfer characteristics. Simulation data show that the heat transfer performance at the hot end of the Kelvin heat exchanger (KCHE) is enhanced by more than 40% compared to the conventional plate-fin structure (FHE), but its flow channel pressure drop characteristics show a significant nonlinear increase. It is noteworthy that the improved Kelvin heat exchanger (EKCHE), optimized by introducing elliptic cell topology, maintains heat transfer while keeping the pressure loss increase within 1.22 times that of the conventional structure. The evaluation of the heat transfer and pressure drop characteristics is consistent for both scales. In addition, the EKC configuration exhibits a superior overall heat transfer capacity. To summarize, this work proposes a systematic numerical framework encompassing cell unit screening through heat exchanger design, offering valuable guidance for the structured development and analysis of porous media heat exchangers in relevant engineering domains. Full article

This paper focuses on the use of advanced optimization design strategies to improve the performance and service life of engine pistons, with emphasis on enhancing their stiffness, strength, and dynamic characteristics. As a core component of the engine, the structural design and optimization of the piston are of great significance to its efficiency and reliability. First, a three-dimensional (3D) model of the piston was constructed and imported into ANSYS Workbench for finite element modeling and high-quality meshing. Based on the empirical formula, the actual working environment temperature and heat transfer coefficient of the piston were accurately determined and used as boundary conditions for thermomechanical coupling analysis to accurately simulate the thermal and deformation state under complex working conditions. Dynamic characteristic analysis was used to obtain the displacement–frequency curve, providing key data support for predicting resonance behavior, evaluating structural strength, and optimizing the design. In the optimization stage, five geometric dimensions are selected as design variables. The deformation, mass, temperature, and the first to third natural frequencies are considered as optimization goals. The response surface model is constructed by means of the design of the experiments method, and the fitted model is evaluated in detail. The results show that the models are all significant. The adequacy of the model fitting is verified by the “Residuals vs. Run” plot, and potential data problems are identified. The “Predicted vs. Actual” plot is used to evaluate the fitting accuracy and prediction ability of the model for the experimental data, avoiding over-fitting or under-fitting problems, and guiding the optimization direction. Subsequently, the sensitivity analysis was carried out to reveal the variables that have a significant impact on the objective function, and in-depth analysis was conducted in combination with the response surface. The multi-objective genetic algorithm (MOGA), screening, and response surface methodology (RSM) were, respectively, used to comprehensively optimize the objective function. Through experiments and analysis, the optimal solution of the MOGA algorithm was selected for implementation. After optimization, the piston mass and deformation remained relatively stable, and the working temperature dropped from 312.75 °C to 308.07 °C, which is conducive to extending the component life and improving the thermal efficiency. The first to third natural frequencies increased from 1651.60 Hz to 1671.80 Hz, 1656.70 Hz to 1665.70 Hz, and 1752.90 Hz to 1776.50 Hz, respectively, significantly enhancing the dynamic stability and vibration resistance. This study integrates sensitivity analysis, response surface models, and genetic algorithms to solve multi-objective optimization problems, successfully improving piston performance. Full article

Iron tailings-based ultra-high-performance concrete (UHPC) was developed using iron tailings as aggregates, with steel fiber incorporation ranging from 0% to 2.5%. This study investigates the effects of steel fiber dosage and curing age on the electrical, electrothermal, and thermal conductivity properties of iron tailings-based UHPC. A comprehensive evaluation protocol was implemented to quantify resistivity, electrothermal conversion efficiency, and heat transfer characteristics, providing a systematic understanding of the material’s multifunctional properties. Results demonstrate that steel fiber incorporation significantly reduces electrical resistivity, achieving optimal conductivity at 1.5% fiber content. Electrothermal analysis under a 60 V applied voltage revealed maximum heating efficiency (ΔT = 32.5 °C/30 min for UHPC cured for 7 days and ΔT = 8.0 °C/30 min for UHPC cured for 28 days) at 1.5% fiber content. Thermal conductivity measurements identified a non-monotonic relationship with steel fiber content, initially increasing and then decreasing, with maximum thermal conductivity observed at 1.5% fiber content. This trend aligns with the observed resistivity behavior, suggesting a strong correlation between electrical and thermal properties. Fiber distribution within the iron tailings-based UHPC matrix revealed that steel fiber dispersion significantly affects material properties, with 1.5% fiber content achieving optimal percolation network formation for electrical current flow and heat transfer. Full article

The enhancement of the thermal performance of transparent envelopes has been demonstrated to be an effective measure for reducing building energy consumption. To achieve enhanced performance in the domain of building windows, considerable economic investments are frequently necessary. The present study focuses on the 70 series of broken-bridge aluminum windows, which are widely used in China. The investigation explores the potential factors affecting the thermal performance of these windows, mainly considering their glass and profiles. The study also explores the influencing characteristics of various factors and their optimal combinations for their combined effect by comprehensively applying the single-variable method, orthogonal test method, and a numerical simulation. The findings of the study indicate a substantial reduction in the heat transfer coefficient of the 70 series of broken-bridge aluminum windows, achieving a decrease of 25.98%. Additionally, the heat transfer coefficient of the frame and edge is reduced by 29–35%, and the heat transfer coefficient of the entire window is reduced by 28.34%. These findings suggest that the energy-saving requirements for green and low-carbon buildings in most regions of China can be met. Furthermore, the product offers a significant economic advantage over similar market offerings with an equivalent performance. Concurrently, the performance enhancement measures derived from the study are applicable to other types of aluminum windows. Full article

Heat exchangers are critical components in various industrial applications, requiring efficient thermal management to enhance thermal performance and energy efficiency. Longitudinal vortex generators (LVGs) have emerged as a potent mechanism to enhance heat transfer within these devices. A precise knowledge of the thermal performance enhancement of HE through LVGs is missing in the literature. Therefore, this study aims to provide a critical review of both numerical simulations and experimental studies focusing on the enhancement of heat transfer through LVGs to further enhance the knowledge of the field. It begins with elucidating the fundamental principles behind LVGs and delineating their role in manipulating flow patterns to augment heat transfer. This is followed by an exploration of the various numerical methods employed in the field, including computational fluid dynamics techniques such as Reynolds-Averaged Navier–Stokes (RANS) models, Large Eddy Simulation (LES), and Direct Numerical Simulation (DNS). Various experimental methods are then summarised, including differential pressure measuring instruments, temperature measurements, velocity measurements, heat transfer coefficient measurements, and flow visualisation techniques. The effectiveness of these methods in capturing the complex fluid dynamics and thermal characteristics induced by LVGs is critically assessed. The review covers a wide range of LVG configurations, including their geometry, placements, and orientations, and their effects on the thermal performance of heat exchangers. Different from previous reviews that mainly focus on classical configurations and historical studies, this review also emphasizes recent developments in computational fluid dynamics and progress in interdisciplinary fields such as innovative materials, additive manufacturing, surface finishing, and machine learning. By bridging the gap between fluid dynamics, thermal enhancement, and emerging manufacturing technologies, this paper provides a forward-looking, comprehensive analysis that is valuable for both academic and industrial innovations. Full article

In the continuous casting of special steel blooms, low casting speeds result in slow renewal of the molten steel surface in the mold, adversely affecting mold flux melting and liquid slag layer supply, which may lead to surface cracks, slag entrapment, and breakout incidents. To optimize the flow and heat transfer behavior in the mold, a three-dimensional numerical model was developed based on the VOF multiphase flow model, $k-ϵ$ RNG turbulence model, and DPM discrete phase model, employing the finite volume method with SIMPLEC algorithm for solution. The effects of casting speed, argon injection rate, and mold flux properties were systematically investigated. Simulation results demonstrate that when casting speed increases from 0.35 m·min⁻¹ to 0.75 m·min⁻¹, the jet penetration depth increases by 200 mm and meniscus velocity rises by 0.014 m·s⁻¹. Increasing argon flow rate from 0.50 L·min⁻¹ to 1.00 L·min⁻¹ leads to 350 mm deeper bubble penetration, 10 mm reduction in jet penetration depth, 0.002 m·s⁻¹ increase in meniscus velocity, and decreased meniscus temperature due to bubble cooling. When mold flux viscosity increases from 0.2 Pa·s to 0.6 Pa·s, the average liquid slag velocity decreases by 0.006 m·s⁻¹ with a maximum temperature drop of 10 K. Increasing density from 2484 kg·m⁻³ to 2884 kg·m⁻³ results in 0.005 m·s⁻¹ higher slag velocity and average 8 K temperature reduction. Comprehensive analysis indicates that optimal operational parameters are casting speed 0.35–0.45 m·min⁻¹, argon flow ≤ 0.50 L·min⁻¹, mold flux viscosity 0.2–0.4 Pa·s, and density 2484–2684 kg·m⁻³. These conditions ensure more stable flow and heat transfer characteristics, effectively reducing slab defects and improving casting process stability. Full article

The Yinchuan Basin harbors significant geothermal resource potential and could be a clean energy source critical for transitioning to a low-carbon economy. However, the current research primarily focuses on the exploration and development of geothermal water in the sedimentary basins, with limited studies on the deep geothermal formation mechanisms and regional geothermal types. Although geophysical methods provide insights into the types and formation mechanisms of deep geothermal resources in the basin, there is still a lack of a connection between quantitative understanding and direct evidence. A series of algorithms based on thermal parameter characteristics can directly extract underground thermal features from raw geophysical signal data, offering a powerful tool for characterizing the structure and aggregation patterns of deep thermal sources. Therefore, this study employed a Bayesian thermal parameter inversion method based on interface information to obtain the spatial distribution of thermal conductivity, surface heat flow, and mantle heat parameters in the Ningxia Basin study area. Additionally, correlation analysis and global sensitivity analysis were conducted to further interpret the predicted results. A comprehensive analysis of the geophysical inversion results showed that the deep thermal anomalies in the basin are primarily controlled by fault activities and the lithospheres’ thermal structure, while shallow high-heat flow anomalies are closely related to convective circulation within faults and heat transfer from deep thermal sources. The established geothermal genesis mechanism and model of the Yinchuan Basin provide crucial support for sustainable regional geothermal development planning and the utilization of deep geothermal resources, contributing to energy security and emission reduction goals. Full article

Ground-source heat pump (GSHP) systems with medium-depth and deeply buried pipes in cold regions are highly important for addressing global climate change and the energy crisis because of their efficient, clean, and sustainable energy characteristics. However, unique geological conditions in cold climates pose serious challenges to the heat transfer efficiency, long-term stability, and adaptability of systems. This study comprehensively analyses the effects of various factors, including well depth, inner-to-outer tube diameter ratios, cementing material, the thermal conductivity of the inner tube, the flow rate, and the start–stop ratio, on the performance of a medium-depth coaxial borehole heat exchanger. Field tests, numerical simulations, and sensitivity analyses are combined to determine the full-cycle thermal performance and heat-transfer properties of medium-depth geological formations and their relationships with system performance. The results show that the source water temperature increases by approximately 4 °C and that the heat transfer increases by 50 kW for every 500 m increase in well depth. The optimization of the inner and outer pipe diameter ratios effectively improves the heat-exchange efficiency, and a larger pipe diameter ratio design can significantly reduce the flow resistance and improve system stability. When the thermal conductivity of the cementing cement increases from 1 W/(m·K) to 2 W/(m·K), the outlet water temperature at the source side increases by approximately 1 °C, and the heat transfer increases by 13 kW. However, the improvement effect of further increasing the thermal conductivity on the heat-exchange efficiency gradually decreases. When the flow rate is 0.7 m/s, the heat transfer is stable at approximately 250 kW, and the system economy and heat-transfer efficiency reach a balance. These findings provide a robust scientific basis for promoting medium-deep geothermal energy heating systems in cold regions and offer valuable references for the green and low-carbon transition in building heating systems. Full article

Vacuum insulation panels (VIPs) have emerged as a cutting-edge strategy for achieving superior thermal insulation across a wide range of applications, including refrigerators, cold-chain transportation and building envelopes. The key factor for the exceptional performance of VIPs is maintaining an ultralow pressure environment within the panels, which is crucial for minimizing heat transfer. However, the presence of non-condensable gases can compromise the vacuum state, leading to a reduced insulation effectiveness during a panel’s service life. This review offers a comprehensive analysis of getter materials used in VIPs, focusing on their fundamental properties, types, integration techniques and performance characteristics, further emphasizing the challenges and potential directions for the development of getter materials. Overall, this review intends to provide novel insights into the development of getter materials for use in VIPs, offering essential viewpoints to aid future studies on this topic. Full article

Determining the electrochemical, thermal, and mass transfer dynamics embedded in an alkaline electrolysis (AEL) system provides important information about the application of ancillary services provided by hydrogen energy for the elimination of carbon emissions. Therefore, there is an urgent need to develop methodologies for evaluating key parameters, such as overvoltage coefficients, stack transfer capacity, diaphragm thickness, and permeability, to accurately capture the system’s fluctuating characteristics. However, limited by the lack of superior sensor technology, some significant variables cannot be measured directly. In this context, comprehensively accurate parameters of an estimation strategy offer a novel alternative to characterize the system’s corresponding intrinsic nature. This paper was motivated by this arduous challenge and aims to address the large branching factors with irregular properties. Specifically, the associated mathematical models reflecting the transient operating parameters in terms of electrochemical, heat transfer, and mass transfer are first established. Subsequently, k-means clustering analysis is conducted to deduce the similarity of distribution of the measured variables, which can function as proxies of the separator to distinguish the working status. Furthermore, online reinforcement learning (RL), renowned for its ability to operate without extensive predefined datasets, is employed to conduct dynamic parameter estimation, thereby approximating the robust nonlinear and stochastic behaviors within AEL components. Finally, the experimental results verify that the proposed model achieves significant improvements in estimation errors compared to existing parameter estimation methods (such as EKF and UKF). The enhancements are 76.7%, 54.96%, 51.84%, and 31% in terms of RMSE, NRMSE, PCC, and MPE, respectively. Full article

The application of carbon nanotube (CNT)-reinforced epoxy matrix composites (CRECs) has attracted extensive attention in various industrial sectors due to the significant improvement of material properties imparted by CNTs. The thermal behavior of these nanocomposites is governed by complex heat transfer mechanisms operating at different scales, resulting in a complex relationship between the effective thermal response and the microstructural characteristics of the composite. In order to fundamentally understand the thermal behavior of the CRECs on the nanoscale, in this study, molecular dynamics (MD) simulation methods were used to investigate the thermal conductivity of CRECs, focusing on the effects of key parameters such as the length and volume fraction of CNTs, the degree of cross-linking within the epoxy matrix, and the temperature on the overall thermal properties. First, the thermal behavior of the epoxy matrix was simulated and analyzed. This approach allowed the isolation of the intrinsic thermal response of the epoxy resin as a benchmark for evaluating the enhancement introduced by CNT reinforcement. By systematically varying those key parameters, the study comprehensively evaluates how nanoscale interactions and structural modifications affect the overall thermal conductivity of CRECs, providing valuable insights for optimizing their design for advanced thermal management applications. The simulation results were validated by comparing them with experimental data from literature and analytical predictions. The results show that for the configurations examined, the thermal conductivity of CRECs increases with increasing CNT length and volume fraction, epoxy cross-linking degree, and the system temperature. From a broader perspective, the approach presented here has the potential to be applied to study a wide range of materials and their properties. Full article

Thermal protection systems play a pivotal role in astronautical engineering fields. However, traditional rectangular fin (RF) structures exhibit low thermo-fluid properties. Inspired by the minimal surfaces in nature, this study develops three types of triply periodic minimal surface (TPMS) lattices, namely, sheet primitive (SP), network I-WP (NW), and sheet I-WP (SW) by using mathematical formulae. The TPMS lattices are fabricated by laser powder bed fusion using AlSi10Mg powder. A convective heat transfer simulation model of TPMS lattices is established and validated through experiments. The fluid flow characteristics, heat transfer characteristics, and overall heat transfer performance of the TPMS lattices are comprehensively investigated based on the simulation model. Results show that the relationship between pressure loss and flow velocity of the TPMS lattices satisfies the Darcy–Forchheimer law. Compared to traditional RF structures, the TPMS lattices exhibit a more uniform temperature distribution at the same flow rate, and the highest convective heat transfer coefficient is increased by approximately 96.62%. This is due to the complex internal structures of the TPMS lattices, which enhance the disturbance of the fluid flow and further improve the heat transfer coefficient. The overall thermal transfer index ($\alpha$) of the TPMS lattices is higher than that of traditional RF structures with an order of ${\alpha }_{SP}>{\alpha }_{SW}>{\alpha }_{NW}>{\alpha }_{RF}$, which confirms the potential applications of TPMS lattices in thermal protection systems. Full article

The heat transfer (HT) characteristics of cylindrical biomass particles (CBPs) in fluidized beds (FBs) are important for their drying, direct combustion, and thermochemical transformation. To provide a deeper insight into the complex mechanisms behind the HT behaviors involving CBPs, this study developed a cylindrical particle HT model within the framework of computational fluid dynamics coupled with the discrete element method (CFD-DEM) in which the CBPs were characterized by the super-ellipsoid model, which has the unique merit of striking a balance between computational accuracy and efficiency. The newly developed heat transfer model considers particle–particle (P-P), particle–wall (P-W), and fluid–particle (F-P). Its accuracy was verified by comparing the numerical results with the experimental infrared thermography measurements in terms of the temperature evolution of the cylindrical particles. The effects of the gas velocity, inlet temperature, and thermal conductivity of particles on the HT behaviors of the CBPs were investigated comprehensively. The results demonstrated the following: (1) Gas velocity can improve the uniformity of bed temperature distribution and shorten the fluctuation process of bed temperature uniformity. (2) A 26.8% increase in inlet temperature leads to a 13.4% increase in the proportion of particles with an orientation in the range of 60–90°. (3) The thermal conductivity of particles has no obvious influence on the bed temperature, convective HT rate, or orientation of particles. Full article