Search Results (426)

During tropical cyclones (TCs), intense exchanges of momentum, heat, and moisture occur across the air–sea interface. The present study was conducted to investigate the role of surface roughness parameterizations under such conditions. To this end, a series of sensitivity experiments was conducted with a focus on Tropical Cyclone Biparjoy, which originated from the Indian Ocean in 2023. The experiments evaluate the impact of different schemes for momentum, thermal, and moisture roughness length on TC track, intensity, significant wave height, and air–sea heat fluxes. The results indicate that the momentum roughness length scheme is critical for accurately forecasting TC track and intensity and for simulating significant wave height; furthermore, Drennan’s parameterization yielded slightly better results in this case, with the smallest track error (72.0 km MAE) among the momentum schemes. Under the premise that Drennan’s parameterization scheme has high accuracy in momentum roughness, sensitivity experiments on thermal and moisture roughness parameterization were conducted. The Drennan–Fairall2014 combination achieved the lowest errors in TC central pressure (4.25 hPa RMSE) and the maximum sustained wind speed (5.31 m/s RMSE). Thermal and moisture roughness mainly affects the efficiency of turbulent heat transfer between the ocean and the atmosphere and thus has a limited impact on the cooling of sea surface temperature, with SST RMSE differences among schemes within 0.3 °C. This effect is mainly confined to the uppermost ocean layer and does not significantly change the thermal structure of the upper layers. Full article

As a prevalent integrated structure-insulation system, sandwich insulation wall panels have emerged as a critical structural configuration for zero- and nearly zero-energy green buildings, owing to their high construction efficiency and superior thermal insulation performance which directly aligns with the core goals of sustainability and sustainable energy utilization in the built environment. However, connectors penetrate the insulation layer and form systematic thermal bridges, which cause substantial heat loss and become a key bottleneck limiting further improvement in the overall thermal performance of wall systems. This study established three-dimensional numerical models of sandwich insulation wall panels with four typical connectors (fiber-reinforced polymers (FRPs), clamp-type stainless steel, plate-type stainless steel, and truss-type stainless steel) using Ansys Fluent 2021R1. The model reliability was verified by calibrated hot-box experiments, with relative errors between simulation and experimental results ranging from 2.1% to 16.1%. Systematic numerical simulations were then performed to investigate the effects of connector type, insulation material, climate zone, inner–outer temperature difference, connector quantity, and wall dimensions on the thermal bridge effect. The results indicated that FRP connectors caused the minimal heat flux increment (only 0.27%), followed by clamp-type stainless steel connectors (9.59%), while plate-type and truss-type stainless steel connectors led to significant increments (27.17% and 27.62%, respectively). The lower the heat transfer coefficient (K-value) of the wall was, the more prominent the connector-induced thermal bridge effect was. Within the typical temperature difference range, the heat flux increment of each connector remained stable, and polyurethane (PU) insulation exhibited a more significant inhibitory effect on thermal bridges than extruded polystyrene (XPS) under the same K-value. Linear fitting formulas for the relationship between wall K-value/temperature difference and the heat flux correction coefficient were derived, with high goodness-of-fit. The maximum impact of connectors on wall thermal performance did not exceed 30%. This study provides theoretical support and design references for the selection of connectors, material optimization, and thermal performance calculation of sandwich insulation wall panels, contributing to the promotion of energy-saving building envelope technologies. Full article

During the extrusion of novel nickel-based powder superalloy bars, the die is subjected to elevated temperatures, high pressures, and severe friction, which readily lead to abrasive wear and thermal-fatigue damage. These failures deteriorate the quality of the extruded products and significantly shorten the service life of the die. Frequent repair and replacement of the tooling ultimately increase the overall manufacturing cost. This study investigates the friction and wear behavior of H13 and 5CrNiMo hot-work tool steels under extreme transient high-temperature conditions by combining finite element simulation with tribological testing. The temperature and stress distributions of the billet and key tooling components during extrusion were analyzed using DEFORM-3D. In addition, pin-on-disk friction and wear tests were conducted at 1000 °C to examine the friction coefficient, wear morphology, and subsurface grain structural evolution under various loading conditions. The results show that the extrusion die and die holder experience the highest loads and most severe wear during the extrusion process. For 5CrNiMo tool steel, the wear mechanism under low loads is dominated by mild abrasive wear and oxidative wear, whereas increasing the load causes a transition toward adhesive wear and severe oxidative wear. In contrast, H13 tool steel exhibits a transition from abrasive wear to severe oxidative wear. In 5CrNiMo steel, friction-induced recrystallization, grain refinement, and softening lead to the formation of a mechanically mixed layer, which, together with a stable third-body layer, markedly reduces and stabilizes the friction coefficient. H13 steel, however, undergoes surface strain localization and spalling, resulting in persistent fluctuations in the friction coefficient. The toughness and adhesion of the oxide film govern the differences in wear mechanisms between the two steels. Owing to its higher Cr, V, and Mo contents, H13 forms a dense but highly brittle oxide scale dominated by Cr and Fe oxides at 1000 °C. This oxide layer readily cracks and delaminates under frictional shear and thermal cycling. The repeated spalling exposes the fresh surface to further oxidation, accompanied by recurrent adhesion–delamination cycles. Consequently, the subsurface undergoes alternating intense shear and transient load variations, leading to localized dislocation accumulation and cracking, which suppresses the progression of continuous recrystallization. Full article

Triply periodic minimal surface (TPMS) structures provide high surface area to volume ratios and tunable conduction pathways, but predicting their thermal behavior across different metallic materials remains challenging because multi-material experimentation is costly and full-scale simulations require extremely fine meshes to resolve the complex geometry. This study develops a physics-informed neural network (PINN) that reconstructs steady-state temperature fields in TPMS Gyroid structures using only two experimentally measured materials, Aluminum and Silver, which were tested under identical heat flux and flow conditions. The model incorporates conductivity ratio physics, Fourier-based thermal scaling, and complete spatial temperature profiles directly into the learning process to maintain physical consistency. Validation using the complete Aluminum and Silver datasets confirms excellent agreement for Aluminum and strong accuracy for Silver despite its larger temperature gradients. Once trained, the PINN can generalize the learned behavior to nine additional metals using only their conductivity ratios, without requiring new experiments or numerical simulations. A detailed heat transfer analysis is also performed for Magnesium, a lightweight material that is increasingly considered for thermal management applications. Since no published TPMS measurements for Magnesium currently exist, the predicted Nusselt numbers obtained from the PINN-generated temperature fields represent the first model-based evaluation of its convective performance. The results demonstrate that the proposed PINN provides an efficient, accurate, and scalable surrogate model for predicting thermal behavior across multiple metallic TPMS structures and supports the design and selection of materials for advanced porous heat technologies. Full article

Accurate prediction of the effective thermal conductivity (ETC) of nuclear fuels is essential for optimizing fuel performance and ensuring reactor safety. However, the experimental determination of ETC is often limited by cost and complexity, while high-fidelity simulations are computationally intensive. This study presents a novel hybrid framework that integrates experimental data, validated mesoscale finite element simulations, and machine-learning (ML) models to efficiently and accurately estimate ETC for advanced uranium-based nuclear fuels. The framework was demonstrated on three fuel systems: UO₂-BeO composites, UO₂-Mo composites, and U-10Zr metallic alloys. Mesoscale simulations incorporating microstructural features and interfacial thermal resistance were validated against experimental data, producing synthetic datasets for training and testing ML algorithms. Among the three regression methods evaluated, namely Bayesian Ridge, Random Forest, and Multi-Polynomial Regression, the latter showed the highest accuracy, with prediction errors below 10% across all fuel types. The selected multi-polynomial model was subsequently used to predict ETC over extended temperature and composition ranges, offering high computational efficiency and analytical convenience. The results closely matched those from the validated simulations, confirming the robustness of the model. This integrated approach not only reduces reliance on costly experiments and long simulation times but also provides an analytical form suitable for embedding in engineering-scale fuel performance codes. The framework represents a scalable and generalizable tool for thermal property prediction in nuclear materials. Full article

As international lunar exploration shifts from mainly understanding the Moon to equally prioritizing its utilization, the requirement for highly similar lunar regolith simulants has grown. Current simulants, produced mainly by mechanical crushing and sieving, reproduce mechanical properties but lack space-weathered microstructures. However, this absence results in significant discrepancies in critical properties such as thermal conductivity and adsorption–desorption behavior, which undermine the reliability of ground-based resource utilization tests. To address this issue, this paper proposes a new preparation method for lunar regolith simulants, which simulates the micrometeorite impact process by utilizing the instantaneous high temperature, pressure, and high-velocity impact generated from the detonation of high-energy explosives in a sealed container. Preliminary experiments confirm that the method produces agglutinates, glass spherules, and porous structures resembling those in lunar regolith. The thermal conductivity of the modified simulant decreases significantly, approaching that of lunar regolith. Further refinement of the process, supported by quantitative 3D characterization, will enable the production of even more similar simulants, providing a reliable material foundation for lunar exploration, in situ resource utilization, and lunar construction activities. Full article

To solve slot temperature accumulation in high thrust density permanent magnet linear synchronous motors (PMLSMs), this paper proposes an additive manufacturing (AM)-based variable cross-section winding design for coating-cooled tapered PMLSMs. Integrating the magnetic circuit features of tapered PMLSMs and AM windings’ technical merits, the motor’s operating mechanism and electromagnetic distribution are analyzed. With the coating cooling structure as the thermal management foundation, simulation reveals the motor’s temperature distribution under water cooling, defining core slot thermal management requirements. A novel cross-section winding design is then presented: first, a lumped-parameter thermal network model quantifies the coupling between the winding cross-sectional area and slot heat source distribution; second, a greedy algorithm optimizes the winding cross-section globally to reduce the slot hot-spot temperature and suppress temperature rise. Validated by a fabricated tapered PMLSM stator prototype and static temperature-rise experiments, the results confirm that winding cross-section reconstruction optimizes heat distribution effectively, offering a new approach for temperature rise suppression in high thrust density PMLSMs. Full article

This study investigates the early-age performance of large-area C30 concrete slabs under different curing regimes using a multi-scale approach combining laboratory experiments, field monitoring, and numerical simulation. The experimental results indicated that standard curing (SC7) maximized the mechanical properties. In contrast, the thermal insulation and moisture retention curing (TC) regime significantly reduced temperature gradients and stress mutation amplitudes by 42% compared to wet curing (WC) by leveraging the synergistic effect of aluminum foil and insulating cotton. This makes TC a preferred solution in situations where engineering constraints apply. Field monitoring demonstrated that WC is suitable for humidity-sensitive scenarios with low-temperature control requirements, while TC is more suitable for large-area concrete or low-temperature environments, balancing early strength development and long-term durability. This multi-field coupled model exhibits significant deviations during the early stage (0–7 days) due to complex boundary interactions, but achieves high quantitative accuracy in the long-term steady state (after 14 days), with a maximum error below 8%. The analysis revealed that the key driving factors for stress evolution are early hydration heat–humidity coupling and mid-term boundary transient switching. The study provides a novel, multi-scale validated curing optimization path for crack control in large-area concrete slabs. Full article

In regions with hot summers and cold winters, elderly care buildings face the dual challenges of high energy consumption and stringent thermal comfort requirements. Using Nanchang as a case study, this research presents an optimization approach that integrates phase change material (PCM) walls with the window-to-wall ratio (WWR). PCM wall performance was tested experimentally, and EnergyPlus simulations were conducted to assess building energy use for WWR values ranging from 0.25 to 0.50, with and without PCM. The phase change material (PCM) used in this study is paraffin (an organic phase change material), which has a melting point of 26 °C and can store and release heat during temperature fluctuations. The experimental results show that PCM walls effectively reduce heat transfer, lowering the surface temperatures of external, central, and internal walls by 3.9 °C, 3.8 °C, and 3.7 °C, respectively, compared to walls without PCM. The simulation results predict that the PCM wall can reduce air conditioning energy consumption by 8.2% in summer and total annual energy consumption by 14.2%. The impact of WWR is orientation-dependent: east and west façades experience significant cooling penalties as WWR increases and should be maintained at or below 0.30; the south façade achieves optimal performance at a WWR of 0.40, with the lowest total energy load (111.2 kW·h·m-2); and the north façade performs best at the lower bound (WWR = 0.25). Under the combined strategy (south wall with PCM and WWR = 0.40), annual total energy consumption is reduced by 9.8% compared to the baseline (no PCM), with indoor temperatures maintained between 18 and 26 °C. This range is selected based on international thermal comfort standards (e.g., ASHRAE) and comfort research specifically targeting the elderly population, ensuring comfort for elderly occupants. These findings offer valuable guidance for energy-efficient design in similar climates and demonstrate that the synergy between PCM and WWR can reduce energy consumption while maintaining thermal comfort. Full article

Lost circulation in oil-based drilling fluids (OBDFs) remains difficult to mitigate because particulate lost circulation materials depend on bridging/packing and gel systems for aqueous media often lack OBDF compatibility and controllable in situ sealing. A dual-precursor oil–water biphasic metal–organic supramolecular gel enables rapid in situ sealing in OBDF loss zones. The optimized formulation uses an oil-phase to aqueous gelling-solution volume ratio of 10:3, with 2.0 wt% Span 85, 12.5 wt% TXP-4, and 5.0 wt% NaAlO₂. Apparent-viscosity measurements and ATR–FTIR analysis were used to evaluate the effects of temperature, time, pH, and shear on MOSG gelation. Furthermore, the structural characteristics and performances of MOSGs were systematically investigated by combining microstructural characterization, thermogravimetric analysis, rheological tests, simulated fracture-plugging experiments, and anti-shear evaluations. The results indicate that elevated temperatures (30–70 °C) and mildly alkaline conditions in the aqueous gelling solution (pH ≈ 8.10–8.30) promote P–O–Al coordination and strengthen hydrogen bonding, thereby facilitating the formation of a three-dimensional network. In contrast, strong shear disrupts the nascent network and delays gelation. The optimized MOSGs rapidly exhibit pronounced viscoelasticity and thermal resistance (~193 °C); under high shear (380 rpm), the viscosity retention exceeds 60% and the viscosity recovery exceeds 70%. In plugging tests, MOSG forms a dense sealing layer, achieving a pressure-bearing gradient of 2.27 MPa/m in simulated permeable formations and markedly improving the fracture pressure-bearing capacity in simulated fractured formations. Full article

This work presents a combined numerical and experimental investigation into the laser machining of aluminum alloy Al 1050 H14 using a high-power Continuous Wave (CW) fiber laser. Advanced three-dimensional, coupled thermal–structural Finite Element Method (FEM) simulations are developed to model key laser–material interaction processes, including laser-induced plastic deformation, laser etching, and engraving. Cases for both static single-shot and dynamic linear scanning laser beams are investigated. The developed numerical models incorporate a Gaussian heat source and the Johnson–Cook constitutive model to capture elastoplastic, damage, and thermal effects. The simulation results, which provide detailed insights into temperature gradients, displacement fields, and stress–strain evolution, are rigorously validated against experimental data. The experiments are conducted on an integrated setup comprising a 2 kW TRUMPF CW fiber laser hosted on a 3-axis CNC milling machine, with diagnostics including thermal imaging, thermocouples, white-light interferometry, and strain gauges. The strong agreement between simulations and measurements confirms the predictive capability of the developed FEM framework. Overall, this research establishes a reliable computational approach for optimizing laser parameters, such as power, dwell time, and scanning speed, to achieve precise control in metal surface treatment and modification applications. Full article

Thermally induced deformation is a major source of dimensional error in end-milling, especially under high-speed or high-load conditions. Direct measurement of workpiece deformation during machining is impractical, while temperature signals can be obtained with good stability using embedded thermocouples. This study proposes an indirect method for predicting milling-induced thermal deformation based on temperature measurements. A three-dimensional thermo-mechanical finite element model is established to simulate the transient temperature field and corresponding deformation of the workpiece during milling. The numerical model is validated using cutting experiments performed under the same boundary conditions and machining parameters. Based on the validated results, the relationship between deformation at critical machining locations and temperature responses at candidate monitoring points is analyzed. To improve applicability to complex workpieces, a statistical prediction model is developed. Temperature monitoring points are optimized, and significant temperature–deformation correlations are identified using multiple linear regression combined with information-criterion-based model selection. The final model is constructed using simulation-derived datasets and provides stable deformation prediction over the entire milling process. Full article

Urban morphology plays a decisive role in regulating microclimate and outdoor thermal comfort in arid cities, where extreme heat and intense solar radiation amplify thermal stress. This study examines the influence of four contrasting urban fabrics in Béchar (Algerian Sahara): the vernacular Ksar, the regular-grid colonial fabric, a modern large-scale residential estate, and low-density detached housing, on local microclimatic conditions. An integrated methodological framework is adopted, combining qualitative morphological analysis, quantitative indicators including density, porosity, height-to-width ratio, and sky view factor, in situ microclimatic measurements, and high-resolution ENVI-met simulations performed for the hottest summer day. Results show that compact urban forms, characterized by low sky view factor values, markedly reduce radiative exposure and improve thermal performance. The vernacular Ksar, exhibiting the lowest SVF, records the lowest mean radiant temperature (approximately 45 °C) and the most favorable average comfort conditions (PMV = 3.77; UTCI = 38.37 °C), representing a reduction of about 3 °C, while its high-thermal-inertia earthen materials ensure effective nocturnal thermal recovery (PMV ≈ 1.06; UTCI = 27.8 °C at 06:00). In contrast, more open modern fabrics, including the colonial grid, large-scale estates, and low-density housing, experience higher thermal stress, reflecting vulnerability to solar exposure and limited thermal inertia. Validation against field measurements confirms model reliability. These findings highlight the continued relevance of vernacular bioclimatic principles for sustainable urban design in arid climates. Full article

Shape Memory Alloy (SMA) actuators offer strong potential for compact, lightweight, silent, and compliant robotic grippers; however, their practical deployment is limited by the challenge of controlling nonlinear and hysteretic thermal dynamics. This paper presents a complete Sim-to-Real control framework for precise temperature regulation of a tendon-driven SMA gripper using Deep Reinforcement Learning (DRL). A novel 12-action discrete control space is introduced, comprising 11 heating levels (0–100% PWM) and one active cooling action, enabling effective management of thermal inertia and environmental disturbances. The DRL agent is trained entirely in a calibrated thermo-mechanical simulation and deployed directly on physical hardware without real-world fine-tuning. Experimental results demonstrate accurate temperature tracking over a wide operating range (35–70 °C), achieving a mean steady-state error of approximately 0.26 °C below 50 °C and 0.41 °C at higher temperatures. Non-contact thermal imaging further confirms spatial temperature uniformity and the reliability of thermistor-based feedback. Finally, grasping experiments validate the practical effectiveness of the proposed controller, enabling reliable manipulation of delicate objects without crushing or slippage. These results demonstrate that the proposed DRL-based Sim-to-Real framework provides a robust and practical solution for high-precision SMA temperature control in soft robotic systems. Full article

Freshwater scarcity is a critical global challenge, particularly in arid and semi-arid regions like southern Iraq. This study evaluates the thermal and distillate performance of a conventional single-slope solar still under extreme summer conditions in Basrah, Iraq. The objective is to analyze and validate a coupled theoretical–experimental model for predicting temperature fields and freshwater productivity. The model incorporates transient energy and mass balance equations with temperature- and salinity-dependent thermophysical properties. Experiments were conducted using brackish water from the Shatt al-Arab River (salinity: 5.2 g/kg), and measured temperatures and productivity were compared against simulations over a 24-h period. Strong agreement was achieved between experimental and theoretical results, with $R^2>0.90$ for temperature predictions and $R^2=0.985$ for hourly productivity. Maximum hourly yield reached $0.46\mathrm{L}/{\mathrm{m}}^2$, with a total daily productivity of $3.5\mathrm{L}/{\mathrm{m}}^2$, The daily thermal efficiency was found to be 26.90% experimentally and 28.20% theoretically. A positive linear relation between the thermal gradient $(T_{\mathrm{w}}-T_{\mathrm{g}})$ and hourly productivity was also established. The findings confirm the reliability of the developed model and highlight the potential of solar distillation as a sustainable freshwater source for high-temperature regions. Full article