Search Results (996)

Rare-earth transition metal-based double perovskite ceramics E₂TMO₆ (where E = rare-earth metals, T = transition metals, and M = metal) have received impressive attention lately for cryogenic applications as a result of their intrinsic physical features such as multiferroicity, dielectric features, and adjustable magnetic transition temperature. However, determination and enhancement of magnetic transition temperature of E₂TMO₆ ceramic are subject to experimental procedures and processes with a significant degree of difficulties and cumbersomeness. This work proposes an extreme learning machine (ELM)-based intelligent method of determining magnetic transition temperature of E₂TMO₆ ceramics with activation function sigmoid (SM) and sine (SE) at varying magnetic field. The outcomes of the SE-ELM and SM-ELM models were compared with genetically optimized support vector regression (GEN-SVR) predictive models using RMSE, CC, and MAE metrics. Using the testing samples of E₂TMO₆ ceramics, SE-ELM predictive model outperforms GEN-SVR with a superiority of 6.3% (using RMSE metric) and 15.7% (using MAE metric). The SE-ELM predictive model further outperforms the SM-ELM model, with an improvement of 5.3%, using CC computed with training ceramic samples. The simplicity of the employed descriptors, coupled with the outstanding performance of the developed predictive models, would potentially strengthen E₂TMO₆ ceramics exploration for low-temperature cryogenic applications and circumvent energy challenges in different sectors. Full article

Bi₂Sr₂CaCu₂O_8+x (Bi2212) high-temperature superconductor exhibits broad application prospects in strong magnetic fields, superconducting magnets, and power transmission due to its exceptional electrical properties. However, during practical applications, Bi2212 superconducting round wires are prone to mechanical loading effects, leading to crack propagation and degradation of superconducting performance, which severely compromises their reliability and service life. To elucidate the damage mechanisms under mechanical loading and their impact on critical current, this study establishes a two-dimensional model with existing cracks based on phase field fracture theory, simulating crack propagation behaviors under varying conditions. The results demonstrate that crack nucleation and propagation paths are predominantly governed by stress concentration zones. The transition zone width of cracks is controlled by the phase field length scale parameter. By incorporating electric fields into the phase field model, coupled mechanical-electrical simulations reveal that post-crack penetration causes significant current shunting, resulting in a marked decline in current density. The research quantitatively explains the mechanism of critical current degradation in Bi2212 round wires under tensile strain from a mechanical perspective. Full article

As a clean and renewable energy source with huge reserves, hot dry rock geothermal resources have received wide attention. The geothermal field plays a crucial role in studying the heat source mechanism of hot dry rock, defining target areas, and evaluating resources. In this study, the three-dimensional structural inversion of the Gonghe Basin is carried out using magnetotelluric sounding, and the Curie isothermal surface is obtained by analyzing regional aeromagnetic data. By coupling low-resistance and high-conductivity zones with temperature distribution and integrating the Curie isothermal surface with high-temperature anomalies of some melts, we constructed an initial temperature field model based on comprehensive geophysical data. The temperature field model of the Gonghe Basin is established by using the adaptive finite-element temperature conduction control equation and the constraints of the temperature data from geothermal wells. The temperature field model provides a basis for the future exploration of hot dry rock resources in the Gonghe area. Full article

Effective thermal management of molds is a governing factor of the quality and stability of the injection molding process. This study introduces and validates an integrated cooling layer within a thin-walled insert mold designed to enhance thermal control and cavity filling performance. A coupled heat transfer simulation model was developed and subsequently calibrated against experimental temperature measurements. To isolate the mold’s intrinsic thermal response, temperatures were measured during distinct heating and cooling cycles, free from the perturbations of polymer melt flow. The validated mold was then installed on a Haitian MA1200 III injection molding machine to conduct molding trials under various injection pressures. A strong correlation was found between the simulation and experimental results, particularly as pressure increased, which significantly improved cavity filling and reduced the deviation between the two methods. The integrated cooling layer was shown to enhance heat dissipation, minimize thermal gradients, and promote a more uniform thermal field. This, in turn, improved filling stability, especially at moderate injection pressures. These findings provide robust quantitative data for simulation model calibration and mold design optimization, highlighting the potential of advanced cooling strategies to significantly enhance injection molding performance. Full article

Cracking in asphalt layers of rigid–flexible composite pavements under coupled ambient temperature fields and traffic loading represents a critical failure mode. Traditional models based on uniform temperature assumptions inadequately capture the crack propagation mechanisms. This study developed a thermo-mechanical coupling model that incorporates realistic temperature-modulus gradients to analyze the compressive-shear behavior and simulate crack propagation using the extended finite element method (XFEM) coupled with a modified Paris’ law. Key findings reveal that the asphalt layer exhibits a predominant compressive-shear stress state; increasing the base modulus from 10,000 MPa to 30,000 MPa reduces the maximum shear stress by 22.8% at the tire centerline and 8.6% at the edge; thermal stress predominantly drives crack initiation, whereas vehicle loading governs the propagation path; field validation via cored samples confirms inclined top-down cracking under thermo-mechanical coupling; and the fracture energy release rate (G_f) reaches a minimum of 155 J·m⁻² at 14:00, corresponding to a maximum fatigue life of 32,625 cycles, and peaks at 350 J·m⁻² at 01:00, resulting in a reduced life of 29,933 cycles—reflecting a 9.0% temperature-induced fatigue life variation. The proposed model, which integrates non-uniform temperature gradients, offers enhanced accuracy in capturing complex boundary conditions and stress states, providing a more reliable tool for durability design and assessment of composite pavements. Full article

This paper presents a novel model for the year-round simulation of evapotranspiration (ET) and substrate temperature on two fundamentally different extensive green roof types: a conventional drainage-based “Economy Roof” and a retention-optimized “Retention Roof” featuring capillary water redistribution. The main scope is to bridge the gap in urban climate adaptation by providing a modeling tool that captures both hydrological and thermal functions of green roofs throughout all seasons, notably including periods with dormancy and low vegetation activity. A key novelty is the explicit and empirically validated integration of core physical processes—water storage layer coupling, explicit rainfall interception, and vegetation cover dynamics—with the latter strongly controlled by plant area index (PAI). The PAI, here quantified as the plant surface area per unit ground area using digital image analysis, directly determines interception capacity and vegetative transpiration rates within the model. This process-based representation enables a more realistic simulation of seasonal fluctuations and physiological plant responses, a feature often neglected in previous green roof models. The model, which can be fully executed without high computational power, was validated against comprehensive field measurements from a temperate climate, showing high predictive accuracy (R² = 0.87 and percentage bias = −1% for ET on the Retention Roof; R² = 0.91 and percentage bias = −8% for substrate temperature on the Economy Roof). Notably, the layer-specific coupling of vegetation, substrate, and water storage advances ecological realism compared to prior approaches. The results illustrate the model’s practical applicability for urban planners and researchers, offering a user-friendly and transparent tool for integrated assessments of green infrastructure within the context of climate-resilient city design. Full article

Deep coalbed methane (CBM) resources possess significant potential. However, their development is challenged by geological characteristics such as high in situ stress and low permeability. Furthermore, existing production strategies often prove inadequate. In order to achieve long-term stable production of deep coalbed methane reservoirs and increase their final recoverable reserves, it is urgent to construct a scientific and reasonable drainage system. This study focuses on the deep CBM reservoir in the Daning-Jixian Block of the Ordos Basin. First, a thermal–hydraulic–mechanical (THM) multi-physics coupling mathematical model was constructed and validated against historical well production data. Then, the model was used to forecast production. Finally, key control measures for enhancing well productivity were identified through production strategy adjustment. The results indicate that controlling the bottom-hole flowing pressure drop rate at 1.5 times the current pressure drop rate accelerates the early-stage pressure drop, enabling gas wells to reach the peak gas production earlier. The optimized pressure drop rates for each stage are as follows: 0.15 MPa/d during the dewatering stage, 0.057 MPa/d during the gas production rise stage, 0.035 MPa/d during the stable production stage, and 0.01 MPa/d during the production decline stage. This strategy increases peak daily gas production by 15.90% and cumulative production by 3.68%. It also avoids excessive pressure drop, which can cause premature production decline during the stable phase. Consequently, the approach maximizes production over the entire life cycle of the well. Mechanistically, the 1.5× flowing pressure drop offers multiple advantages. Firstly, it significantly shortens the dewatering and production ramp-up periods. This acceleration promotes efficient gas desorption, increasing the desorbed gas volume by 1.9%, and enhances diffusion, yielding a 39.2% higher peak diffusion rate, all while preserving reservoir properties. Additionally, this strategy synergistically optimizes the water saturation and temperature fields, which mitigates the water-blocking effect. Furthermore, by enhancing coal matrix shrinkage, it rebounds permeability to 88.9%, thus avoiding stress-induced damage from aggressive extraction. Full article

In deep-sea oil and gas development scenarios, deep-sea dual-channel connectors often face the risk of seal failure due to internal and external temperature difference loads. To address this issue, this paper systematically establishes equivalent heat transfer models for the key parts of the connector based on the third-type boundary condition. On this basis, the quantitative correlation between the equivalent thermal conductivity, composite heat transfer coefficient and temperature of each part is explored. Using the finite element numerical simulation method, the transient temperature field of the connector under three working conditions (heating, cooling and temperature shock) is simulated and analyzed, revealing the temperature distribution characteristics and temperature change trends of the maximum temperature difference of each key component of the connector; combined with thermal–structural coupling simulation, the temperature field is converted into static load, to determine the behavior of the contact stress on the sealing surface under different temperature–pressure coupling working conditions; in addition, by placing the test prototype in a high-low temperature cycle chamber, the seal performance tests under pressurized and non-pressurized working conditions are carried out to verify the reliable sealing performance of the connector under variable temperature conditions. The results of this paper provide comprehensive theoretical support and an experimental basis for the thermodynamic optimization design of deep-sea connectors and the improvement of the reliability of the sealing system. Full article

The aviation wet clutch, as an indispensable component in helicopters, is particularly vulnerable to performance deterioration due to temperature rises, especially in high-power-density and high-torque conditions. Consequently, a comprehensive thermal-fluid-dynamic model, coupled with a dynamic model considering the spline friction and split spring and a thermal model considering the heat transfer parameters in friction pair gaps, was proposed in this work. The effects of operating parameters on the transient thermal behaviors of friction discs were investigated. A rise in rotation speed from 2000 rpm to 2400 rpm facilitates a 10.1% increase in the maximum temperature of the friction discs. An increase in control oil pressure from 1.5 MPa to 1.9 MPa rises the maximum temperature of the friction disc by 19.4%. Moreover, increased lubrication oil flow not only depresses the maximum temperature of the friction disc by 14.5% but also significantly narrows the temperature gradient by 16.7% and improves the temperature field uniformity. Therefore, reasonably increasing lubricant oil flow and decreasing control oil pressure can effectively reduce temperature rises and improve the temperature field uniformity. These results contribute to designing and developing optimal control strategies to enhance the comprehensive performance of helicopter transmission. Full article

Antarctic research stations require reliable low-carbon power under extreme conditions. This study compiles a synchronized PV-meteorological time-series data set on Horseshoe Island (Antarctica) at 30 s, 1 min, and 5 min resolutions and compares four PV module types (monocrystalline, polycrystalline, flexible mono, and semitransparent) under controlled field operation. Model development adopts an interpretable, multi-objective framework: a modified SPEA-2 searches rule sets on the Pareto front that jointly optimize precision and recall, yielding transparent, physically plausible decision rules for operational use. For context, benchmark machine-learning models (e.g., kNN, SVM) are evaluated on the same splits. Performance is reported with precision, recall, and complementary metrics (F1, balanced accuracy, and MCC), emphasizing class-wise behavior and robustness. Results show that the proposed rule-based approach attains competitive predictive performance while retaining interpretability and stability across panel types and sampling intervals. Contributions are threefold: (i) a high-resolution field data set coupling PV output with solar radiation, temperature, wind, and humidity in polar conditions; (ii) a Pareto-front, explainable rule-extraction methodology tailored to small-power PV; and (iii) a comparative assessment against standard ML baselines using multiple, class-aware metrics. The resulting XAI models achieved 92.3% precision and 89.7% recall. The findings inform the design and operation of PV systems for harsh, high-latitude environments. Full article

Inefficient drying of alfalfa round bales causes significant nutrient loss (up to 50%) and quality degradation due primarily to uneven drying in existing processing methods. To address this challenge requiring dedicated equipment and optimized processes, this study developed a specialized hot-air drying test bench (CGT-1). A coupled heat and mass transfer model was established, and 3D dynamic simulations of temperature, humidity, and wind speed distributions within bales were performed using COMSOL multiphysics to evaluate drying inhomogeneity. Single-factor experiments and multi-factor response surface methodology (RSM) based on Box–Behnken design were employed to investigate the effects of hot air temperature (50–65 °C), wind speed (2–5 m/s), and air duct opening diameter (400–600 mm) on moisture content, drying rate, and energy consumption. Results demonstrated that larger duct diameters (600 mm) and higher wind speeds (5 m/s) significantly enhanced field uniformity. RSM optimization identified optimal parameters: temperature at 65 °C, wind speed of 5 m/s, and duct diameter of 600 mm, achieving a drying time of 119.2 min and a drying rate of 0.62 kg/(kg·min). Validation experiments confirmed the model’s accuracy. These findings provide a solid theoretical foundation and technical support for designing and optimizing alfalfa round-bale drying equipment. Future work should explore segmented drying strategies to enhance energy efficiency. Full article

Oil content is a critical component of yield production in Mediterranean olive orchards, but it has received limited attention in modeling olive cultivation under extreme weather conditions. To address this gap, statistical and regression models based on multiple oil content measurements from field trials conducted with representative olive cultivars in the Guadalquivir basin (southern Iberian Peninsula), together with the latest future climate projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for the Iberian Peninsula, were integrated to improve the modeling of its behavior under future climate conditions. Temperature was the most influential factor affecting the olive oil accumulation pattern. Summer temperature was negatively correlated with the onset of oil accumulation, the accumulation rate, and the maximum oil content (MOC), while it was positively correlated with the date at which MOC was reached. When these relationships were combined with CMIP6 climate projections, inland southern Spain emerge as one of the most affected areas in the Iberian Peninsula. In the near future period (2040–2069), projected climate warning is expected to result in an earlier onset of oil accumulation, delays of up to 33 days in reaching MOC, and reductions in MOC of up to 17.5 percentage points, corresponding to an average olive oil yield loss of up to 30.3%, considering only the olive oil yield loss associated with the reduction in MOC. These changes vary in intensity depending on the location, cultivar, climate period and the greenhouse gas emission scenario considered. This study confirms the critical importance of temperature in olive oil production, highlights the need to incorporate functions that account for the effects of rising temperature on MOC, and emphasizes the identification of adaptation measures to cope with increasing temperatures and more frequent heat waves. Full article

To address the challenges of accurately predicting and controlling the annular equivalent circulating density (ECD) in ultra-deepwater gas hydrate-bearing formations of the Qiongdongnan Basin, where joint production of hydrates and shallow gas through dual horizontal wells faces a narrow safe pressure window and hydrate decomposition effects, this study develops an ECD prediction model that incorporates riser drilling operations. The model couples four sub-models, including the static equivalent density of drilling fluid, annular pressure loss, wellbore temperature–pressure field, and hydrate decomposition rate, and is solved iteratively using MatlabR2024a. The results show that hydrate cuttings begin to decompose in the upper section of the riser (at a depth of approximately 600 m), causing a reduction of about 2 °C in wellhead temperature, a decrease of 0.15 MPa in bottomhole pressure, and an 8 kg/m³ reduction in ECD at the toe of the horizontal section. Furthermore, sensitivity analysis indicates that increasing the rate of penetration (ROP), drilling fluid density, and flow rate significantly elevates annular ECD. When ROP exceeds 28 m/h, the initial drilling fluid density is greater than 1064 kg/m³, or the drilling fluid flow rate is higher than 21 L/s, the risk of formation loss becomes considerable. The model was validated against field data from China’s first hydrate trial production, achieving a prediction accuracy of 93%. This study provides theoretical support and engineering guidance for safe drilling and hydraulic parameter optimization in ultra-deepwater hydrate-bearing formations. Full article

This review provides a comprehensive synthesis of the coupled effect of temperature and solar radiation on photovoltaic (PV) module performance and lifespan. Although numerous investigations have examined these stressors in themselves, this research addresses their interrelationship and evaluates the way climatic conditions affect short-term performance fluctuation and long-term degradation mechanisms. The assessment consolidates outcomes from model strategies, laboratory tests, and field monitoring studies. Through the presentation of these findings in a narrative form, the paper identifies recurring difficulties in terms of the absence of shared assessment metrics and the low level of standardisation of long-term test regimes. Second, it underlines the importance of predictive modelling and live monitoring as important management tools for coupled stressors. Finally, the review points out research gaps and underscores future research avenues, including ongoing work towards the development of a coupling index, a composite measure being piloted in individual studies, and advancements in materials technology, predictive methodology, and durability testing. Full article

As a key component for maintaining the efficient and stable operation of flexible DC transmission systems, the arm reactor often suffers from uneven loss distribution and localized overheating in its windings due to the superimposed AC and DC currents, which adversely affects its operational lifespan. Furthermore, arm reactors are frequently deployed in offshore environments for long-distance, high-capacity power transmission, imposing additional requirements on energy utilization efficiency and seismic resistance. To address these challenges, this study proposes an optimization design method for arm reactors based on a triple-constraint mechanism of “equal resistive voltage–equal loss density–equal encapsulation temperature rise,” aiming to achieve “low loss–low temperature rise–low weight.” First, an equivalent electromagnetic model of the arm reactor under combined AC and DC operating conditions is established to analytically calculate the self- and mutual-inductance-distribution characteristics between winding layers and the loss distribution across windings. The calculated losses are then applied as heat sources in a fluid–thermal coupling method to compute the temperature field of the arm reactor. Next, leveraging a Kriging surrogate model to capture the relationship between the winding temperature rise in the bridge-arm reactor and the loss density, encapsulation width, encapsulation height, and air duct width, the revised analytical expression reduces the temperature rise error from 43.74% to 11.47% compared with the traditional empirical formula. Finally, the triple-constraint mechanism of “equal resistive voltage–equal loss density–equal encapsulation temperature rise” is proposed to balance interlayer current distribution, suppress total loss generation, and limit localized hotspot formation. A prototype constructed based on the optimized design demonstrates a 44.51% reduction in total loss, a 39.66% decrease in hotspot temperature rise, and a 24.83% reduction in mass while maintaining rated inductance, validating the effectiveness of the proposed design algorithm. Full article