Search Results (3,756)

Diabrotica virgifera virgifera Le Conte, 1868 (Coleoptera: Chrysomelidae), known as the western corn rootworm, is one of the most important alien insect pests affecting maize crops globally. It causes significant economic losses by feeding on the roots, which affects plant stability and nutrient absorption, as well as by attacking essential aerial organs (leaves, silk, pollen). Since its accidental introduction into Europe, the species has expanded its range across maize-growing regions, raising concerns about future distribution under climate change. This study aimed to estimate the risk of pest establishment across Europe over three future time frames (2034, 2054, 2074) based on geographic coordinates, climate data, and maize distribution. Spatial simulations were performed in QGIS using national centroid datasets, risk classification criteria, and temperature anomaly maps derived from Copernicus and ECA&D databases for 1992–2024. The results indicate consistently high risk in southern and southeastern regions, with projected expansion toward central and western areas by 2074. Risk zones showed clear spatial aggregation and directional spread correlated with warming trends and maize availability. The pest’s high reproductive potential, thermal tolerance, and capacity for human-assisted dispersal further support these predictions. The model emphasizes the need for expanded surveillance in at-risk zones and targeted policies in areas where D. v. virgifera has not yet established. Future work should refine spatial predictions using field validation, genetic monitoring, and dispersal modeling. The results contribute to anticipatory pest management planning and can support sustainable maize production across changing agroclimatic zones in Europe. Full article

This study carried out a detailed investigation into the potential application of hydrothermally treated bituminous coal (hydrochar) as an injectant in blast furnace (BF) ironmaking. A tuyere model was constructed through simulation methods, and the influence of hydrochar injection on the thermal conditions within the BF hearth was also thoroughly analyzed. The results show that the gas flow velocity at the lower part of the tuyere of hydrochar injection increases, and the residual carbon mass fraction of the tuyere decreases. As the oxygen-enriched concentration increases, the CO concentration decreases. The CO concentration in the swirl zone after hydrochar injection is the highest, reaching 43.93%. The distributions of CO and CO₂ exhibit opposite tendencies. Following hydrochar injection, a marked rise in temperature is observed. At an oxygen enrichment level of 30%, the tuyere zone temperature associated with hydrochar injection peaks, surpassing 2700 K. The corresponding pulverized coal burnout rate is also the highest. Thus, the injection of hydrochar has a positive impact on the air flow and temperature field, which can effectively maintain the heat balance and is conducive to strengthening BF smelting. Full article

Ceramic matrix composites (CMCs) are promising candidates for high-temperature structural applications. However, their fracture toughness remains low due to strong chemical bonding between fibers and the matrix. To improve toughness, engineered interfaces such as pyrolytic carbon (PyC) and hexagonal boron nitride (h-BN) are commonly introduced. These interfaces promote crack deflection and fiber bridging, leading to improved damage tolerance and pseudo-ductile behavior. To investigate the influence of interface thickness on mechanical performance and to identify optimal thickness ranges, we propose a microscopic phase-field model that accurately resolves interface thickness and material contrast. This model overcomes the limitations of conventional smeared interface approaches, particularly in systems with variable interface thickness and closely packed fibers. We apply the model to simulate the fracture behavior of unidirectional SiC fiber reinforced SiC matrix (SiC_f/SiC_m) composites with PyC and h-BN interfaces of varying thickness. The numerical results show strong agreement with experimental findings from the literature and reveal optimal interface thicknesses that maximize toughening effects. These results demonstrate the model’s predictive capabilities and its potential as a tool for interface design in brittle composite systems. Full article

This study evaluates the thermal comfort and energy performance of Qiang Zhuangfang manor houses in high-altitude regions, using Mao County’s Heihuzhai settlement as a representative case. Field surveys, tabulated data analysis, and computer simulations were conducted to measure wall surface temperature, ambient radiation temperature, air temperature, and relative humidity, comparing Zhuangfang buildings with brick Qiang houses. Results show that Zhuangfang walls have minor surface temperature differences, lower thermal conductivity, and superior insulation—retaining heat in winter, blocking heat in summer, and reducing solar gain. Optimization measures were tested through a model, revealing that lowering the main structure by 0.1 m and adding a surface material layer improved insulation while maintaining load-bearing capacity. The findings confirm that Zhuangfang houses are better suited to the local climate, offering ecological benefits in energy saving and heat preservation. 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

Accurate prediction of crop phenological stages is essential for effective crop management. Such a prediction provides the timing of phenological stages, thus aiding in scheduling management practices, understanding the potential risks of adverse weather at critical phenological stages, and adjusting sowing dates. Temperature is the dominant climatic factor affecting maize (Zea mays L.) development, with photoperiod serving as a secondary influence. This study used maize field data with recorded flowering and maturity dates to evaluate the stability of phenological stage predictions obtained using the calendar days method, thermal functions, and photothermal functions. These methods were used to calculate the number of days, accumulated temperature, and accumulated photothermal units from sowing to flowering and from flowering to maturity. Results showed that thermal functions produced the most stable predictions, with the lowest average coefficient of variation (CV) being 8.37%. The thermal functions were further categorized as empirical linear, empirical nonlinear, and process-based. Within each category, the functions with the lowest average CVs were growing degree days (GDD_8,34; 9.12%), thermal leaf unit (GTI; 7.74%), and agricultural production system simulator (APSIM; 8.26%), respectively. Among them, GTI had the lowest CV, indicating its superior stability in predicting maize phenological stages. These results provide a basis for selecting thermal models in maize phenology research and can support improved decision-making in crop scheduling and management. Full article

A key aspect of climate change’s impact on organisms lies in understanding their ability to adapt to shifting and stressful environmental conditions. Insects, such as parasitoid wasps, are particularly vulnerable due to limited heat tolerance. Adaptive strategies during mass rearing may enhance the efficacy and resilience of commercially reared biocontrol agents. This study assessed the effects of constant and fluctuating temperature regimens across four generations of mass-reared aphid parasitoids, examining their fitness traits and parasitism success under three thermal environments: colder [10 °C], standard [20 °C], and heat stress [28 °C]. Parasitoids reared under fluctuating temperatures [day/night: 25 °C/17 °C] showed increased parasitism, but reduced progeny survival compared to those reared at a constant temperature [20 °C]. Fluctuating regimens encouraged greater parasitism under heat stress, whereas constant regimens yielded intermediate parasitism across thermal environments, reflecting a pattern consistent with the evolution of specialist–generalist trade-offs. These findings underscore the value of developing adaptive temperature-rearing strategies for mass-rearing systems of parasitoids that more accurately simulate field conditions, improving their performance under climate stress. Future research involving diverse temperature regimens should deepen our understanding of trait trade-offs, such as survival and fecundity, and aid in identifying optimal thermal profiles to maximize efficacy in mass-rearing parasitoid wasps and their performance at the field level. Full article

Sessile marine organisms form the foundation of many coastal ecosystems, playing crucial roles in functions like water filtration and habitat provision. Understanding their population dynamics—particularly the interplay of growth, reproduction, and detachment under environmental stress—is essential for both ecological research and effective coastal management. This work presents a comprehensive numerical model for simulating the growth, reproduction, mortality and detachment of sessile organisms using a hybrid dynamic energy budget (DEB)–statistical approach. Our model incorporates bioenergetic processes, environmental stress responses, space competition, and layering dynamics. The simulation framework considers the effects of temperature, salinity, dissolved oxygen, and food availability on organism physiology while tracking growth, reproduction, and mortality and detachment. Model validation was performed using field data collected from sessile invertebrate populations around a floating platform in the estuary of the Sumida River in Tokyo, Japan, from September 2002 to September 2003. Our approach successfully reproduced observed patterns with high accuracy. The model revealed that temperature stress and salinity fluctuations interact synergistically, amplifying mortality and detachment rates beyond what would be predicted by each factor independently. Comparative analyses with reduced models lacking either mortality or detachment components demonstrated the importance of including both processes for the accurate prediction of population dynamics. Our case study provides a robust framework for predicting sessile organism responses to environmental variability and highlights key areas for future research in benthic ecosystem modeling. 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

The fast and accurate calculation of the internal temperature rise in the oil-immersed transformer is the premise to realize the thermal health management and load energy evaluation of the in-service transformer. In view of the influence of nanofluids on the heat transfer process of transformer, a numerical simulation algorithm based on lattice Boltzmann method (LBM) and finite difference method (FDM) is proposed to study the heat and mass transfer process inside nano-modified oil-immersed transformer. Firstly, the D2Q9 lattice model is used to solve the fluid and thermal lattice Boltzmann equations inside the oil-immersed transformer at the mesoscopic scale, and the temperature field and velocity field are obtained by macroscopic transformation. Secondly, the electric field distribution inside the oil-immersed transformer is calculated by FDM. The viscous resistance in LBM analysis and the electric field force in FDM analysis, as well as the gravity and buoyancy of particles, are used to explore the motion characteristics of nanoparticles and metal particles. Finally, compared with the thermal ring method and the finite volume method (FVM), the relative error is less than 5%, which verifies the effectiveness of the numerical model and provides a method for studying the internal electrothermal convection of nano-modified oil-immersed transformers. Full article

Low-temperature oxidation of titanomagnetite in oceanic basalts distorts the primary thermoremanent magnetization (TRM) signal essential for reconstructing Earth’s magnetic field history, though the specific impact of magma intrusion-induced oxidation on paleointensity preservation remains poorly constrained. This investigation simulates such oxidation processes using a novel experimental design involving isothermal annealing (260 $°$C; 50 µT field; durations 12.5–1300 h) of Red Sea rift basalts (P72/4), employing the Thellier-Coe method to quantify how chemical remanent magnetization (CRM) overprinting affects TRM fidelity under controlled field orientations aligned either parallel or perpendicular to the initial TRM. Results demonstrate two-sloped Arai-Nagata diagrams with reliable TRM preservation below 360 $°$C but significant alteration artifacts above this threshold. Crucially, field orientation during oxidation critically influences accuracy: parallel configurations maintain fidelity (±3% deviation at $Z=0.48$), while perpendicular fields introduce systematic biases (38% overestimation at $Z=0.15$; 20% underestimation at $Z>0.48$), which is attributable to magnetostatic interactions in core-shell grain structures. These findings establish that paleointensity reliability in basalt prone to low-temperature oxidation depends fundamentally on the alignment between oxidation-era magnetic fields and primary TRM direction, necessitating stringent sample selection and directional constraints in marine paleomagnetic research to mitigate CRM-TRM interference. Full article

This work presents a novel Gallium Nitride (GaN) high-electron-mobility transistor (HEMT)-based ultraviolet (UV) photodetector architecture that integrates advanced material and structural design strategies to enhance detection performance and stability under room-temperature operation. This study is conducted as a fully numerical simulation using the Silvaco Atlas platform, providing detailed electrothermal and optoelectronic analysis of the proposed device. The device is constructed on a high-thermal-conductivity silicon carbide (SiC) substrate and incorporates an n-GaN buffer, an indium nitride (InN) channel layer for improved electron mobility and two-dimensional electron gas (2DEG) confinement, and a dual-passivation scheme combining silicon nitride (SiN) and hexagonal boron nitride (h-BN). A p-GaN layer is embedded between the passivation interfaces to deplete the 2DEG in dark conditions. In the device architecture, the metal contacts consist of a 2 nm Nickel (Ni) adhesion layer followed by Gold (Au), employed as source and drain electrodes, while a recessed gate embedded within the substrate ensures improved electric field control and effective noise suppression. Numerical simulations demonstrate that the integration of a hexagonal boron nitride (h-BN) interlayer within the dual passivation stack effectively suppresses the gate leakage current from the typical literature values of the order of ${10}^{-8}$ A to approximately ${10}^{-10}$ A, highlighting its critical role in enhancing interfacial insulation. In addition, consistent with previous reports, the use of a SiC substrate offers significantly improved thermal management over sapphire, enabling more stable operation under UV illumination. The device demonstrates strong photoresponse under 360 nm ultraviolet (UV) illumination, a high photo-to-dark current ratio (PDCR) found at approximately ${10}^6$, and tunable performance via structural optimization of p-GaN width between 0.40 μm and 1.60 μm, doping concentration from $5\times {10}^{16}$ ${\mathrm{cm}}^{-3}$ to $5\times {10}^{18}$ ${\mathrm{cm}}^{-3}$, and embedding depth between 0.060 μm and 0.068 μm. The results underscore the proposed structure’s notable effectiveness in passivation quality, suppression of gate leakage, and thermal management, collectively establishing it as a robust and reliable platform for next-generation UV photodetectors operating under harsh environmental conditions. Full article

The growing interest in smart buildings and the integration of IoT-based technologies is driving the development of new tools for monitoring and optimizing indoor environmental quality (IEQ). However, many existing solutions remain expensive, invasive and inflexible. This paper presents the design and validation of a compact, low-cost, and real-time sensor system, conceived for seamless integration into indoor environments. The system measures key parameters—including air temperature, relative humidity, illuminance, air quality, and sound pressure level—and is embeddable in standard office equipment with minimal impact. Leveraging 3D printing and open-source hardware/software, the proposed solution offers high affordability (approx. EUR 33), scalability, and potential for workspace retrofits. To assess the system’s performance and relevance, dynamic simulations were conducted to evaluate metrics such as the Mean Radiant Temperature (MRT) and illuminance in an open office layout. In addition, field tests with a functional prototype enabled model validation through on-site measured data. The results highlighted significant local discrepancies—up to 6.9 °C in MRT and 28 klx in illuminance—compared to average conditions, with direct implications for thermal and visual comfort. These findings demonstrate the system’s capacity to support high-resolution environmental monitoring within IoT-enabled buildings, offering a practical path toward the data-driven optimization of occupant comfort and energy efficiency. Full article

The existing continuous caster layout curves cause plastic deformation of slabs during bending and straightening segments, while no effective deformation occurs in the basic arc segment, which tends to induce defects, such as cracks, and compromise slab quality. High-temperature creep deformation is generally regarded as detrimental to material performance. If the significant and inevitable creep deformation of a slab could be utilized to accomplish bending and straightening deformation during continuous casting, it would turn a potential harm into an advantage, ultimately enhancing both production efficiency and final product quality. Therefore, a new continuous bending and straightening curve based on the high-temperature creep property of a low-alloy steel slab was designed. The new curve cancelled the original basic arc segment and smoothly connected the bending and straightening segments, which not only substantially prolonged the effective bending and straightening deformation time but also extended the creep time. The locations within the slab corresponding to the temperature range of 1100 °C to 1200 °C were obtained from the simulated temperature field results. Comparing the calculated strain rates with the steady-state creep rates revealed that within the temperature range exhibiting favorable hot ductility, the bending and straightening deformation of the slab could be accomplished entirely through creep deformation. Full article

Polyimide (PI) is widely used in aerospace, electronic packaging, and other fields due to its excellent dielectric and thermophysical properties. However, the performance of traditional PI materials under extreme conditions has become increasingly inadequate to meet the growing demands. To address this, this study designed a PI/Nano-Si₃N₄ advanced composite material and, based on molecular dynamics simulations, thoroughly explored the influence of silane coupling agents with different grafting densities on the interfacial microstructure and their correlation with the overall material’s physical properties. The results show that when the grafting density is 10%, the interfacial bonding of the PI/Nano-Si₃N₄ composite is optimized: non-bonded interaction energy increases by 18.4%, the number of hydrogen bonds increases by 32.5%, and the free volume fraction decreases to 18.13%. These changes significantly enhance the overall performance of the material, manifested by an increase of about 30 K in the glass transition temperature and a 49.5% improvement in thermal conductivity compared to pure PI. Furthermore, the system maintains high Young’s modulus and shear modulus in the temperature range of 300–700 K. The study reveals that silane coupling agents can effectively enhance the composite material’s overall performance by optimizing the interfacial structure and controlling the free volume, providing an efficient computational method for the design and performance prediction of advanced high-performance PI composites. Full article