Search Results (203)

The heat island effect and air stagnation issues caused by high-density built-up areas are becoming increasingly severe. Optimising urban ventilation structures and establishing ventilation corridors have become key approaches to improving the urban thermal environment and enhancing liveability. However, traditional methods for constructing ventilation corridors often rely on empirical weighting or linear models, which struggle to accurately reveal the resistance coefficients of resistance indicators and fail to reflect the threshold at which indicators transition between positive and negative impacts. Consequently, this study employs Shanghai, China, as a case study, integrating machine learning models with the minimum cost path (MCR) model. Key variables were screened through multiple linear regression and variance inflation factor (VIF) analysis. Subsequently, machine learning models were compared to select the optimal model, with parameter optimisation conducted using Optuna, followed by computational implementation. The results indicate that built environment factors (such as building height, shape complexity, and road density) exert a significantly greater influence on ventilation potential than natural green space factors. By introducing the SHAP method, the positive and negative effects of each indicator on the ventilation environment and their threshold relationships were revealed. Negative indicators were converted into ventilation resistance factors to construct a resistance surface. Building upon this, cold and heat sources were identified using LST, NPP, and population density data. The MCR model was then employed to calculate the minimum resistance paths from cold to heat sources, forming an urban ventilation corridor network. The results indicate that primary corridors align with prevailing wind directions, following urban rivers and low-density green spaces. This study reveals the nonlinear effects of building and green space elements on ventilation systems, proposing machine learning-based optimisation strategies for ventilation corridors. It provides quantitative decision support for mitigating the urban heat island effect and enhancing city livability. Full article

Single-walled carbon nanotube (SWCNT) films are promising materials for thermoelectric power generation; however, the dependence of their transport properties on their thickness remains insufficiently understood. This study examined the relationship between the transport properties and the internal structure of SWCNT films with thicknesses ranging from 28 to 193 µm. The structural, mechanical, thermoelectric, and phonon transport properties exhibited a discontinuous dependence on the film thickness. Films up to 72 µm in thickness formed a uniform, dense network that maximized electrical conductivity, whereas films exceeding 97 µm exhibited a coarse and densely layered morphology. This coarse-dense structure increased the contact resistance between SWCNT bundle layers, leading to a reduction in electrical conductivity. Additionally, the increased number of layered interfaces increased phonon scattering, which decreased thermal conductivity and phonon mean free path. These findings provide insights into phonon transport in SWCNT films and have implications for SWCNT-based thermoelectric generator design and optimization. Full article

Natural ventilation is a common cooling strategy in open dairy barns, but its efficiency largely depends on external wind directions and speeds. Misalignment between external airflow and fan jets often led to non-uniform air distribution, reduced local cooling efficiency, and an elevated risk of heat stress in cows. However, few studies have systematically examined the combined effects of wind directions and speeds on airflow and heat dissipation. Most research isolates natural or mechanical ventilation effects, neglecting their interaction. Accurate computational fluid dynamics (CFD) modeling of the coupling between outdoor and indoor airflow is crucial for designing and evaluating mixed ventilation systems in dairy barns. To address this gap, this study systematically analyzed the effects of external wind directions (0°, 45°, 90°, 135°, 180°) and speeds (1, 3, 5, 7, 10 m s⁻¹) on fan jet distribution and convective heat transfer around dairy cows using the open-source CFD platform OpenFOAM. By evaluating body surface airflow and regional convective heat transfer coefficients (CHTCs), this study quantitatively linked barn-scale airflow to animal heat dissipation. Results showed that both wind directions and speeds markedly influenced airflow and heat exchange. Under 0° wind direction, dorsal airflow reached 6.2 m s⁻¹ and CHTCs increased nearly linearly with wind speeds, indicating strong synergy between the fan jet and external wind. Crosswinds (90° wind direction) enhanced abdominal airflow (approximately 5.2 m s⁻¹), whereas oblique and opposing winds (135–180°) caused stagnation and reduced convection. The dorsal-to-abdominal CHTCs ratio ($R_{d/a}$) increased to about 1.6 under axial winds but decreased to 1.1 under cross-flow, reflecting reduced thermal asymmetry. Overall, combining axial and lateral airflow paths improves ventilation uniformity in naturally or mechanically ventilated dairy barns. The findings provide theoretical and technical support for optimizing ventilation design, contributing to energy efficiency, animal welfare, productivity, and the sustainable development of dairy farming under changing climatic conditions. Full article

Promoting the development of aerospace vehicles toward structural–functional integration and intelligent sensing is a key strategy for achieving lightweight, high-reliability, and autonomous operation and maintenance of next-generation aircraft. However, traditional external sensors face significant limitations because of their bulky size, installation challenges, and incompatibility with aerodynamic surfaces. These issues are particularly pronounced on complex, high-curvature substrates, where achieving conformal bonding is difficult, thus restricting their application in critical components. In this study, aerosol jet printing (AJP) was employed to directly fabricate silver nanoparticle-based temperature sensors with real-time monitoring capabilities on the surface of high-curvature stainless steel sleeves, which serve as typical engineering components. This approach enables the in situ manufacturing of high-precision conformal sensors. Through optimized structural design and thermal treatment, the sensors exhibit reliable temperature sensitivity. Microscopic characterization reveals that the printed sensors possess uniform linewidths and well-defined outlines. After gradient sintering at 250 °C, a dense and continuous conductive path is formed, ensuring strong adhesion to the substrate. Temperature-monitoring results indicate that the sensor exhibits a nearly linear resistance response (R² > 0.999) across a broad detection range of 20–200 °C. It also demonstrates high sensitivity, characterized by a temperature coefficient of resistance (TCR) of 2.15 × 10^−3/°C at 20 °C. In repeated thermal cycling tests, the sensor demonstrates excellent repeatability and stability over 100 cycles, with resistance fluctuations kept within 0.5% and negligible hysteresis observed. These findings confirm the feasibility of using AJP technology to fabricate high-performance conformal sensors on complex surfaces, offering a promising strategy for the development of intelligent structural components in next-generation aerospace engineering. Full article

Achieving high reliability remains the critical challenge for pulsed power supplies (PPS), whose core components are susceptible to severe degradation and catastrophic failure due to long-term operation under electrical, thermal and magnetic stresses, particularly those associated with high voltage and high current. This reliability challenge fundamentally limits the widespread deployment of PPSs in defense and industrial applications. This article provides a comprehensive and systematic review of the reliability challenges and recent technological progress concerning PPSs, focusing on three hierarchical levels: component, system integration, and extreme operating environments. The review investigates the underlying failure mechanisms, degradation characteristics, and structural optimization of key components, such as energy storage capacitors and power switches. Furthermore, it elaborates on advanced system-level techniques, including novel thermal management topologies, jitter control methods for multi-module synchronization, and electromagnetic interference (EMI) source suppression and coupling path optimization. The primary conclusion is that achieving long-term, high-frequency operation depends on multi-physics field modeling and robust, integrated design approaches at all three levels. In summary, this review outlines important research directions for future advancements and offers technical guidance to help speed up the development of next-generation PPS systems characterized by high power density, frequent repetition, and outstanding reliability. 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

To improve the accuracy of cable temperature anomaly prediction and ensure the reliability of urban distribution networks, this paper proposes a multi-scale spatiotemporal model called MSST-Net (MSST-Net) for medium-voltage power cables in underground utility tunnels. The model addresses the multi-scale temporal dynamics and spatial correlations inherent in cable thermal behavior. Based on the monthly periodicity of cable temperature data, we preprocessed monitoring data from the KN1 and KN2 sections (medium-voltage power cable segments) of Guangzhou’s underground utility tunnel from 2023 to 2024, using the Isolation Forest algorithm to remove outliers, applying Min-Max normalization to eliminate dimensional differences, and selecting five key features including current load, voltage, and ambient temperature using Spearman’s correlation coefficient. Subsequently, we designed a multi-scale dilated causal convolutional module (DC-CNN) to capture local features, combined with a spatiotemporal dual-path Transformer to model long-range dependencies, and introduced relative position encoding to enhance temporal perception. The Sparrow Search Algorithm (SSA) was employed for global optimization of hyperparameters. Compared with five other mainstream algorithms, MSST-Net demonstrated higher accuracy in cable temperature prediction for power cables in the KN1 and KN2 sections of Guangzhou’s underground utility tunnel, achieving a coefficient of determination (R²), mean absolute error (MAE), and root mean square error (RMSE) of 0.942, 0.442 °C, and 0.596 °C, respectively. Compared to the basic Transformer model, the root mean square error of cable temperature was reduced by 0.425 °C. This model exhibits high accuracy in time series prediction and provides a reference for accurate short- and medium-term temperature forecasting of medium-voltage power cables in urban underground utility tunnels. Full article

This study examines the through-thickness microstructure and crystallographic texture evolution in friction-stir-welded (FSWed) AA5052-H32 and AA6061-T651 aluminum alloys using a tri-flats threaded pin tool. Optical microscopy and electron backscatter diffraction (EBSD) were employed to characterize grain morphology, boundary misorientation, and texture components across the weld thickness. Both alloys exhibited progressive grain refinement and increased high-angle grain boundary fractions from the top to the bottom of the stir zone due to combined thermal and strain gradients. The FSWed AA5052 displayed dominant {111}<110> and Y + γ fiber components at the upper and mid regions, whereas AA6061 showed more randomized textures. At the bottom region, both alloys developed rotated Goss {011}<01-1> and weak A ({112}<110>) and α fiber components. These results clarify how alloy strengthening mechanisms—solid-solution versus precipitation hardening—govern texture evolution under different strain-path and heat input conditions. The findings contribute to optimizing process parameters and material selection for structural-scale FSW aluminum joints in industrial applications such as bridge decks, transportation panels, and marine structures. Full article

In the context of global climate change and intensified water resource constraints, studying the evolution of the urban–agricultural–ecological spatial structure and the water–heat–vegetation responses driven by large-scale irrigation and drainage projects in arid and semi-arid regions is of great significance. Based on multitemporal remote sensing data from 1985 to 2015, this study takes the Inner Mongolia Hetao Plain as the research area, constructs a “multifunctionality–dynamic evolution” dual-principle classification system for urban–agricultural–ecological space, and adopts the technical process of “separate interpretation of each single land type using the maximum likelihood algorithm followed by merging with conflict pixel resolution” to improve the classification accuracy to 90.82%. Through a land use transfer matrix, a standard deviation ellipse model, surface temperature (LST) inversion, and vegetation fractional coverage (VFC) analysis, this study systematically reveals the spatiotemporal differentiation patterns of spatial structure evolution and surface parameter responses throughout the project’s life cycle. The results show the following: (1) The spatial structure follows the path of “short-term intense disturbance–long-term stable optimization”, with agricultural space stability increasing by 4.8%, the ecological core area retention rate exceeding 90%, and urban space expanding with a shift from external encroachment to internal filling, realizing “stable grain yield with unchanged cultivated land area and improved ecological quality with controlled green space loss”. (2) The overall VFC shows a trend of “central area stable increase (annual growth rate 0.8%), eastern area fluctuating recovery (cyclic amplitude ±12%), and western area local improvement (key patches increased by 18%)”. (3) The LST-VFC relationship presents spatiotemporal misalignment, with a 0.8–1.2 °C anomalous cooling in the central region during the construction period (despite a 15% VFC decrease), driven by irrigation water thermal inertia, and a disrupted linear correlation after completion due to crop phenology changes and plastic film mulching. (4) Irrigation and drainage projects optimize water resource allocation, constructing a hub regulation model integrated with the Water–Energy–Food (WEF) Nexus, providing a replicable paradigm for ecological effect assessment of major water conservancy projects in arid regions. Full article

Depending on the factors to which the soils are exposed, many properties and engineering parameters may change. In particular, the temperature parameter affects the strength of the soils, the degree of compressibility, permeability, void ratio, Atterberg limits, and many other parameters. In areas where high temperatures occur, such as heat piles and nuclear waste storage areas, alternative soil mixtures are needed that can stabilize or better optimize the behavior of the soils. For this purpose, additives with high heat transfer capacity and symmetry can be used. In this study, aluminum additive, which is known to have high conductivity, was used together with zeolite–bentonite mixtures. Aluminum-added mixtures were kept at different temperatures, and their thermal conductivity values were measured at the end of different periods. Measurements were first carried out at room temperature for all mixtures. Then, measurements were repeated at the end of 1, 3, and 10 days for 55 °C and 80 °C temperature values. At the end of the heating periods, the samples were left to cool to room temperature, and the thermal conductivity values were examined at the end of the heating–cooling cycle. Experimental results showed that thermal conductivity increased as temperature increased when the same period was taken as a basis, but an increase was observed for 1 and 3 day heating periods, while the thermal conductivity values for the 10th day decreased. The initial increase is attributed to the densification of the material due to the removal of free and weakly bound water or to the improvement of solid–solid contact paths. The subsequent decrease is due to microstructural deterioration, such as increased air-filled porosity, drying shrinkage, and microcracking due to thermal stresses, and material degradation caused by prolonged heating. In addition, thermal conductivity values of the mixtures under high temperature were estimated for days 100 and 365 using the DeepSeek method. The results showed that the thermal conductivity coefficients symmetrically decreased with increasing time. Full article

Flexible microscale neural interfaces are advancing current strategies for recording and modulating electrical activity in the brain and spinal cord. The aim of this review is to colligate recent progress in thin-film micro-electrocorticography (μECoG) systems and establish a framework for their translation toward spinal bioelectronic implants. We first outline substrate and electrode material design, ranging from polymeric and hydrogel-based materials to nanostructured conductive materials that enable high-fidelity recording on mechanically compliant platforms. We then summarize structural design rules for μECoG arrays, including electrode size, pitch, and channel scaling, and relate these to data-driven μECoG applications in brain–computer interfaces and closed-loop neuromodulation. Bidirectional μECoG architectures for simultaneous stimulation and recording are examined, with emphasis on safe charge injection, electrochemical and thermal limits, and state-of-the-art hardware and algorithmic strategies for stimulation-artifact suppression. Building upon these cortical technologies, we briefly describe adaptation to spinal interfaces, where anatomical constraints demand optimized mechanical properties. Finally, we discuss the convergence of flexible bioelectronics, wireless power and telemetry, and embedded AI decoding as a path toward autonomous, clinically translatable μECoG and spinal neuroprosthetic systems. Ultimately, by synthesizing these multidisciplinary advances, this review provides a strategic roadmap for overcoming current translational barriers and realizing the full clinical potential of soft bioelectronics. Full article

Under global climate change, the response of mountain forest soil carbon pools to elevation is central to carbon cycle research, and Pinus yunnanensis stands, which span a wide elevation range, serve as a typical subject for studying how soil properties in mountain ecosystems respond to elevation gradients. To reveal the variation patterns and underlying regulatory mechanisms of soil nutrients and organic carbon components in Pinus yunnanensis stands across different altitudinal gradients, this study took Pinus yunnanensis stands at three altitude gradients (1604 m, 2377 m, 3206 m) within Yunnan Province as research objects, collected stratified soil samples, and determined soil chemical properties, organic carbon components, enzyme activity, and microbial biomass. The results showed that changes in elevation significantly influence soil nutrient content: soil pH gradually decreases with increasing elevation; soil organic carbon, total nitrogen, alkali-hydrolyzable nitrogen, available phosphorus, and readily available potassium first increase then decrease with elevation, reaching their highest levels at Jin’an Town (JA); total phosphorus and total potassium gradually increase with elevation, peaking at Xiaozhongdian Town (XZD); particulate organic carbon, mineral-bound organic carbon, and microbial biomass carbon follow similar patterns to organic carbon, all showing enrichment in the surface layer; JA exhibits the highest carbon cycle enzyme activity and bacterial biomass, while XZD shows dominant fungal biomass. Partial Least Squares Path Modeling (PLS-PM) analysis indicates that elevation strongly positively drives microbial biomass, indirectly regulating enzyme activity and chemical properties, ultimately jointly influencing organic carbon components. In conclusion, soil properties varied markedly, and under stable precipitation, the thermal gradient emerged as the primary driver; the mid-elevation site (2377 m) showed optimal soil functioning, with peak nutrient and carbon stocks linked to heightened microbial and enzymatic activity, and path modeling confirmed that temperature, via microbial mediation, is the key regulator of soil organic carbon dynamics in these pine forests. Full article

This paper presents a systematic review of linear motor-based electromagnetic suspension, a key technology for reconciling vehicle comfort, handling stability, and energy consumption. The review focuses on two core areas: actuator configuration and control strategy. In configuration design, a comparison of moving-coil, permanent magnet synchronous (PMSLM), and switched-reluctance linear motors identifies the PMSLM as the mainstream approach due to its high-power density and performance. Key design challenges for meeting stringent vehicle operating conditions, such as mass-volume optimization, thermal management, and high reliability, are also analyzed. Regarding control strategy, the review outlines the evolutionary path from classical to advanced and intelligent control. It also examines the energy-efficiency trade-off between vibration suppression and energy recovery. Furthermore, the paper summarizes three core challenges for industrialization: nonlinear issues like thrust fluctuation and friction, the coupling of electromagnetic–mechanical–thermal multi-physical fields, and bottlenecks related to high costs and reliability verification. Finally, future research directions are envisioned, including new materials, sensorless control, and active safety integration for autonomous driving. Full article

With the advancement of new power systems, phase-change materials (PCMs), owing to their ability to convert and store electrical energy, are increasingly recognized as a key solution to the intermittency of power supply. Nevertheless, such materials face challenges, including leakage and low thermal conductivity, which lead to reduced utilization efficiency. In this study, guar gum was used as the macroscopic framework, while self-prepared and optimized silica aerogel microsheets served as the microscopic framework to synergistically encapsulate the polyethylene glycol (PEG). Titanium dioxide (TiO₂) nanoparticles were incorporated to improve overall thermal conductivity, resulting in the composite PCM, GTS-PEG. In-depth characterization demonstrated effective PEG retention within the matrix, with a melting heat storage density of 164.16 J/g. Upon 30 min of continuous heating at 90 °C, the mass loss remained as low as 4.83%, indicating excellent thermal stability. The addition of TiO₂ increased thermal conductivity to 0.53 W/(m·K), representing a 140% boost over unmodified material. As a result, GTS-PEG not only successfully overcomes the leakage and thermal conductivity limitations of conventional PCMs but also, as a green and low-carbon innovative solution, paves a new path for the coordinated optimization and efficient conversion of power grid energy systems. Full article

To meet the requirements of high resolution, compact size, and ultra-lightweight for micro–nano satellite optoelectronic payloads while ensuring high structural stability during launch and in-orbit operation, mirrors were designed with high surface accuracy. The opto-thermo-mechanical system of the space camera was designed and analyzed accordingly. First, an optical system was designed to achieve high resolution and a compact form factor. A coaxial triple-reflector configuration with multiple refractive paths was adopted, which significantly shortened the optical path and laid the foundation for a lightweight, compact structure. This design also defined the accuracy and tolerance requirements for the primary and secondary mirrors. Subsequently, mathematical models for topology optimization and dimensional optimization were established to optimize the design of the main support structure, primary mirror, and secondary mirror. Two design schemes for the main support structure and primary mirror were compared. Steady-state thermal analysis and thermal control design were carried out for both mirrors. Simulations were then performed on the main system (including the primary/secondary mirror assemblies and the main support structure). Under the combined effects of gravity, a 4 °C temperature increase, and an assembly flatness deviation of 0.01 mm, the surface accuracy of both mirrors, the displacement of the secondary mirror relative to the primary mirror reference, and the tilt angle all met the overall specification requirements. The system’s first-order natural frequency was 156.731 Hz. After precision machining, fabrication, and assembly, wavefront aberration testing was conducted on the main system with the optical axis horizontal. Under gravity, the root mean square (RMS) wavefront error at the center of the field of view was 0.073λ, satisfying the specification of ≤1/14λ. The fundamental frequency measured during vibration testing was 153.09 Hz, which aligned closely with the simulated value and well exceeded the requirement of 100 Hz. Additionally, in-orbit imaging verification was conducted. All results satisfied the technical specifications of the satellite’s overall requirements. Full article