Search Results (2,030)

This study investigates the control of the phase-structural state in Ni–45Ti–xCu (x = 5, 7 at.%) shape memory alloys fabricated via a shortened powder metallurgy route: mechanical activation → spark plasma sintering (SPS) → heat treatment. Compact samples were produced from mechanically alloyed powders (650–750 rpm, up to 5 h) and sintered at 900 °C. The structure and microstructure were characterized using X-ray diffraction (to identify B2/B19′/Ni₄Ti₃ phases and assess ordering) and SEM–BSE/EDS (to analyze morphology, porosity, and Ni-rich precipitates). Two post-processing treatments were applied: single-stage annealing (500 °C, 2 h) and a three-stage treatment (900 °C/30 min → water quenching → 300 °C/20 min). Mechanical alloying transformed the initial elemental powder mixture (fcc-Ni, hcp-Ti, fcc-Cu) into a supersaturated fcc-(Ni, Cu, Ti) solid solution with emerging NiTi phases, with a minimum particle size achieved after ~300 min at 750 rpm. SPS compaction yielded a high-density matrix consisting predominantly of the B2 phase. Single-stage annealing preserved B19′ martensite and Ni₄Ti₃ precipitates, particularly in the 5 at.% Cu alloy. In contrast, the three-stage treatment dissolved the Ni₄Ti₃ precipitates, suppressed the formation of B19′ and R phases, and stabilized a highly ordered B2 matrix. Increasing the Cu content from 5 to 7 at.% significantly enhanced the B2 phase fraction, reduced secondary nickel-rich phases, and improved structural homogeneity, evidenced by a continuous neck network and closed porosity. The optimized condition—7 at.% Cu combined with the three-stage annealing—produced a microstructure with >95% B2 phase, <1% Ni₄Ti₃, and ~98% relative density. This forms the prerequisite microstructural state for a narrow transformation hysteresis and high functional cyclic stability. Full article

Clustering of aircraft trajectories in terminal airspace is essential for procedure evaluation, flow monitoring, and anomaly detection, yet it is challenged by dense traffic, irregular sampling, and diverse maneuvering behaviors. This study proposes a unified framework that integrates dynamics-aware segmentation, Transformer–Variational Autoencoder (Transformer–VAE)-based representation learning, and density-aware clustering with joint optimization. A dynamic-feature Minimum Description Length (DFE-MDL) algorithm is introduced to preserve maneuver boundaries and reduce reconstruction errors, while the Transformer–VAE encoder captures nonlinear spatiotemporal dependencies and generates compact latent embeddings. Clusters are initialized using Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) and further refined through Kullback–Leibler (KL) divergence minimization to improve consistency and separability. Experiments on large-scale ADS-B data from Guangzhou Baiyun International Airport, comprising over 27,000 trajectories, demonstrate that the framework outperforms conventional geometric and deep learning baselines. Results show higher reconstruction fidelity, clearer cluster separation, and reduced computation time, enabling interpretable flow structures that reflect operational practices. Overall, the framework provides a data-driven and scalable approach for terminal-area trajectory analysis, offering practical value for STAR/SID compliance monitoring, anomaly detection, and airspace management. Full article

Urban coastal areas are increasingly vulnerable to compound flooding due to the convergence of extreme rainfall, storm surges, and infrastructure aging, especially in high-density settings. This study proposes and empirically validates a multi-scale strategy for enhancing urban flood resilience in the Macau Peninsula, a densely built coastal city with complex flood exposure patterns. Building on a previously developed network-based resilience assessment framework, the study integrates hydrodynamic simulation and complex network analysis to evaluate the effectiveness of targeted interventions, including segmented storm surge defense barriers, drainage infrastructure upgrades, and spatially optimized low-impact development (LID) measures. The Macau Peninsula was partitioned into multiple shoreline defense zones, each guided by context-specific design principles and functional zoning. Based on our previously developed flood simulation framework covering extreme rainfall, storm surge, and compound events in high-density coastal zones, this study validates resilience strategies that achieve significant reductions in inundation extent, water depth, and recession time. Additionally, the network-based resilience index showed marked improvement in system connectivity and recovery efficiency, particularly under compound hazard conditions. The findings highlight the value of integrating spatial planning, ecological infrastructure, and systemic modeling to inform adaptive flood resilience strategies in compact coastal cities. The framework developed offers transferable insights for other urban regions confronting escalating hydrometeorological risks under climate change. Full article

Hemp-lime composites, characterized by pro-environmental features, offer an interesting alternative to traditional building materials. The properties of these materials depend on many factors, leading to uncertainty regarding the results obtained when designing building envelopes. Volumetric density—a key factor—depends on the manufacturing technique adopted, among other things, and can be controlled. In this study, materials for use in partitions constituting the building envelope were produced at various densities through varying degrees of compression and subjected to tests to determine their compressive strength, thermal conductivity and water vapor permeability. The values obtained were in the wide ranges of 0.05–1.50 MPa, 0.0671–0.1339 W/(m∙K) and 3.61–10.10, respectively. Furthermore, the specific heat was determined to be 1178–1260 at 60 °C and 773–863 J/(kg∙K) at 30 °C. The test results clearly indicate the dependence of the tested properties on the mixture composition, volumetric density and composite structure. The results of this study demonstrate the suitability of the considered material for construction applications and the significant variations in its properties. Understanding the relationships between the properties of different composites and their degree of compaction can facilitate the design process and help in modeling the mechanical and thermal behaviors of partitions and entire buildings. Full article

This study investigates the performance of mineral–cement–emulsion (MCE) mixtures produced with reclaimed asphalt pavement (RAP) and recycled mineral aggregates for use in road base layers. The aim was to evaluate the mechanical properties, field performance, and key factors influencing the cracking behavior of these sustainable cold-recycled mixtures. Approximately 160 laboratory tests were performed to determine indirect tensile strength (ITS), stiffness modulus (IT-CY), bulk density, and air-void content. The MCE mixture achieved an average ITS of 1.09 MPa and stiffness modulus of 5873 MPa after 28 days of curing, confirming compliance with design requirements. The field investigation of a test section showed good structural integrity and compaction, although several transverse cracks developed during the first year of service. The mechanistic interpretation attributed these cracks to combined cement hydration shrinkage and thermal contraction effects. The results indicate that MCE mixtures made with recycled materials can meet technical specifications while reducing environmental impact, provided that binder proportions and curing conditions are carefully optimized. Full article

We study thrust production in a single-fluid magnetohydrodynamic (MHD) thruster with Hall-type coaxial geometry and show how velocity–field alignment and magnetic topology set the operating regime. Starting from the momentum equation with anisotropic conductivity, the axial Lorentz force density reduces to $f_z={\sigma }_{\theta z}{E}_z{B}_r(\chi -1)$, with the motional-field ratio $\chi \equiv \left(u{B}_r\right)/E_z$. Hence, net accelerating force ($f_z>0$) is achieved if and only if the motional electric field $E_m=u{B}_r$ exceeds the applied axial bias $E_z$ ($\chi >1$), providing a compact, testable design rule. We separate alignment diagnostics (cross-helicity $h_c=\mathit{u}·\mathit{B}$) from the thrust criterion ($\chi$) and generate equation-only axial profiles for $\chi \left(z\right)$, $j_{\theta }\left(z\right)$, and $f_z\left(z\right)$ for representative parameters. In a baseline case $(E_z=150\mathrm{V}{\mathrm{m}}^{-1},{\sigma }_{\theta z}=50\mathrm{S}{\mathrm{m}}^{-1},u_0=12\mathrm{km}{\mathrm{s}}^{-1},B_{r0}=0.02\mathrm{T},L=0.10\mathrm{m})$, the $\chi >1$ band spans $\approx 21.2\%$ of the channel; a lagged correlation peaks at $\Delta z^{★}\approx 8.82\mathrm{mm}$$(C_{HU}=0.979)$, and ${\int }_0^L{f}_z\mathrm{d}z$ is slightly negative—indicating that enlarging the $\chi >1$ region or raising ${\sigma }_{\theta z}$ are effective levers. We propose a reproducible validation pathway (finite-volume MHD simulations and laboratory measurements: PIV, Hall probes, and thrust stand) to map $f_z$ versus $\chi$ and verify the response length. The framework yields concrete design strategies—$B_r\left(z\right)$ shaping where u is high, conductivity control, and modest $E_z$ tuning—supporting applications from station-keeping to deep-space cruise. Full article

To effectively control the deformation of high concrete face rockfill dams, this study proposes an intelligent prediction model (CO–SA–GPR) that integrates the Cheetah Optimizer (CO) and Simulated Annealing (SA) algorithm to optimize Gaussian Process Regression (GPR) for accurately estimating the compaction density of sandy gravel materials. Firstly, a theoretical derivation of the specification-similar gradation scaling method was conducted, clarifying the relationship between gradation parameters before and after scaling. On this basis, the CO and SA algorithms were employed to adaptively optimize the hyperparameters of the GPR model, obtaining the global optimal solution through intelligent search, thereby enhancing the model’s prediction accuracy and robustness. Application of the established model to actual engineering predictions shows that in estimating the maximum and minimum dry densities, the CO–SA–GPR model achieves R² values as high as 0.9752 and 0.9741, with RMSE as low as 0.0022 and 0.0028, respectively, significantly outperforming comparative models. The proposed model enables accurate prediction of compaction density from laboratory scaled-down tests to prototype gradations, providing a reliable new method for quality control in high rockfill dam construction and offering important theoretical and technical reference values for similar coarse-grained soil engineering. Full article

The rational design of transition metal oxides with tailored electronic structures and defect chemistries is critical for advancing high-performance supercapacitors. Herein, we report the engineering of cobalt oxide (Co₃O₄) gels through controlled sol–gel synthesis and rare earth (RE) incorporation using neodymium (Nd), gadolinium (Gd), and dual neodymium/gadolinium (Nd/Gd) doping. X-ray diffraction (XRD) confirmed the preservation of the cubic spinel structure with systematic peak shifts and broadening, evidencing lattice strain, oxygen vacancy generation, and defect enrichment. Field-emission scanning electron microscopy (FE-SEM) analyses revealed distinct morphological evolution from compact nanoparticle assemblies in pristine Co₃O₄ to highly porous, interconnected frameworks in Nd/Gd–Co₃O₄ (Nd/Gd-Co). X-ray photoelectron spectroscopy (XPS) verified the stable incorporation of RE ions, accompanied by electronic interaction with the Co–O matrix and enhanced oxygen defect states. Electrochemical measurements demonstrated that the Nd/Gd–Co electrode achieved a remarkable areal capacitance of 25 F/cm² at 8 mA/cm², superior ionic diffusion coefficients, and the lowest equivalent series resistance (0.26 Ω) among all samples. Long-term cycling confirmed 84.35% capacitance retention with 94.46% coulombic efficiency after 12,000 cycles. Furthermore, the asymmetric pouch-type supercapacitor (APSD) constructed with Nd/Gd–Co as the positive electrode and activated carbon as the negative electrode delivered a wide operational window of 1.5 V, an areal capacitance of 140 mF/cm², an energy density of 0.044 mWh/cm², and 89.44% retention after 7000 cycles. These findings establish Nd/Gd-Co gels as robust and scalable electrode materials and demonstrate that RE co-doping is an effective strategy for bridging high energy density with long-term electrochemical stability in asymmetric supercapacitors. Full article

Wide-Bandgap (WBG) semiconductors—silicon carbide (SiC) and gallium nitride (GaN)— enable high-power-density conversion, but performance is limited by where heat is generated and how it is removed. This review links device-level loss mechanisms (conduction and switching, including output-capacitance hysteresis and dynamic on-resistance) to structure-driven hot spots within the ultra-thin (tens of nanometers) two-dimensional electron gas (2DEG) channel of GaN HEMTs and to thermal boundary resistance at layer interfaces. We compare wire-bondless package concepts—double-sided cooling, embedded packaging, and interleaved planar layouts—and survey system-level cooling that shortens the conduction path and raises heat-transfer coefficients. The impact on reliability is discussed using temperature-sensitive electrical parameters (e.g., on-state VDS, threshold voltage, drain leakage, di/dt, and gate current) for real-time junction-temperature estimation and compact electro-thermal RC models for remaining-useful-life prediction. Evidence from recent literature points to interface resistance in GaN-on-SiC as a primary bottleneck, while near-junction cooling and advanced packages are effective mitigations. We argue for integrated co-design—devices, packaging, electromagnetic interference (EMI)-aware layout, and cooling—together with interface engineering and health monitoring to deliver reliable, high-density WBG systems. Full article

To address the global plastic crisis, recycled plastics from food packaging were used as road materials by the dry method for practical application research. First, the main components of the recycled plastics were identified based on FTIR, and their thermal stability was evaluated through DSC, TG, and microscopic analysis. Then, the workability of the plastic–asphalt mixture was evaluated using the gyratory compaction indicator, void content, and compaction energy index (CEI). Finally, the effect of reused plastics on the cracking resistance of bituminous mixtures was examined with the Superpave IDT test. The results indicate that recycled plastics from food packaging are polyolefin composite materials, primarily consisting of Low-Density Polyethylene (LDPE), Linear Low-Density Polyethylene (LLDPE), High-Density Polyethylene (HDPE), and Polypropylene (PP), and that their thermal stability meets production requirements. Good compaction performance was observed with plastic content below 2% of the aggregate weight, while higher contents reduced void content due to the space occupied by plastics. When the plastic content increased from 0.5% to 2.0%, creep compliance decreased from 68.4% to 77.87%, while the m-value, tensile strength, and elastic energy maximum decreased by 30.77%, 5.6%, and 7%, respectively. In contrast, the failure strain, fracture energy, and maximum DSCE increased by 25.86%, 87.43%, and 133.05%, respectively. The recycled plastic enhanced the toughness of the asphalt mixture, increasing the dissipated energy during crack propagation and improving its resistance to permanent deformation. Moreover, the plastics hindered crack propagation through a bridging effect, leading to fewer cracks within plastic zones compared with surrounding areas. This study provides actionable guidance for the application of composite plastics in asphalt pavements and supports their sustainable development. Full article

FeCoNiCuAl high-entropy alloys exhibit remarkable mechanical properties; nevertheless, these materials struggle to withstand harsh environments because of their insufficient resistance to wear and corrosion. The addition of Si can significantly enhance the alloy’s high-temperature performance, hardness, and wear resistance, thereby making it more suitable for applications in high-temperature or corrosive environments. To overcome these drawbacks, this research investigates how varying Si content affects the microstructure and properties of FeCoNiCuAl coatings. Composite coatings of FeCoNiCuAlSi_x (x = 0, 0.5, 1.0, 1.5, 2.0) were fabricated on 65 Mn substrates using laser cladding. Various testing methods, including metallographic microscopy, Vickers hardness testing, friction and wear testing, and electrochemical analysis, were employed to examine the phase structure, microstructure, and hardness of the coating. It is observed that the FeCoNiCuAl coating begins with a uniform FCC phase structure. However, as the Si content increases, a phase transformation to the BCC structure occurs. The microstructure is primarily composed of isometric crystals and dendrites that become finer and more compact with higher Si content. For the FeCoNiCuAlSi_2.0 coating, the microhardness reaches 581.05 HV_0.2. Additionally, wear resistance shows a positive correlation with Si content. Electrochemical testing in NS4 solution shows that the corrosion potential of the coating increases from −0.471 V for FeCoNiCuAl to −0.344 V for FeCoNiCuAlSi_2.0, while the corrosion current density decreases from 1.566 × 10⁻⁶ A/cm² to 4.073 × 10⁻⁶ A/cm². These results indicate that Si addition plays a crucial role in enhancing the mechanical properties and corrosion resistance of FeCoNiCuAl coatings, making them more suitable for high-performance applications in extreme environments. Full article

Monitoring ecosystem dynamics in arid regions requires robust indicators that can capture spatial heterogeneity and diverse ecological drivers. In this study, we introduce and evaluate two novel ecological indices: the Arid-region Remote Sensing Ecological Index (ARSEI), specifically designed for desert environments, and the Composite Remote Sensing Ecological Index (CoRSEI), which integrates both desert and non-desert systems. These indices are compared with the traditional Remote Sensing Ecological Index (RSEI) in the Tarim River Basin from 2000 to 2023. Principal component analysis (PCA) revealed that RSEI maintained the highest structural compactness (average PCA1 = 87.49%). In contrast, ARSEI (average PCA1 = 78.62%) enhanced sensitivity to albedo and vegetation (NDVI) in arid environments. Spearman correlation analysis further demonstrated that ARSEI was more strongly correlated with NDVI (ρ = 0.49) and precipitation (ρ = 0.62) than RSEI, confirming its improved responsiveness under water-limited conditions. CoRSEI exhibited higher internal consistency and spatial adaptability (mean values ranging from 0.45 to 0.56), with slight ecological improvements observed between 2000 and 2023. Ecological drivers varied across habitat types. In desert areas, evapotranspiration, precipitation, and soil moisture were the main determinants of ecological status, showing high coupling and synchrony. In non-desert regions, soil moisture and precipitation remained dominant, but vegetation indices and disturbance factors (e.g., fire density) exerted stronger long-term influences. Partial dependence analyses further confirmed nonlinear, region-specific responses, such as the threshold effects of precipitation on vegetation growth. Overall, our findings highlight the importance of differentiated ecological modeling. ARSEI enhances sensitivity in desert ecosystems, whereas CoRSEI captures landscape-scale variability across desert and non-desert regions. Both indices contribute to more accurate long-term ecological assessments in hyper-arid environments. Full article

Power electronics is an important feature of the new power system. The high-speed development of the new power system has gradually increased the requirements for high-efficiency and high-reliability high-voltage transmission and substation equipment. Silicon carbide (SiC) devices, which have the advantages of fast switching speed, low power loss, and high-temperature resistance, are the key core technology for the upgrading of high-voltage transmission and substation equipment. The paper begins by examining the evolution of the demand for high efficiency, compact and reliable power electronic devices for high-voltage transmission and substation systems at different stages of energy development. SiC has emerged as a key technological path to break through the physical limits of silicon-based devices, due to its outstanding material properties. Silicon-based devices encounter significant bottlenecks in high-voltage and high-frequency applications, with high switching losses and a junction temperature tolerance that is typically limited to 150 °C. In contrast, SiC devices can reduce switching losses by 60–80% and operate stably at temperatures up to 200 °C or even higher, thereby significantly enhancing system efficiency and power density. Finally, the paper provides a systematic analysis of the application of SiC devices in high-voltage transmission and substation equipment, exploring and identifying the technical bottlenecks and future research directions for SiC-based high-voltage transmission equipment. Full article

Compaction quality control in earthworks and pavements still relies mainly on density-based acceptance referenced to laboratory Proctor tests, which are costly, time-consuming, and spatially sparse. Lightweight dynamic cone penetrometer (LDCP) provides rapid indices, such as $q_{d0}$ and $q_{d1}$, yet acceptance thresholds commonly depend on ad hoc, site-specific calibrations. This study develops and validates a supervised machine learning framework that estimates $q_{d0}$, $q_{d1}$, and $Z_c$ directly from readily available soil descriptors (gradation, plasticity/activity, moisture/state variables, and GTR class) using a multi-campaign dataset of $n=360$ observations. While the framework does not remove the need for the standard soil characterization performed during design (e.g., W, ${\gamma }_{d,\mathrm{field}}$, and $R{C}_{\mathrm{SPC}}$), it reduces reliance on additional LDCP calibration campaigns to obtain device-specific reference curves. Models compared under a unified pipeline include regularized linear baselines, support vector regression, Random Forest, XGBoost, and a compact multilayer perceptron (MLP). The evaluation used a fixed 80/20 train–test split with 5-fold cross-validation on the training set and multiple error metrics ($R^2$, RMSE, MAE, and MAPE). Interpretability combined SHAP with permutation importance, 1D partial dependence (PDP), and accumulated local effects (ALE); calibration diagnostics and split-conformal prediction intervals connected the predictions to QA/QC decisions. A naïve GTR-average baseline was added for reference. Computation was lightweight. On the test set, the MLP attained the best accuracy for $q_{d1}$ ($R^2=0.794$, RMSE $=5.866$), with XGBoost close behind ($R^2=0.773$, RMSE $=6.155$). Paired bootstrap contrasts with Holm correction indicated that the MLP–XGBoost difference was not statistically significant. Explanations consistently highlighted density- and moisture-related variables (${\gamma }_{d,\mathrm{field}}$, $R{C}_{\mathrm{SPC}}$, and W) as dominant, with gradation/plasticity contributing second-order adjustments; these attributions are model-based and associational rather than causal. The results support interpretable, computationally efficient surrogates of LDCP indices that can complement density-based acceptance and enable risk-aware QA/QC via conformal prediction intervals. Full article

This study examines how Windhoek’s urban form, shaped by apartheid-era planning, continues to influence neighbourhood travel behaviour, socio-economic disparity, and residential perceptions. It addresses three key questions: (1) How do socio-economic characteristics, neighbourhood perceptions, and travel patterns differ between compact and sprawled areas? (2) Which socio-economic, perceptual, and spatial factors are associated with the likelihood of neighbourhood-based shopping in compact versus sprawled urban forms? (3) What are the determinants of entertainment and recreational travel behaviour within neighbourhoods across the two urban forms? Using survey data from 1000 residents, the analysis employs chi-square tests, Mann–Whitney U tests, binary logistic regression, and multivariate regression models. Findings reveal that compact areas, characterised by higher incomes, stronger place attachment, and greater infrastructural diversity, support more frequent neighbourhood travel. By contrast, sprawled peripheries, despite higher population densities, remain marked by socio-economic marginalisation, limited amenity access, and negative perceptions that constrain neighbourhood mobility. Across both forms, long-term residence and belonging strongly predict neighbourhood travel, while concerns over traffic safety and crime consistently suppress participation. The results show that spatial proximity alone does not ensure accessibility; emotional, perceptual, and structural barriers mediate neighbourhood mobility. The study highlights the need for integrated planning that addresses both physical infrastructure and lived experience to advance equitable and sustainable mobility in post-colonial contexts. Full article