Search Results (3,601)

Numerical simulation of the electrical conductivity of carbon fiber-reinforced asphalt concrete is essential for understanding its electrical behavior, yet research in this area remains limited. This study prepared six groups of Marshall specimens with carbon fiber (CF) contents of 0.1 wt%, 0.2 wt%, 0.3 wt%, 0.4 wt%, 0.5 wt%, and 0.6 wt%. The resistivity and asphalt concrete (AC) impedance spectra were measured to analyze the effect of fiber content on electrical performance. Nyquist diagrams were fitted to establish an equivalent circuit model, and a representative volume element (RVE) finite element model was developed. The Generalized Effective Medium (GEM) equation was employed to fit the resistivity data. The results show that the resistivity exhibits a two-stage characteristic—an abrupt decrease followed by stabilization, with an optimal CF content range of 0.2–0.4 wt%. Among the equivalent circuit parameters, the contact resistance (R₁) and tunneling resistance (R₂) significantly decreased, the growth of interface capacitance (C₁) slowed, the constant phase element Z_Q increased, and the non-monotonic change of volume resistance (R₃) reflected the heterogeneity of the internal void distribution of the material. The finite element numerical solution for resistivity, derived from the GEM equation, aligns well with experimental values, validating the proposed simulation approach. Full article

A knowledge of the process–structure–property correlation and underlying deformation mechanisms of material under a coupled electro-thermal–mechanical field is crucial for developing novel electrically assisted forming techniques. In this work, numerical simulation and experimental analyses were carried out to study the non-uniform deformation behaviors and microstructure evolution of Ti₂AlNb-based alloy stiffened panels in different characteristic deformation regions during electrically assisted press bending (EAPB). The quantitative relationships between electro-thermal–mechanical routes, microstructural features, and mechanical properties of EAPBed stiffened panels were initially established, and the underlying mechanisms of electrically induced phase transformation and morphological transformation were unveiled. Results show that the temperature of the panel first increases then deceases with forming time in most regions, but it increases monotonically and reaches its peak value of 720.1 °C in the web region close to the central transverse rib. The higher accumulated strain and precipitation of the acicular O phase at mild temperature leads to strengthening of the longitudinal ribs at near blank holder regions, resulting in an ideal microstructure of 3~4% blocky α₂ phase + a dual-scale O structure in a B2 matrix with a maximal hardness of 389.4 ± 7.2 HV_0.3. While the dissolution of the α₂ phase and the spheroidization and coarsening of the O phase bring about softening (up to 9.29%) of the lateral ribs and web near the center region, the differentiated evolution of microstructure and the mechanical property in EAPB results in better deformation coordination and resistance to wrinkling and thickness variation in the rib–web structure. The present work will provide valuable references for achieving shape-performance coordinated manufacturing of Ti₂AlNb-based stiffened panels. Full article

Accurate prediction of the shear strength of rock discontinuities requires accounting for surface roughness, which is a factor neglected in the classical Mohr–Coulomb criterion. This study proposes a fractal-enhanced Mohr–Coulomb model that incorporates the surface fractal dimension Ds as a geometric state variable governing both the cohesion and internal friction angle. The fractal dimension is treated as an objective, scale-invariant descriptor, computable via established methods, such as box-counting and power spectral density analysis, which are known to yield consistent results when applied to joint topography. The model predicts a nonlinear increase in shear strength with Ds, producing a dynamically adjustable failure envelope that can exceed the classical Mohr–Coulomb estimates by 25–40% for rough joints, which is consistent with trends observed in experimental shear tests. By linking strength parameters directly to measurable surface geometry, the framework provides a physically interpretable bridge between micro-scale roughness and macro-scale mechanical response. Although the current formulation assumes monotonic, dry, and quasi-static conditions, the explicit dependence on Ds offers a foundation for future extensions that incorporate anisotropy, damage evolution, and hydro-mechanical coupling. Full article

Carbon fiber reinforced polymer (CFRP) is prone to delamination damage during drilling, which seriously affects the processing quality. This study focuses on the use of variable parameter drilling technology. Firstly, an anisotropic constitutive model and a Hashin failure model for CFRP were constructed. Then, based on ABAQUS and VUMAT user subroutines, the influence laws of cutting parameters (spindle speed and feed rate) on delamination damage were explored. For the two methods of conventional fixed parameter drilling and variable parameter drilling (dynamic adjustment of feed rate when the drill reaches the exit plane), comparative simulation experiments were conducted. Subsequently, the genetic algorithm was introduced to optimize the spindle speed and feed rate under the variable parameter mode, and the results were verified through hole-making experiments. The results show that: under a constant spindle speed, the delamination damage factor increases monotonically with the increase in feed rate; under a constant feed rate, the delamination damage factor decreases first and then increases with the increase in spindle speed, presenting a nonlinear change characteristic. Among them, the variable parameter strategy of “first high feed, then low feed” can significantly reduce the delamination damage; the obtained optimal parameters can effectively balance the drilling quality and processing efficiency. This research provides theoretical and experimental support for optimizing CFRP hole-making parameters, addressing delamination control challenges in traditional drilling, and facilitating CFRP applications in aerospace and intelligent manufacturing. Full article

Langasite (LGS)-based surface acoustic wave (SAW) sensors are promising for high-temperature pressure detection. However, their performance is limited by the low pressure sensitivity of conventional sealed-cavity packaging and temperature-induced measurement drift. To address these issues, this study introduces a novel LGS SAW pressure sensor featuring two key innovations: a Kovar alloy point-force packaging structure to amplify pressure-induced LGS substrate deformation, enhancing sensitivity compared to traditional designs, and SAW resonators fabricated on an LGS (0°, 138.5°, 26.7°) cut, selected based on electromechanical simulations for its superior intrinsic pressure sensitivity and monotonic frequency–temperature response, effectively mitigating temperature interference on pressure measurements. Experimental characterizations show the resonator achieves a high Q-value of ~3000 at ~357 MHz. Tested under conditions of 250 °C and 0–0.4 MPa, the sensor exhibits a pressure sensitivity of 0.1866 MHz/MPa with a relative error of only 4.8% versus the finite element method (FEM)-simulated 0.196 MHz/MPa, demonstrating the proposed design’s effectiveness for accurate, stable pressure monitoring in harsh high-temperature environments such as turbine engines and high-temperature manufacturing lines. Full article

Ammonia (NH₃) is a zero-carbon fuel and an attractive hydrogen (H₂) carrier for gas turbine power generation due to its high energy density, ease of storage, and transportation. This study numerically investigates NH₃/air combustion using a hybrid Well-Stirred Reactor (WSR) and Plug Flow Reactor (PFR) model in Cantera at pressures of 1–20 atm, temperatures of 1850–2150 K, and equivalence ratios (ϕ) of 0.7–1.2. The effects of pressure, equivalence ratio, and temperature on NH₃ conversion and NO formation are examined. Results show that NH₃ exhibits a non-monotonic conversion curve with pressure after the WSR, reaching a minimum near 5 atm, whereas NO formation decreases monotonically from 1 to 20 atm. Equivalence ratio sweeps show that NO decreases steeply as ϕ increases from 0.7 to ~1.1 as nitrogen is redirected toward N₂ and oxidizer availability declines; residual NH₃ increases rapidly for ϕ > 1.0, especially at high pressure. Increasing temperature accelerates NH₃ oxidation and raises NO formation, most strongly at low pressure where thermal and NH/OH pathways are least inhibited. These results indicate that co-tuning pressure and equivalence ratio near rich operation enables low-NO_x ammonia combustion suitable for advanced gas turbine applications. Full article

This study presents the development and validation of a high-speed optical data acquisition system for detecting and characterizing hydrodynamic cavitation downstream of a triangular nozzle. The system integrates a PIN photodiode, a transimpedance amplifier, and a high-sampling-rate microcontroller. Its performance was first evaluated using controlled sinusoidal signals, and statistical stability was assessed as a function of the number of acquired samples. Experiments were subsequently conducted in a converging–diverging conduit under biphasic flow conditions, where mean irradiance, standard deviation, and frequency spectra were analyzed downstream of the nozzle. The optical signal distributions revealed transitions in flow behavior associated with cavitation development, which were quantified through statistical metrics and spectral features. The Strouhal number was estimated from dominant frequencies extracted from the spectra, exhibiting a non-monotonic dependence on the Reynolds number, consistent with changes in flow structure and turbulence intensity. Spectral analysis further indicated frequency bands associated with energy transfer across turbulent scales and bubble dynamics. Overall, the results demonstrate that the proposed optical system constitutes a viable and non-intrusive methodology for detecting and characterizing cavitation intensity in a way that complements other optical and acoustic methods. Full article

We report a defect-selective luminescence response in calcium-deficient hydroxyapatite (HAp) induced by electron and ion irradiation. Compacted HAp pellets prepared from hydrothermally grown nanofibers were investigated to analyze defect-related luminescence using photoluminescence (PL) and cathodoluminescence (CL) techniques, both before and after compaction. Low-energy electron beam irradiation (15 keV) produced a two-stage luminescent response, an initial enhancement arising from field-assisted activation of OH-channel vacancies (V_OH and V_OH + H_i), followed by an exponential decay attributed to defect annealing. Monochromatic transient CL measurements show that this rise–decay behavior is selective to the OH-related bands at 2.57 and 2.95 eV, whereas the 3.32 and 3.67 eV emissions exhibit only a monotonic exponential decay. The corresponding decay constants further indicate that the activated OH-channel vacancies anneal more rapidly than the other centers, consistent with their higher electron-capture probability and lower structural stability. In contrast, ${\mathrm{Ga}}^{+}$ ion irradiation (30 keV, 1.4 × 10⁻¹³ A/µm²) induced progressive monotonic luminescence quenching, primarily driven by selective annealing of oxygen vacancies in $\mathrm{P}{\mathrm{O}}_4^{3-}$ groups. These complementary pathways, electron-induced activation and ion-driven suppression, demonstrate that irradiation serves as a versatile tool for defect engineering in hydroxyapatite. Beyond providing fundamental insights into vacancy stability, these results open new routes for tailoring the optical, sensing, and bioimaging functionalities of HAp through controlled irradiation. Full article

Horse flies (Tabanidae) negatively affect livestock by reducing productivity, compromising animal welfare, and serving as mechanical vectors of pathogens. However, the spatial processes shaping their community organization in southern Brazil’s Coastal Plain of Rio Grande do Sul (CPRS) remain poorly understood. To address this, we conducted standardized Malaise-trap surveys and combined them with historical–contemporary comparisons to examine distance–decay patterns in community composition. We evaluated both abundance-based (Bray–Curtis) and presence–absence (Jaccard) dissimilarities using candidate models. Across sites, Tabanus triangulum emerged as the dominant species. Dissimilarity in community structure increased monotonically with geographic distance, with no evidence of abrupt thresholds. The square-root model provided the best fit for abundance-based data, whereas a linear model best described presence–absence patterns, reflecting dispersal limitation and environmental filtering across a heterogeneous coastal landscape. Sites within riparian forests and conservation units displayed higher diversity, emphasizing the ecological role of protected habitats and the importance of maintaining connected corridors. Collectively, these findings establish a process-based framework for surveillance and landscape management strategies to mitigate vector, host contact. Future directions include integrating remote sensing and host distribution, applying predictive validation across temporal scales. Full article

The Rasch model has the desirable property that item parameter estimation can be separated from person parameter estimation. This implies that no assumptions about the ability distribution are required when estimating item difficulties. Pairwise estimation approaches in the Rasch model exploit this principle by estimating item difficulties solely from sample proportions of respondents who answer item i correctly and item j incorrectly. A recent contribution by Tutz introduced Tutz’s pairwise separation estimator (TPSE) for the more general class of homogeneous monotone (HM) models, extending the idea of pairwise estimation to this broader setting. The present article examines the asymptotic behavior of the TPSE within the Rasch model as a special case of the HM framework. It should be emphasized that both analytical derivations and a numerical illustration show that the TPSE yields asymptotically biased item parameter estimates, rendering the estimator inconsistent, even for a large number of items. Consequently, the TPSE cannot be recommended for empirical applications. Full article

Sealing tunnel portals is widely recognized as a pivotal strategy for mitigating fire hazards in tunnel safety management. Nevertheless, the interplay between fire source locations—both longitudinally and transversely—and its impact on flame behavior and ceiling temperature profiles within enclosed structures has not been fully elucidated. Utilizing a 1:15 reduced-scale rectangular tunnel model, this research investigates how varying the fire source position affects the maximum ceiling temperature under enclosed scenarios. Dimensionless parameters, including the longitudinal dimensionless distance D and transverse dimensionless distance Z′, were derived through dimensional analysis. Observations indicate that as the fire approaches the enclosed end, the flame initially leans toward the boundary, peaking in inclination at D = 0.73, and subsequently exhibits a “wall-attached combustion” pattern due to wall confinement. While lateral displacement of the fire source pushes the high-temperature zone toward the corresponding side wall, the longitudinal temperature rise follows a non-monotonic pattern: declining continuously in in Region I (0 ≤ D ≤ 0.73) and rebounding in Region II (0.73 < D < 1). Based on these findings, a dimensionless prediction model incorporating heat release rate (HRR), transverse offset, and longitudinal fire location was developed. Furthermore, a thermal accumulation factor was introduced to refine the predictive model in Region II. The results offer theoretical insights to support fire protection design and risk assessment in enclosed tunnels. Full article

The dynamic behavior of relaxed steel wire ropes under slowly varying pulse loads is dominated by the geometric wave impedance effect caused by the helical geometric topology. This study proposes a numerical analysis framework based on high-fidelity parametric solid modeling and implicit dynamics to investigate a Seale-type 6×19S-WSC steel wire rope. Under baseline conditions without pretension and friction, the helical structure forces significant modal conversion and geometric scattering of the axially incident waves, producing an energy attenuation effect akin to “geometric filtering”. Parametric analysis varying the core wire diameter reveals that the helical structure causes the axial wave speed to decrease by orders of magnitude compared to the material’s inherent wave speed. Furthermore, changes in core wire size induce a non-monotonic variation in the dynamic response, revealing a competitive mechanism between overall stiffness increase and a “dynamic decoupling” effect caused by interlayer gaps. This study confirms the dominant role of geometric wave impedance in the dynamic performance of relaxed steel wire ropes. Full article

This study focuses on a bulb tubular pump to clarify the flow characteristics and energy loss laws of low-lift tubular pumps under variable speed regulation and addresses deviations from optimal operating conditions in complex scenarios. For two typical rotational speeds, a full-flow passage model was established; the SST k-ω turbulence model was used to solve 3D incompressible viscous flow, energy loss was analyzed via entropy production theory, and simulations were experimentally validated. The results showed the following: pump efficiency exhibited a “first rise then fall” trend, head decreased monotonically with flow rate, and the optimal operating point shifted to lower flow rates at slower speeds. Meanwhile, local entropy production rate effectively characterized loss location and intensity, with aggravated off-design loss concentrated near the hub and rim along the spanwise direction and within 30 mm of the near-wall region. This study clarifies core energy loss mechanisms, providing a quantitative basis for operation optimization and structural improvement to support the safe, economical operation of low-lift pump stations. Full article

Coastal shipping plays a critical role in meeting maritime decarbonization targets under the International Maritime Organization’s (IMO) Carbon Intensity Indicator (CII) and the European Union Emissions Trading System (EU ETS); however, operators currently lack robust tools to forecast route-specific carbon intensity and evaluate the causal benefits of fuel switching. This study developed a distribution-free causal forecasting framework for voyage-level Carbon Dioxide (CO₂) intensity using an enriched panel of 1440 real-world voyages across four Nigerian coastal routes (2022–2024). We employed a physics-informed monotonic Light Gradient Boosting Machine (LightGBM) model trained under a strict leave-one-route-out (LORO) protocol, integrated with split-conformal prediction for uncertainty quantification and Causal Forests for estimating heterogeneous treatment effects. The model predicted emission intensity on completely unseen corridors with a Mean Absolute Error (MAE) of 40.7 kg CO₂/nm, while 90% conformal prediction intervals achieved 100% empirical coverage. While the global average effect of switching from heavy fuel oil to diesel was negligible (≈−0.07 kg CO₂/nm), Causal Forests revealed significant heterogeneity, with effects ranging from −74 g to +29 g CO₂/nm depending on route conditions. Economically, targeted diesel use becomes viable only when carbon prices exceed ~100 USD/tCO₂. These findings demonstrate that effective coastal decarbonization requires moving beyond static baselines to uncertainty-aware planning and targeted, route-specific fuel strategies rather than uniform fleet-wide policies. Full article

Grasslands, as dominant terrestrial ecosystems, significantly influence soil microbial communities through alterations in soil properties. However, their effects on spatial patterns of soil microbial communities are still under-investigated. To address this, we quantified taxa–area (TAR) and node–area (NAR) relationships for prokaryotic and fungal communities across temperate steppe (TS), alpine steppe (AS), and alpine meadow (AM). Our findings indicated that the spatial turnover of both prokaryotic and fungal communities were higher in alpine steppe and alpine meadow than in temperate steppe, mirroring the gradient of soil environmental heterogeneity. Notably, overall species richness increased logarithmically with sampling area in all grasslands; in striking contrast, co-occurring richness exhibited an increasing and then decreasing trend in AS and AM, but declined monotonically in TS, indicating that microbial interaction networks collapse once a critical spatial threshold is exceeded regulated by ecosystem type and environmental heterogeneity. In growing season, the stochastic dominance in prokaryotic assembly (Normalized stochasticity ratio = 0.71–0.89) and deterministic dominance in fungal assembly (Normalized stochasticity ratio = 0.23–0.37) can be explained by their differences in niche breadth and migration rate. These scale-dependent biogeographic patterns demonstrate that grassland type impacts distinct interactions and spatial patterns of microbial communities. These findings provide novel insights into a comprehensive understanding of how grassland type mediates soil microbial community. Full article