Search Results (683)

As an important pillar of the global economic system, the cotton industry faces critical challenges from non-fibrous impurities (e.g., leaves and debris) during processing, which severely degrade product quality, inflate costs, and reduce efficiency. Traditional detection methods suffer from insufficient accuracy and low efficiency, failing to meet practical production needs. While deep learning models excel in general object detection, their massive parameter counts render them ill-suited for real-time industrial applications. To address these issues, this study proposes Cotton-YOLO, an optimized yolov8 model. By leveraging principles of symmetry in model design and system setup, the study integrates the CBAM attention module—with its inherent dual-path (channel-spatial) symmetry—to enhance feature capture for tiny impurities and mitigate insufficient focus on key areas. The C2f_DSConv module, exploiting functional equivalence via quantization and shift operations, reduces model complexity by 12% (to 2.71 million parameters) without sacrificing accuracy. Considering angle and shape variations in complex scenarios, the loss function is upgraded to Wise-IoU for more accurate boundary box regression. Experimental results show that Cotton-YOLO achieves 86.5% precision, 80.7% recall, 89.6% mAP50, 50.1% mAP50–95, and 50.51 fps detection speed, representing a 3.5% speed increase over the original yolov8. This work demonstrates the effective application of symmetry concepts (in algorithmic structure and performance balance) to create a model that balances lightweight design and high efficiency, providing a practical solution for industrial impurity detection and key technical support for automated cotton sorting systems. Full article

The rapid advancement of artificial intelligence continuously increases the demand for high computing power, leading to substantial rises in chip power consumption and heat generation. As a result, efficient thermal management has become essential. Inspired by the placoid scales on shark skin, we designed a bionic microchannel heat sink by introducing biomimetic structures on the inner channel surfaces to enhance heat dissipation. Numerical simulations are performed to investigate thermal behavior under different structural configurations. The results show that the arrangement, number, and inclination angle of the placoid structures significantly influence heat transfer by modifying flow patterns, enlarging the heat transfer area, and altering the thermal boundary layer. Notably, at a flow velocity of 2 m/s, the cooling performance differs significantly between inclination angles of 0° and 17°. Moreover, the influence of different quantities of placoid structures shows a consistent trend across various flow rates. These findings demonstrate that bionic surface structures can effectively improve the thermal performance of microchannel heat sinks, offering a promising strategy for high-performance chip cooling. Full article

The extensive use of copper in thermal and electrical systems calls for constant performance enhancement by means of innovative material treatments. The effects on the microstructural, mechanical, and electrical characteristics of copper in deep cryogenic treatment (DCT) and deep cryogenic treatment followed by heat treatment (DCT + HT) are investigated in this work. Copper samples were treated for various soaking durations ranging from 6 to 24 h. Mechanical properties such as tensile strength, hardness, and wear rate were analyzed. In the DCT-treated samples, tensile strength increased, reaching a peak of 343 MPa at 18 h, alongside increased hardness (128 HV) and a refined grain size of 9.58 µm, primarily due to elevated dislocation density and microstrain. At 18 h of soaking, DCT + HT resulted in improved structural stability, high hardness (149 HV), a fine grain size (7.42 µm), and the lowest wear rate (7.73 × 10⁻¹⁰ mm³/Nm), consistent with Hall–Petch strengthening. Electrical measurements revealed improved electron mobility (52.08 cm²/V·s) for samples soaked for 24 h in DCT + HT, attributed to increased crystallite size (39.9 nm), reduced lattice strain, and higher (111) texture intensity. SEM–EBSD analysis showed a substantial increase in low-angle grain boundaries (LAGBs) in DCT + HT-treated samples, correlating with enhanced electrical conductivity. Overall, an 18 h soaking duration was found to be optimal for both treatments. However, the strengthening mechanism in DCT + HT is influenced by grain boundary stabilization and thermal recovery and is different to DCT, which is strain-induced enhancement. Full article

The concept of “material effort” appears in continuum mechanics wherever the response of a material to the currently existing state of loads and boundary conditions loses its previous, predictable character. However, within the material, which still descriptively remains a continuous medium, new physical structures appear and new previously unused physical features of the continuum are activated. The literature is dominated by a simplified way of thinking, which assumes that all these states can be characterized and described by one and the same measure of effort—for metals it is the Huber–Mises–Hencky equivalent stress. Quantitatively, perhaps 90% of the literature is dedicated to this equivalent stress. The remaining authors, as well as the author of this paper, assume that there is no single universal measure of effort that would “fit” all operating conditions of materials. Each state of the structure’s operation may have its own autonomous measure of effort, which expresses the degree of threat from a specific destruction mechanism. In the current energy sector, we are increasingly dealing with “low-cycle thermal fatigue states”. This is related to the fact that large, difficult-to-predict renewable energy sources have been added. Professional energy based on coal and gas units must perform many (even about 100 per year) starts and stops, and this applies not only to the hot state, but often also to the cold state. The question arises as to the allowable shortening of start and stop times that would not to lead to dangerous material effort, and whether there are necessary data and strength characteristics for heat-resistant steels that allow their effort to be determined not only in simple states, but also in complex stress states. Do these data allow for the description of the material’s yield surface? In a previous publication, the author presented the results of tension and compression tests at elevated temperatures for two heat-resistant steels: St12T and 26H2MF. The aim of the current work is to determine the properties and strength characteristics of these steels in a pure torsion test at elevated temperatures. This allows for the analysis of the strength of power turbine components operating primarily on torsion and for determining which of the two tested steels is more resistant to high temperatures. In addition, the properties determined in all three tests (tension, compression, torsion) will allow the determination of the yield surface of these steels at elevated temperatures. They are necessary for the strength analysis of turbine elements in start-up and shutdown cycles, in states changing from cold to hot and vice versa. A modified testing machine was used for pure torsion tests. It allowed for the determination of the sample’s torsion moment as a function of its torsion angle. The experiments were carried out at temperatures of 20 °C, 200 °C, 400 °C, 600 °C, and 800 °C for St12T steel and at temperatures of 20 °C, 200 °C, 400 °C, 550 °C, and 800 °C for 26H2MF steel. Characteristics were drawn up for each sample and compared on a common graph corresponding to the given steel. Based on the methods and relationships from the theory of strength, the yield stress and torsional strength were determined. The yield stress of St12T steel at 600 °C was 319.3 MPa and the torsional strength was 394.4 MPa. For 26H2MH steel at 550 °C, the yield stress was 311.4 and the torsional strength was 382.8 MPa. St12T steel was therefore more resistant to high temperatures than 26H2MF. The combined data from the tension, compression, and torsion tests allowed us to determine the asymmetry and plasticity coefficients, which allowed us to model the yield surface according to the Burzyński criterion as a function of temperature. The obtained results also allowed us to determine the parameters of the Drucker-Prager model and two of the three parameters of the Willam-Warnke and Menetrey-Willam models. The research results are a valuable contribution to the design and diagnostics of power turbine components. Full article

Room-temperature rotary swaging was conducted on microalloyed high-ductility Mg-0.7Sm-0.3Zr alloy rods to investigate microstructural and mechanical variations across different swaging passes and radial positions. The results indicate that following room-temperature rotary swaging, the alloy rods exhibit a large number of tensile twins and low-angle grain boundaries, leading to significant grain refinement. After two swaging passes, the microstructure exhibits a pronounced radial gradient, characterized by progressively finer grain sizes from the core to the edge regions, with a hardness difference of 3.8 HV between the edge and the core. After five swaging passes, the grain size was refined from an initial 4.37 μm to 2.02 μm. The yield strength and ultimate tensile strength of the alloy increased from 157 MPa and 210 MPa in the extruded state to 292 MPa and 302 MPa, respectively. This observed strengthening is primarily attributed to grain refinement, dislocation hardening, and texture strengthening, with grain refinement playing the dominant role. The grain refinement process during rotary swaging can be divided into two stages: in the initial stage, coarse grains are subdivided by tensile twinning; in the later stage, high-stress-induced grain boundary bulging leads to new dynamic recrystallization, further refining the microstructure. Full article

This study systematically investigates the effects of heat treatment at 800–1000 °C on the microstructure and mechanical properties of 10 wt.% TiB₂@Ti/AlCoCrFeNi_2.1 eutectic high-entropy alloy matrix composites (EHEAMCs) prepared by vacuum hot-pressing sintering. The results show that the materials consist of FCC, BCC, TiB₂, and Ti phases, with a preferred orientation of the (111) crystal plane of the FCC phase. As the temperature increases, the diffraction peak of the BCC phase separates from the main FCC peak and its intensity increases, while the diffraction peak positions of the FCC and BCC phases shift at small angles. This is attributed to the diffusion of TiB₂@Ti from the grain boundaries into the matrix, where the Ti solid solution increases the lattice constant of the FCC phase. Microstructural observations reveal that the eutectic region transforms from lamellar to island-like structures, and the solid solution zone narrows. With increasing temperature, the Ti concentration in the solid solution zone increases, while the contents of elements such as Ni decrease. Element diffusion is influenced by binary mixing enthalpy, with Ti and B tending to solidify in the FCC and BCC phase regions, respectively. The mechanical properties improve with increasing temperature. At 1000 °C, the average hardness is 579.2 HV, the yield strength is 1294 MPa, the fracture strength is 2385 MPa, and the fracture strain is 19.4%, representing improvements of 35.5% and 24.9% compared to the as-sintered state, respectively, without loss of plasticity. The strengthening mechanisms include enhanced solid solution strengthening due to the diffusion of Ti and TiB₂, improved grain boundary strength due to the diffusion of alloy elements to the grain boundaries, and synergistic optimization of strength and plasticity. Full article

In the Direct Energy Deposition (DED) process, the deposited material experiences intricate thermo-mechanical processes. Subsequent thermal cycling can trigger Dynamic Recrystallization (DRX) under suitable conditions, with specific strain and temperature parameters facilitating grain refinement and homogenization. While prior research has examined the impact of thermal cycling in continuous wave (CW) lasers on DRX in 316 L stainless steel deposits, this study delves into the effects of pulsed wave (PW) laser thermal cycling on DRX. Here, the thermo-mechanical response to PW cyclic thermal loading is empirically assessed, and the evolution of microstructure, grain morphology, geometric dislocation density (GND), and misorientation map during PW DED of 316 L stainless steel is scrutinized. Findings reveal that DRX is activated between the 8th and 44th thermal cycles, with temperatures fluctuating in the range of 680 K–750 K–640 K and grains evolving within a 5.6%–6.2%–5.2% strain range. After 90 thermal cycles, the grain microstructure undergoes significant alteration. Throughout the thermal cycling, dynamic recovery (DRV) occurs, marked by sub-grain formation and low-angle grain boundaries (LAGBs). Continuous dynamic recrystallization (CDRX) accompanies discontinuous dynamic recrystallization (DDRX), with LAGBs progressively converting into high-angle grain boundaries (HAGBs). Elevated temperatures and accumulated strain drive dislocation movement and entanglement, augmenting GND. The study also probes the influence of frequency and duty cycle on grain microstructure, finding that low pulse frequency spurs CDRX, high pulse frequency favors DRV, and the duty cycle has minimal impact on grain microstructure under PW cyclic thermal load. Full article

The integration of tilted photovoltaic strings on large, flat roofs, typical of industrial and commercial buildings, raises complex design challenges, particularly regarding wind-induced loads. This study presents a comprehensive wind tunnel investigation aimed at evaluating the aerodynamic effects on rooftop PV strings under various representative configurations and the correlation between characteristic geometric parameters such as tilt angle, bottom clearance, row spacing, and wind direction. Following a literature review, a detailed 1:10 scaled model with geometric adjustment capabilities was developed and eventually tested in a boundary-layer wind tunnel. High-resolution pressure measurements were processed to derive force and moment resultants normalised by reference wind pressure. Envelopes of force/moment resultants are presented for each representative geometric configuration and for each wind exposure angle. The results present severe variations in local wind actions, particularly significant at the strings’ free ends and for oblique wind angles. The severe underestimation of local wind loads by standard codes is discussed. The findings underline the importance of detailed wind-load assessment for both new constructions and retrofits, suggesting that reliance solely on code provisions might result in unsafe designs. Full article

This study mainly investigates the high-temperature oxidation properties of GH3230 alloys fabricated by selective laser melting after different heat treatments. The SLM-formed GH3230 samples were subjected to solid-solution treatments at 1100 °C, 1230 °C, and 1320 °C for 30 min, followed by water quenching to room temperature. High-temperature oxidation tests were conducted at 1100 °C for 100 h. The results show that the as-built sample is composed of many columnar grains with cellular dendrites. Many M₂₃C₆ carbides are distributed in the interdendritic of the as-built sample. After solid-solution treatment, the dendrite structures completely disappear and the M₂₃C₆ carbides are transformed into M₆C carbides. The M₆C carbides dissolve completely as the solid-solution temperature increases to 1320 °C. The average grain size of GH3230 samples increased gradually with the increase in the solid-solution treatment temperature. However, the degree of recrystallization increased with the heat treatment temperature, leading to the transformation of low-angle grain boundaries into high-angle grain boundaries. A relatively dense oxide film, mainly including Cr₂O₃ and CrMn₂O_4, are formed in the GH3230 alloy after high-temperature oxidation. Suitable solid-solution treatment improves the high-temperature oxidation resistance of the GH3230 alloy, and the enhanced oxidation-resistance mechanisms are discussed. Full article

The use of high-resolution satellite stereo pairs for dense image matching is a core technology for the low-cost generation of large-scale digital surface models (DSMs). However, water areas in satellite imagery often exhibit weak texture characteristics. This leads to serious issues in reconstructing water surface DSMs with traditional dense matching methods, such as significant holes and abnormal undulations. These problems significantly impact the intelligent application of satellite DSM products. To address these issues, this study innovatively proposes a water region DSM reconstruction method, boundary plane-constrained surface water stereo reconstruction (BPC-SWSR). The algorithm constructs a water surface reconstruction model with constraints on the plane’s tilt angle and boundary, combining effective ground matching data from the shoreline and the plane constraints of the water surface. This method achieves the seamless planar reconstruction of the water region, effectively solving the technical challenges of low geometric accuracy in water surface DSMs. This article conducts experiments on 10 high-resolution satellite stereo image pairs, covering three types of water bodies: river, lake, and sea. Ground truth water surface elevations were obtained through a manual tie point selection followed by forward intersection and planar fitting in water surface areas, establishing a rigorous validation framework. The DSMs generated by the proposed algorithm were compared with those generated by state-of-the-art dense matching algorithms and the industry-leading software Reconstruction Master version 6.0. The proposed algorithm achieves a mean RMSE of 2.279 m and a variance of 0.6613 m² in water surface elevation estimation, significantly outperforming existing methods with average RMSE and a variance of 229.2 m and 522.5 m², respectively. This demonstrates the algorithm’s ability to generate more accurate and smoother water surface models. Furthermore, the algorithm still achieves excellent reconstruction results when processing different types of water areas, confirming its wide applicability in real-world scenarios. Full article

Proton-conducting ceramics have gained significant attention in various applications. Yttrium-doped barium cerium zirconate (BaCe_xZr_1−x−yY_yO_3–δ) is the state-of-the-art proton-conducting electrolyte but poses a major challenge because of its high sintering temperature. Sintering aids have been found to substantially reduce the sintering temperature of BaCe_xZr_1−x−yY_yO_3–δ. This work evaluates, for the first time, the impact of NiO and ZnO addition in three different loadings (1, 3, 5 mol%), via wet mechanical mixing, on the sintering and electrical properties of a low cerium-containing composition, BaCe_0.2Zr_0.7Y_0.1O_3–δ (BCZY). The sintering temperature remarkably dropped from 1600 °C (for pure BCZY) to 1350 °C (for NiOBCZY and ZnOBCZY) while achieving > 95% densification. In general, ZnO gave higher densification than NiO, the highest being 99% for 5 mol% ZnOBCZY. Dilatometric studies revealed that ZnOBCZY attained complete shrinkage at temperatures lower than NiOBCZY. Up to 650 °C, ZnO showed higher conductivity compared to NiO for the same loading, mostly due to a higher extent of Zn incorporation inside the BCZY lattice as seen from the BCZY peak shift to a lower Bragg’s angle in X-ray diffractograms, and the bigger grain sizes of ZnO samples compared to NiO captured in scanning electron microscopy. At any temperature, the variation in conductivity as a function of sintering aid concentration followed the orders 1 mol% > 3 mol% > 5 mol% (for ZnO) and 1 mol% < 3 mol%~5 mol% (for NiO). This difference in conductivity trends has been attributed to the fact that Zn fully dissolves into the BCZY matrix, unlike NiO which mostly accumulates at the grain boundaries. At 600 °C, 1 mol% ZnOBCZY showed the highest conductivity of 5.02 mS/cm, which is, by far, higher than what has been reported in the literature for a Ce/Zr molar ratio <1. This makes ZnO a better sintering aid than NiO (in the range of 1 to 5 mol% addition) in terms of higher densification at a sintering temperature as low as 1350 °C, and higher conductivity. Full article

Using numerical simulations, this study investigated the seismic response of concrete dams when subjected to near-fault obliquely incident P waves. For comparison, several near-fault pulse-like movements with different motion parameters were selected and decomposed into non-pulse residual components. A seismic input procedure for P wave oblique incidence was developed and verified based on the viscous-spring artificial boundary theory. A finite element model of a concrete dam system was used for nonlinear time history analyses. The damage and displacement responses were analyzed under pulse-like and non-pulse motions with incident angles varying from −90° to 90°. The response differences induced by the pulse characteristics incident direction were examined. The relationship between the seismic parameters and response indices was also determined to obtain the optimal seismic parameter describing the variation under different incident conditions. Moreover, the coupled effect of the pulse feature and oblique incidence on the dynamic response and seismic behavior was examined. Finally, a nonlinear three-dimensional predictive model was proposed based on the optimal seismic parameter S_a(T₁) and incident angle, exhibiting high correlation and accuracy. The results demonstrated that incident angles between 60° and 75° (with higher spectral acceleration values) intensified the dam damage and vibration when subjected to the oblique near-fault P waves, a crucial discovery for improving the seismic design and safety measure of concrete dams located in regions prone to near-fault seismic hazards. Full article

Air quality modeling has become a strategic area within data science, particularly in urban contexts where pollution exhibits high variability and nonlinear dynamics. This study provides a mathematical and computational comparison between two predictive paradigms: the classical Long Short-Term Memory (LSTM) model, designed for sequential analysis of time series, and the quantum model Quantum Support Vector Machine (QSVM), based on kernel methods applied in Hilbert spaces. Both approaches are applied to real PM2.5 concentration data collected at the Plaza Castilla monitoring station (Madrid) over the period 2017–2024. The LSTM model demonstrates moderate accuracy for smooth seasonal trends but shows limited performance in detecting extreme pollution events. In contrast, the QSVM achieves perfect binary classification through a quantum kernel based on angle encoding, with significantly lower training time and computational cost. Beyond the empirical results, this work highlights the growing potential of Quantum Artificial Intelligence as a hybrid paradigm capable of extending the boundaries of classical models in complex environmental prediction tasks. The implications point toward a promising transition to quantum-enhanced predictive systems aimed at advancing urban sustainability. Full article

Low-carbon lath martensite is highly susceptible to hydrogen embrittlement due to the presence of a high density of lath/block boundaries. In this study, I employ a continuum decohesion model to investigate the effects of varying hydrogen concentrations and tensile loads on the cohesive strength of low- and high-angle block boundaries. The thermodynamic properties of the cohesive zone are described using excess variables, which establish a link between atomistic energy calculations and the continuum model for gradual decohesion at a grain boundary. The aim of this study is to develop an in-depth understanding of how hydrogen affects the cohesive strength of block boundaries in a lath martensitic structure by integrating continuum and atomistic computational modeling and to apply the resulting insights to investigate the effects of varying hydrogen concentrations and tensile loads on interface decohesion. I incorporate hydrogen mobility and segregation at low- and high-angle twist boundaries in body-centered cubic (bcc) Fe to quantify the hydrogen-induced effects on progressive decohesion under tensile stress. A constant hydrogen flux through the free surfaces of a bicrystal containing a block boundary is imposed to simulate realistic boundary conditions. The results of the simulations show that, in the presence of hydrogen flux, separation across the block boundaries occurs at a tensile load significantly lower than the critical stress required for rupture in a hydrogen-free lath martensitic structure. Full article

To address the interception problem against maneuvering targets, this paper proposes a multi-agent cooperative guidance law based on a multi-directional interception formation. A three-dimensional agent–target engagement kinematics model is established, and a fixed-time observer is designed to estimate the target acceleration. By utilizing the agent-to-agent communication network, real-time exchange of motion state information among the agents is realized. Based on this, a control input along the line-of-sight (LOS) direction is designed to directly regulate the agent–target relative velocity, effectively driving the agent swarm to achieve time-to-go consensus within a fixed-time boundary. Furthermore, adaptive variable-power sliding mode control inputs are designed for both elevation and azimuth angles. By adjusting the power of the control inputs according to a preset sliding threshold, the proposed method achieves fast convergence in the early phase and smooth tracking in the latter phase under varying engagement conditions. This ensures that the elevation and azimuth angles of each agent–target pair converge to the desired values within a fixed-time boundary, forming a multi-directional interception formation and significantly improving the interception performance against maneuvering targets. Simulation results demonstrate that the proposed cooperative guidance law exhibits fast convergence, strong robustness, and high accuracy. Full article