Search Results (93)

Efficient prediction of aerodynamic loads on wind turbine blades under yawed inflow remains challenging due to the complexity of three-dimensional unsteady flow phenomena. In this work, a modified blade element momentum (BEM) method, incorporating multiple correction models, is systematically compared with high-fidelity computational fluid dynamics (CFD) simulations for the NREL Phase VI wind turbine across a range of inflow velocities (7–15 m/s) and yaw angles ($0^{°}$–${60}^{°}$). A normalized absolute error metric, referenced to experimental measurements, is employed to quantify prediction discrepancies at different yaw conditions, wind speeds, and spanwise blade locations. Results indicate that the corrected BEM method maintains good agreement with measurements under non-yawed attached flow, with errors within 2%, but its accuracy declines substantially in separated and yawed flow regimes, where errors can exceed 20% at high yaw angles (e.g., ${60}^{°}$) and low tip-speed ratios. CFD flow-field visualizations, including vorticity and Q-criterion iso-surfaces, reveal that yawed inflow strengthens vortex interactions on the leeward side and generates Coriolis-driven spanwise vortex structures, promoting stall progression from tip to root. These unsteady phenomena induce load fluctuations that are not captured by steady-state BEM formulations. Based on these insights, future studies could incorporate vortex structure and spanwise flow features extracted from CFD into unsteady correction models for BEM, enhancing prediction robustness under complex operating conditions. Full article

Traditional X-ray fluorescence computed tomography (XFCT) suffers from issues such as low photon collection efficiency, slow data acquisition, severe noise interference, and poor imaging quality due to the limitations of mechanical collimation. This study proposes to design an X-ray fluorescence imaging system based on bilateral Compton cameras and to develop an optimized reconstruction algorithm to achieve high-quality 2D/3D imaging of low-concentration samples (0.2% gold nanoparticles). A system equipped with bilateral Compton cameras was designed, replacing mechanical collimation with “electronic collimation”. The traditional LM-MLEM algorithm was optimized through improvements in data preprocessing, system matrix construction, iterative processes, and post-processing, integrating methods such as Total Variation (TV) regularization (anisotropic TV included), filtering, wavelet-domain constraints, and isosurface rendering. Successful 2D and 3D reconstruction of 0.2% gold nanoparticles was achieved. Compared with traditional algorithms, improvements were observed in convergence, stability, speed, quality, and accuracy. The system exhibited high detection efficiency, angular resolution, and energy resolution. The Compton camera-based XFCT overcomes the limitations of traditional methods; the optimized algorithm enables low-noise imaging at ultra-low concentrations and has potential applications in early cancer diagnosis and material analysis. Full article

This paper investigates the influence of airfoil parameters on the cavitation performance of water jet propulsion pumps through numerical simulation methods. The effects of a varying inlet pressure and different airfoil structures on the critical net positive suction head (NPSH), head, and efficiency were systematically studied. Subsequently, the impact pattern of the airfoil structure on the cavitation performance was analyzed. The results demonstrate that the NACA0009-16_0004-16 airfoil exhibited the lowest required NPSH and superior cavitation resistance relative to the other tested airfoils. Nevertheless, the NACA0009-13_0004-13 airfoil demonstrated an optimal comprehensive performance, balancing the efficiency, head, and cavitation resistance. By extracting a water velocity isosurface of 23.6 m/s, we further investigated the flow characteristics of the suction surfaces of different airfoils at different cavitation conditions and found that the cavitation mainly includes TIP cavitation and sheet cavitation. With an increasing cavitation intensity, the sheet cavitation region progressively develops axially from the blade tip towards the blade outlet, extends radially from the shroud to the hub, and eventually nearly extends over the entire blade surface. The area of the TIP cavitation also expands, spreading downward in the same direction as the impeller rotation. The velocity vector exhibits a significantly higher density near the shroud and blade tips, suggesting potential flow separation and complex vortex structures in these regions. Near the blade leading edge, the water velocity isosurface area contracts, whereas near the trailing edge, it expands. These alterations indicate that the cavitation development modifies the flow field velocity distribution and adversely affects the impeller performance. This study establishes a theoretical foundation and offers practical guidelines for the multi-objective collaborative design of water jet propulsion pumps. Full article

Twin-screw compressors (TSCs) are widely used in various industries. Their performance is influenced by several parameters, such as rotor profiles, clearance gaps, operating speed, and thermal effects. Traditionally, optimizing these parameters relied on experimental methods, which are costly and time-consuming. However, advancements in computational tools, such as Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA), have revolutionized compressor analysis. This study presents a CFD analysis of a specific model of a TSC in a 5 male/6 female lobe configuration using the SolidWorks Flow Simulation environment—an approach not traditionally applied to such positive displacement machines. The results visually present internal flow trajectories, fluid velocities, pressure distributions, temperature gradients, and leakage behaviors with high spatial and temporal resolution. Additionally, torque fluctuations and isosurface visualizations revealed insights into mechanical loads and flow behavior. The proposed method allows for relatively easy adaptation to different TSC configurations and can also be a useful tool for engineering and educational purposes. Full article

Point defects in two-dimensional materials such as MoS₂ can critically impact their electronic and optoelectronic properties. Precise identification of these defects is essential for understanding defect physics and device performance. In this work, we acquire high-resolution scanning tunneling microscopy (STM) images of monolayer MoS₂ and apply the Segment Anything Model (SAM) to automatically segment possible defect regions in the STM images. Each segmented region is then classified by a convolutional neural network (CNN) architecture into defect categories. This deep learning pipeline is trained on augmented STM image data and evaluated against manual annotations. The model achieves a classification accuracy of 95.06% on a modest dataset comprising merely 198 samples, demonstrating its robustness despite limited data availability. We also perform density functional theory (DFT) calculations of representative defect structures to support interpretation of the STM features. Charge density isosurfaces of the DFT models reveal localized mid-gap states associated with sulfur vacancies, consistent with STM observations. The integration of SAM segmentation, CNN classification, and DFT modeling provides a comprehensive approach to quantify defect populations in MoS₂. These results show the potential of combining data-driven image analysis with physics-based modeling to accelerate defect characterization in 2D materials. Full article

Reconstructing neuronal morphology from microscopy image stacks is essential for understanding brain function and behavior. While existing methods are capable of tracking neuronal tree structures and creating membrane surface meshes, they often lack seamless processing pipelines and suffer from stitching artifacts and reconstruction inconsistencies. In this study, we propose a new approach utilizing implicit neural representation to directly extract neuronal isosurfaces from raw image stacks by modeling signed distance functions (SDFs) with multi-layer perceptrons (MLPs). Our method accurately reconstructs the tubular, tree-like topology of neurons in complex spatial configurations, yielding highly precise neuronal membrane surface meshes. Extensive quantitative and qualitative evaluations across multiple datasets demonstrate the superior reliability of our approach compared to existing methods. The proposed method achieves a volumetric reconstruction accuracy of up to 98.2% and a volumetric IoU of 0.90. Full article

In this paper, the geometric effect on flow structure and mixing performance of two miscible fluids (deionized water and glycerol) in a planetary centrifugal mixer (PCM) during the spin-up is numerically evaluated, using the OpenFOAM interMixingFoam solver. Six different aspect ratios, specifically 0.5, 1, 1.25, 1.5, 2, and 2.5, are considered. The flow structure in each geometric configuration is illustrated by the liquid interface and vorticity isosurface represented by the Q criterion, while the mixing performance is evaluated in terms of a mixing index $MI$. As the aspect ratio increases from small to large, $MI$ first increases and then decreases. The peak $MI$ at the end of spin-up reaches 0.196 for the aspect ratio of 1.25, rather than the other five aspect ratios in our study. The mechanism analysis shows that under an aspect ratio of 1.25, the vortex structure is most violently dissipated, the interface collapse degree is the largest, and the low-velocity region volume is the smallest, which enhances the chaotic convection mixing. Full article

Rice is a staple food for nearly half the global population and, with rising living standards, the demand for high-quality grain is increasing. Chalkiness, a key determinant of appearance quality, requires accurate detection for effective quality evaluation. While traditional 2D imaging has been used for chalkiness detection, its inherent inability to capture complete 3D morphology limits its suitability for precision agriculture and breeding. Although micro-CT has shown promise in 3D chalk phenotype analysis, high-throughput automated 3D detection for multiple grains remains a challenge, hindering practical applications. To address this, we propose a high-throughput 3D chalkiness detection method using micro-CT and VSE-UNet. Our method begins with non-destructive 3D imaging of grains using micro-CT. For the accurate segmentation of kernels and chalky regions, we propose VSE-UNet, an improved VGG-UNet with an SE attention mechanism for enhanced feature learning. Through comprehensive training optimization strategies, including the Dice focal loss function and dropout technique, the model achieves robust and accurate segmentation of both kernels and chalky regions in continuous CT slices. To enable high-throughput 3D analysis, we developed a unified 3D detection framework integrating isosurface extraction, point cloud conversion, DBSCAN clustering, and Poisson reconstruction. This framework overcomes the limitations of single-grain analysis, enabling simultaneous multi-grain detection. Finally, 3D morphological indicators of chalkiness are calculated using triangular mesh techniques. Experimental results demonstrate significant improvements in both 2D segmentation (7.31% improvement in chalkiness IoU, 2.54% in mIoU, 2.80% in mPA) and 3D phenotypic measurements, with VSE-UNet achieving more accurate volume and dimensional measurements compared with the baseline. These improvements provide a reliable foundation for studying chalkiness formation and enable high-throughput phenotyping. Full article

Ultra-low-carbon, high-strength steels have gained significant attention due to their exceptional mechanical properties. To enhance the performance of the steel, understanding the precipitation behavior of strengthening precipitates is crucial. In this study, the precipitation behavior of ultra-low-carbon high-strength steel strengthened by nanoscale copper (Cu)-rich precipitates (CRPs) and carbonitride (CN) atomic clusters was characterized using atom-probe tomography after tempering at 400, 450, 600, and 650 °C for 2 h. The results revealed that the nanoscale copper CRPs and the CN atomic clusters were the main strengthening precipitates. The CRPs, enriched only in Cu, were observed at 400 °C. Segregation of nickel (Ni) and manganese (Mn) to the CRPs occurred at 450 °C, and the number densities of CRPs achieved the maximum value, leading to the highest strengthening effects. The size of the CRPs increased with increasing temperature; however, the size of the clusters of the carbide-forming atoms remained at almost ~1.6 nm. At 650 °C, the concentration of Cu, Ni, and Mn atoms in the CRPs was about 85.4, 4.5, and 4 at.%, respectively; however, that of Fe decreased significantly. In the lath boundaries, the size of 10% C and 0.4% C iso-surfaces was relatively larger than that in the matrix. In a reverted austenite region at 600 °C, the concentration of Ni in the reverted austenite, CRPs, and matrix was about 15, 2.5, and 2.5 at.%, respectively. Full article

Flow around clustered cylinders is widely encountered in engineering applications such as wind energy systems, pipeline transport, and marine engineering. To investigate the hydrodynamic performance and vortex dynamics of multiple cylinders under forced vibration at low Reynolds numbers, with a focus on understanding the interference characteristics in various configurations, this study is based on a self-developed radial basis function iso-surface ghost cell computing platform, which improves the implicit iso-surface interface representation method to track the moving boundaries of multiple cylinders, and employs a self-constructed CPU/GPU heterogeneous parallel acceleration technique for efficient numerical simulations. This study systematically investigates the interference characteristics of multiple cylinder configurations across various parameter domains, including spacing ratios, geometric arrangements, and oscillation modes. A quantitative analysis of key parameters, such as aerodynamic coefficients, dimensionless frequency characteristics, and vorticity field evolution, is performed. This study reveals that, for a dual-cylinder system, there exists a critical gap ratio between X/D = 2.5 and 3, which leads to an increase in the lift and drag coefficients of both cylinders, a reduction in the vortex shedding periodicity, and a disruption of the wake structure. For a three-cylinder system, the lift and drag coefficients of the two upstream cylinders decrease with increasing spacing. On the other hand, this increased spacing results in a rise in the drag of the downstream cylinder. In the case of a four-cylinder system, the drag coefficients of the cylinders located on either side of the flow direction are relatively high. A significant increase in the lift coefficient occurs when the spacing ratio is less than 2.0, while the drag coefficient of the downstream cylinder is minimized. The findings establish a comprehensive theoretical framework for the optimal configuration design and structural optimization of multicylinder systems, while also providing practical guidelines for engineering applications. Full article

The exponential increase in population has led to a shortage of land for constructing tall buildings, resulting in the need to design irregular structures due to the limited availability of land. Assessing the impact of wind-generated effects can be achieved utilizing the Computational Fluid Dynamics (CFD) method, specifically employing ANSYS. This involves resolving the intricate fluid dynamics problem through numerical analysis using the ANSYS software. The validation study is performed on a standard shape-building model where the result is compared with experimental values and other international standards. The outcomes are presented in a graphical format, such as mean pressure, streamline, and pressure distribution in the vertical and horizontal planes. This research has studied four building models with equal area and height. Models A and B have regular shapes, while Models C and D exhibit an irregular ‘Y’ shape. The wind incidence angle was adjusted between 0 and 180 degrees at every 15-degree interval. The results were validated to ensure the accuracy of the numerical techniques employed. This involved performing validation and grid sensitivity analyses, which showed consistent results comparable to experimental data and established international standards. Model-C irregular-shaped buildings demonstrated the highest efficiency in minimizing wind loads among the building models examined in this study. Full article

In this study, a fish scale structure with low viscous drag was proposed and applied to the suction surface of a compressor cascade to reduce total pressure loss and suppress corner separation, a key source of compressor inefficiency. By using CFD simulations, the biomimetic structure was identified and integrated into the cascade design. To evaluate its effects, we analyzed secondary flow structures using 2D projected streamlines, axial velocity density (AVD), and vortex visualization techniques. The results show that the fish scale structure effectively reduces the volume of low-energy fluid by 18.36% and decreases total pressure loss at the outlet by 3.5%. Additionally, the AVD iso-surface proved instrumental in identifying low-energy fluid regions, which correlate closely with total pressure loss distribution. These findings highlight the potential of biomimetic-inspired designs to improve compressor performance by mitigating corner separation and reducing flow losses. Full article

Triiodide salts are of interest for a variety of applications, including but not limited to electrochemical and photochemical devices, as antimicrobials and disinfectants, in supramolecular chemistry and crystal engineering, and in ionic liquids and deep eutectic solvents. Our work has focused on the design of salt–solvate cocrystals and deep eutectic solvents in which the triiodide anion interacts as a halogen bond acceptor with organoiodine molecules. To understand structure–property relationships in these hybrid materials, it is essential to have benchmark structural and physical data for the parent triiodide salt component. Herein, we report the structure and thermal properties of eight new triiodide salts, three of which exhibit polymorphism: tetrapentylammonium triiodide (1a and 1b), tetrahexylammonium triiodide (2), trimethylphenylammonium triiodide (3), trimethylbenzylammonium triiodide (4), triethylbenzylammonium triiodide (5), tri-n-butylbenzylammonium triiodide (6), 3-methylbenzothizolium triiodide (7a and 7b), and 2-chloro-1-methylpyridinium triiodide (8a and 8b). The structural features of the triiodide anion, Raman spectroscopic analysis, and melting and thermal decomposition behavior of the salts, as well as a computational analysis of the polymorphs, are discussed. The polymorphic pairs here are distinguished by symmetric versus asymmetric triiodide anions, as well as different packing patterns. Computational analyses revealed more subtle differences in their isosurface plots. Importantly, this study provides reference data for these new triiodide salts for comparison to hybrid cocrystals and deep eutectic solvents formed from their combination with various organoiodines. Full article

This study addresses the features of the internal structure of the geological layers adjacent to the Polychrome Hall ceiling of the Cave of Altamira (Spain) and their link to the distribution of moisture and geological discontinuities mainly as fractures, joints, bedding planes and detachments, using 3D Ground Penetrating Radar (GPR) mapping. In this research, 3D GPR data were collected with 300 MHz, 800 MHz and 1.6 GHz center frequency antennas. The data recorded with these three frequency antennas were combined to further our understanding of the layout of geological discontinuities and how they link to the moisture or water inputs that infiltrate and reach the ceiling surface where the rock art of the Polychrome Hall is located. The same 1 × 1 m² area was adopted for 3D data acquisition with the three antennas, obtaining 3D isosurface (isoattribute-surface) images of internal distribution of moisture and structural features of the Polychrome Hall ceiling. The results derived from this study reveal significant insights into the overlying karst strata of Polychrome Hall, particularly the interface between the Polychrome Layer and the underlying Dolomitic Layer. The results show moisture patterns associated with geological features such as fractures, joints, detachments of strata and microcatchments, elucidating the mechanisms driving capillary rise and water infiltration coming from higher altitudes. The study primarily identifies areas of increased moisture content, correlating with earlier observations and enhancing our understanding of water infiltration patterns. This underscores the utility of 3D GPR as an essential tool for informing and putting conservation measures into practice. By delineating subsurface structures and moisture dynamics, this research contributes to a deeper analysis of the deterioration processes directly associated with the infiltration water both in this ceiling and in the rest of the Cave of Altamira, providing information to determine its future geological and hydrogeological evolution. Full article

Tutton salts form an isomorphic crystallographic family that has been intensively investigated in recent decades due to their attractive thermal and optical properties. In this work, we report four mixed Tutton crystals (obtained by the slow solvent evaporation method) with novel chemical compositions based on K₂V_1−xM’_x(SO₄)₂(H₂O)₆, where M’ represents Co, Ni, Cu, and Zn, aiming at thermochemical energy storage applications. Their structural and thermal properties were correlated with theoretical studies. The crystal structures were solved by powder X-ray diffraction using the Rietveld method with similar compounds. All of the samples crystallized in monoclinic symmetry with the P2₁/a-space group. A detailed study of the intermolecular interactions based on Hirshfeld surfaces and 2D fingerprint mappings showed that the main interactions arise from hydrogen bonds (H∙∙∙O/O∙∙∙H) and dipole–ion (K∙∙∙O/O∙∙∙K). On the other hand, free space percentages in the unit cells determined by electron density isosurfaces presented low values ranging from 0.53 (V–Ni) to 0.81% (V–Cu). The thermochemical findings from thermogravimetry, a differential thermal analysis, and differential scanning calorimetry indicate that K₂V_0.47Ni_0.53(SO₄)₂(H₂O)₆ salt is the most promising among mixed salts (K₂V_1−xM’_x(SO₄)₂(H₂O)₆) for heat storage potential, achieving a low dehydration temperature (≈85 °C), high dehydration enthalpy (≈360 kJ/mol), and high energy storage density (≈1.84 GJ/m³). Full article