Search Results (206)

Reconstructing hand and object shapes from a single view during interaction remains challenging due to severe mutual occlusion and the need for high physical plausibility. To address this, we propose a novel framework for hand–object interaction reconstruction based on holistic, multi-stage collaborative optimization. Unlike methods that process hands and objects independently or apply constraints as late-stage post-processing, our model progressively enforces physical consistency and geometric accuracy throughout the entire reconstruction pipeline. Our network takes an RGB-D image as input. An adaptive feature fusion module first combines color and depth information to improve robustness against sensing uncertainties. We then introduce structural priors for 2D pose estimation and leverage texture cues to refine depth-based 3D pose initialization. Central to our approach is the iterative application of a dense mutual attention mechanism during sparse-to-dense mesh recovery, which dynamically captures interaction dependencies while refining geometry. Finally, we use a Signed Distance Function (SDF) representation explicitly designed for contact surfaces to prevent interpenetration and ensure physically plausible results. Through comprehensive experiments, our method demonstrates significant improvements on the challenging ObMan and DexYCB benchmarks, outperforming state-of-the-art techniques. Specifically, on the ObMan dataset, our approach achieves hand CD_h and object CD_o metrics of 0.077 cm² and 0.483 cm², respectively. Similarly, on the DexYCB dataset, it attains hand CD_h and object CD_o values of 0.251 cm² and 1.127 cm², respectively. Full article

Accurate vertical distribution of fire-induced heat fluxes in the atmosphere is critical for realistic coupled fire–atmosphere simulations. In response to concerns raised by Shamsaei et al. (2023) regarding potential energy conservation issues in the WRF-SFIRE heat distribution scheme, this study first conducts a comprehensive theoretical analysis, demonstrating that the original exponential formulation exhibits negligible error under typical domain configurations. Then, it introduces a novel formulation, called the Versatile Energy-Conservative Distribution scheme, that rigorously guarantees energy conservation while providing enhanced flexibility in specifying vertical distribution profiles. The proposed method accommodates multiple profiles, including exponential, Gaussian, and gamma, and enables the independent treatment of surface and canopy heat fluxes, thereby yielding a more flexible representation of fire heat fluxes. Numerical evaluations on both fine and coarse non-uniform meshes confirm that the new formulation maintains perfect energy balance across various configurations and overcomes the limitations observed in other schemes, such as the truncated Gaussian approach. These advancements not only refute previous claims of significant energy misrepresentation but also offer a robust and flexible framework intended to improve the representation of fire–atmosphere interactions in numerical models. Full article

Numerical modelling of airflow in underground mines is gaining importance in modern ventilation system design and safety assessment. Computational Fluid Dynamics (CFD) simulations enable detailed analyses of air movement, contaminant dispersion, and heat transfer, yet their reliability depends strongly on the accuracy of the geometric representation of excavations. Raw point cloud data obtained from laser scanning of underground workings are typically irregular, noisy, and contain discontinuities that must be processed before being used for CFD meshing. This study presents a methodology for automatic segmentation and regularization of large-scale point cloud data of underground excavation systems. The proposed approach is based on skeleton extraction and trajectory analysis, which enable the separation of excavation networks into individual tunnel segments and crossings. The workflow includes outlier removal, alpha-shape generation, voxelization, medial-axis skeletonization, and topology-based segmentation using neighbor relationships within the voxel grid. A proximity-based correction step is introduced to handle doubled crossings produced by the skeletonization process. The segmented sections are subsequently regularized through radial analysis and surface reconstruction to produce uniform and watertight models suitable for mesh generation in CFD software (Ansys 2024 R1). The methodology was tested on both synthetic datasets and real-world laser scans acquired in underground mine conditions. The results demonstrate that the proposed segmentation approach effectively isolates single-line drifts and crossings, ensuring continuous and smooth geometry while preserving the overall excavation topology. The developed method provides a robust preprocessing framework that bridges the gap between point cloud acquisition and numerical modelling, enabling automated transformation of raw data into CFD-ready geometric models for ventilation and safety analysis of complex underground excavation systems. Full article

The Trepponti bridge in Comacchio (Italy) is a significant masonry landmark characterised by a complex geometry. Its structure comprises five irregularly connected segments, creating pronounced geometric discontinuities. Accurately modelling this configuration is challenging due to the highly complex mechanical behaviour of masonry. This study presents a robust computational strategy for the nonlinear structural assessment of such heritage bridges. The methodology integrates a parametric meshing environment (PoliBrick plugin) with nonlinear finite-element analysis in Straus7. An initial discretisation is generated through PoliBrick, undergoes geometric optimisation to produce an analysis-ready model. The bridge is homogeneously modelled and meshed through macro-blocks obeying a Mohr–Coulomb failure criterion. Material parameters are defined according to the LC1 knowledge level stipulated by the Italian structural code. Differential settlement scenarios are simulated by imposing controlled vertical displacements on individual and paired piers. This approach enables evaluation of structural displacement, stress distribution, and crack propagation. The analyses reveal a markedly asymmetric structural response, identifying two specific piers as critical vulnerable elements. The proposed framework demonstrates that parametric meshing effectively reconciles accurate geometric representation with computational efficiency. It offers a practical tool for guiding the conservation and safety evaluation of irregular vaulted masonry bridges. Full article

Fuel cells offer a promising route to eliminating in-flight emissions from regional aviation, but certification requires proof that stacks can withstand the vibration and shock environment of turboprop aircraft. As part of the EU-funded NEWBORN project, we combined detailed finite element modeling with shaker tests to evaluate the vibration immunity of PowerCell Group’s prototype stack. The numerical model combined an orthotropic, two-zone 3D mesh of the cell package with reduced-order representations of plates, compression bands, disc springs and the mounting cage. The assembled stack was excited between 10 and 300 Hz using pseudo-random and sine-sweep inputs up to 2.0 g, from which 54 frequency response functions were obtained. The tuned model accurately reproduced the first global modes and captured the overall dynamic behavior with good, though not perfect, agreement. The combined numerical–experimental methodology therefore offers a framework for refining test campaigns and delivering early, qualitative evidence of vibration immunity in fuel cell stacks destined for flight. Full article

Free/Libre and Open-Source Hardware requires documentation that ensures replicability and accessibility for both experts and non-experts. Existing tools for generating assembly animations are often difficult to use, require specialized knowledge, and are poorly suited for instructional or workshop contexts. This paper addresses this gap by proposing a method for generating implosion-style CAD animations that separates transformation logic from geometry. The method enables fast, low-effort creation of animations through either manual grouping or large language model (LLM) automation. The approach is validated through a web-based implementation that can produce complete animations within minutes using mesh or boundary-representation input. The system supports step-wise playback, interactive part grouping, and export of vector-based views for technical documentation. Evaluation includes nine models ranging from simple parts to assemblies with over 1400 components. The system successfully generated animations for all models, with the LLM-based schema generation achieving high sequence coherence and coverage in most cases. The proposed method enables scalable, reusable, and version-controlled animation workflows that are particularly suited for open-source documentation, manufacturing education, and distributed design environments. Full article

Background/Objectives: Nowadays, the importance of educating and ensuring communication with patients is also emphasized in groups of patients undergoing anesthesia. The safety and quality of services provided to this group of patients may be related to the information received by them. Therefore, the aim of this review is to explore the patients’ knowledge observed globally and discuss the potential influencing factors. Methods: This review was based on a search of PubMed using MeSH terms and keywords. Additionally, citation searching for relevant articles was performed. Results: The related literature illustrates high heterogeneity among studies with varying results. The knowledge concerning appropriate recognition of anesthesiologists as doctors ranged from 32,8% to 90.5%. However, most studies concluded that patients’ knowledge regarding anesthesia is poor. There was no homogenous pattern regarding the possible impact of age, sex, education, profession or previous anesthesia on patients’ knowledge. Patients’ most common concern was not waking up after anesthesia. The response to patients’ varying knowledge may be the use of educational aids including online alternatives. This approach limits the use of medical resources and may help to alleviate patients’ anxiety. Conclusions: Future studies may focus on a thorough analysis of knowledge in a representable population followed by an observation of aspects shaping the level of education. The precise influence of patients’ education on anesthesia outcomes is yet to be determined. However, further investigation may bring appropriate clinical guidance and help to ensure the best quality of anesthesia services is provided. Full article

Three-dimensional Human Reconstruction from Monocular Vision is a key technology in Virtual Reality and digital humans. It aims to recover the 3D structure and pose of the human body from 2D images or video. Current methods for dynamic 3D reconstruction of the human body, which are based on monocular views, have low accuracy and remain a challenging problem. This paper proposes a fast reconstruction method based on Instant Human Model (IHM) generation, which achieves highly realistic 3D reconstruction of the human body in arbitrary poses. First, the efficient dynamic human body reconstruction method, InstantAvatar, is utilized to learn the shape and appearance of the human body in different poses. However, due to its direct use of low-resolution voxels as canonical spatial human representations, it is not possible to achieve satisfactory reconstruction results on a wide range of datasets. Next, a voxel occupancy grid is initialized in the A-pose, and a voxel attention mechanism module is constructed to enhance the reconstruction effect. Finally, the Instant Human Model (IHM) method is employed to define continuous fields on the surface, enabling highly realistic dynamic 3D human reconstruction. Experimental results show that, compared to the representative InstantAvatar method, IHM achieves a 0.1% improvement in SSIM and a 2% improvement in PSNR on the PeopleSnapshot benchmark dataset, demonstrating improvements in both reconstruction quality and detail. Specifically, IHM, through voxel attention mechanisms and Mesh adaptive iterative optimization, achieves highly realistic 3D mesh models of human bodies in various poses while ensuring efficiency. Full article

This study introduces the Graph-Structured Physics-Informed DeepONet (GS-PI-DeepONet), a novel neural network framework designed to address the challenges of solving parametric Partial Differential Equations (PDEs) in structural analysis, particularly for problems with complex geometries and dynamic boundary conditions. By integrating Graph Neural Networks (GNNs), Deep Operator Networks (DeepONets), and Physics-Informed Neural Networks (PINNs), the proposed method employs graph-structured representations to model unstructured Finite Element (FE) meshes. In this framework, nodes encode physical quantities such as displacements and loads, while edges represent geometric or topological relationships. The framework embeds PDE constraints as soft penalties within the loss function, ensuring adherence to physical laws while reducing reliance on large datasets. Extensive experiments have demonstrated the GS-PI-DeepONet’s superiority over traditional Finite Element Methods (FEMs) and standard DeepONets. For benchmark problems, including cantilever beam bending and Hertz contact, the model achieves high accuracy. In practical applications, such as stiffness analysis of a recliner mechanism and strength analysis of a support bracket, the framework achieves a 7–8 speed-up compared to FEMs, while maintaining fidelity comparable to FEM, with R² values reaching up to 0.9999 for displacement fields. Consequently, the GS-PI-DeepONet offers a resolution-independent, data-efficient, and physics-consistent approach for real-time simulations, making it ideal for rapid parameter sweeps and design optimizations in engineering applications. Full article

The optimization design of the face gear split-torque transmission (FGST) consumes a lot of modeling and calculation costs. Implementing closed-loop design for data generation optimization improves system design efficiency. However, there are two challenges: firstly, the lack of a mapping method for the tooth surface modification parameters to discrete mesh coordinates, which makes it difficult to generate data samples; secondly, a quantitative representation method for evaluating contact performance has not been proposed, making it difficult to achieve quantitative design. In this paper, we propose a fast integration method of analysis and optimization to the contact performance design of a face gear split-torque transmission. An efficient mapping method from FGST geometric parameters to discrete grids is established to achieve fast data generation. A quantitative evaluation method for contact performance based on image processing has been proposed to achieve rapid optimization. The time required for modeling and optimization is shortened to less than 0.5 h, significantly improving design efficiency. Full article

Adjoint-based mesh adaptation method serves as an effective approach to improve the predictive accuracy of aerodynamic characteristics. However, viscous boundary layer grids often encounter issues such as hanging nodes, negative volumes, and directional constraints during adaptation, significantly limiting their practical application. To address these challenges, this study proposes an innovative polyhedral conversion strategy. Cells containing hanging nodes resulting from refinement are converted into polyhedra, effectively eliminating topological constraints between adjacent mesh elements. This approach is combined with surface-conforming projection and distance function-based mesh deformation techniques to ensure precise geometric representation and high mesh quality after adaptation. Numerical experiments demonstrate that the proposed viscous boundary layer mesh adaptation strategy successfully handles both refinement and coarsening of boundary layer grids. In a typical high-angle-of-attack case for the NACA0012 airfoil, the adjoint-based mesh adaptation method reduced lift coefficient error from 4.21% to 0.30% after four adaptation cycles. For the CHN-F1 low-aspect-ratio flying wing configuration, the method reduced the lift discrepancy from 10.05% to 6.65% at 40° angle of attack. The polyhedral conversion approach effectively resolves common challenges in viscous boundary layer mesh adaptation, providing a robust solution for high-fidelity prediction of aerodynamic characteristics with significantly improved accuracy. Full article

Reliable simulations of any flow require proper preservation of the fundamental principles governing the mechanics of its motion, whether in differential or integral form. When these principles are solved in differential form, discretization schemes introduce errors by transforming the continuous physical domain into a discrete representation that only approximates it. This paper analyzes the numerical performance of the solver for supersonic chemically active flows, rhoCentralRfFoam, using integral conservation principles of mass, momentum, energy, and chemical species as a validation tool in a classical test case with a highly refined mesh under nonlinear pre-established reference conditions. The analysis is conducted on this specific test case; however, the methodology presented here can be applied to any problem under study. It may serve as an a posteriori verification tool or be integrated into the solver’s workflow, enabling automatic verification of conservation at each time step. The resulting deviations are evaluated, and it is observed that the numerical errors remain below $0.25\%$, even in cases with a high degree of nonlinearity. These results provide preliminary validation of the solver’s accuracy, as well as its ability to capture physically consistent solutions using only information generated internally by the solver for validation. This represents a significant advantage over validation methods that require external comparison with reference solutions, numerical benchmarks, or exact solutions. Full article

Turbulence and wind gusts pose significant risks to the safety and efficiency of UAVs (uncrewed aerial vehicles) in urban environments. In these settings, wind dynamics are strongly influenced by interactions with buildings and terrain, giving rise to small-scale phenomena such as vortex shedding and gusts. These wind speed oscillations generate unsteady forces that can destabilise UAV flight, particularly for small vehicles. Additionally, predicting their formation requires high-resolution Computational Fluid Dynamics (CFD) models, as current weather forecasting tools lack the resolution to capture these phenomena. However, such models require 3D representations of study areas with high geometric consistency and detail, which are not available for most cities. To address this issue, this work introduces an automated methodology for urban CFD mesh generation using open-source data. The proposed method generates error-free meshes compatible with OpenFOAM and includes tools for geometry modification, enhancing solver convergence and enabling adjustments to mesh complexity based on computational resources. Using this approach, CFD simulations are conducted for the city of Ourense, followed by an analysis of their impact on UAV operations and the integration of the system into a trajectory optimisation framework. The CFD model is also validated using experimental anemometer measurements. Full article

The rising urbanization and climate change have increased pluvial flood risks, especially in highly urbanized areas. This study focuses on the Lake Ganzirri area in Messina, Italy, where street-level floods have raised concerns for infrastructure resilience and public safety. This study aims to explore how to effectively represent key urban features, emphasizing buildings and low-impact development/sustainable urban drainage systems (LID/SUDS). For the buildings, a combination of referred approaches to represent buildings is compared against the widely used method to represent buildings as voids in a 2D mesh, ignoring them in the water balance calculations. For the LID/SUDS control elements, a 2D representation is presented and compared against the widely used 1D approach to model such elements. The study uses three well-known software packages—EPA-SWMM 5.2, HEC-RAS 6.2, and InfoWorks ICM 2021.9—applied to the Lake Ganzirri area, to explore the representation of buildings using the building void method (available in InfoWorks ICM 2021.9) against the proposed method (in HEC-RAS 6.2) to replicate runoff flow over a 2D model of a highly urbanized area. From scenario S0, three more scenarios were derived: S1 (S0 with pluvial drainage network), S2 (S1 with LID/SUDS control elements), and S3 (S0 with 2D representation of LID/SUDS), which were then compared against using four comparison schemes. Results show that the proposed method for representing buildings computed the propagation of the runoff comparable to when the building void method is used, with some shortcomings regarding mesh adjustments and computational times. Regarding the 2D representation of LID/SUDS, the effects were unperceivable on water depth maps (reduction in water depths of 1.5 mm on average for all the rainfall events). Still, they were reflected in the increase of 62% of the infiltration volume on average of all the rainfall scenarios and a decrease of 9.1% of water flowing outside the 2D area, therefore replicating the effect of capturing water. Full article

Floods are among the most frequent and destructive natural hazards worldwide, with increasingly severe socioeconomic consequences due to rapid urbanization, land use changes, and climate variability. While the combination of Geographic Information Systems (GIS) with models such as HEC-RAS has been extensively explored for flood risk management, many existing studies remain limited to one-dimensional (1D) models or use coarse-resolution terrain data, often underestimating flood risk and failing to produce critical multivariate flood characteristics in densely built urban areas. This study applies a two-dimensional (2D) hydraulic modeling framework in HEC-RAS combined with GIS-based spatial analysis, using a high-resolution (1 × 1 m) LiDAR-derived Digital Terrain Model (DTM) and a hybrid mesh refined between 2 × 2 m and 8 × 8 m, with the main contributions represented by the specific application context and methodological choices. A key methodological aspect is the direct integration of synthetic hydrographs with defined exceedance probabilities (10%, 1%, and 0.1%) into the 2D model, thereby reducing the need for extensive hydrological simulations and defining a data-driven approach for resource-constrained environments. The primary novelty is the application of this high-resolution urban modeling framework to a Romanian urban–peri-urban setting, where detailed hydrological observations are scarce. Unlike previous studies in Romania, this approach applies detailed channel and floodplain discretization at high spatial resolution, explicitly incorporating anthropogenic features like buildings and detailed land use roughness for the accurate representation of local hydraulic dynamics. The resulting outputs (inundation extents, depths, and velocities) support risk assessment and spatial planning in the Ungheni locality (Iași County, Romania), providing a practical, transferable workflow adapted to data-scarce regions. Scenario results quantify vulnerability: for the 0.1% exceedance probability scenario (with a calibration accuracy of ±15–30 min deviation for peak flow timing), the flood risk may affect 882 buildings, 42 land parcels, and 13.5 km of infrastructure. This framework contributes to evidence-based decision-making for climate adaptation and disaster risk reduction strategies, improving urban resilience. Full article