Search Results (200)

This paper discusses the potential application of computational design and additive manufacturing in veterinary prosthetics, demonstrated with the example of a feline limb. A finite element analysis (FEA)-based design optimization framework was used to develop eight prosthetic leg geometries in CAD and analyze them in ANSYS (2024R) under a static loading condition, to evaluate their performance under the loading condition. Structural variations were in the form of grooves, holes and shell reinforcements, which were investigated to see how they affect stiffness, stress distribution and viability of the 3D-printed prosthetics. Design variations were introduced through the inclusion or exclusion of structural attributes such as grooves, holes, and shell reinforcements. The simulations evaluated total deformation, von Mises stress, and equivalent elastic strain to determine the mechanical efficiency of each configuration. Results showed that designs incorporating shells and holes provided the best overall performance, as groove-free designs minimized stress concentrations and achieved the highest stiffness. Notably, the configuration featuring a hole and shell without grooves achieved the lowest mean deformation (14.09 µm) and stress values, making it the most structurally viable and suitable for real-life application. This study highlights the potential of 3D printing to produce cost-effective, patient-specific prosthetics and underscores the importance of structural optimization for improving biomechanical compatibility and mobility. The next stage of this work will involve fabricating the optimized design using 3D printing, followed by mechanical testing to validate the simulation results and assess real-world performance. Future work will also incorporate topology optimization to further reduce weight while maintaining structural integrity. Full article

Droplet-based microlens fabrication using Ultra Violet (UV) curable polymers demands the precise measurement of three-dimensional geometries, especially for non-axisymmetric shapes influenced by electric field deformation. In this work, we present a polar coordinate-based contour fitting method combined with Hermite interpolation to reconstruct 3D droplet geometries from two orthogonal shadowgraphy images. The image segmentation process integrates superpixel clustering with active contours to extract the droplet boundary, which is then approximated using a spline-based polar fitting approach. The two resulting contours are merged using a polar Hermite interpolation algorithm, enabling the reconstruction of freeform droplet shapes. We validate the method against both synthetic Computer-Aided Design (CAD) data and precision-machined reference objects, achieving volume deviations below 1% for axisymmetric shapes and approximately 3.5% for non-axisymmetric cases. The influence of focus, calibration, and alignment errors is quantitatively assessed through Monte Carlo simulations and empirical tests. Finally, the method is applied to real electrically deformed droplets, with volume deviations remaining within the experimental uncertainty range. This demonstrates the method’s robustness and suitability for metrology tasks involving complex droplet geometries. Full article

Three-dimensional bioprinting holds great promise for tissue engineering, but struggles with fabricating complex curved geometries such as vascular networks. Though precise, traditional Cartesian bioprinters are constrained by linear layer-by-layer deposition along fixed axes, resulting in limitations such as the stair-step effect. Multi-axis robotic bioprinting addresses these challenges by allowing dynamic nozzle orientation and motion along curvilinear paths, enabling conformal printing on anatomically relevant surfaces. Although robotic arms offer lower mechanical precision than CNC stages, accuracy can be enhanced through methods such as vision-based toolpath correction. This study presents a modular multi-axis robotic embedded bioprinting platform that integrates a six-degrees-of-freedom robotic arm, a pneumatic extrusion system, and a viscoplastic support bath. A streamlined workflow combines CAD modeling, CAM slicing, robotic simulation, and automated execution for efficient fabrication. Two case studies validate the system’s ability to print freeform surfaces and vascular-inspired tubular constructs with high fidelity. The results highlight the platform’s versatility and potential for complex tissue fabrication and future in situ bioprinting applications. Full article

Quantum hydrodynamic theory (QHT) provides a computationally efficient alternative to time-dependent density functional theory for simulating plasmonic nanostructures, but its predictive power depends critically on the choice of ground-state electron density and energy functional. To construct ground-state densities, we adopt orbital-free density functional theory and numerically evaluate the effect of different exchange–correlation functionals and kinetic energy functionals. A suitable energy functional to reproduce both the DFT-calculated work function and charge density is identified. In the excited-state part, we adopt this obital-free ground-state density and investigate how variations in the von Weizsäcker kinetic energy fraction within the Laplacian-level functional affect the resonance energy and oscillator strengths. The appropriate functional form is identified, achieving an accuracy comparable to that reported in previous studies. Applied to sodium nanodimers, our approach captures nonlinear density responses at sub-nanometer gaps. This work extends QHT beyond idealized geometries and offers a robust path toward efficient quantum plasmonic modeling. Full article

Fast, spark-free detection of hydrogen leaks is indispensable for large-scale hydrogen deployment, yet electronic sensors remain power-intensive and prone to cross-talk. Optical schemes based on surface plasmons enable remote read-out, but single-metal devices offer either weak H2 affinity or poor plasmonic quality. Here we employ full-wave finite-difference time-domain (FDTD) simulations to map the hydrogen response of nanohole arrays (NAs) that can be mass-produced by colloidal lithography. Square lattices of 200 nm holes etched into 100 nm films of Pd, Mg, Ti, V, or Zr expose an intrinsic trade-off: Pd maintains sharp extraordinary optical transmission modes but shifts by only 28 nm upon hydriding, whereas Mg undergoes a large dielectric transition that extinguishes its resonance. Vertical pairing of a hydride-forming layer with a noble metal plasmonic cap overcomes this limitation. A Mg/Pd bilayer preserves all modes and red-shifts by 94 nm, while the predicted optimum Ag (60 nm)/Mg (40 nm) stack delivers a 163 nm shift with an 83 nm linewidth, yielding a figure of merit of 1.96—surpassing the best plasmonic hydrogen sensors reported to date. Continuous-film geometry suppresses mechanical degradation, and the design rules—noble-metal plasmon generator, buried hydride layer, and thickness tuning—are general. This study charts a scalable route to remote, sub-ppm, optical hydrogen sensors compatible with a carbon-neutral energy infrastructure. Full article

Elasticity is a well-established field within mathematical physics, yet new formulations can provide deeper insight and computational advantages. This study explores the geometry of two- and three-dimensional elastic curves using the formalism of geometric algebra, offering a unified and coordinate-free approach. This work systematically derives the Frenet, Darboux, and Bishop frames within the three-dimensional geometric algebra and employs them to integrate the elastica equation. A concise Lagrangian formulation of the problem is introduced, enabling the identification of Noetherian, conserved, multi-vector moments associated with the elastic system. A particularly compact form of the elastica equation emerges when expressed in the Bishop frame, revealing structural simplifications and making the equations more amenable to analysis. Ultimately, the geometric algebra perspective uncovers a natural correspondence between the theory of free elastic curves and classical beam models, showing how constrained theories, such as Euler–Bernoulli and Kirchhoff beam formulations, arise as special cases. These results not only clarify foundational aspects of elasticity theory but also provide a framework for future applications in continuum mechanics and geometric modeling. Full article

In freeform surface grid structures, quadrilateral meshes offer high visual transparency and simple joint connections, but their structural stability is relatively limited. To enhance stability, designers often introduce additional structural elements along the diagonals of the quadrilateral mesh, forming double-layer quadrilateral grid systems such as cable-braced gridshells. However, current design methodologies do not support the simultaneous optimization of both layers. As a result, the two layers are often designed independently in practical applications, leading to complex joint detailing that compromises construction efficiency, architectural aesthetics, and overall structural performance. To address these challenges, this study presents a weighted multi-objective geometry optimization framework based on a Guided-Projection algorithm. The proposed method integrates half-edge data structure and multiple geometric and structural constraints, enabling the simultaneous optimization of quadrilateral mesh planarity (i.e., panels lying on flat planes) and the orthogonality (i.e., angles approaching 90°) of diagonal cable layouts. Through multiple case studies, the method demonstrates significant improvements in panel planarity and cable orthogonality. The results also highlight the algorithm’s rapid convergence and high computational efficiency. Finite element analysis further validates the structural benefits of the optimized configurations, including reduced peak axial forces in cables, more uniform cable force distribution, and enhanced overall stiffness and buckling resistance. In conclusion, the method improves structural stability, constructability, and design efficiency, offering a practical tool for optimizing freeform cable-braced gridshells. Full article

Barrel tools are increasingly used in high-precision machining of free-form surfaces. However, limited studies evaluate their performance specifically on spherical geometries, where tool–surface contact characteristics differ significantly. Understanding how tool geometry and process parameters influence surface quality and cutting forces in such cases remains underexplored. This study evaluates how barrel cutter radius and varying machining parameters affect cutting forces and surface roughness when milling internal and external spherical surfaces. Machining tests were conducted on structural steel 1.1191 using two barrel cutters with different curvature radii (85 mm and 250 mm) on a 5-axis CNC machine. Feed per tooth and radial depth of cut were systematically varied. Cutting forces were measured using a dynamometer, and surface roughness was assessed using the Rz parameter, which is more sensitive to peak deviations than Ra. Novelty lies in isolating spherical surface shapes (internal vs. external) under identical path trajectories and systematically correlating tool geometry to force and surface metrics. The larger curvature tool (250 mm) consistently generated up to twice the cutting force of the smaller radius tool under equivalent conditions. External surfaces showed higher Rz values than internal ones due to less favorable contact geometry. Radial depth of the cut had a linear influence on force magnitude, while feed rate had a limited effect except at higher depths. Smaller-radius barrel tools and internal geometries are preferable for minimizing cutting forces and achieving better surface quality when machining spherical components. The aim of this paper is to determine the actual force load and surface quality when using specific cutting conditions for internal and external spherical machined surfaces. Full article

Ice accumulation on exposed surfaces presents substantial economic and safety challenges across various industries. To overcome limitations associated with traditional anti-icing methods, such as the use of nanoparticles, this study introduces a novel and facile approach for fabricating superhydrophobic and anti-icing microstructures using cost-effective LCD 3D printing technology. The influence of diverse pillar geometries, including square, cylindrical, hexagonal, and truncated conical forms, was analyzed to assess their effects on the hydrophobic and anti-icing/icephobic performance in terms of wettability, ice adhesion strength, and icing delay time. The role of microstructure topography was further investigated through cylindrical patterns with varying geometric parameters to identify optimal designs for enhancing hydrophobic and icephobic characteristics. Furthermore, the effectiveness of surface functionalization using a low surface energy material was evaluated. Our findings demonstrate that the synergistic combination of tailored microscale geometries and surface functionalization significantly enhances anti-icing performance with reliable repeatability, achieving ice adhesion of 13.9 and 17.9 kPa for square and cylindrical pillars, respectively. Critically, this nanoparticle-free 3D printing and low surface energy treatment method offers a scalable and efficient route for producing high-performance hydrophobic/icephobic surfaces, opening promising avenues for applications in sectors where robust anti-icing capabilities are crucial, such as renewable energy and transportation. Full article

Effective maintenance and management of road infrastructure are essential for community well-being, economic stability, and cost efficiency. Well-maintained roads reduce accident risks, improve safety, shorten travel times, lower vehicle repair costs, and facilitate the flow of goods, all of which positively contribute to GDP and economic development. Accurate intersection mapping forms the foundation of effective road asset management, yet traditional manual digitization methods remain time-consuming and prone to gaps and overlaps. This study presents an automated computational geometry solution for precise road intersection mapping that eliminates common digitization errors. Unlike conventional approaches that only detect intersection positions, our method systematically reconstructs complete intersection geometries while maintaining topological consistency. The technique combines plane surveying principles (including line-bearing analysis and curve detection) with spatial analytics to automatically identify intersections, characterize their connectivity patterns, and assign unique identifiers based on configurable parameters. When evaluated across multiple urban contexts using diverse data sources (manual digitization and OpenStreetMap), the method demonstrated consistent performance with mean Intersection over Union greater than 0.85 and F-scores more than 0.91. The high correctness and completeness metrics (both more than 0.9) confirm its ability to minimize both false positive and omission errors, even in complex roadway configurations. The approach consistently produced gap-free, overlap-free outputs, showing strength in handling interchange geometries. The solution enables transportation agencies to make data-driven maintenance decisions by providing reliable, standardized intersection inventories. Its adaptability to varying input data quality makes it particularly valuable for large-scale infrastructure monitoring and smart city applications. Full article

Collision welding represents a promising solid-state joining technique for combining both similar and dissimilar metals without the thermal degradation of mechanical properties typically associated with fusion-based methods. This makes it particularly attractive for lightweight structural applications. In the context of collision welding, it is typically assumed that ideally smooth and defect-free surface conditions exist prior to welding. However, this does not consistently reflect industrial realities, where surface imperfections such as scratches are often unavoidable. Despite this, the influence of such surface irregularities on weld integrity and quality has not been comprehensively investigated to date. In this study, collision welding is applied to the material combination of AA6110A-T6 and AA6060-T6. Initially, the process window for this material combination is determined by systematically varying the collision velocity and collision angle—the two primary process parameters—using a special model test rig. Subsequently, the effect of surface imperfections in the form of defined scratch geometries on the resulting weld quality is investigated. In addition to evaluating the welding ratio and tensile shear strength, weld quality is assessed through scanning electron microscopy (SEM) of the bonding interface and high-speed imaging of jet formation during the collision process. Full article

This study investigates the coupled hygrothermal behavior of mycelium-based composites (MBCs) as a function of their microstructural organization, governed by fungal species, substrate type, additive incorporation, and treatment method. Eleven composite formulations were selected and characterized using a multi-scale experimental approach, combining scanning electron microscopy, dynamic vapor sorption, vapor permeability tests, capillary uptake measurements, and transient thermal conductivity analysis. SEM analysis revealed that Ganoderma lucidum forms dense and interconnected hyphal networks, whereas Trametes versicolor generates looser, localized structures. These morphological differences directly influence water vapor transport and heat conduction. Additive-enriched composites exhibited up to 21.8% higher moisture uptake at 90% RH, while straw-based composites demonstrated higher capillary uptake and free water saturation (up to 704 kg/m³), indicating enhanced moisture sensitivity. In contrast, hemp-based formulations with Ganoderma lucidum showed reduced sorption and vapor permeability due to limited pore interconnectivity. Thermal conductivity varied nonlinearly with temperature and moisture content. Fitting the experimental data with an exponential model revealed a moisture sensitivity coefficient thirty times lower for GHOP compared to VHOP, highlighting the stabilizing effect of a compact microstructure. The distinction between total and effective porosity emerged as a key factor in explaining discrepancies between apparent and functional moisture behavior. These findings demonstrate that hygric and thermal properties in MBCs are governed not by porosity alone, but by the geometry and connectivity of the internal fungal network. Optimizing these structural features enables fine control overheat and mass transfer, laying the groundwork for the development of high-performance, bio-based insulation materials. Full article

This work shows a three-dimensional (3D) layerwise model for static and free vibration analyses of functionally graded piezomagnetic materials (FGPM) spherical shell structures where magnetic and elastic fields are completely coupled. The 3D magneto-elastic governing equations for spherical shells are made of the three equations of equilibrium in three-dimensional form and the three-dimensional divergence equation for the magnetic induction. Governing equations are written in the orthogonal mixed curvilinear reference system ($\alpha$, $\beta$, z) allowing the analysis of several curved and flat geometries (plates, cylindrical shells and spherical shells) thanks to proper considerations of the radii of curvature. The static cases, actuator and sensor configurations and free vibration investigations are proposed. The resolution method uses the imposition of the Navier’s harmonic forms in the two in-plane directions and the exponential matrix methodology in the transverse normal direction. Single-layered and multilayered simply-supported FGPM structures have been investigated. In order to understand the behavior of FGPM structures, numerical values and trends along the thickness direction for displacements, stresses, magnetic potential, magnetic induction and free vibration modes are proposed. In the results section, a first assessment phase is proposed to demonstrate the validity of the formulation and to fix proper values for the convergence of results. Therefore, a new benchmark section is presented. Different cases are proposed for several material configurations, load boundary conditions and geometries. The possible effects involved in this problem (magneto-elastic coupling and effects related to embedded materials and thickness values of the layers) are discussed in depth for each thickness ratio. The innovative feature proposed in the present paper is the exact 3D study of magneto-elastic coupling effects in FGPM plates and shells for static and free vibration analyses by means of a unique and general formulation. Full article

The objective of the presented work is the stern duct design for the JBC (Japan Bulk Carrier) hull form. Since the original duct only provides a 0.6% resistance reduction, an innovative duct will be proposed to improve the ship resistance and propulsion performance. The duct section geometry is based on the NACA (National Advisory Committee for Aeronautics) 4-digit foil series. First, we analyze whether the wake flow field and total resistance of the ship are improved, and then we investigate the self-propulsion performance for the selected ones. The research tool is the CFD (Computational Fluid Dynamics) software OpenFOAM 9 with the viscous free surface flow field modelled by the VOF (Volume of Fluid) method and the SST (Shear Stress Transport) k–ω turbulence model. The propeller effect is implemented by the MRF (Multi-Reference Frame). Compared to the original duct, two ducts, namely, NACA 7908 and NACA 6.3914, show the best (2.8%) resistance reduction in the bare hull condition. By installing both ducts, the propeller thrust decreases 6 and 5% to reach the self-propulsion point, and the behind-hull efficiency increases 7 and 6%. Both ducts save the energy, i.e., effective horsepower, by 4.3%, and produce obvious flow acceleration, achieving around 10% higher effective wake factor (1 − w). The nominal and propeller wakes are improved as well. Full article

Continuous fiber-reinforced polymer (CoFRP) parts offer significant potential for reducing future product consumption and CO₂ emissions due to their high tensile properties and low density. Additive manufacturing enables the tool-free production of complex geometries with optimal material utilization, making it a promising approach for creating load-path-optimized CoFRP parts. Recent advancements have integrated continuous fibers into laser sintering processes, allowing for the support-free production of complex parts with improved material properties. However, additive manufacturing faces challenges such as long production times, small component dimensions, and defects like high void content. New processes, including Arburg Polymer Freeforming (APF), robotic direct extrusion (DES) and the integration of thermoplastic tapes, and laser sintering, have enabled the production of CoFRPs to address these issues. A comparison of these new processes with existing material extrusion methods is necessary to determine the most suitable approach for specific tasks. The fulfillment factor is used to compare composites with different matrix and fiber materials, representing the percentage of experimentally achieved material properties relative to the theoretical maximum according to the Voigt model. The fulfillment factor varies significantly across different processes and materials. For FFF processes, the fulfillment factor ranges from 20% to 77% for stiffness and 14% to 84% for strength, with an average of 52% and 37%, respectively. APF shows a high fulfillment factor for stiffness (94%) but is lower for strength (23%), attributed to poor fiber–matrix bonding and process-induced pores. The new DES process improves the fulfillment factor due to additional consolidation steps, achieving above-average values for strength (67%). The CoFRP produced by the novel LS process also shows a high fulfillment factor for stiffness (85%) and an average fulfillment factor for strength (39%), influenced by suboptimal process parameters and defects. Full article