Search Results (29)

The network architecture has demonstrated considerable potential for enhancing the strength–ductility synergy in metal matrix composites (MMCs). Intuitively, the intersections of network layers are expected to induce a stress concentration, leading to premature brittle fractures. Introducing chamfers to round the network cells may mitigate the local stress concentration and thereby improve elongation. Here, a numerical simulation framework was developed to investigate the effect of chamfering on the mechanical behavior of a three-dimensional (3D) continuous SiC_3D/Al composite with a network architecture. A Voronoi tessellation algorithm was employed to generate the continuous network structural SiC phase. By inducing ductile and brittle damage criterions in the matrix and reinforcement elements, respectively, the mechanical behavior can be predicted via the finite element method (FEM). The predicted mechanical properties reveal an unexpected trend: chamfering results in a simultaneous reduction in both strength (from 367 MPa to 312 MPa) and elongation (from 4.1% to 2.0%). With chamfering, the enlarged intersection of the network layer bears a lower load, whereas the narrower network plates exhibit higher stress concentrations. As a result, the overall load-bearing capacity of the SiC_3D reinforcement decreases monotonically with an increasing chamfer size f. Furthermore, the non-uniform stress distribution promotes the premature fracture of the SiC_3D, which reduces elongation. Additionally, the crack deflection behavior is suppressed in the chamfered models, leading to decreasing energy dissipation. This unanticipated outcome highlights an important architectural design principle: maintaining uniform geometric dimensions is critical for achieving optimal composite performance. Full article

Chinese fir, as a crucial fast-growing tree species in the hilly regions of southern China, exhibits spatial structure characteristics that directly influence both the ecological functionality and productivity of its stands. This study focused on Chinese fir plantations in the Yangkou State-Owned Forest Farm, Fujian Province. Using UAV-LiDAR point cloud data, individual tree parameters such as height and crown width were extracted, and a DBH inversion model was constructed by integrating machine learning algorithms. Spatial structure parameters were quantified through weighted Voronoi diagrams. A comprehensive evaluation system was established based on the combined weighting method and fuzzy evaluation model to systematically analyze spatial structure characteristics and their evolutionary patterns across different age classes. The results demonstrated that growth environment indicators (openness and openness ratio) progressively declined with the stand’s age, reflecting deteriorating light conditions due to increasing canopy closure. Growth superiority (size ratio and angle competition index) exhibited a “V”-shaped trend, with the most intense competition occurring in the middle-aged stands before stabilizing in the over-mature stage. The resource utilization efficiency (uniform angle and forest layer index) showed continuous optimization, reaching optimal spatial configuration in over-mature stands. This study developed a spatial structure evaluation system for Chinese fir plantations by combining UAV data and cloud modeling, elucidating structural characteristics and developmental patterns across different growth stages, thereby providing theoretical foundations and technical support for close-to-nature management and the precision quality improvement of Chinese fir plantations. Full article

As a discontinuous deformation method, the block element method (BEM) characterizes a material’s elastoplastic behavior through the constitutive relation of thin-layer elements between adjacent blocks. To realistically simulate rock damage paths, this work improves the traditional BEM by using random Voronoi polygonal grids for discrete modeling. This approach mitigates the distortion of damage paths caused by regular grids through the randomness of the Voronoi grids. As the innovation of this work, the iterative algorithm is combined with polygonal geometric features so that the area–perimeter fractal dimension can be introduced to optimize random Voronoi grids. The iterative control index can effectively improve the geometric characteristics of the grid while maintaining the necessary randomness. On this basis, a constitutive relation model that considers both normal and tangential damage is proposed. The entire process from damage initiation to macroscopic fracture failure in rocks is described using two independent damage surfaces and a damage relationship based on geometric mapping relationships. The analysis results are in good agreement with existing experimental data. Furthermore, the sensitivity method is used to analyze the influence of key mechanical parameters in the constitutive model. Full article

Unmanned Aerial Vehicles (UAVs) face significant challenges in global path planning within complex terrains, as traditional algorithms (e.g., A*, PSO, APF) struggle to balance computational efficiency, path optimality, and safety. This study proposes a Voronoi–A* fusion algorithm, combining Voronoi-vertex-based rapid trajectory generation with A* supplementary expansion for enhanced performance. First, an adaptive DEM layering strategy divides the terrain into horizontal planes based on obstacle density, reducing computational complexity while preserving 3D flexibility. The Voronoi vertices within each layer serve as a sparse waypoint network, with greedy heuristic prioritizing vertices that ensure safety margins, directional coherence, and goal proximity. For unresolved segments, A* performs localized searches to ensure complete connectivity. Finally, a line-segment interpolation search further optimizes the path to minimize both length and turning maneuvers. Simulations in mountainous environments demonstrate superior performance over traditional methods in terms of path planning success rates, path optimality, and computation. Our framework excels in real-time scenarios, such as disaster rescue and logistics, although it assumes static environments and trades slight path elongation for robustness. Future research should integrate dynamic obstacle avoidance and weather impact analysis to enhance adaptability in real-world conditions. Full article

Honeycomb structures are widely constructed as cores in sandwich panels with lightweight characteristics and excellent out-of-plane properties. However, their in-plane performances are significantly inferior. This research proposed a novel isotropy-enhanced honeycomb (IEH) with interleaved layers, which is constructed by offsetting the initial seed distributions across layers and then generating hexagonal cells via Voronoi tessellation. Numerical models with three layer-to-layer interval gradients were developed for simulations, and corresponding samples were additively manufactured for experimental validations. The in-plane and out-of-plane performances of IEH and the regular hexagonal honeycombs (RHHs) were comprehensively compared and investigated from quasi-static compression, energy absorption, mechanical properties, and dynamic loading. The results demonstrated that the IEH extremely enhances the in-plane properties by around 500% compared to the RHH, including stiffness, strength, plateau stress, and specific energy absorption (SEA). Although the improvements come at the expense of a partial reduction in out-of-plane stiffness, strength, and SEA, the in-plane performances of IEH reach approximately 70% of their out-of-plane performances, greatly improving the structural isotropy. Introducing layer-to-layer interval gradient leads to a slight reduction in out-of-plane mechanical properties while improving the early-stage deceleration under impact. These findings promote the considerable potential of sandwich panels utilizing IEH cores for applications requiring enhanced resistance to multi-directional impacts. Full article

This study aimed to investigate the impact of local canopy environmental characteristics on the regeneration of common tree species in the understory of broadleaved Korean pine forests, thus deepening the understanding of species coexistence and forest growth cycle mechanisms. This study focused on nine tree species found in the Liangshui National Nature Reserve in Heilongjiang Province, China. We stratified trees by height and simulated the LAI distribution of each class using Voronoi polygons. These layers were overlaid to generate an integrated LAI spatial map. All these procedures were integrated into the self-developed R package Broadleaf.Korean.pine.LAI, which was used to calculate individual-level canopy environment indicators, including average local LAI, local LAI standard deviation, canopy percent, vertical distribution tendency degree, local coniferous LAI, and local broadleaf LAI. These indicators were then compared with the average values of uniformly distributed understory sampling points. A principal component analysis (PCA) was conducted to reduce the dimensionality of the local canopy environmental characteristics for both the uniformly distributed points and regeneration habitats of each tree species, resulting in comprehensive canopy environmental characteristics. Wilcoxon rank-sum tests were applied to assess the significance of differences between the regeneration habitats and the understory average, as well as between the regeneration habitats of seedlings and saplings within the same species. Cliff’s delta effect size was used to evaluate the impact of each environmental factor on the transition of regeneration from seedlings to saplings. The results showed that, based on both individual canopy environmental indicators and composite indices derived from principal component analysis, seedlings tended to regenerate in areas with higher canopy coverage, whereas saplings were more commonly established in relatively open habitats. Clear differences exist between the regeneration habitats of coniferous and broadleaf species, with coniferous species tending to regenerate in areas with higher local broadleaf LAIs compared with broadleaf species. The effect size analysis showed that canopy percent, vertical distribution tendency degree, average local LAI, and local coniferous LAI have greater impacts on the transition from seedlings to saplings, while the effect of local broadleaf LAI is relatively small. These findings suggest that strong shade tolerance allows species to establish seedling banks under canopy patches, while interspecific differences in growth response to microhabitats shape their roles in the forest growth cycle. Future research should explore the physiological responses and trait characteristics of tree regeneration under varying canopy patch environments. Long-term monitoring of regeneration processes—including invasion, growth, and mortality—across different canopy patches will help elucidate the mechanisms shaping understory spatial patterns. Full article

To address the issues of insufficient safety distance and unsmooth paths in AGV path planning for narrow road scenarios, this paper proposes a method that integrates Voronoi-skeleton-based custom layers with traditional cost maps. First, key nodes of the Voronoi skeleton are extracted to generate a custom layer, which is then combined with static, obstacle, and expansion layers to form a new four-layer network cost map. This approach accurately distinguishes obstacle influences and enhances algorithm robustness. The A* algorithm based on this new map guides the automated guided vehicle (AGV) to travel safely along the road center. Second, an improved A* algorithm is employed for global planning to ensure safe navigation. Finally, B-spline smoothing is applied to the global path to enhance the AGV’s efficiency and stability in complex environments. The experimental results show that in narrow road scenarios, the proposed algorithm improves AGV path planning safety by 82%, reduces the number of spatial turning points by 55.85%, and shortens planning time by 48.98%. Overall, this algorithm significantly enhances the robustness and real-time performance of path planning in narrow roads, ensuring the AGV moves safely in an optimal manner. Full article

The issue of energy transfer is extremely important. In order to achieve the lowest possible energy consumption and the required thermal efficiency in energy-efficient buildings, it is necessary, among other things, to minimize the heat-transfer coefficient, which depends on the properties of the insulating material. Analyses of the relationship between the structure of a material and its thermal conductivity coefficient have shown that lower values of this coefficient can be achieved with a more complex structure that mimics natural forms. This paper presents a design method based on the Voronoi diagram to obtain a three-dimensional structure of a porous composite material. The method was found to be effective in producing structures with predefined and functionally graded porosity. The porous specimens were fabricated from a biodegradable soybean oil-based resin using mSLA additive technology. Analyses were performed to determine the thermal parameters of the anisotropic composites. Experimental results showed that both porosity and irregularity affect the thermal properties. The lowest thermal conductivity coefficients were obtained for a 100 mm-thick prototype composite with the following parameters: wall thickness D = 0.2 mm, cell size S = 4 mm, number of structural layers n = 2, and degree of irregularity R = 4. The lowest possible thermal conductivity of the insulation was 0.026 W/(m·K), and the highest possible thermal resistance was 3.92 (m²·K)/W. The method presented in this study provides an effective solution for nature-inspired design and topological optimization of porous structures. Full article

Fatigue-induced crack initiation and propagation are a major concern in pearlitic railway rails and wheels. Rails and wheels undergo significant plastic deformation on their near-surface layers during service, leading to the initiation and propagation of cracks within the deformed region. Existing models typically use finite element models (FEMs) to describe these kinds of fatigue phenomena. However, they fail to establish a strong connection between the microstructure of the undeformed and the deformed materials and their corresponding fatigue properties. Therefore, a model based on the soft-contact discrete element method (DEM) was developed that considers microstructural details such as prior austenite grains (PAGs), pearlite blocks, pearlite colonies, and lamellar orientation of the ferrite–cementite structure of the pearlite. The Voronoi Tessellation method was used to generate a hierarchical mesh to represent these microstructural details, considering the distribution of microstructural details. Crack propagation is simulated by applying damage laws on the microstructural interface level that degrade the stiffness of the fibers connecting the mesh elements. The model’s crack growth predictions are compared with experimental results from the literature to validate its accuracy for different deformation degrees. The developed model can be used in the designing and material selection phase in the railway industry to help select the material with optimum microstructural features. Also, it can be used for the selection of the optimum heat treatment process considering materials resistance to the fatigue crack growth. Full article

In modern society, the autonomous exploration of unknown environments has attracted extensive attention due to its broad applications, such as in search and rescue operations, planetary exploration, and environmental monitoring. This paper proposes a novel collaborative exploration strategy for multiple mobile robots, aiming to quickly realize the exploration of entire unknown environments. Specifically, we investigate a hierarchical control architecture, comprising an upper decision-making layer and a lower planning and mapping layer. In the upper layer, the next frontier point for each robot is determined using Voronoi partitioning and the Multi-Agent Twin Delayed Deep Deterministic policy gradient (MATD3) deep reinforcement learning algorithm in a centralized training and decentralized execution framework. In the lower layer, navigation planning is achieved using A* and Timed Elastic Band (TEB) algorithms, while an improved Cartographer algorithm is used to construct a joint map for the multi-robot system. In addition, the improved Robot Operating System (ROS) and Gazebo simulation environments speed up simulation times, further alleviating the slow training of high-precision simulation engines. Finally, the simulation results demonstrate the superiority of the proposed strategy, which achieves over 90% exploration coverage in unknown environments with a significantly reduced exploration time. Compared to MATD3, Multi-Agent Proximal Policy Optimization (MAPPO), Rapidly-Exploring Random Tree (RRT), and Cost-based methods, our strategy reduces time consumption by 41.1%, 47.0%, 63.9%, and 74.9%, respectively. Full article

In this paper, we numerically investigate the dynamic response and explosion resistance of gradient aluminum foam sandwich tubes subjected to external blast loads. Based on 3D-Voronoi technology, we construct density-graded aluminum foam cores to systematically explore the influence of core density distribution, density gradient, and average relative density on the protective performance of these structures. Our primary objective is to identify optimal design parameters that maximize explosion mitigation capabilities while balancing energy absorption and specific energy absorption capacities. The research results show that a positive gradient core configuration exhibits superior anti-explosion performance, significantly outperforming its uniform and negatively graded counterparts, particularly when the gradient value is substantial. For the positive gradient cores, an increase in the gradient value leads to a corresponding enhancement in explosion resistance. Conversely, in negatively graded cores, a higher gradient value diminishes the anti-explosion performance. Furthermore, while augmenting the relative density of the core layer does improve the overall explosion resistance of the sandwich tube, it comes at the cost of reduced energy absorption and specific energy absorption capabilities, highlighting the need for a delicate balance among these competing factors. Full article

This paper investigated the feasibility of using 3D printing processes, specifically material extrusion (MEX) and vat photopolymerization (DLP—Digital Light Processing), to produce customized wrist–hand orthoses. Design, printability, and usability aspects were addressed. It was found that minimizing printing time for orthoses with intricate shapes, ventilation pockets, and minimal thickness is difficult. The influence of build orientation and process parameters, such as infill density, pattern, layer thickness, and wall thickness, on printing time for ten parameter configurations of orthoses in both ready-to-use and flat thermoformed shapes was examined. The findings revealed that the optimized orientations suggested by Meshmixer and Cura (Auto-orient option) did not reliably yield reduced printing times for each analyzed orthoses. The shortest printing time was achieved with a horizontal orientation (for orthoses manufactured in their ready-to-use form, starting from 3D scanning upper limb data) at the expense of surface quality in contact with the hand. For tall and thin orthoses, 100% infill density is recommended to ensure mechanical stability and layer fill, with caution required when reducing the support volume. Flat and thermoformed orthoses had the shortest printing times and could be produced with lower infill densities without defects. For the same design, the shortest printing time for an orthosis 3D-printed in its ready-to-use form was 8 h and 24 min at 60% infill, while the same orthosis produced as flat took 4 h and 37 min for the MEX process and half of this time for DLP. Usability criteria, including perceived immobilization strength, aesthetics, comfort, and weight, were evaluated for seven orthoses. Two healthy users, with previous experience with traditional plaster splints, tested the orthoses and expressed satisfaction with the 3D-printed designs. While the Voronoi design of DLP orthoses was visually more appealing, it was perceived as less stiff compared to those produced by MEX. Full article

The optimization of structure and thermal properties in 3D-printed insulation materials remains an underexplored area in the literature. This study aims to address this gap by investigating the impact of 3D printing on the thermal properties of manufactured cellular composites. The materials studied were closed-cell foams with a complex cell structure based on the Voronoi cell model, manufactured using incremental technology (3D printing). The influence of the cellular structure of the composite, the type of material used, and the number of layers in the composite structure on its thermal properties, i.e., thermal conductivity coefficient, thermal resistance, and coefficient of heat transfer, was analyzed. Samples of different types of thermosetting resins, characterized by different values of emissivity coefficient, were analyzed. It was shown that both the type of material, the number of layers of the composite, and the number of pores in its structure significantly affect its thermal insulating properties. Thermal conductivity and permeability depended on the number of layers and decreased up to 30% as the number of layers increased from one to four, while thermal resistance increased to 35%. The results indicate that material structure is key in regulating thermal conduction. Controlling the number of cells in a given volume of composite (and thus the size of the air cells) and the number of layers in the composite can be an effective tool in designing materials with high insulation performance. Among the prototype composites produced, the best thermal performance was that of the metalized four-layer cellular composites (λ = 0.035 ± 0.002 W/m·K, R_c = 1.15 ± 0.02 K·m²/W, U = 0.76 ± 0.01 W/m²·K). Full article

Convective transport of drug solutes in biological tissues is regulated by the interstitial fluid pressure, which plays a crucial role in drug absorption into the lymphatic system through the subcutaneous (SC) injection. In this paper, an approximate continuum poroelasticity model is developed to simulate the pressure evolution in the soft porous tissue during an SC injection. This poroelastic model mimics the deformation of the tissue by introducing the time variation of the interstitial fluid pressure. The advantage of this method lies in its computational time efficiency and simplicity, and it can accurately model the relaxation of pressure. The interstitial fluid pressure obtained using the proposed model is validated against both the analytical and the numerical solution of the poroelastic tissue model. The decreasing elasticity elongates the relaxation time of pressure, and the sensitivity of pressure relaxation to elasticity decreases with the hydraulic permeability, while the increasing porosity and permeability due to deformation alleviate the high pressure. An improved Kedem–Katchalsky model is developed to study solute transport across the lymphatic vessel network, including convection and diffusion in the multi-layered poroelastic tissue with a hybrid discrete-continuum vessel network embedded inside. At last, the effect of different structures of the lymphatic vessel network, such as fractal trees and Voronoi structure, on the lymphatic uptake is investigated. In this paper, we provide a novel and time-efficient computational model for solute transport across the lymphatic vasculature connecting the microscopic properties of the lymphatic vessel membrane to the macroscopic drug absorption. Full article

Ag paste has been recognized as a promising substitute for Sn/Pb solder in SiC or GaN power electronic devices, owing to its ability to withstand high temperatures and facilitate low-temperature packing. The reliability of these high-power circuits is greatly influenced by the mechanical properties of sintered Ag paste. However, there exist substantial voids inside the sintered silver layer after sintering, and the conventional macroscopic constitutive models have certain limitation to describe the shear stress–strain relationship of sintered silver materials. To analyze the void evolution and microstructure of sintered silver, Ag composite pastes composed of micron flake silver and nano-silver particles were prepared. The mechanical behaviors were studied at different temperatures (0–125 °C) and strain rates (1 × 10⁻⁴–1 × 10⁻²) for Ag composite pastes. The crystal plastic finite element method (CPFEM) was developed to describe the microstructure evolution and shear behaviors of sintered silver at varied strain rates and ambient temperatures. The model parameters were obtained by fitting experimental shear test data to a representative volume element (RVE) model built on representative volume elements, also known as Voronoi tessellations. The numerical predictions were compared with the experimental data, which showed that the introduced crystal plasticity constitutive model can describe the shear constitutive behavior of a sintered silver specimen with reasonable accuracy. Full article