Search Results (2,418)

As a method of lightweight design, multi-material design aims to make targeted use of materials in order to reduce CO₂ emissions. In this context, it can be described as one of the product development methods used to meet the challenges of climate change. However, since the design of structures in multi-material design is complex, topology optimization can be used to support the product developer. In this article, a multi-material topology optimization method is developed that combines the Velocity Field Level Set method with the Reconciled Level Set method. Furthermore, the current design is explicitly resolved in each iteration by means of multi-material remeshing. The edge collapse phase in the remeshing process is achieved by applying the producer consumer pattern. The developed method is then validated using known examples from the state of research, and the influence of the parameters of the method on the result is analyzed by means of studies. Full article

This paper presents a drone system that uses an improved network topology and MultiAgent Reinforcement Learning (MARL) to enhance mission performance in Unmanned Aerial Vehicle (UAV) swarms across various scenarios. We propose a UAV swarm system that allows drones to efficiently perform tasks with limited information sharing and optimal action selection through our Efficient Self UAV Swarm Network (ESUSN) and reinforcement learning (RL). The system reduces communication delay by 53% and energy consumption by 63% compared with traditional MESH networks with five drones and achieves a 64% shorter delay and 78% lower energy consumption with ten drones. Compared with nonreinforcement learning-based systems, mission performance and collision prevention improved significantly, with the proposed system achieving zero collisions in scenarios involving up to ten drones. These results demonstrate that training drone swarms through MARL and optimized information sharing significantly increases mission efficiency and reliability, allowing for the simultaneous operation of multiple drones. Full article

In this study, we investigated the spatial distribution and homogeneity of gold nanoparticles (AuNPs) on an alumina (Al₂O₃; AAO) substrate for potential application as surface-enhanced Raman scattering (SERS) sensors. The AuNPs were synthesized through thermal treatment at 450 °C at varying times (5, 15, 30, and 60 min), and their distribution was characterized using field-emission scanning electron microscopy (FE-SEM) and scanning transmission electron microscopy (STEM). The FE-SEM and STEM analyses revealed that the size and interparticle distance of the AuNPs were significantly influenced by the duration of thermal treatment, with shorter times promoting smaller and more closely spaced nanoparticles, and longer times resulting in larger and more dispersed particles. Raman spectroscopy, using Rhodamine 6G (R6G) as a probe molecule, was employed to evaluate the SERS enhancement provided by the AuNPs on the AAO substrate. Raman mapping (5 µm × 5 µm) was conducted on five sections of each sample, demonstrating improved homogeneity in the SERS effect across the substrate. The topological features of the AuNPs before and after R6G incubation were analyzed using atomic force microscopy (AFM), confirming the correlation between a decrease in surface roughness and an increase in R6G adsorption. The reproducibility of the SERS effect was quantified using the maximum intensity deviation (D), which was found to be below 20% for all samples, indicating good reproducibility. Among the tested conditions, the sample synthesized for 15 min exhibited the most favorable characteristics, with the smallest average nanoparticle size and interparticle distance, as well as the most consistent SERS enhancement. These findings suggest that AuNPs on AAO substrates, particularly those synthesized under the optimized condition of 15 min at 450 °C, are promising candidates for use in SERS-based sensors for detecting cancer biomarkers. This could be attributed to temperature propagation promoted at the time of synthesis. The results also provide insights into the influence of thermal treatment on the spatial distribution of AuNPs and their subsequent impact on SERS performance. Full article

To address the shortcomings of the Dung Beetle Optimization (DBO) algorithm in ship power-system fault reconfiguration, such as low population diversity and an imbalance between global exploration and local exploitation, the authors of this paper propose an improved Dung Beetle Optimization (LESSDBO) algorithm. The improvements include optimizing the initial population using Latin hypercube sampling and an elite population strategy, optimizing parameters with an improved sigmoid activation function, introducing the sine–cosine algorithm (SCA) for position update optimization, and performing multi-population mutation operations based on individual quality. The LESSDBO algorithm was applied to simulate the fault reconfiguration of a ship power system, and it was compared with the traditional DBO, Genetic Algorithm (GA), and Modified Particle Swarm Optimization (MSCPSO) methods. The simulation results showed that LESSDBO outperformed the other algorithms in terms of convergence accuracy, convergence speed, and global search capability. Specifically, in the reconfiguration under Fault 1, LESSDBO achieved optimal convergence in seven iterations, reducing convergence iterations by more than 30% compared with the other algorithms. In the reconfiguration under Fault 2, LESSDBO achieved optimal convergence in eight iterations, reducing convergence iterations by more than 23% compared with the other algorithms. Additionally, in the reconfiguration under Fault Condition 1, LESSDBO achieved a minimum of four switch actions, which is 33% fewer than the other algorithms, on average. In the reconfiguration under Fault Condition 2, LESSDBO achieved a minimum of eight switch actions, which is a 5.9% reduction compared with the other algorithms. Furthermore, LESSDBO obtained the optimal reconfiguration solution in all 50 trials for both Faults 1 and 2, demonstrating a 100% optimal convergence probability and significantly enhancing the reliability and stability of the algorithm. The proposed method effectively overcomes the limitations of the traditional DBO in fault reconfiguration, providing an efficient and stable solution for the intelligent topology reconfiguration of ship power systems. Full article

Polyaniline−magnesia (PANI/MgO) composites with a fibrous nanostructure were synthesized via in situ oxidative polymerization, enabling uniform MgO integration into the polyaniline matrix. These composites were characterized using FTIR spectroscopy to analyze intermolecular bonding, XRD to assess crystallographic structure and phase purity, and SEM to examine surface morphology and topological features. The resulting PANI/MgO nanofibers were utilized to develop ammonia (NH₃) gas-sensing probes with evaluations conducted at room temperature. The study addresses the critical challenge of achieving high sensitivity and selectivity in ammonia detection at low concentrations, which is a problem that persists in many existing sensor technologies. The nanofibers demonstrated high selectivity and optimal sensitivity for ammonia detection, which was attributed to the synergistic effects between the polyaniline and MgO that enhance gas adsorption. Furthermore, the study revealed that the MgO content critically influences both the morphology and the sensing performance, with higher MgO concentrations improving sensor response. This work underscores the potential of PANI/MgO composites as efficient and selective ammonia sensors, highlighting the importance of MgO content in optimizing material properties for gas-sensing applications. Full article

To determine the ES allocation based on a specific number of EVs connected to a combined WPESS, this paper develops an ESS allocation model that considers the impact of EV charging behavior on LSD, ES allocation cost, new energy utilization rate, and self-power rate. First, several scenarios are generated using Monte Carlo sampling (MCS), and a typical day is selected through Backward Reduction (BR). Next, the Monte Carlo method is employed to generate conventional EV charging curves and optimize EV charging behavior by considering LSD and user charging costs. Subsequently, an ES capacity allocation model is developed, considering system costs, new energy utilization rate, and self-power rate. Finally, an improved triangulation topology aggregation optimizer (TTAO) is proposed, incorporating the logistic map, Golden Sine Algorithm (Gold-SA) strategy, and lens inverse imaging learning strategy. These enhancements improve the algorithm’s ability to identify global optimal solutions and facilitate its escape from local optima, significantly enhancing the optimization effectiveness of TTAO. The analysis of the calculation example indicates that after optimizing the charging behavior of EVs, the average daily cost is reduced by 204.94, the self-power rate increases by 2.25%, and the utilization rate of new energy sources rises by 2.50%, all while maintaining the same ES capacity. Full article

Lattice structures show advantages in mechanical properties and energy absorption efficiency owing to their lightweight, high strength and adjustable geometry. This article reviews lattice structure classification, design and applications, especially those based on additive manufacturing (AM) technology. This article first introduces the basic concepts and classification of lattice structures, including the classification based on topological shapes, such as strut, surface, shell, hollow-strut, and so on, and the classification based on the deformation mechanism. Then, the design methods of lattice structure are analyzed in detail, including the design based on basic unit, mathematical algorithm and gradient structure. Next, the effects of different lattice elements, relative density, material system, load direction and fabrication methods on the mechanical performance of AM-produced lattice structures are discussed. Finally, the advantages of lattice structures in energy absorption performance are summarized, aiming at providing theoretical guidance for further optimizing and expanding the engineering application potential of lattices. Full article

Stroke often causes neuromotor disabilities, impacting index finger function in daily activities. Due to the role of repetitive, even passive, finger movements in neuromuscular re-education and spasticity control, this study aims to design a rehabilitation exoskeleton based on the pulp pinch movement. The exoskeleton uses an underactuated RML topology with a single degree of mobility, customized from 3D scans of the patient’s hand. It consists of eight links, incorporating two consecutive four-bar mechanisms and the third inversion of a crank–slider. A two-stage genetic optimization was applied, first to the location of the intermediate joint between the two four-bar mechanisms and later to the remaining dimensions. A targeted genetic optimization process monitored two quality metrics: average mechanical advantage from extension to flexion, and its variability. By analyzing the relationship between these metrics and key parameters at different synthesis stages, the population evaluated is reduced by up to 96.2%, compared to previous studies for the same problem. This custom-fit exoskeleton uses a small linear actuator to deliver a stable 12.45 N force to the fingertip with near-constant mechanical advantage during flexion. It enables repetitive pulp pinch movements in a flaccid finger, improving rehabilitation consistency and facilitating home-based therapy. Full article

The topological characteristics of the down-skin surfaces for as-built components by laser powder bed fusion (LPBF) are particularly representative, while the study on the improvement of the surface quality of these surfaces remains largely unexplored. Herein, the laser polishing of LPBF-built components with different inclination angles was systematically investigated with an emphasis on the down-skin surfaces. Our result shows that the topography of the top surface is independent of the inclination angle, and the surface topography of the down-skin surface is dominated by additional angle-dependent surface characteristics. It also indicates that the surface roughness can be reduced sharply when increasing the laser power from 40 W to 60 W, and the reduction slows down when further increasing the laser power while decreasing the scanning speed leads to a progressive improvement of the surface morphology. Moreover, a second-order regression model was established to evaluate the influence of the initial surface morphology and polishing parameters on the polished surface roughness and to achieve surface roughness optimization. Therefore, our established methodology can be readily applied to surface morphology manipulation and process optimization for laser polishing of widely used metals and alloys fabricated by the additive manufacturing process. Full article

Integrated energy systems (IESs) are complex multisource supply systems with integrated source, grid, load, and storage systems, which can provide various flexible resources. Nowadays, there exists the phenomenon of a current power system lacking flexibility. Thus, more research focuses on enhancing the flexibility of power systems by considering the participation of IESs in distribution network optimization scheduling. Therefore, the optimal scheduling of IESs considering virtual heat storage and electric vehicles (EVs) is proposed in this paper. Firstly, the basic structure of IESs and mathematical models for the operation of the relevant equipment are presented. Then, an optimal scheduling strategy of an IES considering virtual heat storage and electric vehicles is proposed. Finally, an IES with an IEEE 33-node distribution network, 20-node Belgian natural gas network, and 44-node heating network topologies is selected to validate the proposed strategy. The proposed models of integrated demand response (IDR), EV orderly charging participation, virtual heat storage, and actual multitype energy storage devices play the role of peak shaving and valley filling, which also helps to reduce the scheduling cost from CNY 11,253.0 to CNY 11,184.4. The simulation results also demonstrate that the proposed model can effectively improve the operational economy of IESs, and the scheduling strategy can promote the consumption of renewable energy, with the wind curtailment rate decreasing from 63.62% to 12.50% and the solar curtailment rate decreasing from 56.92% to 21.34%. Full article

The article proposes a new model for defining and implementing performance tests used in the process of designing and operating IT systems. By defining the objectives, types, topological patterns, and methods of implementation, a coherent description of the test preparation and execution is achieved, facilitating the interpretation of results and enabling straightforward replication of test scenarios. The model was used to develop and implement performance tests in a laboratory environment and in a production system. The proposed division of the testing process into layers correlated with the test preparation steps allows to separate quasi-independent areas, which can be handled by isolated teams of engineers. Such an approach allows to accelerate the process of implementation of performance tests and may affect the optimization of the cost of their implementation. Full article

As modern diesel engine design progresses toward higher burst pressure and power density, strict performance indices impose greater demands on the structural strength and reliability of crankshafts. We integrated finite element analysis and strength testing methods to achieve a lightweight crankshaft design. A comparison of the simulated results with the test data revealed that the crankshaft safety factor surpassed the permissible safety factor by 3.5 times, demonstrating significant safety redundancy in the design. We employed topology optimization techniques to create various crankshaft optimization models, yielding near-optimal solutions. Consequently, we identified the crankshaft with the best overall performance following comparative evaluations. We examined the influence of the fillet structure on the safety factor to mitigate stress concentration issues. Through multibody dynamic fatigue analysis, optimizing the crankshaft fillet resulted in a 6~7% increase in the safety factor. The minimum safety factor for the designed crankshaft was 1.6 times higher than the material permissible safety factor, which was 1.15. Utilizing the developed transient dynamics model of the lightweight crankshaft and a backpropagation genetic algorithm, we created a crankshaft fillet design tool to streamline the design process, which holds significant importance for the marine engine sector. Full article

In this study, a novel non-cooperative two-player game for minimizing static (Player 1) and dynamic (Player 2) compliances is introduced, implemented, and demonstrated using a multi-scale topology optimization framework for triply periodic minimal surface (TPMS)-based lattice structures. Player 1 determines the optimal macro-layout by minimizing the static compliance based on a micro-layout provided by Player 2. Conversely, player 2 identifies the optimal micro-layout (grading of the TPMS-based lattice structure) by minimizing the dynamic compliance given a macro-layout from Player 1. The multi-scale topology optimization formulations are derived using two density variables in each finite element. The first variable is the standard density, which dictates whether the finite element is void or contains the graded lattice structure and is governed by the rational approximation of material properties (RAMP) model. The second density variable represents the local relative density of the TPMS-based lattice structure, determining the effective orthotropic elastic properties of the finite element. The multi-scale game is implemented for three-dimensional problems, and solved using a Gauss–Seidel algorithm with sequential linear programming. It is numerically demonstrated for several benchmarks that the proposed multi-scale game generates equilibrium designs with strong performance for both static and harmonic load cases, effectively avoiding resonance at harmonic load frequencies. Validation is achieved through modal analyses of finite element models of the optimal designs. Full article

Real-time status monitoring is crucial in ensuring the safety of railway tunnel traffic. The primary monitoring method currently involves deploying sensors to form a Wireless Sensor Network (WSN). Due to the linear characteristics of railway tunnels, the resulting sensor networks usually have a linear topology known as a thick Linear Wireless Sensor Network (LWSN). In practice, sensors are deployed randomly within the area, and to balance the energy consumption among nodes and extend the network’s lifespan, this paper proposes a self-organizing network and routing method based on thick LWSNs. This method can discover the topology, form the network from randomly deployed sensor nodes, establish adjacency relationships, and automatically form clusters using a timing mechanism. In the routing, considering the cluster heads’ load, residual energy, and the distance to the sink node, the optimal next-hop cluster head is selected to minimize energy disparity among nodes. Simulation experiments demonstrate that this method has significant advantages in balancing network energy and extending network lifespan for LWSNs. Full article

This study investigates the fluidic properties of the Diamond and SplitP structures with varying porosity levels (55%, 65%, and 75%) for tissue engineering applications using computational analysis. The scaffolds were designed using nTopology software and optimized to achieve the desired porosity and mechanical properties. The power law model was utilized to analyze blood as a non-Newtonian fluid. The study aims to optimize the scaffolds by observing fluidic characteristics such as permeability, pressure drop, and wall shear stress (WSS) to make them the optimal choice for bone tissue engineering applications. The results demonstrate that increasing porosity leads to higher permeability and lower pressure drop and WSS across the scaffolds. The findings suggest that the optimized Diamond and SplitP scaffolds with appropriate porosity levels can provide a suitable environment for cell adhesion, migration, proliferation, and differentiation, making them promising candidates for bone tissue engineering applications. Full article