Search Results (74)

The use of aluminum honeycomb structures is fast expanding in advanced sectors such as the aeronautics, aerospace, marine, and automotive industries. However, processing these structures represents a major challenge for producing parts that meet the strict standards. To address this issue, an innovative manufacturing method using longitudinal ultrasonic vibration-assisted cutting, combined with a CDZ10 hybrid cutting tool, was developed to optimize the efficiency of traditional machining processes. To this end, a 3D numerical model was developed using the finite element method and Abaqus/Explicit 2017 software to simulate the complex interactions among the cutting tool and the thin walls of the structures. This model was validated by experimental tests, allowing the study of the influence of milling conditions such as feed rate, cutting angle, and vibration amplitude. The numerical results revealed that the hybrid technology significantly reduces the cutting force components, with a decrease ranging from 10% to 42%. In addition, it improves cutting quality by reducing plastic deformation and cell wall tearing, which prevents the formation of chips clumps on the tool edges, thus avoiding early wear of the tool. These outcomes offer new insights into optimizing industrial processes, particularly in fields with stringent precision and performance demands, like the aerospace sector. Full article

An innovative high-order dimensionality reduction approach, which integrates a condensed finite-difference scheme with proper orthogonal decomposition techniques, has been explored for solving diffusion equations. The difference scheme with forth order accurate in both space and time is introduced through the idea of interpolation approximation. The quartic spline function and $(2,2)$ Padé approximation were utilized in space and time discretization, respectively. The stability and convergence were proven. Moreover, the dimensionality reduction formulas were derived using the proper orthogonal decomposition (POD) method, which is based on the matrix representation of the compact finite-difference scheme. The bases of the POD method were established by cumulative contribution rate of the eigenvalues of snapshot matrix that is different from the traditional ways in which the bases were established by the first eigenvalues. The method of cumulative contribution rate can optimize the degree of freedom. The error analysis of the reduced bases high-order POD finite-difference scheme was provided. Numerical experiments are conducted to validate the soundness and dependability of the reduced-order algorithm. The comparisons between the $(2,2)$ finite-difference method, the traditional POD method, and reduced dimensional method with cumulative contribution rate were discussed. Full article

In recent years, the traditional orchard sprayer has had problems, such as waste of liquid agrochemicals, low target coverage, high manual dependence, and environmental pollution. In this study, an automatic swing-arm sprayer for orchards was developed based on the standardized pear orchard in Pinggu, Beijing. Firstly, the structural principles of a crawler-type traveling system and swing-arm sprayer were simulated using finite element software design. The combination of a diffuse reflection photoelectric sensor and Arduino single-chip microcomputer was used to realize real-time detection and dynamic spray control in the pear canopy, and the sensor delay compensation algorithm was used to optimize target recognition accuracy and improve the utilization rate of liquid agrochemicals. Through the integration of innovative structural design and intelligent control technology, a vertical droplet distribution test was carried out, and the optimal working distance of the spray was determined to be 1 m; the nozzle angle for the upper layer was 45°, that for the lower layer was 15°, and the optimal speed of the swing-arm motor was 75 r/min. Finally, a particle size test and field test of the orchard sprayer were completed, and it was concluded that the swing-arm mode increased the pear tree canopy droplet coverage by 74%, the overall droplet density by 21.4%, and the deposition amount by 23% compared with the non-swing-arm mode, which verified the practicability and reliability of the swing-arm spray and achieved the goal of on-demand pesticide application in pear orchards. Full article

Machining Nomex honeycomb cores is essential for manufacturing components that meet the stringent requirements of industrial sectors, but the complexity of this type of structure material requires specialized techniques to minimize defects, ensure optimal surface quality and extend cutting tool life. For this reason, an innovative machining technology based on longitudinal–torsional ultrasonic vibration assistance has been integrated into a CZ10 combined cutting tool, with the aim of optimizing the efficiency of conventional machining processes. To this end, a three-dimensional numerical model based on the finite element method, developed using Abaqus/Explicit 2017 software, was used to simulate the complex interactions between the cutting tool and the thin walls of the structures to be machined. This study aimed to validate the numerical model through experimental tests, quantifying the surface condition, cutting force and tool wear, while evaluating the impact of key machining parameters, such as feed rate and wall thickness, on process performance. The obtained results reveal a substantial reduction in cutting forces, varying from 20 to 40%, as well as a notable improvement in surface finish and a significant extension of tool life. These conclusions open up new perspectives for the optimization of industrial processes, particularly in high-demand sectors such as aeronautics. Full article

In the context of sustainable manufacturing practices, minimum quantity lubrication (MQL) has been extensively employed in machining operations involving hard-to-cut materials. While substantial experimental and numerical investigations on MQL-assisted machining have been conducted, existing simulation approaches remain inadequate for modeling the dynamic flow field variations inherent to MQL processes, significantly compromising the predictive reliability of current models. This study introduced an innovative bidirectional iterative coupling framework integrating finite element (FE) analysis and computational fluid dynamics (CFD) to enhance simulation accuracy. Since fluid flow characteristics critically influence tribological and thermal management at the tool–workpiece interface during machining, CFD simulations were initially performed to evaluate how MQL parameters govern fluid flow behavior. Subsequently, an integrated FE-CFD modeling approach was developed to simulate Ti-6Al-4V alloy turning under MQL conditions with varying feed rates. The novel methodology involved transferring thermal flux data from FE simulations to CFD’s heat source domain, followed by incorporating CFD-derived convective heat transfer coefficients back into FE computations. This repetitive feedback process continued until the thermal exchange parameters reached convergence. Validation experiments demonstrated that the proposed method achieved improved alignment between the simulated and experimental results for both cutting temperature profiles and principal force components across different feed conditions, confirming the enhanced predictive capability of this coupled simulation strategy. Full article

The implementation of lean drilling and completion design techniques is a pivotal strategy for the petroleum and natural gas industry to achieve green, low-carbon, and intelligent transformation and innovation. These techniques significantly enhance oil and gas recovery rates. In shale gas development, the shale brittleness index plays a crucial role in evaluating fracturing ability during hydraulic fracturing. Indoor experiments on Gulong shale oil were conducted under a confining pressure of 30 MPa. Based on Rickman’s brittleness evaluation method, this study performed numerical simulations of triaxial compression tests on shale using the finite discrete element method. The fractal dimensions of the fractures formed during shale fragmentation were calculated using the box-counting method. Utilizing the obtained data, a multiple linear regression equation was established with elastic modulus and Poisson’s ratio as the primary variables, and the coefficients were normalized to propose a new brittleness evaluation method. The research findings indicate that the finite discrete element method can effectively simulate the rock fragmentation process, and the established multiple linear regression equation demonstrates high reliability. The weights reassigned for brittleness evaluation based on Rickman’s method are as follows: the coefficient for elastic modulus is 0.43, and the coefficient for Poisson’s ratio is 0.57. Furthermore, the new brittleness evaluation method exhibits a stronger correlation with the brittleness mineral index. The fractal characteristics of crack networks and the relationship between symmetry response and mechanical parameters offer a new theoretical foundation for brittle weight distribution. Additionally, the scale symmetry characteristics inherent in fractal dimensions can serve as a significant indicator for assessing complex crack morphology. Full article

This research introduces an innovative probabilistic method for examining torsional stress behavior in spherical shell structures through Monte Carlo simulation techniques. The spherical geometry of these components creates distinctive computational difficulties for conventional analytical and deterministic numerical approaches when solving torsion-related problems. The authors develop a comprehensive mesh-free Monte Carlo framework built upon the Feynman–Kac formula, which maintains the geometric symmetry of the domain while offering a probabilistic solution representation via stochastic processes on spherical surfaces. The technique models Brownian motion paths on spherical surfaces using the Euler–Maruyama numerical scheme, converting the Saint-Venant torsion equation into a problem of stochastic integration. The computational implementation utilizes the Fibonacci sphere technique for achieving uniform point placement, employs adaptive time-stepping strategies to address pole singularities, and incorporates efficient algorithms for boundary identification. This symmetry-maintaining approach circumvents the mesh generation complications inherent in finite element and finite difference techniques, which typically compromise the problem’s natural symmetry, while delivering comparable precision. Performance evaluations reveal nearly linear parallel computational scaling across up to eight processing cores with efficiency rates above 70%, making the method well-suited for multi-core computational platforms. The approach demonstrates particular effectiveness in analyzing torsional stress patterns in thin-walled spherical components under both symmetric and asymmetric boundary scenarios, where traditional grid-based methods encounter discretization and convergence difficulties. The findings offer valuable practical recommendations for material specification and structural design enhancement, especially relevant for pressure vessel and dome structure applications experiencing torsional loads. However, the probabilistic characteristics of the method create statistical uncertainty that requires cautious result interpretation, and computational expenses may surpass those of deterministic approaches for less complex geometries. Engineering analysis of the outcomes provides actionable recommendations for optimizing material utilization and maintaining structural reliability under torsional loading conditions. Full article

The interference of metal working surfaces on the electric field can lead to performance variations between the flush mounting and non-flush mounting of capacitive proximity sensors in industrial applications. Traditional active shielding circuit designs are complex, while grounding shields not only reduce the sensor sensitivity but are also unsuitable for grounded sensors. To address this issue, this paper proposes an innovative near-ground (NG) shielding structure. This structure effectively concentrates the electric field between the sensing electrode and ground by adding a common ground electrode around the sensing electrode, thereby reducing the electrical coupling between the metal working surface and the sensing electrode and achieving the desired shielding effect. Through finite element analysis and experimental verification, this study performed an in-depth investigation of the capacitance difference $C_d$ and the rate of change of capacitance with the target distance of sensors under the two mounting methods. The proposed structure achieved a performance comparable with active shielding (17 fF $C_d$) while operating passively, which addressed a critical cost–adaptability trade-off in industrial CPS designs. The results show that although the performance of the NG shielding was slightly inferior to active shielding, it was significantly better than traditional grounding shielding, and its structure was simple and low cost, showing great potential in practical applications. Full article

In this study, the effect of plastic residual strain on the corrosion behavior of ZK60 magnesium alloy was systematically revealed using a research method combining experimental characterization and numerical simulation. Based on the multiphysical field coupling theory, a numerical model containing deformation field, corrosion phase field, and material transfer field was constructed, and the dynamic simulation of plastic residual strain-induced corrosion damage was successfully realized. Tafel polarization curves obtained from electrochemical tests were fitted to the key parameters of the secondary current distribution. The kinetic parameter L controlling the corrosion rate in the phase-field model was innovatively determined by the inverse calibration method, and a quantitative relationship between the kinetics of electrochemical corrosion and the phase-field theory was established. The corrosion depth distribution of the pre-strained specimens is quantitatively characterized and the results are in agreement with the finite element simulation results. The coupled strain-corrosion analysis method proposed in this study provides a theoretical basis for the design and life prediction of corrosion resistance of components under complex stress states. Full article

The Global Navigation Satellite System (GNSS) has emerged as a critical spatiotemporal infrastructure for ensuring the integrity of remote sensing data links. However, traditional GNSS antenna arrays, typically configured with the antenna spacing of half a wavelength, are constrained by the spatial limitations of remote sensing platforms. This limitation results in a restricted number of interference-resistant antennas, posing a risk of failure in scenarios involving distributed multi-source interference. To address this challenge, this paper focuses on the multidimensional trade-off problem in the design of compact GNSS anti-interference arrays under finite spatial constraints. For the first time, we systematically reveal the intrinsic relationships and game-theoretic mechanisms among key parameters, including the number of antennas, antenna spacing, antenna size, null width, coupling effects, and receiver availability. First, we propose a novel null width analysis method based on the steering vector correlation coefficient (SVCC), elucidating the inverse regulatory mechanism between increasing the number of antennas and reducing antenna spacing on null width. Furthermore, we demonstrate that increasing antenna size enhances the signal-to-noise ratio (SNR) while also introducing trade-offs with mutual coupling losses, which degrade SNR after compensation. Building on these insights, we innovatively propose a multi-objective optimization framework based on the non-dominated sorting genetic algorithm-II (NSGA-II) model, integrating antenna electromagnetic characteristics and signal processing constraints. Through iterative generation of the Pareto front, this framework achieves a globally optimal solution that balances spatial efficiency and anti-interference performance. Experimental results show that, under a platform constraint of 1 wavelength × 1 wavelength, the optimal number of antennas ranges from 15 to 17, corresponding to receiver availability rates of 89%, 72%, and 55%, respectively. Full article

The development of prosthetic limbs has benefited individuals who suffered amputations due to accidents or medical conditions. During the development of conventional prosthetics, several challenges have been observed regarding the functional limitations, the restricted degrees of freedom compared to an actual human limb, and the biocompatibility issues between the surface of the prosthetic limb and the human tissue or skin. These issues could result in mobility impairments due to failed mimicry of the actual stress distribution, causing discomfort, chronic pain, and tissue damage or possible infections. Especially in cases where underlying conditions exist, such as diabetes, possible trauma, or vascular disease, a failed adaptation of the prosthetic limb could lead to complete abandonment of the prosthetic part. To address these challenges, the insertion of topologically optimized parts with a biomimetic approach has allowed the optimization of the mimicry of the complex functionality behavior of the natural body parts, allowing the development of lightweight efficient anthropomorphic structures. This approach results in unified stress distribution, minimizing the practical limitations while also adding an aesthetic that aids in reducing any possible symptoms related to social anxiety and impaired social functioning. In this paper, the development of a novel anthropomorphic designed prosthetic foot with a novel Thermoplastic Polyurethane-based composite (TPU-Ground Tire Rubber 10 wt.%) was studied. The final designs contain advanced sustainable polymeric materials, gyroid lattice geometries, and Finite Element Analysis (FEA) for performance optimization. Initially, a static evaluation was conducted to replicate the phenomena at the standing process of a conventional replicated above-knee prosthetic. Furthermore, dynamic testing was conducted to assess the mechanical responses to high-intensity exercises (e.g., sprinting, jumping). The evaluation of the dynamic mechanical response of the prosthetic limb was compared to actual plantogram-derived foot pressure data during static phases (standing, light walking) and dynamic phenomena (sprinting, jumping) to address the optimal geometry and density, ensuring maximum compatibility. This innovative approach allows the development of tailored prosthetic limbs with optimal replication of the human motion patterns, resulting in improved patient outcomes and higher success rates. The proposed design presented hysteretic damping factor and energy absorption efficiency adequate for load handling of intense exercises (0.18 loss factor, 57% energy absorption efficiency) meaning that it is suitable for further research and possible upcycling. Full article

Cranial sutures play critical roles in load distribution and neuroprotection, with their biomechanical performance intimately linked to morphological complexity. The purpose of this study was to investigate the effect of different morphologies of cranial sutures on their biomechanical behavior. Based on the different morphologies of the cranial sutures, six groups of finite element models (closed, straight, sine wave, tight sinusoidal wave, layered sinusoidal wave, and layered sinusoidal wave + sutural bone) of the bone–suture–bone composite structures that ranged from simple to complex were constructed. Each model was subjected to 50 kPa impact and 98 N bilateral tensile loads to evaluate von Mises stress and total deformation variations across all groups under combined loading conditions. Key findings reveal that morphological complexity directly governs stress dynamics and mechanical adaptation; layered sinusoidal configurations delayed peak stress by 19–36% and generated elevated von Mises stresses compared to closed sutures, with stress concentrations correlating with interfacial roughness. Under impact, sutures exhibited localized energy dissipation (<0.2 μm deformation), while tensile loading induced uniform displacements (≤11 μm) across all morphologies (p > 0.05), underscoring their dual roles in localized energy absorption and global strain redistribution. Craniosacral therapy relevant forces produced sub-micron deformations far below pathological thresholds (≥1 mm), which implies the biomechanical safety of recommended therapeutic force. Staggered suture–bone in open sutures (31.93% closure rate) enhances shear resistance, whereas closed sutures prioritize rigidity. The findings provide mechanistic explanations for suture pathological vulnerability and clinical intervention limitations, offering a quantitative foundation for future research on cranial biomechanics and therapeutic innovation. Full article

In line with Sustainable Development Goal 9 (sustainable industrialisation and innovation), environmentally responsible engineering designs in modern robotics should consider factors such as renewability, sustainability, and biodegradability. The robotics sector is growing at an exponential rate and, as a consequence, its contribution to e-waste is a growing concern. Our work contributes to the technological development of caninoid necro-robots, robots that are built from the skeletons of deceased dogs. The already formed skeletal structures of deceased dogs (and other animals) are ideal natural material replacements for synthetic robotic architectures such as plastics, metals, and composites. Since dog skeletons are disarticulated, simple but effective methods need to be developed to rearticulate their bodies. The canine head is essentially a large end effector, but its mandible is held together by a fibrocartilaginous joint (symphysis) that degrades at a higher rate than the bone itself. The degradation of the symphysis would ordinarily negate the utility of a canine head as a necro-robotic end effector; however, in this research, we consider simple methods of mandible reinforcement to circumvent this problem. Our research uses 3D scans of a real canine head, which is modelled using the finite element method to ascertain optimal geometrical reinforcements for the mandible. The full head structures and their reinforcements are printed and adhesively connected to determine the most effective reinforcing strategy of the mandible. Here, we elucidate geometrically selected reinforcement designs that are evidenced through mechanical testing, to successfully increase the stiffness of a disarticulated mandible. Full article

In this paper, we employ interpolation and projection methodologies to establish a superconvergence outcome for the Stokes problem, as approximated by the mixed finite element method (FEM) utilizing Bernstein polynomial basis functions. It is widely recognized that the convergence rate of the FEM in the L²-norm is $\mathcal{O}\left(h^{m+2}\right)$. However, this paper presents an innovative superconvergence result: specifically, in terms of the L²-norm, the error convergence rate between the mixed finite element approximate solution and the local projection is $\mathcal{O}\left(h^{m+2}\right)$, with m denoting the order of the Bernstein polynomial basis function. Full article

This study presents the design, development, and implementation of a novel modular three-axis cutting force measurement system for turning lathes. The system employs miniature load cells in an innovative two-channel slotted dynamometer structure, offering a cost-effective and compact alternative to conventional dynamometers. The primary structure utilizes a cantilever concept, in which cutting forces induce deformation, compressing strategically positioned load cells. A 300 kgf load cell measures the main cutting force, while a 100 kgf load cell detects the feed force. Additionally, a 20 kgf load cell measures the radial force through a sliding tool holder mechanism. Finite element analysis was employed to optimize the dynamometer’s parameters, striking a balance between maximum deflection and structural integrity. The optimized design achieved a safety factor of 4.377, with maximum deflections of 8.81 µm and 9.89 µm for the main cutting and feed force measurements, respectively. Static calibration of the load cells demonstrated robust correlations between voltage and force, with the coefficient of determination (R²) values exceeding 0.999. The system’s precision was evaluated through cutting experiments on mild steel of varying depths (0.5, 0.75, 1.0 mm) and feed rates (0.105, 0.150, 0.210 mm/rev). The experimental results indicate that the main cutting force consistently exceeded feed and radial forces across all conditions. The system exhibited high precision, with relative standard deviation (RSD) percentages below 5% on average and not exceeding 7.5% in individual experiments. This modular dynamometer design offers a flexible, precise, and cost-effective solution for cutting force measurement in turning operations. Its modularity facilitates easy maintenance and adaptation to various cutting conditions, rendering the developed modular turning dynamometer suitable for both research and industrial applications. Full article