Search Results (280)

Underwater wireless sensor networks (UWSNs) support critical applications such as environmental monitoring, offshore exploration, and surveillance; however, their performance is constrained by high propagation delay, limited energy resources, and node mobility caused by ocean dynamics. Many clustering approaches assume static nodes and use fixed-weight objective aggregation, which may reduce adaptability and lead to premature convergence. This paper proposes a cluster-head selection and cluster formation method for UWSNs based on a binary multi-objective Dragonfly Algorithm (BMDA-UWSN). The method considers energy consumption, acoustic latency, and load balance within a Pareto-based optimization framework, thereby reducing dependence on fixed-weight aggregation during the search stage. In addition, the Dragonfly-based optimization process uses dynamically adjusted coefficients to regulate the balance between exploration and exploitation while preserving solution diversity. To represent underwater node displacement, a semicircular mobility model with angular variation of ±45° is incorporated into the simulation scenario. Results obtained for a 100-node network show that BMDA-UWSN achieved better performance than Direct Transmission, LEACH, LEACH-C, SS-GSO, and CDFO-UWSN in terms of network lifetime, packet delivery, latency, and residual energy under the evaluated conditions. In particular, the first node dies at iteration 126 with BMDA-UWSN, compared with iteration 95 for CDFO-UWSN, while packet delivery increases by approximately 20% and latency decreases by about 5%. These findings suggest that BMDA-UWSN is a competitive clustering approach for underwater monitoring scenarios when evaluated under controlled node mobility conditions. Full article

This study proposes a stress field data-driven prediction method that combines a finite element thermo-mechanical coupling model with a multi-machine learning framework. This method takes the inversion of stress based on the shrinkage behavior of deposition layers as the core logic, extracts the node displacement shrinkage during the cooling to solidification process of the melt pool in the thermal coupling simulation as the key feature input, and constructs extreme gradient boosting (XGBoost), Gaussian process regression (GPR), and deep convolutional neural network (DCNN) models, respectively, to achieve accurate prediction of nodal effect stress and triaxial stress in the laser directed energy deposition (L-DED) node process. The experimental results show that the XGBoost algorithm performs the best in various stress prediction indicators, and its generated stress distribution cloud map is highly consistent with the thermal coupling simulation results, suggesting a strong correlation between deposition layer shrinkage behavior and the stress field under the investigated conditions. In addition, compared to traditional finite element simulations, this method significantly improves computational efficiency while ensuring prediction accuracy, providing a new approach for rapid assessment of residual stresses. Full article

This work explores the key capabilities of emerging sensing technologies in the context of Structural Health Monitoring (SHM) of civil infrastructures, aiming to contribute to research on integrated and intelligent systems for more accessible and efficient monitoring solutions. As a case study, it focuses on the analysis of the static and dynamic behavior of the Edgar Cardoso stay-cable bridge during its rehabilitation, using fully customized transducers and equipment. The developed system integrates sensors capable of measuring accelerations, displacements, and temperature, which are connected to an autonomous data acquisition and transmission network. A digital interface was also developed to store, process, and visualize the collected data, enabling remote access for subsequent interpretation and analysis. The main contribution of this research lies in the use of optimized wireless monitoring systems with extended autonomy. This is achieved by employing edge computing techniques to minimize energy consumption during data transmission, as well as by managing the sleep modes of the sensor nodes. At same time, a methodology was proposed for the automatic and real-time estimation of axial forces in cables. This approach relies on the use of innovative edge computing tools, combined with the taut string theory as a simplified modelling framework. The results confirm the effectiveness of the developed system in achieving long-term operation without compromising monitoring performance. In addition, the developed system enabled the identification of the structure’s dynamic properties, particularly natural frequencies. The temperature profiles in critical sections, as well as displacements in the expansion joint were also measured and evaluated. The results demonstrate the potential of customized sensing solutions as effective tools for the management, maintenance, and long-term preservation of strategic infrastructures. Full article

Public health suffers from noxious gas emitted by massive beached Sargassum algae. Net-barrages deployed in near-shore seas can contain Sargassum, provided they efficiently resist the additional hydrodynamic pressure induced by the catch. Nowadays, the design and installation of net-barrages are empiric. Structural breaks and anchor and mooring chain drifts can arise. We provide a mechanical model to evaluate stresses and loads on a structure made of fishing nets and buoy moorings. Hydrodynamic uncertainties occur through catches, fouling and sea current amplitudes appearing in lagoons or sheltered bays. This study presents a non-linear four-node finite-element model for continuous elastic membranes undergoing large displacements and small strains. The model relies on the Lagrangian linearly elastic membrane theory, employing the non-linear Green strain tensor and a non-updated hydrodynamic loading. We study forcings fixed a priori on a netting section of barrage that is 50 m long and 1 m high with double layer, e.g., two net-faces. We consider low and moderate current velocities, 0.05 and 0.35 m∙s⁻¹, while assuming specific vertical and horizontal catch pressures. A barrage installed in the reef lagoon at Le François on Martinique Island that is observable by satellite imagery could benefit of the computed net and mooring tensions. Full article

Vision-based structural health monitoring offers a promising alternative to conventional wired sensing systems; however, its adoption is often limited by high hardware costs and computational constraints at sensing nodes. This study presents the design and laboratory validation of a low-cost vision-based system for displacement and strain monitoring using a centralized processing architecture. The proposed system separates image acquisition from computation, where an ESP32-CAM module serves as a lightweight edge node for grayscale image capture and wireless transmission, while computational tasks including displacement tracking, subpixel localization, scale calibration, and strain estimation are performed on a centralized unit. This enables low-cost deployment at USD 60 per node with low power consumption at 1 W. System performance was evaluated through controlled experiments, including a 24 h zero-drift test and quasi-static displacement tests up to 15 μm. Validation against a Linear Variable Differential Transformer (LVDT) shows close agreement, with an absolute error of 2.63 µε and drift within ±2 μm. The system achieves an effective strain range of ±35,000 με. These results demonstrate the potential of low-cost centralized vision-based systems, demonstrating strong potential for practical deployment in structural health monitoring applications. Full article

Addressing the persistent challenges of low resource utilization efficiency and the difficulty in quantifying hidden costs within the beef cattle sector, this study proposes an integrated diagnostic methodology that couples Material Flow Cost Accounting (MFCA) with Value Stream Mapping (VSM). Using a cohort of 1623 beef cattle finished in 2024 at the case study farm in Heilongjiang Province, China, the full life-cycle accounting reveals that hidden costs constitute 6.43% of total inputs. Attribution analysis further pinpoints two critical nodes: feed loss and bedding consumption, which account for 33.14% and 35.77% of negative product costs, respectively. Based on these diagnostics, two optimization strategies were devised: refined feed supply chain management and a recycled bedding system centered on the aerobic fermentation of cattle manure. Empirical estimates indicate that upgrading hardware facilities could reduce the feed loss rate to under 2%, yielding annual savings of ¥485,200. Furthermore, the bedding recycling system not only achieves zero waste discharge but also generates an average annual displacement income of ¥3.504 million, with an investment payback period of just 0.54 years. These findings demonstrate the efficacy of the coupled MFCA-VSM model in identifying environmental costs and unlocking economic potential, thereby providing an actionable pathway for the livestock industry’s transition toward more intensive and circular practices. Full article

This paper presents a symmetric positive definite (SPD) coupling between the boundary element method (BEM) and the finite element method (FEM) in the framework of the numerical manifold method (NMM) for two-dimensional linear elastic static problems. The BEM subdomain is treated as a single mathematical patch whose local approximation is derived from the displacement boundary integral equation, thereby preserving the nonlocal nature of BEM. The remaining domain is covered by a finite element mesh, with each node defining a patch and the associated shape functions serving as weight functions. Weight functions are defined over the entire mathematical cover, with explicit zero values outside the support of each patch. This global definition ensures that the partition of unity holds everywhere and enables the global displacement approximation to be expressed as a superposition of contributions from all patches. Within this unified framework, the interface between the BEM and FEM subdomains emerges naturally as a transition zone of weight functions, rather than a distinct boundary. Displacement continuity is automatically satisfied through the partition of unity, and traction equilibrium is approximately enforced through the variational formulation. To fully incorporate the coupling formulation into the minimum potential energy framework, the tractions on the BEM patch are eliminated in favor of displacements using the displacement boundary integral equation (BIE). Prescribed tractions on the BEM patch are enforced via a penalty method. The resulting algebraic system is symmetric by construction and remains positive definite when either constant or isoparametric boundary elements are used. This work serves as a proof-of-concept study for the SPD coupling framework with constant elements. Numerical examples demonstrate the accuracy and convergence of the method. The results show that the coupling procedure preserves the intrinsic convergence properties of each subdomain: the BEM part converges at a rate close to unity for displacements and approximately 2.0 for stresses, while the FEM part achieves quadratic convergence for both. The study also reveals that near-singular integrals in the strain BIE can affect the convergence rate when the element size becomes sufficiently small. Full article

Many challenges are commonly encountered in the underground mining of steeply dipping thin-to-medium-thick orebodies associated with weak hanging wall rockmass, such as stope back collapse, high ore dilution, and poor stoping stability. To address these issues, a synergistic mining method combining sidewall retaining and open stoping with a delayed backfilling method is proposed. Taking the north wing orebody of the Erlihe lead–zinc mine as the engineering background, a 3D finite element numerical simulation model was established using MIDAS GTS(2026 version) to conduct a comparative analysis between the proposed mining method and the current mining method. The mechanical response characteristics of crown pillar stress, crown pillar settlement, hanging wall displacement, and plastic zone evolution were systematically investigated under different mining stages. The results show that the proposed method improves the stress and deformation distribution at the bottom of the crown pillar. The peak stress decreases from 13.72 MPa to 12.86 MPa, and the spatial extent of the high-stress zone is noticeably reduced. Meanwhile, the maximum crown pillar subsidence decreases, while the width of the main subsidence zone decreases from 11 nodes to 9 nodes, and the settlement of the end region decreases by 6.05%. In terms of hanging wall response, the maximum displacement is reduced by 9.3–26.5% during the stope extraction stage and 9.6–10.0% during the inter-pillar recovery stage, with an overall average reduction of approximately 14.0%. Furthermore, the plastic zone in the hanging wall surrounding rock becomes smaller and develops later under the proposed mining method. Our findings demonstrate that the new proposed mining method effectively modifies the stress transfer path, mitigates deformation of both the crown pillar and hanging wall rock, and delays the development of plastic failure, thereby improving stope stability under weak hanging wall rockmass conditions. The proposed method provides a practical technical solution for the safe and efficient extraction of steeply dipping thin-to-medium-thick orebodies. Full article

As the most prevalent type of existing building in China, masonry structures are susceptible to cracking due to the low tensile strength of the masonry material. In the event of a sudden, strong earthquake, they are highly prone to brittle collapse, leaving occupants little time and space to escape. Based on this, combining the advantages of the elastoplastic mechanical theory and the nonlinear finite element (FE) method, this study adopts different modeling methods: integral modeling (IM), contact element discrete modeling (CEDM), spring element discrete modeling (SEDM), and co-node discrete modeling (CNDM). FE models of unreinforced masonry walls (UMWs) are established, respectively, and a monotonic pushover mechanical performance analysis is carried out. The accuracy of the adopted modeling methods is verified against existing test results for UMW specimens. Through parametric analysis of aspect ratios (0.5, 0.75, 1.0, and 1.25), axial compression ratios (0.1, 0.3, 0.5, 0.7, and 0.8), and mortar strengths (M5, M7.5, and M10), the characteristic mechanical performance factors of UMWs are determined. A novel strength index is proposed to discriminate between failure modes and elucidate the damage mechanism of UMWs. The results indicate that the ultimate load and its corresponding displacement change systematically with variations in aspect ratios, axial compression ratios, and mortar strengths. Furthermore, integrating stress cloud maps with the proposed strength index provides a quantitative basis for discriminating between flexural and shear failure modes in UMWs. All four modeling methods can, to varying degrees, capture the pushover behavior of UMWs, and quantifiable selection schemes are provided to balance analysis accuracy and computational cost. The analytical methods and findings presented in this work can be applied to performance assessment, seismic design, and engineering practice of UMWs. Full article

Excessive vibration during critical speed traversal remains a primary challenge in assembling multi-stage rotors of aero-engines. Conventional assembly optimization methods, which target static geometric and mass eccentricity errors or vibration at a fixed operating speed, are inadequate to ensure smooth passage through multiple critical speeds. To address this gap, we propose a novel, vibration-suppression-oriented assembly optimization model. A normalized objective function is formulated to minimize the overall vibration response across multiple rotor nodes specifically at the first and second critical speeds. This function integrates an assembly error propagation model with a rotor dynamic model that considers flexible dynamic deflection. The optimal assembly angle sequence is solved using a genetic algorithm. Experimental validation on a four-stage rotor demonstrates that the proposed method reduces the maximum vibration displacement amplitude at the first and second critical speeds by 74.7% and 11.9%, respectively, significantly outperforming conventional objectives based on geometric error, unbalanced mass, or single-speed vibration. This work provides a practical and effective strategy to enhance rotor dynamic safety by ensuring low-vibration operation across the critical speeds encountered before reaching the operating speed through optimal assembly. Full article

Objectives: This study aimed to analyze the three-dimensional displacement of maxillary first molars using a finite element model with two headgear configurations, namely cervical and horizontal pull headgears, as well as pendulum, infrazygomatic miniscrews, Bollard miniplates, Advanced Molar Distalization Appliance (AMDA), and Beneslider. The goal was to clarify how variations in anchorage design and force direction influence molar movement across the sagittal, vertical, and transverse planes. Methods: A three-dimensional finite element model of the maxillary dentition and supporting structures was constructed using reference anatomical data and standardized material properties. Each appliance was virtually simulated under its clinically recommended force magnitude and direction to ensure realistic biomechanical conditions. The orientation of each force vector relative to the molar’s center of resistance (CR) was analyzed, and resulting tooth displacements were quantified along the sagittal (Z), vertical (Y), and transverse (X) axes using 49-node reference paths connecting key anatomical landmarks. Results: Appliances applying forces through or above the molar CR, such as the AMDA, infrazygomatic miniscrews, and Bollard miniplates, produced nearly bodily distalization with minimal tipping (<0.6° (range 0.3–0.6°)) and slight intrusion (−0.12 to −0.18 mm). Conversely, systems delivering forces below the CR, such as the cervical headgear and pendulum, resulted in greater crown tipping and extrusion. The Beneslider exhibited an intermediate displacement pattern with moderate vertical control. Conclusions: Force vector height and direction relative to the molar CR critically determine 3D displacement behavior. Skeletal anchorage and adjustable systems, particularly the AMDA, demonstrated the most controlled distalization pattern with minimal tipping, whereas conventional tooth-borne designs induced more tipping and extrusion. Full article

Vibration energy harvesting is a promising approach to support and supplement power, thereby extending the lifetime of low-power sensor nodes under suitable vibration conditions, i.e., in environments where sufficient ambient vibrations are available. It is not a universal autonomous power-supply solution, particularly when generalized across the Internet of Things (IoT), because the harvested power is typically limited to the µW–mW range and depends strongly on the vibration frequency content, amplitude, and operating point relative to resonance. Furthermore, many practical harvesters rely on resonant mechanisms, which are inherently narrowband, and therefore their performance can degrade significantly under detuning or broadband/variable-frequency excitations. In addition, energy-management and power-conditioning electronics (rectification, storage, and regulation) are required to convert the generated electrical energy into a stable and usable DC supply for practical loads. In this work, we develop a nonlinear state-space model of a three-phase electromagnetic vibration energy harvester with spatially displaced coils and evaluate its electrical output characteristics and DC power behavior using numerical simulations. Full article

Frequent large-scale construction projects have rendered subway box structures vulnerable to displacements. This study examined the adequacy of foundation reinforcement for a subway box structure exhibiting displacement behavior. A displacement function was derived from the optical leveling data, and a three-dimensional numerical analysis was performed by applying the computed subgrade elastic modulus as a boundary condition. The analysis produced estimates of uplift and subsidence at the nodes along both the transverse and longitudinal directions of the structure. To determine the required amount of reinforcement (grouting volume), the nodal reinforcement depth obtained from the analysis was applied to a grid-based volumetric calculation method. The nodal intervals were subdivided to the maximum feasible extent, and rectangular grids with sufficient resolution were established to ensure accurate reinforcement-volume calculation. The reinforcement volumes estimated through the numerical analysis were compared with actual field values to assess the adequacy of the foundation reinforcement. Some differences were observed, which were attributed to field constraints that prevented reinforcements at certain required locations. Based on these findings, additional reinforcements can be applied at the analytically identified locations to ensure the structural safety of the subway box structure. Full article

Reinforced concrete conical shell silo roofs continue to present construction challenges, despite the widespread adoption of slip-form technology for silo walls. This study introduces a novel combined temporary support system for cast-in-place conical shell silo roofs, validated through an engineering case in Suiping. The proposed system consists of (i) an umbrella-type conical shell combined support structure and (ii) a cross-type vertical core-tube support. Focusing on the umbrella subsystem, a shell–truss framework is developed based on the geometry of cylindrical–conical shell roofs. Special structural components, along with prestressed reinforcement techniques, are introduced following the principles of structural and elastic mechanics. The traditional inclined-beam shoring concept is incorporated into an arched load path: inclined members are circumferentially connected at nodes to form a shell–arch support mechanism, thereby improving force transfer efficiency and reducing flexural demands. Finite element analyses of representative construction stages are conducted to evaluate displacement and stress responses. The results show that the proposed combined support system meets strength and stiffness requirements during roof construction and provides an efficient and practical solution for large-span conical shell silo roofs. Full article

Modal superposition enables efficient estimation of full-field structural displacements from sparse measurements, forming a keystone of structural health monitoring (SHM) in linear elastic systems. Accurate reconstruction critically depends on selection of the most relevant vibration modes, traditionally guided by the Internal Strain Potential Energy Criterion (ISPEC), which identifies modes contributing most to internal strain energy. However, the purely analytical formulation of ISPEC requires full knowledge of the deformation field, limiting its applicability in real-time monitoring. This study extends ISPEC using supervised machine learning to enable adaptive mode selection for previously unseen deformation states. A Random Forest classifier is trained on synthetic deformation data generated from a finite element model of a square steel plate. Measurement signals are obtained from a transient analysis in which harmonic displacements are applied to four nodes at the plate plane. Reconstruction performance is evaluated numerically by comparing predicted displacements against reference finite element solutions, using instantaneous residuals, normalised root-mean-square error (NRMSE) and normalised cross-correlation. Results demonstrate that the hybrid ISPEC–machine learning approach accurately reconstructs full-field deflections from eight measurement nodes, with NRMSE typically below 5% and cross-correlation above 0.75. Minor overestimation at peak deflections indicates conservative predictions, while computational efficiency allows real-time implementation. Full article