Search Results (38,723)

In this study, variational Bayesian inference (VBI) with Gaussian mixture models is applied to update models of nonlinear structures, and then, the calibrated model is employed to estimate the failure probability of structures using a subset simulation (SS) algorithm. To improve the computation efficiency of probabilistic nonlinear model updating, a Gaussian Process (GP) model is used to construct a surrogate likelihood function in Bayesian inference using an active learning algorithm, and then, Gaussian mixture models (GMMs) are employed to approximate the unknown posterior probabilistic density functions (PDFs) of model parameters. The optimized hyperparameters of GMMs can be obtained by maximizing the evidence lower bound (ELBO), and the stochastic gradient search method is used to solve this optimization problem. Based on the optimized hyperparameters, the posterior distributions of model parameters can be approximated using a combination of multiple Gaussian components. Subsequently, the SS algorithm is used to calculate the earthquake-induced failure probability of structures based on the calibrated nonlinear model. To verify the feasibility and effectiveness of the proposed method, a numerical simulation of a two-span bridge structure subjected to seismic excitations was developed. Moreover, the proposed strategy is further applied to estimate the failure probability of a scaled monolithic column structure subjected to bi-directional earthquake excitations. Both numerical and experimental results indicate that the proposed method is feasible and effective for probabilistic nonlinear model updates, and the updated model can significantly enhance the accuracy of structural failure probability predictions. Full article

Remotely operated underwater vehicles (ROVs) play a significant role in the domain of underwater robotics, as observed in the field of deep-sea aquaculture. However, conventional stationary suction-tube underwater collection robots often struggle to efficiently collect target organisms located within complex reef environments. To address this limitation, this paper proposes an underwater object suction robot with a variable flexible tube. For vision-based object recognition tasks, stable vehicle motion is essential, as hydrodynamic disturbances can significantly degrade visual accuracy. Therefore, a systematic numerical investigation is conducted into the hydrodynamic characteristics of the ROV under different suction-tube shapes. Computational fluid dynamics (CFD) simulations are used to evaluate the resistance acting on the vehicle. The results provide guidance for motion control strategies aimed at reducing disturbance effects and improving the robustness of underwater robotic vision. Full article

Plunge shaving is a widely used finishing process for high-precision gears due to its high productivity and cost-effectiveness. However, manufacturing the plunge-shaving cutter itself remains challenging, particularly for modified tooth profiles. Because the theoretical cutter flank exhibits a hyperboloid-like geometry in the lead direction, conventional disk-wheel grinding tends to introduce systematic twist-like topographic bias. To overcome this limitation, a comprehensive mathematical framework is developed for the generative grinding of plunge-shaving cutters using an involute-helicoid grinding worm. Based on envelope theory and homogeneous coordinate transformations, the theoretical cutter surface is first derived, followed by the establishment of a complete kinematic grinding model. A linear least-squares optimization algorithm is then formulated to determine the optimal center-distance compensation parameter for minimizing the normal deviation between the generated and theoretical surfaces. Numerical simulations demonstrate that the proposed method significantly suppresses twist-related topographic errors. In a benchmark moderate-helix case, the maximum residual deviation is controlled to approximately 2 µm. For a more demanding large-helix configuration, a two-level optimization strategy—combining machine-setting compensation and grinding-worm helix-angle adjustment—reduces the peak deviation from about 5.5 µm to 4.7 µm, corresponding to an improvement of approximately 15%. This confirms that worm-geometry tuning provides an additional, effective degree of freedom for high-helix cutter applications. Full article

In the automotive industry, the most critical factor affecting dimensional stability during the forming of Advanced High-Strength Steels (AHSSs) is the springback phenomenon. This study systematically investigates the springback behavior of four distinct dual-phase steel grades (DP450, DP600, DP800, and DP1000) in U-shaped body-in-white (BIW) structures across 180 distinct scenarios. The experimental design varied sheet thicknesses (1.2, 1.6, 2 mm), die clearance angles (5°, 10°, 15°), and bending radii (R6, R8, R10, R12, R14). Numerical simulations using Autoform R8 were validated against Atos 3D optical scanning data, achieving values exceeding 0.90 for all grades. Quantitative validation metrics showed exceptional fidelity for lower-strength grades with error margins below 1.1%, while the maximum deviation was limited to 3.1% for the ultra-high-strength DP1000 grade. The findings demonstrate that while increasing material strength substantially intensifies springback, the strategic augmentation of sheet thickness and optimization of die radius effectively mitigate these deviations, thereby enhancing process stability. Full article

In this paper, we investigate parameter estimation for a class of linear self-attracting diffusion processes. Specifically, we consider processes with a drift coefficient given by $-\theta \left({\int }_0^t(X_t-X_u)du\right)$. Employing both maximum likelihood estimation and least squares estimation, we show that the resulting estimators coincide. We establish the consistency and asymptotic normality of ${\widehat{\theta }}_N$ for high-frequency data, and assess its numerical performance through simulation studies. Full article

Master–slave bilateral teleoperation systems face several practical challenges, including model uncertainties, time-varying communication delays, and environment-induced force disturbances. To address these issues, this paper proposes an adaptive super-twisting sliding-mode control scheme to achieve high-precision position tracking and real-time force-feedback synchronization. First, joint-space dynamic models are established for both the master and the slave manipulators, and a passive impedance model is adopted to characterize the interaction dynamics at the operator–master and environment–slave interfaces. Second, to attenuate measurement noise in the environment interaction force, a first-order low-pass filter is used to preprocess the raw force measurements, and a radial basis function neural network (RBFNN) is employed to approximate the environment torque online. Furthermore, a super-twisting sliding-mode controller is developed and combined with an adaptive law to compensate online for system uncertainties, including dynamic parameter variations and environment-induced force disturbances. The stability of the resulting closed-loop system is rigorously analyzed using Lyapunov stability theory. Finally, the effectiveness of the proposed method is validated through numerical simulations, virtual experiments conducted in the MuJoCo physics engine, and real-world hardware experiments. The results show that the proposed strategy achieves accurate position synchronization and force tracking while maintaining stable haptic interaction in the presence of bounded time-varying delays, parameter uncertainties, and external disturbances. Full article

Groundwater contamination caused by dense non-aqueous phase liquid (DNAPL) has long been recognized as a persistent environmental challenge, particularly in fractured porous media. DNAPL migration is highly uncertain due to the heterogeneity and complexity of fracture networks, which complicates risk assessment and remediation design. This paper begins with an overview of mathematical models for multiphase flow migration in fractured media, followed by a systematic analysis and classification of DNAPL migration mechanisms based on laboratory experiments and numerical simulations. Subsequently, key challenges in current DNAPL remediation practices are discussed, including difficulties in monitoring and characterizing fractured aquifers, limited delivery and utilization efficiency of remedial agents, and the back-diffusion of DNAPL from low-permeability zones. Based on this analysis, three primary DNAPL remediation approaches—physical, chemical, and biological methods—are reviewed and evaluated. Finally, future research directions for understanding DNAPL migration and improving remediation strategies in fractured media are proposed. Overall, this review bridges mechanistic knowledge, simulation research, and remediation practice, providing insights that contribute to future technological progress and management decision-making in DNAPL-contaminated fractured aquifers. Full article

The corrosion of prestressed tendons in concrete structures remains a major durability concern, especially for post-tensioned members exposed to aggressive environments. High-strength aluminum alloy (AA) bars exhibit favorable characteristics such as corrosion resistance, low density, and high ductility and may therefore provide an alternative or supplementary prestressing material in durability-oriented structural design. In this study, a bonded post-tensioned T-shaped concrete beam with hybrid prestressing combining prestressed steel (PS) strands and 7075 AA bars was investigated. A refined finite element model was developed by considering the bond-slip relationship between the AA tendons and grout inside corrugated tubes. The flexural behavior of the beam was analyzed through a combination of finite element simulation and sectional theoretical analysis. In addition, a fatigue-life assessment framework was established based on vehicle fatigue loads and material fatigue constitutive models, and the fatigue performance of the proposed hybrid beams was compared with that of conventional prestressed concrete beams. The theoretical predictions agreed reasonably well with the numerical results. Results indicated that partial replacement of PS strands with corrosion-resistant AA bars could alter the governing fatigue failure mode and improve the fatigue durability of prestressed beams under corrosive conditions. These findings highlight the potential of hybrid AA–PS prestressing as a durability-oriented strategy for concrete beams in corrosive environments. Full article

Repeated impact loading can induce progressive fatigue delamination in composite laminates, in which both damage accumulation and strain-rate sensitivity of the interlaminar interface play important roles. In this work, an adopted rate-dependent fatigue cohesive formulation is extended to a three-dimensional framework for simulating interlaminar delamination in composite laminates subjected to repeated impact. The constitutive formulation incorporates separation-rate-dependent critical tractions and fracture toughness together with cumulative fatigue damage, enabling a unified description of dynamic rate effects and progressive interface degradation. A time-incremental algorithm is developed and implemented in ABAQUS 2020/Explicit through a user-defined cohesive element subroutine (VUEL). The cohesive formulation is further coupled with the Hashin intralaminar failure criterion to represent the interaction between interlaminar delamination and intralaminar damage. Numerical simulations are conducted for composite laminates with three structural configurations—conventional, drop-off, and wrapped drop-off—to systematically examine the influence of rate dependence on fatigue delamination under repeated impact. The results show that the developed framework captures the progressive evolution of delamination and impact response under repeated impact and indicate that the sensitivity to rate-dependent interlayer properties depends on both laminate configuration and impact velocity. The present study provides a feasible computational framework for the comparative simulation and assessment of fatigue delamination under repeated impact and offers numerical insight into the role of structural configuration and interfacial rate dependence in composite laminates. Full article

The development of renewable energy and the increasing demand for electricity underscore the importance of pumped storage for grid stability. Under low-flow pump operating conditions, pump-turbines frequently exhibit hump characteristics, causing severe hydraulic instability and strong pressure pulsations. This study investigates the formation of a hump using full-channel numerical simulations based on the Scale-Adaptive Simulation turbulence model. The numerical flow–head characteristics were validated against the available experimental H–Q data, while the pressure pulsation results were used for qualitative mechanism analysis. The results reveal three major mechanisms: pre-swirl and spiral backflow in the draft tube, non-uniform runner inflow, and vortex flow-induced separation in the wicket gates. An analysis of entropy production reveals that vortex dissipation is responsible for as much as 71% of hydraulic losses in the hump region. In order to mitigate these effects, four stabilizing fins were installed inside the draft tube. The simulations indicate that the fins possess the capability to inhibit swirl and backflow, confine the vortices within the fin–runner interface, improve inflow uniformity and reduce overall hydraulic losses. As a result, the structural modification significantly attenuates the pressure pulsation amplitudes at key monitoring points and visibly shortens the recovery periods. The region of the hump and positive slope of the performance curve are considerably reduced while the head near the region of the hump is increased. Although the intrinsic hump characteristic is still present, the fin-based flow-control strategy can effectively improve the performance and stability of the pump-turbine, which can guide the design and optimization of high-efficiency pumped-storage plants. Full article

During fires, the temperature difference between indoor and outdoor environments induces out-of-plane deformation in steel studs. Due to the differential coefficients of thermal expansion between panels and steel, the panels exert a restraining effect on the studs. However, there remains a lack of systematic experimental and theoretical models addressing the failure modes, restraining mechanisms, and synergistic effects of various panels on steel studs. This study conducted high-temperature bending tests to compare the failure modes, load–displacement curves, and key mechanical parameters (peak load, elastic stiffness) of connections combining steel studs with three types of panels: autoclaved lightweight concrete (ALC) panels, fire-resistant gypsum boards, and medium-density calcium silicate board. The research clarifies the constraining effect and temperature sensitivity of different panels. Based on experimental data, a bending constitutive model was developed to quantify the attenuation of the out-of-plane constraining effect at elevated temperatures. The results indicate that the load–displacement curves exhibit three distinct stages: Elastic Ascending Stage, Elastoplastic Ascending Stage, and Post-Peak Stage. A two-stage bending constitutive model was proposed and formulated. Comparison between numerical simulations and experimental specimens in terms of failure modes and characteristic parameters demonstrated that simplifying the panels as spring elements, with stiffness defined by the proposed bending constitutive model, yields errors within 15%, confirming the accuracy of the model. This study systematically investigates the influence of sheathing panels on the high-temperature out-of-plane mechanical behavior of cold-formed steel studs, innovatively proposes a two-stage bending constitutive model, provides theoretical and data support for cold-formed steel structural fire-resistant design, and offers new perspectives and methodologies for future research. Full article

To address the problem of insufficient shear bearing capacity of highway reinforced concrete (RC) T-beams, this paper systematically conducts a comparative study on the shear performance of RC T-beams strengthened with UHPC-CFP toughened composite plates of different configurations, and proposes a shear strengthening method using UHPC-CFP toughened composite plates. Comparative tests on different strengthening configurations are carried out. Meanwhile, a finite element numerical model is established to compare with the experimental results, analyze the influences of different strengthening schemes on the shear bearing capacity and mechanical properties of the beams, reveal the shear strengthening mechanism, and put forward a recommended formula for calculating the shear bearing capacity. The results show that after the diagonal cracks appeared in Beam T-0, they propagated rapidly from the support to the loading point. Beam T-1 had more diagonal cracks in the concrete between the UHPC-CFP toughened composite strips, while Beam T-2 had fewer. Fine cracks occurred in the UHPC-CFP toughened composite strips of Beams T-1 and T-2, whereas no cracking was observed in the UHPC composite rectangular plate of Beam T-3. The shear capacity of all strengthened beams was improved, with increases of 27.0%, 40.5%, and 43.2% for Beams T-1, T-2, and T-3, respectively. Beam T-3 exhibited the maximum deflection, and the strengthening configuration of Beam T-2 was determined to be the optimal. The carbon fiber strips embedded in UHPC effectively delayed the propagation of cracks in the UHPC plate and played the role of “reinforcement”. The truss–arch model theory is also applicable to the shear mechanism of concrete T-beams strengthened with UHPC-CFP toughened composite plates. Verification of Beams T-2 and T-3 using the proposed formula for shear design of strengthened beams showed that the average ratio of the calculated shear capacity to the experimental value was 0.87, indicating the reliability of the calculation results. Full article

Glass fiber-reinforced epoxy composites were modified with carbon nanotubes (CNTs), Al₂O₃, and TiO₂ nanoparticles to comparatively evaluate their influence on tensile, flexural, and low-velocity impact performance within an integrated experimental–numerical framework. Nanoparticles were incorporated at controlled weight fractions to identify dispersion-controlled reinforcement regimes and the onset of heterogeneity-driven mechanical transitions. Among all formulations, 0.5 wt% CNTs provided the most pronounced static mechanical enhancement, increasing tensile strength to 419.50 MPa (≈21% improvement over the reference GF laminate) and flexural strength to 230.23 MPa (≈26% increase). In contrast, impact performance exhibited a non-monotonic evolution; the highest absorbed energy (9.64 J) was observed at 2 wt% CNTs, indicating that dynamic energy dissipation mechanisms do not necessarily scale proportionally with static strength gains. Oxide-filled systems demonstrated stiffness-dominated behavior, where increasing filler content amplified elastic mismatch and progressively reduced strength despite modulus enhancement. Finite element simulations conducted in ANSYS LS-DYNA (MAT_022) reproduced global stiffness trends within the dispersion-controlled regime. Tensile strength predictions agreed within 0–9% at optimal CNT loading, whereas larger deviations (up to ~33%) emerged under bending-dominated loading in oxide-rich systems, reflecting amplified sensitivity to microstructural heterogeneity. The coupled evolution of stiffness–strength decoupling (SSDI) and FEM deviation (η) enabled identification of a Composite Heterogeneity Threshold (CHT), defined as the nanoparticle concentration beyond which stiffness enhancement no longer translates into proportional strength or toughness improvement. Beyond this threshold, dispersion-induced heterogeneity not only reduces mechanical efficiency but also marks the boundary of homogenized continuum model adequacy across static and dynamic loading conditions. Full article

The increasing demand for autonomous wireless sensors in Internet of Things (IoT) applications has intensified research on vibration energy harvesting, particularly in the low-frequency range where ambient vibrations are most prevalent. However, most vibration energy harvesters operate efficiently only at a single resonance mode, resulting in a narrow operational bandwidth and pronounced performance degradation under frequency detuning. To address this limitation, this paper proposes a multimodal hybrid piezoelectric–electromagnetic vibration energy harvester that exploits both the first and second resonance modes of a cantilever-based structure to achieve broadband low-frequency operation. The design is guided by the complementary utilization of strain-dominated and velocity-dominated regions associated with different vibration modes. Numerical modeling and finite element simulations are employed to investigate the influence of mass distribution, deformation characteristics, and relative velocity on energy conversion performance. A secondary cantilever carrying the electromagnetic coil is introduced to enhance the relative motion between the coil and the magnetic field, thereby extending the effective operational bandwidth. The experimental results demonstrate increased harvested power, improved energy conversion efficiency, and a significantly broadened effective frequency range compared to conventional single-mode piezoelectric and electromagnetic energy harvesters. Full article

Historically, the sustainable development of education bears the mission of advancing the sustainable development of human society, and the transformation of universities is a crucial link in the sustainable development of higher education. This paper addresses the top-down, government-led transformation of local undergraduate universities, a process currently hampered by ambiguous objectives, insufficient internal motivation, and a mismatch in supporting systems, resources, and institutional culture. To analyze and optimize this process, we establish an asymmetric evolutionary game model involving the local government, local universities, and teachers. By integrating optimization theory, this study determines the optimal equilibrium conditions for the game system. We then use numerical simulations to depict the system’s evolutionary paths under various transformation scenarios. Furthermore, we have analyzed the key influencing factors for promoting university transformation and development, which form the basis for proposing targeted policy recommendations. Full article