Search Results (1,778)

As a novel type of ocean monitoring tool, unmanned sailboats exhibit significant application potential. In this study, a novel wing sail structure for offshore unmanned sailboats is proposed and its performance compared with that of the conventional NACA 0021 wing sail. The Reynolds-averaged Navier–Stokes (RANS) equations are employed for numerical analysis, and the aerodynamic performance is evaluated using ANSYS Fluent. The results indicate that the lift coefficient and lift-to-drag ratio of the HF-14-CE-01 wing sail are significantly superior to those of the NACA 0021 wing sail. Compared to the NACA 0021 wing sail, the HF-14-CE-01 wing sail has undergone structural optimization. The HF-14-CE-01 wing sail demonstrates improved wind direction efficiency, uniform force distribution, ease of adjustment, and extends the service life of the sail. Subsequent research examined the influence of aspect ratio on both the aerodynamic performance of the wing sail and the thrust generated by the unmanned sailboat, identifying an optimal aspect ratio of 4 for the HF-14-CE-01 wing sail. Analysis of the velocity and static pressure contour maps for the HF-14-CE-01 wing sail identified a critical angle of attack of 28°, providing a clear visual representation of its aerodynamic performance. Furthermore, compared with other rigid sail designs, the HF-14-CE-01 wing sail achieved a 30.9% increase in peak lift coefficient, indicating superior propulsion capability. Full article

Objectives: To study the effects of internal and marginal polymerization shrinkage stress and distribution in different resin composite class III dental restorations in relation to the restorative technique using numerical finite element analysis (FEA). Methods: A 3D model of a human hemi-maxilla with a sound maxillary central incisor were created. Four class III distal cavities were shaped and differently restored. Four groups of resin composite combinations were analyzed: group C (three increments of conventional composite); group B (two increments of bulk-fill composite); group FC (flowable base + three increments of conventional composite); and group FB (flowable bulk-fill base + two increments of conventional composite). The resulting four models were exported to FEA software for static structural analysis. Polymerization shrinkage was simulated using thermal analogy, and stress distribution was analyzed using the Maximum Principal Stress criterion at the marginal and internal cavity interfaces. Results: Group FC showed the highest stress at the level in the proximal region (9.05 MPa), while group FB showed the lowest (4.48 MPa). FB also exhibited the highest internal dentin stress, indicating potential risks for long-term bond degradation. In the cavo-surface incisal angle, the average peak stress across all groups was 3.76 MPa. At the cervical cavo-surface angle, stress values were 3.3 MPa (C), ~3.36 MPa (B), 3.41 MPa (FC), and 3.27 MPa (FB). Conclusions: Restorative technique did not significantly influence marginal stress distribution in class III composite restorations. However, the bevel area at the cervical margin showed the highest concentration of shrinkage stress. Full article

High-fidelity finite element analysis (FEA) plays a key role in structural engineering by enabling accurate simulation of displacement, stress, and internal forces under static loads. However, its high computational cost limits applicability in real-time control, iterative design, and large-scale uncertainty quantification. Surrogate modeling provides a computationally efficient alternative by learning input–output mappings from precomputed simulations. Yet, the performance of individual surrogates is often sensitive to data distribution and model assumptions. To enhance both accuracy and robustness, we propose a model averaging framework based on Jackknife Model Averaging (JMA) that integrates six surrogate models: polynomial response surfaces (PRSs), support vector regression (SVR), radial basis function (RBF) interpolation, eXtreme Gradient Boosting (XGB), Light Gradient Boosting Machine (LGBM), and Random Forest (RF). Three ensembles are formed: JMA1 (classical models), JMA2 (tree-based models), and JMA3 (all models). JMA assigns optimal convex weights using cross-validated out-of-fold errors without a meta-learner. We evaluate the framework on the Static Analysis Dataset with over 300,000 FEA simulations. Results show that JMA consistently outperforms individual models in root mean squared error, mean absolute error, and the coefficient of determination, while also producing tighter, better-calibrated conformal prediction intervals. These findings support JMA as an effective tool for surrogate-based structural analysis. Full article

The article presents an analysis of the mechanical properties of S700MC steel, which represents advanced low-alloy high-strength steels. The influence of microstructure, shaped by a controlled thermo-mechanical rolling process, on the strength, ductility, and resistance to cracking and fatigue of the material is discussed. Particular attention is paid to the anisotropy of mechanical properties resulting from the orientation relative to the rolling direction, manifested by variations in yield strength, tensile strength, and total elongation of the specimens. The analysis also includes the material’s behavior under dynamic conditions, where the steel’s strength increases with the strain rate. Experimental investigations conducted using the digital image correlation (DIC) method enabled a detailed assessment of local strains and fracture characteristics of specimens subjected to both static and dynamic testing. The results showed that specimens cut along the rolling direction exhibited, on average, 6.4% higher tensile strength and 6.8% higher yield strength compared to those cut transversely. Moreover, dynamic loading led to an increase in load-bearing capacity of over 10% compared to static tests. The obtained data are highly relevant from the perspective of structural design, where the selection of material orientation and the consideration of strain rate effects are crucial for ensuring the reliability of components made from S700MC steel. Full article

The synergistic advancement of “Digital China” and “Beautiful China” represents a pivotal national strategy for achieving high-quality economic development and a low-carbon transition. To illuminate the intrinsic mechanisms linking the digital economy (DE) to urban carbon emission performance (CEP), this study develops a novel two-sector theoretical framework. Leveraging panel data from 278 Chinese prefecture-level cities (2011–2023), we employ a comprehensive evaluation method to gauge DE development and utilize calibrated nighttime light data with downscaling inversion techniques to estimate city-level CEP. Our empirical analysis integrates static panel fixed effects, panel threshold, and moderating effects models. Key findings reveal that the digital economy demonstrably enhances urban carbon emission performance, although this positive effect exhibits a threshold characteristic linked to the maturity of digital infrastructure; beyond a specific developmental stage, the marginal benefits diminish. Crucially, this enhancement operates primarily through the twin engines of fostering technological innovation and driving industrial structure upgrading, with the former playing a dominant role. The impact of DE on CEP displays significant heterogeneity, proving stronger in northern cities, resource-dependent cities, and those characterized by higher levels of inclusive finance or lower fiscal expenditure intensities. Furthermore, the effectiveness of DE in reducing carbon emissions is dynamically moderated by policy environments: flexible economic growth targets amplify its carbon reduction efficacy, while environmental target constraints, particularly direct binding mandates, exert a more pronounced moderating influence. This research provides crucial theoretical insights and actionable policy pathways for harmonizing the “Dual Carbon” goals with the overarching Digital China strategy. Full article

Rapid urbanization and climate change have intensified urban flood risks, necessitating resilient upstream infrastructure to ensure metropolitan water security and effective flood mitigation. Gravity dams, as critical components of urban flood protection systems, regulate discharge to downstream urban areas. Gravity dams are critical for regulating flood discharge, yet their seismic vulnerability poses significant challenges, particularly under compound effects involving concurrent seismic loading and climate-induced elevated reservoir levels. This study introduces a novel seismic analysis framework for gravity dams using the scaled boundary finite element method (SBFEM), which efficiently models dam–water and dam–foundation interactions in infinite domains. A two-dimensional numerical model of a concrete gravity dam, subjected to realistic seismic loading, was developed and validated against analytical solutions and conventional finite element method (FEM) results, achieving discrepancies as low as 0.95% for static displacements and 0.21% for natural frequencies. The SBFEM approach accurately captures hydrodynamic pressures and radiation damping, revealing peak pressures at the dam heel during resonance and demonstrating computational efficiency with significantly reduced nodal requirements compared to FEM. These findings enhance understanding of dam behavior under extreme loading. The proposed framework supports climate-adaptive design standards and integrated hydrological–structural modeling. By addressing the seismic safety of flood-control dams, this research contributes to the development of resilient urban water management systems capable of protecting metropolitan areas from compound climatic and seismic extremes. Full article

Reducing carbon dioxide emissions in freight transportation is considered a key objective in contemporary sustainable supply chain management. While several tools and standards have been developed to estimate transport-related emissions, most rely on static assumptions, generic emission factors and are limited to single-scenario evaluation. Therefore, their operational applicability remains restricted especially in dynamic and complex environments where fast responsiveness is essential. Moreover, these tools are often disconnected from real-world constraints and rarely incorporate expert’s input. To address this gap, this study introduces a hybrid decision-support CO₂ assessment framework combining theoretical models with field-based inputs. The proposed approach combines structured interviews conducted with 300 supply chain consultants and is operationalized through a dynamic digital tool that enables users to simulate multiple scenarios simultaneously. The tool accounts for critical variables including transport mode, routing distance, vehicle configuration, and shipment characteristics, thereby enabling a contextualized and flexible analysis of carbon emissions. A validation case study was conducted to confirm the applicability of the tool to industrial settings. Computational results show significant variation in emissions across different routing strategies and modal configurations, highlighting the tool’s capacity to support environmentally informed decisions. This research offers both a replicable methodology and a practical contribution: a user-centered, multi-scenario tool that improves the accuracy, adaptability, and strategic value of CO₂ emission calculations in freight transport planning. Full article

This article focuses on activities addressed in the European project hydrogen lightweight & innovative tank for zero-emission aircraft, H2ELIOS. The authors propose a preliminary approach oriented to the design of a structural health monitoring SHM system conceived for a cryo-tank liquid hydrogen storage for medium range vehicles. The system was ideated to be installed on board and operating during service, to provide early detection and localization of potential damage, critical both in terms of safety and maintenance. The use of optical fibers for strain measurement is justified, on one hand, by the capability of pure silica fiber to prevent hydrogen darkening effects and, on the other hand, by the absence of metal components, which eliminates the risk of embrittlement. In detail, distributed and fiber Bragg grating FBG sensors designed for this specific application have demonstrated reliable monitoring capabilities, even after exposure to hydrogen and at cryogenic temperatures. Furthermore, another key contribution of this preliminary activity is the analysis of thermoplastic material faults by correlating damage characteristics with static and dynamic response. This is due to the fact that the investigated physics strongly depend on the nature of occurring damage. Achievements lie in the demonstrated ability to assess the health status of the reference composite structure, establishing the first steps for a future qualification of the proprietary system, made of commercial and original hardware and software. Full article

This study investigates the influence of vacancy engineering and nitrogen doping on the structural, electronic, and optical properties of T-graphene fragments (TFs) using density functional theory (DFT) and time-dependent DFT (TD-DFT). A central vacancy and five pyridinic nitrogen doping configurations are explored to modulate the optoelectronic behavior. All systems are thermodynamically stable, exhibiting tunable HOMO–LUMO gaps, orbital distributions, and charge transfer characteristics. Optical absorption spectra show redshifts and enhanced oscillator strengths in doped variants, notably v-NTF2 and v-NTF4. Nonlinear optical (NLO) analysis reveals significant enhancement in both static and frequency-dependent responses. v-NTF2 displays an exceptionally high first-order hyperpolarizability (⟨β⟩ = 1228.05 au), along with a strong electro-optic Pockels effect (β (−ω; ω, 0)) and second harmonic generation (β (−2ω; ω, ω)). Its third-order response, γ (−2ω; ω, ω, 0), also exceeds 1.2 × 10⁵ au under visible excitation. Conceptual DFT descriptors and energy decomposition analysis further supports the observed trends in reactivity, charge delocalization, and stability. These findings demonstrate that strategic nitrogen doping in vacancy-engineered TFs is a powerful route to tailor electronic excitation, optical absorption, and nonlinear susceptibility. The results offer valuable insight into the rational design of next-generation carbon-based materials for optoelectronic, photonic, and NLO device applications. Full article

The resilience concept is well established in engineering, but the quantitative studies of vessel impact resilience for bridge structures remain limited. This paper presents an integrated framework for assessing vessel impact resilience under combined rebar corrosion and vessel collision effects. First, a corroded reinforced concrete bridge is considered for nonlinear static analysis to quantify initial corrosion damage and for nonlinear dynamic analysis to evaluate post-impact function loss. Then, recovery for each damage state is modeled by using both negative exponential and triangular recovery functions to estimate restoration times and to obtain a vessel impact resilience index. The results show that increasing corrosion severity markedly reduces resilience capacity. Furthermore, resilience indices obtained from the negative exponential function generally exceed those from the triangular function, and this improvement becomes more significant at lower resilience levels. Resilience indices calculated by using negative exponential and triangular recovery functions show negligible differences when the concrete bridge is in the uncorroded initial state and the vessel impact velocity is below 1.5 m/s. However, as reinforcement corrosion increases, the maximum discrepancy between these two recovery functions also increases, reaching a value of 67% at a corrosion level of 15.0%. From the numerical results obtained from a case study, it is important to select an appropriate recovery model when assessing vessel impact resilience. For rapid initial restoration followed by slower long-term recovery, the negative exponential model yields greater resilience gains compared to the triangular model. The proposed method thus provides an effective tool for engineers and decision makers to evaluate and improve the vessel impact resilience of aging bridges under the combined corrosion and impact effects. This proposes a quantitative metric for resilience-based condition assessment and maintenance planning. Full article

This study proposes an integrated framework that combines nonlinear stochastic vibration analysis with reliability assessment to address the safety issues of cable systems under damage conditions. First of all, a mathematical model of the damaged cable is established by introducing damage parameters, and its static configuration is determined. Using the Pearl River Huangpu Bridge as a case study, the accuracy of the analytical solution for the cable’s sag displacement is validated through the finite difference method (FDM). Furthermore, a quantitative relationship between the damage parameters and structural response under stochastic excitation is developed, and the nonlinear stochastic dynamic equations governing the in-plane and out-of-plane motions of the damaged cable are derived. Subsequently, a Gaussian Radial Basis Function Neural Network (GRBFNN) method is employed to solve for the steady-state probability density function of the system response, enabling a detailed analysis of how various damage parameters affect structural behavior. Finally, the First-Order and Second-Order Reliability Method (FORM/SORM) are used to compute the reliability index and failure probability, which are further validated using Monte Carlo simulation (MCS). Results show that the severity parameter η shows the highest sensitivity in influencing the failure probability among the damage parameters. For the system of the Pearl River Huangpu bridge, an increase in the damage extent δ from 0.1 to 0.4 can reduce the reliability-based service life of by approximately 40% under fixed values of the damage severity and location, and failure risk is highest when the damage is located at the midspan of the cable. This study provides a theoretical framework from the point of stochastic vibration for evaluating the response and associated reliability of mechanical systems; the results can be applied in practice with guidance for the engineering design and avoid potential damages of suspended cables. Full article

Fiber-reinforced and laminated composite materials, widely used in engineering applications, may develop periodic curvature during manufacturing due to technological requirements. Given such curvatures in widely used composites, static and dynamic analyses of plates and shells under loads, along with related stability issues, have been extensively investigated. However, studies focusing specifically on the static analysis of such materials remain limited. Composite materials with structural curvature exhibit complex mechanical behavior, making their analysis particularly challenging. Predicting their mechanical response is crucial in engineering. In response to this need, the present study conducts a static analysis of plates made of periodically curved composite materials using the Navier method. The plate equations were derived based on the Kirchhoff–Love plate theory within the framework of the Continuum Theory proposed by Akbarov and Guz’. Using the Navier method, deflection, stress, and moment distributions were obtained at every point of the plate. Numerical results were computed using MATLAB. After verifying the convergence and accuracy of the developed MATLAB code by comparing it with existing solutions for rectangular homogeneous isotropic and laminated composite plates, results were obtained for periodically curved plates. This study offers valuable insights that may guide future research, as it employs the Navier method to provide an analytical solution framework. This study contributes to the limited literature with a novel evaluation of the static analysis of composite plates with periodic curvature. Full article

In the design of small-scale test models for hull structures, the directional dimensional analysis method is commonly employed. However, conventional dimensional analysis based on elasticity theory may be insufficient to capture the nonlinear behaviors of structural materials under dynamic loading, which restricts its applicability in ultimate strength tests for small-scale hull structure models. This paper presents a scaling method grounded in the theory of finite similitude. Based on the finite similitude theory, this paper deduces similarity scaling criteria applicable to the static and dynamic responses of box girders and designs a series of trial models of box girders. The scaling criteria are verified and analyzed through numerical tests conducted under static and dynamic loads. On the basis of the numerical test results of dynamic responses, the dynamic response similarity criteria considering the similarity relationship of material constitutive parameters are modified and verified. By applying the static response scaling criteria in this paper to select appropriate materials, the prediction deviation of the box girder trial models under static loads is less than 2%. With the modified dynamic response scaling criteria proposed in this paper, the prediction deviations of each trial model under dynamic loads are less than 2% and 7%. A comprehensive analysis of material parameters was conducted to examine their impact on the nonlinear similarities observed in the processes. To validate the ultimate strength and nonlinear response scaling criterion based on the finite similitude approach, numerical experiments were performed to assess the ultimate strength and dynamic buckling response characteristics of the box girder across various scaling ratios and material parameters. The analysis demonstrated that the ultimate strength scaling criterion and the nonlinear response scaling criterion derived from the finite similitude approach effectively captured material nonlinearity. The results from the small-scale model provided accurate predictions of the ultimate strength of the full-scale model. Full article

Refining the land use structure can boost land utilization efficiency and curtail regional carbon emissions. Nevertheless, prior research has predominantly concentrated on static linear planning analysis. It has failed to account for how future dynamic alterations in driving factors (such as GDP and population) affect simulation outcomes and how the land use spatial configuration impacts the attainment of the carbon-neutrality goal. In this research, 1 km spatial resolution LULC products were employed to meticulously simulate multiple land use scenarios across China at the national level from 2030 to 2060. This was performed by taking into account the dynamic changes in driving factors. Subsequently, an analysis was carried out on the low-carbon land use spatial structure required to reach the carbon-neutrality target. The findings are as follows: (1) When employing the PLUS (Patch—based Land Use Simulation) model to conduct simulations of various land use scenarios in China by taking into account the dynamic alterations in driving factors, a high degree of precision was attained across diverse scenarios. The sustainable development scenario demonstrated the best performance, with kappa, OA, and FoM values of 0.9101, 93.15%, and 0.3895, respectively. This implies that the simulation approach based on dynamic factors is highly suitable for national-scale applications. (2) The simulation accuracy of the PLUS and GeoSOS-FLUS (Systems for Geographical Modeling and Optimization, Simulation of Future Land Utilization) models was validated for six scenarios by extrapolating the trends of influencing factors. Moreover, a set of scenarios was added to each model as a control group without extrapolation. The present research demonstrated that projecting the trends of factors having an impact notably improved the simulation precision of both the PLUS and GeoSOS-FLUS models. When contrasted with the GeoSOS-FLUS model, the PLUS model attained superior simulation accuracy across all six scenarios. The highest precision indicators were observed in the sustainable development scenario, with kappa, OA, and FoM values reaching 0.9101, 93.15%, and 0.3895, respectively. The precise simulation method of the PLUS model, which considers the dynamic changes in influencing factors, is highly applicable at the national scale. (3) Under the sustainable development scenario, it is anticipated that China’s land use carbon emissions will reach their peak in 2030 and achieve the carbon-neutrality target by 2060. Net carbon emissions are expected to decline by 14.36% compared to the 2020 levels. From the perspective of dynamic changes in influencing factors, the PLUS model was used to accurately simulate China’s future land use. Based on these simulations, multi-scenario predictions of future carbon emissions were made, and the results uncover the spatiotemporal evolution characteristics of China’s carbon emissions. This study aims to offer a solid scientific basis for policy-making related to China’s low-carbon economy and high-quality development. It also intends to present Chinese solutions and key paths for achieving carbon peak and carbon neutrality. Full article

A method for configuration synthesis of a reconfigurable decoupled parallel mechanical leg is proposed. In addition, a configuration evaluation index is proposed to evaluate the synthesized configurations and select the optimal one. Kinematic analysis and performance optimization of the selected mechanism’s configuration are carried out, and the motion mode of the robot’s reconfigurable mechanical leg is selected according to the task requirements. Then, the robot’s gait in walking mode is planned. Firstly, based on bionic principles, the motion characteristics of a mechanical leg based on a mammalian model and an insect model were analyzed. The input and output characteristics of the mechanism were analyzed to obtain the reconfiguration principle of the mechanism. Using type synthesis theory for the decoupled parallel mechanism, the configuration synthesis of the chain was carried out, and the constraint mode of the mechanical leg was determined according to the constraint property of the chain and the motion characteristics of the moving platform. Secondly, an evaluation index for the complexity of the reconfigurable mechanical leg structure was developed, and the synthesized mechanism was further analyzed and evaluated to select the mechanical leg’s configuration. Thirdly, the inverse position equations were established for the mechanical leg in the two motion modes, and its Jacobian matrix was derived. The degrees of freedom of the mechanism are completely decoupled in the two motion modes. Then, the workspace and motion/force transmission performance of the mechanical leg in the two motion modes were analyzed. Based on the weighted standard deviation of the motion/force transmission performance, the global performance fluctuation index of the mechanical leg motion/force transmission is defined, and the structural size parameters of the mechanical leg are optimized with the performance index as the optimization objective function. Finally, with the reconfigurable mechanical leg in the insect mode, the robot’s gait in the walking operation mode is planned according to the static stability criterion. Full article