Search Results (1,078)

This study applies a deep neural network (DNN) to optimize the 22.5 m pontoon hull form of a small waterplane area twin hull (SWATH) vessel with fin stabilizers, aiming to reduce calm water resistance at a Froude number of 0.8 under even keel conditions. The vessel’s resistance is simplified into three components: pontoon, strut, and fin stabilizer. Four design parameters define the pontoon geometry: fore-body length, aft-body length, fore-body angle, and aft-body angle. Computational fluid dynamics (CFD) simulations using STAR-CCM+ 2302 provide 1400 resistance data points, including fin stabilizer lift and drag forces at varying angles of attack. These are used to train a DNN in MATLAB 2018a with five hidden layers containing six, eight, nine, eight, and seven neurons. K-fold cross-validation ensures model stability and aids in identifying optimal design parameters. The optimized hull has a 7.8 m fore-body, 6.8 m aft-body, 10$°$ fore-body angle, and 35$°$ aft-body angle. It achieves a 2.2% resistance reduction compared to the baseline. The improvement is mainly due to a reduced Munk moment, which lowers the angle of attack needed by the fin stabilizer, thereby reducing drag. The optimized design provides cost-efficient construction and enhanced payload capacity. This study demonstrates the effectiveness of combining CFD and deep learning for hull form optimization. Full article

The existence of fault zones in high-intensity earthquake areas has a serious impact on engineering structures, and the longitudinal response of tunnels crossing faults needs further in-depth research. To analyze the tangential contact effect between the surrounding rock and the tunnel lining, and the axial deformation characteristics of the tunnel structure, tangential foundation springs were introduced and a theoretical model for the longitudinal response of the tunnel under fault dislocation was established. Firstly, the tunnel was simplified as a finite-length beam. The normal and tangential springs were taken to represent the interaction between the soil and the lining. The fault’s free-field displacement was applied at the end of the normal foundation spring to simulate fault dislocation, and the differential equation for the longitudinal response of the tunnel structure was obtained. The analytical solution of the structural response was obtained using the Green’s function method. Then, the three-dimensional finite difference method was used to verify the effectiveness of the analytical model in this paper. The results show that the tangential contact effect between the surrounding rock and the lining has a significant impact on the longitudinal response of the tunnel structure. Ignoring this effect leads to an error of up to 35.33% in the peak value of the structural bending moment. Finally, the influences of the width of the fault zone, the soil stiffness of the fault zone, and the stiffness of the tunnel lining on the longitudinal response of the tunnel were explored. As the fault width increases, the internal force of the tunnel structure decreases. Increasing the lining concrete grade leads to an increase in the internal force of the structure. The increase in the elastic modulus of the surrounding rock in the fault area reduces the bending moment and shear force of the structure and increases the axial force. The research results can provide a theoretical basis for the anti-dislocation design of tunnels crossing faults. Full article

Monitoring position and movements of preterm infants is important to ensure their well-being and optimal development. This study evaluates the feasibility of a pressure-sensitive fiber-optic mattress (FM), made entirely of plastic, for two-dimensional analysis of preterm infant movements and positioning. Before clinical use, we developed a simple, replicable, and cost-effective test protocol to simulate infant movements and positions, enabling early identification of technical limitations. Using data from 20 preterm infants, we assessed the FM’s potential to monitor posture and limb motion. FM-derived pressure patterns were compared with camera-based manual annotations to distinguish between different positions and out-of-bed moments, as well as limb-specific movements. Bench-test results demonstrated the FM’s sensitivity to motion and pressure changes, supporting its use in preclinical validation. Clinical data confirmed the FM’s reliability in identifying infant positions and movement patterns, showing an accuracy comparable to camera annotations. However, limitations such as calibration, sensitivity to ambient light, and edge-related artifacts were noted, indicating areas for improvement. In conclusion, the test protocol proved effective for early-stage evaluation of smart mattress technologies. The FM showed promising clinical feasibility for non-obtrusive monitoring of preterm infants, though further optimization is needed for robust performance in neonatal care. Full article

The physicochemical processes that occur during selective transfer in the contact area of a bronze/steel friction pair lubricated with glycerin are experimentally studied by the polarization method to observe how they influence the tribological properties (friction and wear) of the pair. The proposed method allows for the study of tribochemical transformations of glycerin and the friction pair materials during the work process with selective transfer. The analysis of the experimental results allows for the establishment of the conditions for a stable and stationary selective transfer during the operation of the bronze/steel pair, by friction, at which the friction coefficient (COF) values and wear are low. This was achieved by implementing continuous lubrication with fresh glycerin in the contact area, choosing the optimal flow rate, and maintaining an optimal ratio between glycerin and the chemical transformation products, within well-established limits, to avoid undesirable consequences. Acrolein, as a product of chemical transformation (resulting from the catalytic dehydration of glycerin), is the most important for the initiation and stability of the selective transfer, and as the main reaction product, also represents a pathway of regeneration. Thus, it was found that the friction relative moments and the acrolein concentration presented conclusive/specific results at loads of 4–15 MPa and a sliding speed of 0.3 m/s. The optimum lubricant entry speed is 15–30 mg/min, for a minimum COF and reduced wear (about 0.028–0.03 at relatively high operating temperatures (45 and 60 °C)), and at low temperatures (30 °C) the minimum COF is about 0.038, but the lubricant inlet entry speed increases considerably, by around 1000 mg/min. Therefore, this paper aims to demonstrate the possibility of moving to another stage of practical use of a friction pair (with greatly improved tribological properties) that operates with selective transfer, much different from the ones still present, using a lubricant with special properties (glycerin). The research method used (polarization) highlights the physicochemical properties, tribochemical transformations of the lubricant, and the friction pair materials present in the contact area, for the understanding, maintenance, and stability of selective transfer, based on experiments, as a novelty compared to other studies. Full article

Reliable estimation of extreme waves is essential for offshore wind turbine system design; however, site-specific conditions limit the application of one-size-fits-all statistical methods. We analyzed extreme wave conditions at potential offshore wind farm sites in South Korea using high-resolution hindcast data (1979–2022) based on the Weather Research and Forecasting (WRF) model. While previous studies have typically relied on a limited combination of distribution types and parameter estimation methods, this study systematically applied various Weibull distribution models and parameter estimation techniques to the environmental contour (EC) method. The results show that the optimal statistical approach varied by site according to the tail characteristics of the wave height distribution. The inverse second-order reliability method (I-SORM) provided the highest accuracy in regions with rapidly decaying tails, achieving root mean square error (RMSE) values of 0.21 in Shinan (using the three-parameter Weibull distribution with maximum likelihood estimation, MLE) and 0.34 in Chujado (with the method of moments, MOM). In contrast, the inverse first-order reliability method (I-FORM) yielded superior performance in areas where the tail decays more gradually, such as Yokjido (RMSE = 0.47 with MLE using the exponentiated Weibull distribution) and Ulsan (RMSE = 0.29, with MLE using the exponentiated Weibull distribution). These findings underscore the importance of selecting site-specific combinations of statistical models and estimation techniques based on wave distribution characteristics, thereby improving the accuracy and reliability of extreme design wave predictions. The proposed framework can significantly contribute to the establishment of reliable design criteria for offshore wind turbine systems by reflecting region-specific marine environmental conditions. Full article

Circular deep excavations, characterized by their symmetrical geometry, are commonly employed in constructing foundations for large-span suspension bridges and as launching shafts for shield tunneling. However, the mechanical behavior of such excavations under asymmetric surface surcharge remains inadequately understood due to a paucity of relevant investigations. This study addresses this knowledge gap by establishing a three-dimensional finite element model (3D-FEA) based on the anchor deep excavation project of a specific bridge. The model is utilized to investigate the influence of asymmetric surcharge on the forces and deformations within the supporting structure. The results show that both the internal force and displacement cloud diagrams of the support structure exhibit asymmetric characteristics. The distribution of displacement and internal forces has spatial effects, and the maximum values all occur in the areas where asymmetric loads are applied. The maximum values of the displacement, axial force, and shear force of underground continuous walls increase with the increase in the excavation depth. The total displacement curves all show the feature of a “bulging belly”. The maximum displacement is 13.3 mm. The axial force is mainly compression, with a maximum value of −9514 kN/m. The maximum positive and negative values of the shear force are 333 kN/m and −705 kN/m, respectively. The bending moment diagram of different monitoring points shows the characteristics of “bow knot”. The maximum values of the positive bending moment and negative bending moment are 1509.4 kN·m/m and −2394.3 kN·m/m, respectively. The axial force of the ring beam is mainly compression, with a maximum value of −5360 kN, which occurs in ring beams 3, 4, and 5. The displacement cloud diagram of the support structure under symmetrical loads shows symmetrical characteristics. Under different load conditions, the displacement curve of the diaphragm wall shows the characteristics of “bulge belly”. The forms of loads with displacements from largest to smallest at the same position are as follows: asymmetric loads, symmetrical loads, and no loads. These findings provide valuable insights for optimizing the structural design of similar deep excavation projects and contribute to promoting sustainable urban underground development. Full article

The model explicitly incorporates boundary conditions that account for the complex interplay between sections experiencing varying degrees of reduction. This interaction significantly influences the overall deformation behavior and force loading. The control effect is associated with boundary conditions determined by the unevenness of the compression, which have certain quantitative and qualitative characteristics. These include additional loading, which is less than the main load, which implements the process of plastic deformation, and the ratio of control loads from the entrance and exit of the deformation site. According to this criterion, it follows from experimental data that the controlling effect on the plastic deformation site occurs with a ratio of additional and main loading in the range of 0.2–0.8. The next criterion is the coefficient of support, which determines the area of asymmetry of the force load and is in the range of 2.00–4.155. Furthermore, the criterion of the regulating force ratio at the boundaries of the deformation center forming a longitudinal plastic shear is within the limits of 2.2–2.5 forces and 1.3–1.4 moments of these forces. In this state, stresses and deformations of the plastic medium are able to realize the effects of plastic shaping. The force effect reduces with an increase in the unevenness of the deformation. This is due to a change in height of the longitudinal interaction of the disparate sections of the strip. There is an appearance of a new quality of loading—longitudinal plastic shear along the deformation site. The unbalanced additional force action at the entrance of the deformation source is balanced by the force source of deformation, determined by the appearance of a functional shift in the model of the stress state of the metal. The developed theory, using the generalized method of an argument of functions of a complex variable, allows us to characterize the functional shift in the deformation site using invariant Cauchy–Riemann relations and Laplace differential equations. Furthermore, the model allows for the investigation of material properties such as the yield strength and strain hardening, influencing the size and characteristics of the identified limit state zone. Future research will focus on extending the model to incorporate more complex material behaviors, including viscoelastic effects, and to account for dynamic loading conditions, more accurately reflecting real-world milling processes. The detailed understanding gained from this model offers significant potential for optimizing mill roll designs and processes for enhanced efficiency and reduced energy consumption. Full article

This study explores virtual sensing techniques for the Eolink floating offshore wind turbine (FOWT), which features a pyramidal platform and a single-point mooring system that enables weathervaning to maximize power production and reduce structural loads. To address the challenges and costs associated with monitoring submerged components, virtual sensors are investigated as an alternative to physical instrumentation. The main objective is to design a virtual sensor of mooring hawser loads using a reduced set of input features from GPS, anemometer, and inertial measurement unit (IMU) data. A virtual sensor is also proposed to estimate the bending moment at the joint of the pyramid masts. The FOWT is modeled in OrcaFlex, and a range of load cases is simulated for training and testing. Under defined sensor sampling conditions, both supervised and physics-informed machine learning algorithms are evaluated. The models are tested under aligned and misaligned environmental conditions, as well as across operating regimes below- and above-rated conditions. Results show that mooring tensions can be estimated with high accuracy, while bending moment predictions also perform well, though with lower precision. These findings support the use of virtual sensing to reduce instrumentation requirements in critical areas of the floating wind platform. Full article

Accurate rainfall quantile estimation is critical for urban flood management, particularly given the escalating climate change impacts. This study comprehensively compared at-site frequency analysis and regional frequency analysis for sub-hourly rainfall quantile estimation, using data from 27 sites across Seoul. The analysis focused on Seoul’s disaster prevention framework (30-year and 100-year return periods). Employing L-moment statistics and Monte Carlo simulations, the rainfall quantiles were estimated, the methodological performance was evaluated, and Seoul’s current disaster prevention standards were assessed. The analysis revealed significant spatio-temporal variability in Seoul’s precipitation, causing considerable uncertainty in individual site estimates. A performance evaluation, including the relative root mean square error and confidence interval, consistently showed regional frequency analysis superiority over at-site frequency analysis. While at-site frequency analysis demonstrated better performance only for short return periods (e.g., 2 years), regional frequency analysis exhibited a substantially lower relative root mean square error and significantly narrower confidence intervals for larger return periods (e.g., 10, 30, 100 years). This methodology reduced the average 95% confidence interval width by a factor of approximately 2.7 (26.98 mm versus 73.99 mm). This enhanced reliability stems from the information-pooling capabilities of regional frequency analysis, mitigating uncertainties due to limited record lengths and localized variabilities. Critically, regionally derived 100-year rainfall estimates consistently exceeded Seoul’s 100 mm disaster prevention threshold across most areas, suggesting that the current infrastructure may be substantially under-designed. The use of minute-scale data underscored its necessity for urban hydrological modeling, highlighting the inadequacy of conventional daily rainfall analyses. Full article

Optical networks serve as the backbone of modern communication, requiring statistical analysis and modeling to optimize performance, reliability, and scalability. This review paper explores statistical methodologies for analyzing network characteristics, dimensioning, parameter estimation, and cost prediction of optical networks, and provides a generalized framework based on the idea of convex areas, and link length and shortest path length distributions. Accurate dimensioning and cost estimation are crucial for optical network planning, especially during early-stage design, network upgrades, and optimization. However, detailed information is often unavailable or too complex to compute. Basic parameters like coverage area and node count, along with statistical insights such as distribution patterns and moments, aid in determining the appropriate modulation schemes, compensation techniques, repeater placement, and in estimating the fiber length. Statistical models also help predict link lengths and shortest path lengths, ensuring efficiency in design. Probability distributions, stochastic processes, and machine learning improve network optimization and fault prediction. Metrics like bit error rate, quality of service, and spectral efficiency can be statistically assessed to enhance data transmission. This paper provides a review on statistical analysis and modeling of optical networks, which supports intelligent optical network management, dimensioning of optical networks, performance prediction, and estimation of important optical network parameters with partial information. Full article

Compared to spiral bevel gear drives with localized conjugation, line contact spiral bevel gears possess a significantly larger meshing area, theoretically achieving full tooth surface contact and substantially enhancing load capacity. To accurately support the root strength calculation and parameter design of line contact spiral bevel gear drives, this paper presents a theoretical analysis and experimental study of the root bending stress of gear pairs. First, based on the analysis of the meshing characteristics of line contact spiral bevel gear pairs, the load distribution along the contact lines is investigated. Using the slicing method, the load distribution characteristics along the contact line are obtained, and the load sharing among multiple tooth pairs during meshing is further studied. Then, by applying a cantilever beam bending stress model, the root bending stress on such a gear drive is calculated. A root bending moment distribution model is proposed based on the characteristics of the line load distribution previously obtained, from which a formula for calculating root bending stress is derived. Finally, static-condition experiments are conducted to test the root bending stress. The accuracy of the proposed calculation method is verified through experimental testing and finite element analysis. The results of this study provide a foundation for designing lightweight and high-power-density spiral bevel gear drives. Full article

In this research work, the authors propose an approach for analyzing a traffic accident involving a motorcycle and a pedestrian. The study was conducted under the condition that there are objects in the accident area that limit the visibility of the participants. For this purpose, a three-dimensional simulation model was developed to determine the relative positions of the pedestrian and the motorcycle-driver system at discrete moments, examining the period of time from the moment the pedestrian steps onto the roadway to the moment of contact between the participants. Data from a real traffic accident were used. Full article

The rise of artificial intelligence (AI) has revolutionized the processing and analysis of video sensor data, driving advancements in areas such as surveillance, autonomous driving, and personalized content recommendations. However, leveraging video data presents unique challenges, particularly in the time-intensive feature extraction process required for model training. This challenge is intensified in research environments lacking advanced hardware resources like GPUs. We propose a new method called the multimodal latent representation learning framework (MLRL) to address these limitations. MLRL enhances the performance of downstream tasks by conducting additional representation learning on pre-extracted features. By integrating and augmenting multimodal data, our method effectively predicts latent representations, leveraging pre-extracted features to reduce model training time and improve task performance. We validate the efficacy of MLRL on the video moment retrieval task using the QVHighlight dataset, benchmarking against the QD-DETR model. Our results demonstrate significant improvements, highlighting the potential of MLRL to streamline video data processing by leveraging pre-extracted features to bypass the time-consuming extraction process of raw sensor data and enhance model accuracy in various sensor-based applications. Full article

Field foundation pile loading tests were conducted in the context of an actual bridge pile foundation project. The test data were analyzed to determine the reasons for the variation in the complex geological conditions of the seashore. Moreover, finite element analysis was conducted to evaluate the influence of pile length and diameter on the settlement of coastal friction foundation piles. Increasing the pile length from 65 m to 75 m reduced the settlement by 25.7%, while increasing the diameter from 1.5 m to 2.0 m led to a 35.9% reduction. Increasing the pile spacing reduced the amount of structural settlement. Group pile foundation pile spacings should be 2.5–3.0 D. Pile group superposition reduced the most obvious effects and the settlement reduction rate was the fastest. Under seismic conditions, the pile group foundation exhibited 5.60 times greater horizontal displacement, 3.57 times higher bending moment, and 5.30 times increased shear force relative to static loading. The formula for predicting the settlement of oversized friction pile group foundations was modified based on settlement values calculated using finite elements. The revised formula is suitable for calculating the settlement of friction pile group foundations in coastal areas. Full article

To address the issue of structural tilting caused by uneven foundation settlement in soft soil areas, this study combined a specific engineering case to conduct numerical simulations of the rectification process for an inclined reinforced concrete building using ABAQUS finite element software. Micropile-raft combined jacking technology was employed, applying staged jacking forces (2400 kN for Axis A, 2200 kN for Axis B, and 1700 kN for Axis C) with precise control through 20 incremental steps. The results demonstrate that this technology effectively halted structural tilting, reducing the maximum inclination rate from 0.51% to 0.05%, significantly below the standard limit. Post-rectification, the peak structural stress decreased by 42%, and displacements were markedly reduced. However, the jacking process led to a notable increase in the column axial forces and directional changes in beam bending moments, reflecting the dynamic redistribution of internal forces. The study confirms that micropile-raft combined jacking technology offers both controllability and safety, while optimized counterforce pile layouts enhance the long-term stability of the rectification system. Based on stress and displacement cloud analysis, a monitoring scheme is proposed, forming an integrated “rectification-monitoring-reinforcement” solution, which provides a technical framework for building rectification in soft soil regions. Full article