Search Results (572)

To solve the problems of numerous influencing factors, such as the high uncertainty and leakage risk of gas production pipelines in high-sulfur gas fields, a dynamic analysis of a gas production pipeline’s leakage risk using a dynamic Bayesian network is proposed. By means of Bow-tie model analysis, the primary risk sources of gas pipeline leakage and different accidents are summarized. A temporal dimension was introduced to construct a dynamic Bayesian network model, utilizing the Leaky noisy-OR gate model to rectify and compute conditional probability, thereby facilitating dynamic risk prediction of gas pipeline leakage. Taking the first section of the pipeline of a municipal gas collection station as an example, with the help of GeNIe 4.0 Academic software, the influence degree of each basic event on pipeline gas leakage was revealed. The change curve of gas leakage probability over time was drawn, and the occurrence probability of potential consequences of accidents was computed. The results indicate that the status of flanges, valves, and pipelines are key factors in determining the occurrence of gas leakage accidents, and six risk sources, including medium corrosion in gas leakage accidents, were determined, with these having practical conspicuousness for strengthening the leakage protection of gas pipelines and providing proper support for the formulation of relevant safety measures. Full article

Background/Objectives: Aural toilet using microsuction is a common procedure in ENT clinics, and vertigo is a frequent complaint during this procedure. This study aimed to investigate the characteristics and incidence of microsuction-induced nystagmus and vertigo based on the appearance of the tympanic membrane (TM). Methods: In 85 patients with various TM appearances, microsuction-induced vertigo and nystagmus were assessed. Results: Microsuction elicited nystagmus in 95% (81 of 85) of patients and vertigo in 36% (31 of 85). The nystagmus direction was towards the ipsilateral ear in a bowing position and towards the contralateral ear in a leaning position. The proportion of patients who complained of rotatory vertigo was significantly higher in those with TM perforation, open cavity mastoidectomy, and adhesive otitis media (74%, 26 of 35) compared to those without TM perforation (10%, 5 of 50) (p < 0.001, X² test). Conclusions: Aural toilet using microsuction commonly induces vertigo due to convection in the lateral semicircular canal endolymph caused by the cooling effect. While microsuction-induced nystagmus was observed in most patients, the incidence of vertigo varied depending on the TM condition. Clinicians should closely monitor patients for vertigo during the procedure, and methods to prevent microsuction-induced vertigo should be explored. Full article

Petroleum storage and transport systems necessitate robust safety measures to mitigate oil spill risks threatening marine ecosystems and sustainable development through ecological and socioeconomic safeguards. We aimed to gain a deeper understanding of the evolution patterns of accidents and effectively mitigate risks. An improved risk assessment method that combines the Bow-Tie (BT) theory and Dynamic Bayesian theory was applied to evaluate the safety risks of petroleum storage and transportation facilities. Additionally, a scenario modeling approach was utilized to construct a model of the event chain resulting from accidents, facilitating quantitative analysis and risk prediction. By constructing an accident chain based on fault trees, the BT model was converted into a Bayesian Network (BN) model. A Dynamic Bayesian Network (DBN) model was established by incorporating time series parameters into the static Bayesian model, enabling the dynamic risk assessment of an oil storage and transportation base in the Zhoushan archipelago. This study quantitatively analyzes the dynamic risk propagation process of storage tank leakage, establishing time-dependent risk probability profiles. The results demonstrate an initial leakage probability of 0.015, with risk magnitude doubling for the temporal progression and concurrent probabilistic escalation of secondary hazards, including fire or explosion scenarios. A novel risk transition framework for the consequences of petrochemical leaks has been developed, providing a predictive paradigm for risk evolution trajectories and offering critical theoretical and practical references for emergency response optimization. Full article

To mitigate the risk of hydrogen leakage in ship fuel systems powered by internal combustion engines, a Bayesian network model was developed to evaluate the risk of hydrogen fuel leakage. In conjunction with the Bow-tie model, fuzzy set theory, and the Noisy-OR Gate model, an in-depth analysis was also conducted to examine both the causal factors and potential consequences of such incidents. The Bayesian network model estimates the likelihood of hydrogen leakage at approximately 4.73 × 10⁻⁴ and identifies key risk factors contributing to such events, including improper maintenance procedures, inadequate operational protocols, and insufficient operator training. The Bow-tie model is employed to visualize the causal relationships between risk factors and their potential consequences, providing a clear structure for understanding the events leading to hydrogen leakage. Fuzzy set theory is used to address the uncertainties in expert judgments regarding system parameters, enhancing the robustness of the risk analysis. To mitigate the subjectivity inherent in root node probabilities and conditional probability tables, the Noisy-OR Gate model is introduced, simplifying the determination of conditional probabilities and improving the accuracy of the evaluation. The probabilities of flash or pool fires, jet fires, and vapor cloud explosions following a leakage are calculated as 4.84 × 10⁻⁵, 5.15 × 10⁻⁵, and 4.89 × 10⁻⁷, respectively. These findings highlight the importance of strengthening operator training and enforcing stringent maintenance protocols to mitigate the risks of hydrogen leakage. The model provides a valuable framework for safety evaluation and leakage risk management in hydrogen-powered ship fuel systems. Full article

Resistance is a key index of a ship’s hydrodynamic performance, and studying the design of the bulbous bow is an important method to reduce ship resistance. Based on the ship resistance sample data obtained from computational fluid dynamics (CFD) simulation, this study uses a machine learning method to realize the fast prediction of ship resistance corresponding to different bulbous bows. To solve the problem of insufficient accuracy in the single surrogate model, this study proposes a CBR surrogate model that integrates convolutional neural networks with backpropagation and radial basis function models. The coordinates of the control points of the NURBS surface at the bulbous bow are taken as the design variables. Then, a convergence factor is introduced to balance the global and local search abilities of the whale algorithm to improve the convergence speed. The sample space is then iteratively searched using the improved whale algorithm. The results show that the mean absolute error and root mean square error of the CBR model are better than those of the BP and RBF models. The accuracy of the model prediction is significantly improved. The optimized bulbous bow design minimizes the ship resistance, which is reduced by 4.95% compared with the initial ship model. This study provides a reliable and efficient machine learning method for ship resistance prediction. Full article

This study investigates the hydrodynamic and morphological effects caused by non-powered floating objects (e.g., barges, pontoons, and floating or moored platforms) that are towed by external forces (such as tugboats) across flat, shallow seabeds. This study employs an integrated approach combining advanced computational fluid dynamics (CFD) simulations with multivariate polynomial regression analysis to systematically investigate the hydrodynamic and morphological effects of non-powered floating objects on sediment resuspension. A total of 96 simulation scenarios were conducted, of which 84 significant cases (where the floating object did not touch the seabed) were analyzed. Variations included bow geometries (blunt and raked), towing speeds, and operational parameters. The results indicate that, under similar towing speeds and clearance heights, blunt bows increase the suspended sediment concentration by approximately 90–190% compared to raked bows. The regression model, attaining an R-squared value of 0.9647, identified the Froude number, squat ratio, squared towing time, and object type as critical predictors of suspended sediment concentration. Furthermore, the interaction terms between the Froude number and object type were significant, enhancing the model’s predictive accuracy. These results underscore the importance of optimized design and operational strategies in minimizing the environmental impact of floating structures, especially in shallow marine environments where sediment dynamics play a crucial role in ecological balance. Careful consideration of towing speed, object geometry, and operational parameters can significantly reduce sediment resuspension, mitigating ecological consequences. Full article

Numerical studies were performed to investigate bow flare slamming loads under irregular waves. To estimate the slamming forces in the simulations, two time windows were selected based on existing experimental data. This study examined horizontal and vertical slamming phenomena by analyzing the relationship between the motions and the resulting slamming forces. The horizontal and vertical slamming forces from the simulations were directly compared with the experimental data. Furthermore, the experiment and simulation results were compared against a representative classification code for additional validation. The findings provide insights into the physical phenomena of horizontal and vertical slamming and confirm that the formulation suggested by classification societies provides a reasonable estimation of slamming loads. Finally, the results emphasize that both horizontal and vertical slamming forces are significant design parameters. Full article

The potential value of the new type of vector propulsor in submarine movement has been confirmed. However, some key mechanical issues are not fully understood, especially the hydrodynamic characteristics during oblique motion. By using dynamic mesh simulation methods, a systematic study was conducted on the fluid dynamic behavior of pump-jet vector propulsor submarines during oblique and yawing processes, supplemented by the scientific validity of related experimental verification results. The research indicates that oblique movement causes a local stagnation positive pressure zone to form at the bow of the hull and a relative back pressure zone to form in the middle of the pump shell. As the angle of drift during oblique movement increases, significant improvements are observed in the lateral force, lateral velocity, and lateral moment of the submarine. During yawing motion, a negative pressure zone appears on the right side of the bow, with a local positive pressure zone appearing on the left side. In both oblique and yawing movements, the rotational speed has an amplifying effect on the appearance of the jet wake phenomenon for the submarine. Based on numerical results, a polynomial fitting method is used to establish a mathematical model for the variation in the speed coefficient and angular velocity system of the pump-jet vector propulsor submarine with the spiral mixed-flow pump speed. This study provides theoretical guidance for the application and optimization of pump-jet vector propulsors. Full article

Black-odorous water (BOW) in urban areas poses significant risks to water safety and human health. Chemical oxygen demand (COD) is a critical parameter for the control and monitoring of BOW. However, traditional methods for COD determination are expensive, time-consuming, and involve the use of hazardous chemicals. In this study, reduced graphene oxide (rGO) and transitional metal particles (Cu, Ni) were used as working electrode materials for facile on-site determination of COD in BOW. Three composite materials (rGO/Cu, rGO/Ni, and rGO/Cu/Ni) were synthesized by one-step chemical reduction with different ratios, and their microstructure and chemical composition were characterized. Glucose solution and real water were used to evaluate the electrocatalytic performance of the different sensors. The ternary composite (rGO/Cu/Ni) screen-printed electrode sensor demonstrated excellent performance in COD analysis, with a low limit of detection (18.9 mg L⁻¹), a broad linear detection range from 53 to 1500 mg L⁻¹, and a 1.61% relative error for real water samples. The testing results were highly consistent with those obtained using the standard chromium sulfate method. This study offers promising prospects for the mass production of cost-effective COD electrochemical sensors, facilitating real-time, on-site monitoring of water bodies in major urban areas. Full article

An arrow’s attack angle continuously changes during its flight, which affects the position of the aerodynamic pressure center. To account for the offset between the aerodynamic pressure center and the center of mass of an arrow in recurve bow shooting, two equations for describing the variation of the aerodynamic pressure center with the attack angles were fitted via CFD simulation. On this basis, a new theoretical aerodynamic model was developed by integrating the above equations with the current model to predict the flight along the outer ballistic trajectory more accurately than ever. With regard to actual archery competition occasions, the distance, initial velocity, and attack angle were set to 70 m, 57 m/s, and −3° to 3°, respectively; the attitude and trajectory of the arrow flying details under background wind, such as crosswind, headwind, and tailwind, were numerically analyzed to reveal the accuracy deviation mechanism. A comparison was conducted with previous models, indicating that the model proposed in this study achieved improvements in accuracy of 15% under crosswind conditions and 8% under headwind/tailwind conditions. The results could, from a fluid physics perspective, provide valuable recommendations not only for archers and coaches but also for arrow manufacturers. Full article

With the rapid expansion of social media, detecting offensive language has become critically important for healthy online interactions. This poses a considerable challenge for low-resource languages such as Roman Urdu which are widely spoken on platforms like Facebook. In this paper, we perform a comprehensive study of offensive language detection models on Roman Urdu datasets using both Machine Learning (ML) and Deep Learning (DL) approaches. We present a dataset of 89,968 Facebook comments and extensive preprocessing techniques such as TF-IDF features, Word2Vec, and fastText embeddings to address linguistic idiosyncrasies and code-mixed aspects of Roman Urdu. Among the ML models, a linear kernel Support Vector Machine (SVM) model scored the best performance, with an F1 score of 94.76, followed by SVM models with radial and polynomial kernels. Even the use of BoW uni-gram features with naive Bayes produced competitive results, with an F1 score of 94.26. The DL models performed well, with Bi-LSTM returning an F1 score of 98.00 with Word2Vec embeddings and fastText-based Bi-RNN performing at 97.00, showcasing the inference of contextual embeddings and soft similarity. The CNN model also gave a good result, with an F1 score of 96.00. The CNN model also achieved an F1 score of 96.00. This study presents hybrid ML and DL approaches to improve offensive language detection approaches for low-resource languages. This research opens up new doors to providing safer online environments for widespread Roman Urdu users. Full article

High-fidelity simulations are used to study the stability of a coupled parachute–payload system in different configurations. A 8.53 m ring–slot canopy is attached to two separate International Organization for Standardization (ISO) container payloads representing a Twenty Foot Equivalent (TEU). To minimize risk and as an alternative to a relatively expensive traditional test program, a multi-phase design and evaluation program using computational tools validated for uncoupled parachute system components was completed. The interaction of the payload wake suspended at different locations and orientations below the parachute were investigated to determine stability characteristics for both subsonic and supersonic freestream conditions. The DoD High-Performance Computing Modernization Program CREATE^TM-AV Kestrel suite was used to perform CFD and fluid–structure interaction (FSI) simulations using both delayed detached-eddy simulations (DDES) and implicit Large Eddy Simulations (iLES). After analyzing the subsonic test cases, the simulations were used to predict the coupled system’s response to the supersonic flow field during descent from a high-altitude deployment, with specific focus on the effect of the payload wake on the parachute bow shock. The FSI simulations included structural cable element modeling but did not include aerodynamic modeling of the suspension lines or suspension harness. The simulations accurately captured the turbulent wake of the payload, its coupling to the parachute, and the shock interactions. Findings from these simulations are presented in terms of code validation, system stability, and drag performance during descent. Full article

In this paper, the low-cycle reciprocating load test was carried out on four-limb concrete-filled steel tubular (CFST) lattice columns with different slenderness ratios and axial compression ratios, and the seismic performance was studied. Two performance indicators, namely damage and hysteretic energy dissipation, were defined as the objective functions, and the axial compression ratio was used as an optimization variable to perform the multi-objective optimization analysis of four-limb CFST lattice columns. Optimization using the max–min problem approach aims to optimize the axial compression ratio to minimize damage and maximize the dissipation of hysteresis energy. The seismic performances before and after optimization were determined using a restoring force model and were evaluated by the finite element method under different axial compression ratios. The results show that, under low-cycle reciprocating loads, the load–displacement hysteresis curve is a bow shape (Members 1 and 2), inverse S-shape (Member 3), and approximate shuttle shape (Member 4). Through multi-objective optimization, the optimized axial compression ratio is 0.25 and the finite element analysis indicates that the optimal seismic performance is at an axial compression ratio of 0.25. Through the optimized design, the maximum horizontal load of lattice columns, the elastic stiffness, the dissipation capacity, and the seismic performance are all improved, under the premise of satisfying the structural safety. Full article

This work studies the influence of a growing boundary layer on the process of supersonic flow around an aerodynamic body. The task is to select and implement in an experiment the parameters of a supersonic flow and to study the flow pattern near the surface of an aerodynamic body at different viscosity values for the incoming flow. Visualization of the shock wave configuration in front of the body and studying the change in the pressure field in the flow region under these conditions is the main goal of this work. The experiment was carried out on an experimental stand created on the basis of a shock tube. The aerodynamic body under study (a semi-cylinder pointed along a circle or an ellipse) was placed in a supersonic nozzle. The model was clamped by lateral transparent walls, which were simultaneously a source of boundary layer growth and the viewing windows for visualizing the flow. For selected modes with Reynolds numbers from 8200 to 45,000, schlieren flow patterns and pressure distribution fields near the surface of the streamlined models and the plate of the growing boundary layer were obtained. The data show a complex, unsteady flow pattern realized near the model which was caused by the viscous-inviscid interaction of the boundary layer with the bow shock wave near the wall. Full article

Computer-assisted learning can help erhu learners to analyze their playing performance and identify areas for improvement. Therefore, in this study, a computerized system based on a You Only Look Once (YOLO)-OD model was developed for erhu bowing training. First, Therblig analysis was performed to segment the erhu bowing process into multiple steps, which were then analyzed thoroughly to identify critical objects for detection. Second, a YOLO-OD model was developed to detect and track the critical objects identified in video frames. Third, scoring methodologies were developed for bow level and bow straightness. The YOLO-OD model and the aforementioned scoring methodologies were incorporated into a computerized training system for erhu bowing, which enables erhu learners to practice independently. It provides scores for bow level and bow straightness, allowing learners to evaluate their technique, as well as feedback and instant alerts regarding incorrect motions and postures, which enable learners to adjust their actions and postures in real time. In addition, teachers or coaches can refer to the videos and other data collected using the proposed system in order to identify problematic erhu bowing techniques and provide students with relevant suggestions and feedback. Full article