Experimental study of the vortex-induced vibration of marine risers under middle flow

A considerable number of studies for vortex induced vibration (VIV) under uniform flow have been performed. However, investigation of VIV under middle flow is scarce. An experiment for VIV under middle flow was conducted in a deep-water offshore basin. Various measurements were obtained by the fiber Bragg grating strain sensors placed on the riser, and VIV under the effect of middle flow with was investigated. Results show that the riser vibrates at different order natural frequencies along the water depth in the CF and IL directions appearing as the multi-frequencies under middle flow. The variation vortex shedding frequencies along the riser under middle flow may generate different wake modes and vibration modals as the corresponding vortex shedding frequencies approach the riser natural frequencies. The dominant vibration frequency of the entire riser is consistent, and determined by high order natural frequency and the corresponding closing vortex shedding frequencies under the middle flow. Meanwhile, the vibration modal under middle flow appears multi-modals and other lower modal have effect on riser vibration. The VIV mechanism under middle flow possesses some aspects similar to those of uniform flow and several unique features

Lift force, drag force, and tension response in vortex-induced vibration for marine risers under shear flow

An experiment was performed in a deep-water basin to investigate VIV mechanisms under shear flow. Lift force, drag force, and tension response were obtained. Results show that multiple frequencies are appeared for nonuniform vortex shedding frequency and interaction between the IL and CF vibrations. Beat phenomenon is observed in time history of lift force, and decreased with the increasing riser pretension. Dominant frequencies of riser tension are consistent with the IL and CF dominant frequency, and amplitudes of the tension are not uniform. VIV is inhibited with increasing riser pretension and the dominant frequencies also increase with increasing riser tension

Effect of drilling pipe rotation on vortex induced vibration response of drilling riser

An experiment was carried out in a basin to investigate rotation of drilling pipe on vortex induced vibration response of drilling riser. Vibration displacement time-history and frequency are obtained. Results show that dominant vibration frequency in the in-line direction is almost twice as high as that in the cross-flow direction. The vibration amplitudes in both the cross-flow and in-line direction increase with an increase in rotation speed of drilling pipe under the experimental conditions. However, the influence of rotation speed drilling pipe on drilling riser vibration amplitude is insignificant. Dominant frequencies are invariant with variation of drilling pipe rotation under experimental conditions

Factors influencing drivers' queue-jumping behavior at urban intersections: A covariance-based structural equation modeling analysis

Queue-jumping is widely acknowledged as one of the most vexing driving behaviors and a prevalent traffic violation at urban intersections in China, exerting detrimental effects on both traffic operational efficiency and safety. To investigate the motivational factors underlying drivers' queue-jumping behavior at urban intersections, a questionnaire was designed to collect data based on an extended theory of planned behavior (TPB). A total of 427 valid responses were received through an online self-reported questionnaire survey conducted in China. The Pearson's chi-square test was employed to examine potential demographic disparities in self-reported queue-jumping behavior among drivers at urban intersections. Covariance-based structural equation modeling (CB-SEM) with bootstrapping was utilized to elucidate the impact of various factors on drivers' engagement in queue-jumping behavior. The findings revealed significant gender and age differences regarding drivers' propensity for queue-jumping at urban intersections, with male and young drivers exhibiting higher inclination compared to female and older counterparts, respectively. Furthermore, the extended TPB effectively accounted for both behavioral intention and actual occurrence of queue-jumping among drivers at urban intersections. Behavioral intention (β = 0.391, p = 0.002) and perceived behavior control (β = 0.282, p = 0.002) emerged as influential determinants of queue-jumping. Among all influencing factors shaping drivers' behavioral intention toward engaging queue-jumping at urban intersections, attitude (β = 0.316, p = 0.005) proved to be the most significant factor followed by perceived risk (β = 0.230, p = 0.001), moral norms (β = 0.184, p = 0.002), subjective norms (β = 0.175, p = 0.002), and perceived behavior control (β = 0.122, p = 0.05). These results offer valuable insights for urban road traffic managers seeking effective strategies for public awareness campaigns as well as practical intervention measures aimed at curbing improper driving behavior of queue-jumping at urban intersections

LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendations

The extraordinary performance of large language models has not only reshaped the research landscape in the field of NLP but has also demonstrated its exceptional applicative potential in various domains. However, the potential of these models in mining relationships from graph data remains under-explored. Graph neural networks, as a popular research area in recent years, have numerous studies on relationship mining. Yet, current cutting-edge research in graph neural networks has not been effectively integrated with large language models, leading to limited efficiency and capability in graph relationship mining tasks. A primary challenge is the inability of LLMs to deeply exploit the edge information in graphs, which is critical for understanding complex node relationships. This gap limits the potential of LLMs to extract meaningful insights from graph structures, limiting their applicability in more complex graph-based analysis. We focus on how to utilize existing LLMs for mining and understanding relationships in graph data, applying these techniques to recommendation tasks. We propose an innovative framework that combines the strong contextual representation capabilities of LLMs with the relationship extraction and analysis functions of GNNs for mining relationships in graph data. Specifically, we design a new prompt construction framework that integrates relational information of graph data into natural language expressions, aiding LLMs in more intuitively grasping the connectivity information within graph data. Additionally, we introduce graph relationship understanding and analysis functions into LLMs to enhance their focus on connectivity information in graph data. Our evaluation on real-world datasets demonstrates the framework's ability to understand connectivity information in graph data

Genetic Engineering of Starch Biosynthesis in Maize Seeds for Efficient Enzymatic Digestion of Starch during Bioethanol Production

Maize accumulates large amounts of starch in seeds which have been used as food for human and animals. Maize starch is an importantly industrial raw material for bioethanol production. One critical step in bioethanol production is degrading starch to oligosaccharides and glucose by alpha-amylase and glucoamylase. This step usually requires high temperature and additional equipment, leading to an increased production cost. Currently, there remains a lack of specially designed maize cultivars with optimized starch (amylose and amylopectin) compositions for bioethanol production. We discussed the features of starch granules suitable for efficient enzymatic digestion. Thus far, great advances have been made in molecular characterization of the key proteins involved in starch metabolism in maize seeds. The review explores how these proteins affect starch metabolism pathway, especially in controlling the composition, size and features of starch. We highlight the roles of key enzymes in controlling amylose/amylopectin ratio and granules architecture. Based on current technological process of bioethanol production using maize starch, we propose that several key enzymes can be modified in abundance or activities via genetic engineering to synthesize easily degraded starch granules in maize seeds. The review provides a clue for developing special maize cultivars as raw material in the bioethanol industry

Using an Improved SWAT Model to Simulate Karst Sinkholes: A Case Study in Southwest China

Hydrological simulation of the karst area is significant for assessing water resources accurately and exploring the relationship in the hydrologic cycle. However, the existence of sinkholes causes the spatial heterogeneity of aquifers and changes the distribution of surface water as well as groundwater, which makes the traditional hydrogeological model difficult to quantitatively characterize the hydrological processes of the sinkhole. Hence, improving the hydrological model for the karst area is a necessary direction at present. The soil and water assessment tool (SWAT) is one of the most widely used semi-distributed hydrological models right now in the world. In this study, we focused on the upper course of the South Panjiang River and used the pond module of the SWAT model to simulate karst sinkholes, modifying the source code to realize the rapid response to the recharge in karst sinkholes. After the improvement, the surface runoff, especially the peak value of the Xiqiao Hydrological Station at the outlet, has been reduced, while the baseflow of modified subbasins has been increased and the water yield is under a state of water balance. In addition, the model evaluation factor R2 was strengthened from 0.76 to 0.83 and NSE was strengthened from 0.66 to 0.79 of the Xiqiao Hydrological Station during the validation period. The improved model was used to analyze the spatial distribution of hydrological components. Also, it was found there are spatial relations between runoff modulus–slope and baseflow–surface runoff–land use types. The analysis demonstrated that the improved SWAT model could effectively change the hydrological components and simulate the rapid replenishment of karst sinkholes

Lift force, drag force, and tension response in vortex-induced vibration for marine risers under shear flow

An experiment was performed in a deep-water basin to investigate VIV mechanisms under shear flow. Lift force, drag force, and tension response were obtained. Results show that multiple frequencies are appeared for nonuniform vortex shedding frequency and interaction between the IL and CF vibrations. Beat phenomenon is observed in time history of lift force, and decreased with the increasing riser pretension. Dominant frequencies of riser tension are consistent with the IL and CF dominant frequency, and amplitudes of the tension are not uniform. VIV is inhibited with increasing riser pretension and the dominant frequencies also increase with increasing riser tension

A Sensor-Based Visual Effect Evaluation of Chevron Alignment Signs’ Colors on Drivers through the Curves in Snow and Ice Environment

The ability to quantitatively evaluate the visual feedback of drivers has been considered as the primary research for reducing crashes in snow and ice environments. Different colored Chevron alignment signs cause diverse visual effect. However, the effect of Chevrons on visual feedback and on the driving reaction while navigating curves in SI environments has not been adequately evaluated. The objective of this study is twofold: (1) an effective and long-term experiment was designed and developed to test the effect of colored Chevrons on drivers’ vision and vehicle speed; (2) a new quantitative effect evaluation model is employed to measure the effect of different colors of the Chevrons. Fixation duration and pupil size were used to describe the driver’s visual response, and Cohen’s d was used to evaluate the colors’ psychological effect on drivers. The results showed the following: (1) after choosing the proper color for Chevrons, drivers reduced the speed of the vehicle while approaching the curves. (2) It was easier for drivers to identify the road alignment after setting the Chevrons. (3) Cohen’s d related to different colors of Chevrons have different effect sizes. The conclusions provide evident references for freeway warning products and the design of intelligent vehicles