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The development of high-speed railway networks and the increased running speeds of high-speed trains (HSTs) have made the aerodynamic interference between HSTs and their surrounding environments increasingly important. Compared with a traditional wind tunnel test, systematically understanding the aerodynamic characteristics of HSTs involves relatively more stringent requirements, highlighting the need to develop experimental methods and technologies with enhanced dynamic performance. Central South University (CSU) developed a wireless data acquisition system, named as the in-model sensory and wireless data acquisition — remote control and processing system (ISWDA-RCPS), which can operate onboard a novel moving train and infrastructure rig. The system was developed to meet current wind tunnel data collection needs, and it avoids the physical cables used in conventional devices, which are extremely susceptible to induced noise. The system accepts inputs from various sensors and transfers the data wirelessly to an access point outside a wind tunnel’s test section. To analyze the feasibility of the ISWDA-RCPS concerning its sensing capabilities and wireless communications, we conduct experiments in multiple operating conditions. Finally, pressure measurements are acquired from a moving Fuxing HST model at different points and used to analyze the aerodynamic behavior of the model. [ABSTRACT FROM AUTHOR]

To better understand the aerodynamic characteristics of a train-bridge system under crosswind, an in-house experimental apparatus was developed in a wind tunnel at Central South University (CSU). The new facility consists of trains, a bridge, U-shaped slide rails, and positioning systems with winches. A wireless data acquisition system for pressure measurements was mounted within the train carriage to avoid any potential aerodynamic interference. A 1:25 scaled model of CRH2 running over a simply supported girder bridge was tested in a wind tunnel. The aerodynamic characteristics of the train-bridge system under various combinations of crosswind speed, train speed, and vehicle location on the bridge were identified. The experimental results reveal that the cosine law for surface wind pressure on a train under crosswind is no longer valid when the train runs on the bridge. The moving model method can better capture the more practical aerodynamic characteristics and the impact of train movement on the bridge. The present study indicates that the wind tunnel experiments using the stationary model cannot fully reveal the aerodynamic characteristics of both the train and bridge during crossing. The results captured using this unique approach provide insight into the aerodynamic characteristics of trains and bridges. [ABSTRACT FROM AUTHOR]

High-speed trains (HSTs) are being buffeted by accelerating running speed, and with that comes the aerodynamic issues. The slipstream is related to the train aerodynamic characteristics and of importance to the safety of surrounding people and structures. In this study, the ensemble-averaged and instantaneous characteristics of the slipstream of a simplistic high-speed train model with a square-back were experimentally investigated using a novel moving model rig. The present investigation indicates that the double-line substructure causes obvious asymmetry in the slipstream even at locations apart from the bridge surface with a large distance. The square-back of the HST attenuates its slipstream significantly relative to that with a streamlined tail. Besides, the decaying rate of the slipstream is higher in the wake of a square-back HST. The presents results suggest that the trailing vortices downstream of the square-back HST are substantially suppressed. [ABSTRACT FROM AUTHOR]

CO2 and CO, the by-products of fossil fuels; one of them is a major cause of global warming and the other endangers the nervous and cardiovascular systems of humans. Therefore, real-time monitoring towards those harmful gases is of practical significance. Nano-structured materials have attracted the attention of scholars for their enormous potential for harmful gas detection. In this work, the adsorption and sensing behavior of C3B and Al-doped C3B monolayers for these two typical hazardous gases were investigated theoretically. The most stable doping model was obtained, and the adsorption process for CO and CO2 was simulated based on this model. The adsorption system shows that the gas molecules are all deformed and that the charge transfer and adsorption energy are significantly increased. Moreover, the adsorption mechanism was investigated by analyzing the electronic behavior of the adsorbent, and the physical adsorption between the hazardous gas and the adsorbent was more favorable for desorption. The good adsorption performance and sensing mechanism suggest that the CO/CO2 sensor prepared using Al–C3B has great potential for application. Our work may provide some guidance for the application of toxic gas monitoring and adsorption. [ABSTRACT FROM AUTHOR]

On account of its superior insulating performance and low global warming potential (GWP), C4F7N has been the focus of replacing SF6. Based on density functional theory, the adsorption mechanism and electrical characteristics of GeSe monolayer towards C4F7N decomposition species (COF2, CF4, CF3CN and C2F5CN) are explored to investigate the feasibility of GeSe gas sensors. Compared with other decomposition products, GeSe monolayers are more capable of capturing for C2F5CN, as evidenced by the smallest band gap (0.781 eV) and the highest adsorption energy (−0.427 eV). The adsorption behaviors lead to a larger GeSe band gap and thus a decrease in the conductivity of the adsorption system. The adsorption types of GeSe for four gases are all physical adsorption and can have good desorption properties at room temperature (298 K) with the adsorption capabilities: C2F5CN>CF3CN>COF2>CF4. Theoretically, GeSe monolayers can be used to create a novel gas sensor for and industrial application, which can be utilized to monitor and diagnose high-voltage insulated equipment in real time. [ABSTRACT FROM AUTHOR]

Real-time and accurate detection of H2S has been an urgent problem in industry and human health. In view of practical problems of the existing nano sensors such as poor selectivity, low sensitivity, strong or weak adsorption capacity, H2S sensors based on metal oxide nanoparticles (XO, X = Cu, Zn, Ni) doped GeSe monolayer are proposed. Compared with pure system, the improvement of the adsorption distance of doped systems proves the obvious interaction between the activated atoms and H2S. The excellent sensitivity ensures the detection effect of H2S at low concentration. The ideal adsorption energy makes doped systems have attractive adsorption and desorption properties. In addition, the excellent water resistance, high thermal stability and fascinating selectivity to H2S of doped systems verify the feasibility in practical application. This study lays a theoretical foundation for the development of new generation of wearable gas sensor for health and industrial monitoring. [ABSTRACT FROM AUTHOR]

CO 2 and CO, the by-products of fossil fuels; one of them is a major cause of global warming and the other endangers the nervous and cardiovascular systems of humans. Therefore, real-time monitoring towards those harmful gases is of practical significance. Nano-structured materials have attracted the attention of scholars for their enormous potential for harmful gas detection. In this work, the adsorption and sensing behavior of C 3 B and Al-doped C 3 B monolayers for these two typical hazardous gases were investigated theoretically. The most stable doping model was obtained, and the adsorption process for CO and CO 2 was simulated based on this model. The adsorption system shows that the gas molecules are all deformed and that the charge transfer and adsorption energy are significantly increased. Moreover, the adsorption mechanism was investigated by analyzing the electronic behavior of the adsorbent, and the physical adsorption between the hazardous gas and the adsorbent was more favorable for desorption. The good adsorption performance and sensing mechanism suggest that the CO/CO 2 sensor prepared using Al-C 3 B has great potential for application. Our work may provide some guidance for the application of toxic gas monitoring and adsorption.

Background: Corticostriatal circuits, particularly the dorsomedial striatum (DMS) and lateral orbitofrontal cortex, are critical for navigating reversal learning under probabilistic uncertainty. These same areas are implicated in the reversal learning impairments observed in individuals with psychosis as well as their psychotic symptoms, suggesting that they may share a common neurobiological substrate. To address this question, we used psychostimulant exposure and specific activation of the DMS during reversal learning in mice to assess corticostriatal activity., Methods: We used amphetamine treatment to induce psychosis-relevant neurobiology in male mice during reversal learning and to examine pathway-specific corticostriatal activation. To determine the causal role of DMS activity, we used chemogenetics to drive midbrain inputs during a range of probabilistic contingencies., Results: Mice treated with amphetamine showed altered punishment learning, which was associated with decreased shifting after losses and increased perseverative errors after reversals. Reversal learning performance and strategies were dependent on increased activity in lateral orbitofrontal cortex to DMS circuits as well as in the DMS itself. Specific activation of midbrain to DMS circuits also decreased shifting after losses and reversal learning performance. However, these alterations were dependent on the probabilistic contingency., Conclusions: Our work suggests that the DMS plays a multifaceted role in reversal learning. Increasing DMS activity impairs multiple reversal learning processes dependent on the level of uncertainty, confirming its role in the maintenance and selection of incoming cortical inputs. Together, these outcomes suggest that elevated dopamine levels in the DMS could contribute to decision-making impairments in individuals with psychosis., (© 2022 The Authors.)