Estimating the accuracy of the random walk simulation of mass transport

The mass transport processes always accompanies the flow phenomena and have attracted many researches. A lot of numerical methods have been developed to study them. These numerical methods can be classified into the Eulerian and the Lagrangian approaches. The Lagrangian approach has advantages in high stability and simplicity over the Eulerian approach, but suffers from heavy computational cost. In this paper, we are mainly concerned with the trade-offs between the accuracy and computational cost when applying the random walk method, which is a Lagrangian approach for examining the mass transport scenario. We introduce a linear model to assess the accuracy of the random walk method in several computational configurations. Studies on computational parameters, i.e. the size of time step and number of particles, are conducted with the focus on estimation of the longitudinal dispersion coefficient in steady flows. The results show that the proposed linear model can satisfactorily explain the computational accuracy, both in sample and out-of-sample. Furthermore, we find a constant dimensionless parameter, which quantifies a generic relationship between the accuracy and the number of particles regardless of the flow and diffusion conditions. This dimensionless parameter is of theoretic value and offers guidelines for choosing the correct computational parameters to achieve the required numerical accuracy.National Natural Science Foundation of China (51809219), State key Laboratory of Hydroscience and Engineering (sklhse-2019-B-02), Royal Academy of Engineering (Grant No. UUFRIP\100051), Ministry of Education and State Administration of Foreign Experts Affair

SYNTHESIS OF PROPYLENE CARBONATE FROM UREA AND 1,2-PROPYLENE GLYCOL OVER METAL CARBONATES

A series of single-metal carbonates and Pb-Zn mixed-metal carbonates were prepared as catalysts for alcoholysis of urea with 1,2-propylene glycol (PG) for the synthesis of propylene carbonate (PC). The mixed carbonates all show much better catalytic activities than the single carbonates, arising from a strong synergistic effect between the two crystalline phases, hydrozincite and lead carbonate. The mixed carbonate with Pb/Zn = 1:2 gives the highest yield of PC, followed by the mixed carbonate with Pb/Zn = 1:3. Furthermore, Taguchi method was used to optimize the synthetic process for improving the yield of PC. It is shown that the reaction temperature is the most significant factor affecting the yield of PC, followed by the reaction time, and that the optimal reaction conditions are the reaction time 5 h, the reaction temperature 180 °C and the catalyst amount 1.8 mass%, resulting in the highest PC yield of 96.3%

Perceptions of Heroism: Characteristics, Functions and Influencing Factors among Chinese College Students in the Post-pandemic Era

Heroes play a significant role in shaping the popular perceptions of morality, justice, and social values in general. During the Covid-19 pandemic, people’s anticipation for heroes doubles and their heroism may be reshaped by the pandemic. This paper attempts to investigate the perceived heroism of Chinese higher education students(n=847) in the post-pandemic era by means of the online questionnaire. Firstly, we explore the main characteristics of heroes worshipped by Chinese higher education students, which are summarized as diversified, epoch-making and civilian. Then we investigate the functions of heroes, which are categorized as enhancing, moral modeling and protecting. Finally, we analyze the five factors (intrinsic attraction, social reinforcement, education, family background and publicity) that may predict students’ heroism worship. As the regression analysis reveals, the five factors have significantly positive influences on higher education students’ perceptions of heroism and the weights of intrinsic attraction, social reinforcement, publicity, family background and education are 0.364, 0.316, 0.227, 0.190 and 0.156 respectively. These findings not only provide a theoretical and empirical contribution to the study of heroism, but also help develop Chinese higher education sustainable development in the post-pandemic era

Movable Antenna-Enhanced Multiuser Communication: Optimal Discrete Antenna Positioning and Beamforming

Movable antennas (MAs) are a promising paradigm to enhance the spatial degrees of freedom of conventional multi-antenna systems by flexibly adapting the positions of the antenna elements within a given transmit area. In this paper, we model the motion of the MA elements as discrete movements and study the corresponding resource allocation problem for MA-enabled multiuser multiple-input single-output (MISO) communication systems. Specifically, we jointly optimize the beamforming and the MA positions at the base station (BS) for the minimization of the total transmit power while guaranteeing the minimum required signal-to-interference-plus-noise ratio (SINR) of each individual user. To obtain the globally optimal solution to the formulated resource allocation problem, we develop an iterative algorithm capitalizing on the generalized Bender's decomposition with guaranteed convergence. Our numerical results demonstrate that the proposed MA-enabled communication system can significantly reduce the BS transmit power and the number of antenna elements needed to achieve a desired performance compared to state-of-the-art techniques, such as antenna selection. Furthermore, we observe that refining the step size of the MA motion driver improves performance at the expense of a higher computational complexity

Globally Optimal Resource Allocation Design for Discrete Phase Shift IRS-Assisted Multiuser Networks with Perfect and Imperfect CSI

Intelligent reflecting surfaces (IRSs) are a promising low-cost solution for achieving high spectral and energy efficiency in future communication systems by enabling the customization of wireless propagation environments. Despite the plethora of research on resource allocation design for IRS-assisted multiuser communication systems, the optimal design and the corresponding performance upper bound are still not fully understood. To bridge this gap in knowledge, in this paper, we investigate the optimal resource allocation design for IRS-assisted multiuser systems employing practical discrete IRS phase shifters. In particular, we jointly optimize the beamforming vector at the base station (BS) and the discrete IRS phase shifts to minimize the total transmit power for the cases of perfect and imperfect channel state information (CSI) knowledge. To this end, two novel algorithms based on the generalized Benders decomposition (GBD) method are developed to obtain the globally optimal solution for perfect and imperfect CSI, respectively. Moreover, to facilitate practical implementation, we propose two corresponding low-complexity suboptimal algorithms with guaranteed convergence by capitalizing on successive convex approximation (SCA). In particular, for imperfect CSI, we adopt a bounded error model to characterize the CSI uncertainty and propose a new transformation to convexify the robust quality-of-service (QoS) constraints. Our numerical results confirm the optimality of the proposed GBD-based algorithms for the considered system for both perfect and imperfect CSI. Furthermore, we unveil that both proposed SCA-based algorithms can achieve a close-to-optimal performance within a few iterations. Moreover, compared with the state-of-the-art solution based on the alternating optimization (AO) method, the proposed SCA-based scheme achieves a significant performance gain with low complexity

UAV-Assisted Sensor Data Dissemination in mmWave Vehicular Networks Based on Network Coding

Due to good maneuverability, UAVs and vehicles are often used for environment perception in smart cities. In order to improve the efficiency of sensor data sharing in UAV-assisted mmWave vehicular network (VN), this paper proposes a sensor data sharing method based on blockage effect identification and network coding. The concurrent sending vehicles selection method is proposed based on the availability of mmWave link, the number of target vehicles of sensor data packet, the distance between a sensor data packet and target vehicle, the number of concurrent sending vehicles, and the waiting time of sensor data packet. The construction method of the coded packet is put forward based on the status information about the existing packets of vehicles. Simulation results demonstrated that efficiency of the proposed method is superior to baseline solutions in terms of the packet loss ratio, transmission time, and packet dissemination ratio

UAV-assisted data dissemination based on network coding in vehicular networks

Efficient and emergency data dissemination service in vehicular networks (VN) is very important in some situations, such as earthquakes, maritime rescue, and serious traffic accidents. Data loss frequently occurs in the data transition due to the unreliability of the wireless channel and there are no enough available UAVs providing data dissemination service for the large disaster areas. UAV with an adjustable active antenna can be used in light of the situation. However, data dissemination assisted by UAV with the adjustable active antenna needs corresponding effective data dissemination framework. A UAV-assisted data dissemination method based on network coding is proposed. First, the graph theory to model the state of the data loss of the vehicles is used; the data dissemination problem is transformed as the maximum clique problem of the graph. With the coverage of the directional antenna being limited, a parallel method to find the maximum clique based on the region division is proposed. Lastly, the method\u27s effectiveness is demonstrated by the simulation; the results show that the solution proposed can accelerate the solving process of finding the maximum clique and reduce the number of UAV broadcasts. This manuscript designs a novel scheme for the UAV-assisted data dissemination in vehicular networks based on network coding. The graph theory is used to model the state of the data loss of the vehicles. With the coverage of the directional antenna being limited, then a parallel method is proposed to find the maximum clique of the graph based on the region division. The effectiveness of the method is demonstrated by the simulation

Efficient Message Dissemination on Curve Road in Vehicular Networks

Effective emergency message dissemination is a great importance on a specific road in vehicular networks (VN). The existing methods are not most efficient solutions for message dissemination on the curve road, which primarily focus on highway and urban road. In order to improve the efficiency of message dissemination on the curved road, the paper proposed a message dissemination method based on bidirectional relay nodes. The message can be disseminated in two directions simultaneously. The paper designed a relay node selection method based on the neighbor nodes’ coverage length of the road. Different waiting delays are assigned to the neighbor nodes according to the cover capability of the road in which the message has not arrived. Simulation results demonstrated that the efficiency of the proposed method is superior to the common solutions in terms of the contention delay and the propagation velocity