In recent years, with the gradual development of the aviation industry, how to make supersonic aircraft truly used in military air defense has become a global problem. In this paper, the wing design of supersonic aircraft is studied, a swept back symmetrical wing suitable for supersonic reconnaissance aircraft is designed with reasonable aspect ratio, span length, sweep angle, thrust weight ratio and wing load. On the basis of the aerodynamic characteristics of the aircraft analyzed, the inboard electron, outboard electron, flasheron, leading edge flap and all moving tip are designed to ensure the controllability in the flight line and to maintain the balance and stability of the aircraft. The qualitative analysis of the flight performance of the wing is also performed. This paper provides a possibility for the design of supersonic aircraft in the future.

With the development and change of big data related technologies, more and more large amounts of data need to be analyzed. Now there are companies like Google, Yahoo, etc. Frameworks such as MapReduce, Hadoop, Spark, etc. are developed for processing large amounts of data. In this paper, relevant discussions and researches are carried out on time series forecasting under the new era of big data. Now there are time series forecasting methods based on map reduce, Hadoop, spark data processing framework, including nearest neighbor distribution method, neural network method, etc., which have made quite good achievements in big data time series forecasting. By reading the relevant research literature, it is universally acknowledged that the Spark’s framework has good application prospects and potential in predicting big data time series. As a result, this paper is mainly aimed at the optimization and improvement of the big data time series forecasting method on the basis of the spark framework. The author noticed that most of the default configurations of spark clusters are generated by default or automatically, rather than the optimal solution obtained after algorithm optimization, so there is still room for improvement in this regard. In this regard, this paper proposes a kernel method for visual data processing of related configurations and parameters, and then optimizes the default data configuration as much as possible to improve the accuracy and feasibility of the big data time series prediction method on the basis of the spark framework. In this paper, the optimized scheme is used to forecast the domestic electricity consumption in the past five years, and the results show that the optimized scheme has a good improvement performance on the basis of the original method.

This paper analyses the application of Automated Guided Vehicle (AGV) in ports and evaluates the 20 ports' efficiency with the consideration of AGV application. Using the data envelopment analysis (DEA) method and the simulated data, this paper further identifies the optimal number of AGVs for these 20 ports. The DEA-CCR and DEA-BCC results show that most of these 20 ports are already efficient. And Ningbo port, Osaka port, and Hamburg port are the most efficient port as they obtained the highest scores in super-efficiency analysis. But using the simulation data, the result suggests that some ports, such as Busan Port and Antwerp Port, are able to improve their efficiency by adjusting the application of AGV. The finding of this paper suggests that existing automated port can improve their economic efficiency by reducing the number of AGVs, or enhancing their service efficiency by increasing the application of AGVs. But for traditional ports, expanding the application of AGV can increase both port economic and service efficiency.

This article elaborates on molecular dynamics simulation, which is a technology that supports us in analyzing the structure and dynamics of materials and their properties at a microscopic level. In this article, the molecular dynamics simulation develops on Lennard-Jones potential. The simulation is based on the fundamental understanding between Argon-Argon molecules. The application for running molecular dynamics simulation is Moldy. The Argon particles’ size is changed by altering van der Waals radius from Lennard-Jones potential parameters, and the mixture of Argon and different sizes’ particles will be simulated by Moldy. The average potential energy is collected and compared. It discusses how the size of particles affect the average potential energy. Moreover, the trend of potential energy respects to timesteps for each molecule is depicted and compared graphicly by Gnuplot. It discusses how the potential energy changes according to timesteps for different sizes’ particles. In the end, the result is collected and summarized. It discovers that potential energy increases slowly when particles’ sizes increase, and the potential energy decreases significantly when particles’ sizes decrease. In addition, it founds out that molecules with different sizes have a noticeable change initially. Oddly, there is no observation of significant changes in the potential energy of the original molecule. Moreover, the initial decrease for molecules that increase in size is not as significant as that for molecules that decrease in size.

Classical and Quantum mechanics are the two milestones of physics and mathematics. The path integral describes the generalised form of action from classical to quantum mechanics. This paper has reviewed some fundamental concepts and results in classical dynamics and quantum mechanics. The research method of the whole project is mainly theoretical derivations of applied mathematics and mathematical physics. This paper provides different perspectives to investigate the applications of path integrals. This paper also builds a connection between path integrals and the Unruh temperature.

As a rehabilitation robot for aiding in the movement of lower limbs, the lower limb exoskeleton is a beneficial device. In order to make the most effective use of the exoskeleton, the control strategy plays a crucial role. This review paper provides a background and classification of lower limb exoskeleton control strategies, such as model-based and hierarchy-based control. Further, we presented mainly the high-level control architecture of lower limb exoskeletons, which is aimed at detecting the intention of human movement. An in-depth discussion is provided in this paper regarding manual user input (MUI), surface electromyography (sEMG), and brain-computer interface (BCI). Many people need exoskeletons, which is why this review was written. Exoskeletons, however, are expensive and cannot be mass-produced, and their control methods are immature, making them ineffective. Thus, the objective of this review is to identify research gaps and common limitations in previous research to obtain future directions for improving the usability of the control mechanism. In an alternative approach, MUI and BCI are combined to reduce the time spent switching movement modes and the amount of concentration required to do so.

The theory of antimatter was proposed long ago and thought of as made up of antiparticles. Antimatter was believed to exist based on the theory of relativity and quantum mechanics, which are thought to be two fundamental concepts in modern physics. However, it turned out that scientists had great difficulty in finding antimatter. This has led to a discussion about what dark matter is made of and how it exists. Depending on the context of algebraic quantum field theory, antimatter does not consist of antiparticles, which means that antiparticles are particles that consist of antimatter. The notion of antimatter will be explained through the quantum field theory (QFT) theory. How we define the antimatter depends on our criteria in the physical state space. Recent research in AQFT（Advanced Quantum Field Theory) shows that all different quantum states possess antimatter counterparts, which has greatly expanded the field of antimatter research. Then several possible explanations for the distribution of antimatter and their theoretical foundation will be discussed. After exploration and observation across nearly one century, scientists still cannot get a reasonably clear picture of the distribution of antimatter. Why antimatter appeared and disappeared is still unknown, and attempts to find antimatter that exists in nature are going on. Scientists have had some good success when focused on the center of black holes and supermassive objects in space. There have been a lot of observations of antimatter in progress since decades of years ago.

The multiple traveling salesmen problems (MTSP) is a combinatorial optimization and np-hard problem. In practice, the computational resource required to solve such problems is usually prohibitive, and, in most cases, using heuristic algorithms is the only practical option. This paper implements genetic algorithms (GA) and simulated annealing (SA) to solve the MTSP and does an experimental study based on a benchmark from the TSPLIB instance to compare the performance of two algorithms in reality. The results show that GA can achieve an acceptable solution in a shorter time for any of the MTSP cases and is more accurate when the data size is small. Meanwhile, SA is more robust and achieves a better solution than GA for complex MTSP cases, but it takes more time to converge. Therefore, the result indicates that it is hard to identify which algorithm is comprehensively superior to the other one. However, It also provides an essential reference to developers who want to choose algorithms to solve MTSP in real life, facilitating them to balance the algorithm’s performance on different metrics they value.

Directional liquid transport has many cutting-edge applications, such as fog collection, agricultural drip irrigation, biochemical microreactors, water harvesting, non-powered micro-drug delivery, thin-film lubrication etc. There are many surfaces or linear structures in the natural systems can occur directional transport of water. In this paper, two bionic structures inspired by natural structures and two artificially fabricated surface structures are presented and their flow laws and mechanical mechanisms are described. Thereby, it is analysed that surface-driven external forces, such as the gradient of surface energy and the gradient of Laplace pressure, and surface pinning in other directions are the key points to drive the directional flow of liquids.

Elliptic flow signal, v_2, is widely studied in heavy ion collisions. Researches have been done to obtain the pseudorapidity dependence of v_2, while the measurement of transverse momentum dependence is relatively few. This paper presents the transverse momentum dependence of v_2 in Pb+Pb collision at√(s_NN )=5.02 TeV. The measurement is performed in the region with pseudorapidity |η|<2.8 and transverse momentum 〖0.2 < p〗_T<6.0GeV. In this work, we use sub-event method to measure elliptic flow for the collisions in different ranges of transverse momentum. The result shows a polynomial relation between elliptic flow signal and transverse momentum. In Section 4, the limitation of our measurement is also discussed.