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A telecommunication network used for the transmission of astronomical observation data, telescope remote control and other astronomical research purposes is a critical infrastructure. The monitoring and analysis of network traffic, which help improve the network performance and the utilization of network resources, are a challenging task. The accurate identification of the astronomical data traffic will effectively improve transmission efficiency. In this paper, a classification method applied to types of traffic containing astronomical data using deep learning is proposed. The advantages of a convolutional neural network model in image classification are exploited to classify types of traffic containing astronomical data. The objective is to identify the mixed traffic in the network and accurately identify types of traffic containing astronomical data. The effectiveness of the model in improving classification accuracy is also discussed. Actual traffic data captured by Tcpdump and Wireshark are tested, and the experimental results indicate that the proposed method can accurately classify types of traffic containing astronomical data.

The Xinjiang Astronomical Observatory Data Center faces issues related to delay-affected services. As a result, these services cannot be implemented in a timely manner due to the overloading of transmission links. In this paper, the software-defined network technology is applied to the Xinjiang Astronomical Observatory Data Center Network (XAO-DCN). Specifically, a novel reconfiguration method is proposed to realise the software-defined Xinjiang Astronomical Observatory Data Center Network (SDXAO-DCN), and a network model is constructed. To overcome the congestion problem, a traffic load-balancing algorithm is designed for fast transmission of the service traffic by combining three factors: network structure, congestion level and transmission service. The proposed algorithm is compared with current commonly load-balancing algorithms which are used in data center to verify its efficiency. Simulation experiments show that the algorithm improved transmission performance and transmission quality for the SDXAO-DCN.

The horizontal section of the horizontal gas well will form a horizontally enlarged borehole due to factors such as the collapse of the well wall, and it is easy to form gas accumulation in the enlarged section, which will cause accidents such as overflow. Therefore, it is very important to study the gas accumulation law in the horizontal enlarged section. Based on the actual horizontal wellbore size, a three-dimensional horizontal rectangular-enlarged borehole model and a three-dimensional horizontal curved-enlarged borehole model are established in this paper to simulate the phenomenon of gas clustering in the enlarged diameter section. The research results show that, under the same length of the enlarged section, the gas discharge of the horizontally rectangular-enlarged borehole is difficult, which is more likely to cause gas accumulation, but the horizontally curved-enlarged borehole is less likely to cause gas accumulation; When the fluid flows through the horizontal enlarged diameter section, the pressure will increase and the pressure flowing out of the expansion section will decrease, and the faster the flow velocity, the greater the pressure in the expanding section.

In recent years, exploring and developing oil and gas continuously expands into high-temperature environments, such as the Gulf of Mexico, North Sea, South China Sea, etc. Development of a high-temperature oil field from a platform always requires directional wells or extended reach wells (ERWs) departing from a central cluster to their targets at different depth of water in various azimuth. When drilling wells in high temperature formations, there is commonly associated with a suite of wellbore instability problems that are not normally encountered in onshore and normal temperature formations drilling. These problems are usually related to the presence of typically weak overburden sediments, unconsolidated formations, a small sedimentary coverage above the reservoir, and a great temperature difference between the drilling fluid and formation at the bottom hole In the past decades, a number of studies have been conducted to study the wellbore stability. However, few of the models are specific for wellbore stability of the inclined high temperature wellbores. In this work, an inclined wellbore stability model for high temperature formations is developed. The numerical method of the model is also provided. The study shows that drilling along the direction of minimum horizontal in-situ stress is safer than drilling in other directions, and the wellbore with a high inclination poses more risk of wellbore instability than the wellbore with a low inclination. It also shows that both of the wellbore collapse pressure gradients and wellbore fracture pressure gradients will increase as the temperature of borehole rises, and the fracture pressure is more sensitive to temperature. The model provides a practical tool to predict the stability of inclined wellbores for high temperature formations.

Reaming while drilling (RWD) is a drilling technique that uses a reamer and a pilot bit to expand the size of an open hole segment to be larger than the inner diameter of an upper casing string while fully drilling, especially in deep wells. This technique reduces the number of trips and is highly efficient and widely used in deep wells, ultra-deep wells, small clearance wells, and side-drilling and complex well conditions. However, in the actual operation process, the mismatching between the pilot bit and reamer often leads to slippage, string vibration, and low-quality borehole.In this paper, based on the mechanical specific energy model and the RWD weight distribution model, combined with the drilling weight, torque, and formation confined compressive strength at the interface of the pilot bit and reamer, a real-time rate of penetration (ROP) prediction model suitable for RWD is derived. Through the analysis of the downhole condition of the RWD operation, reasonable drilling parameters are determined and a set of real-time RWD performance prediction and optimization algorithm is proposed.Studies show that during the RWD operation, the size of the pilot bit and reamer and the shape of the cutter have an enormous influence on ROP. When drilling in different formations, the excellent cooperation among the pilot bit, reamer, and formation is the key to improve ROP and bottom hole assembly stability. How to optimize the bit and reamer to drill with the same ROP and predict the ROP is the focus of this paper.Field logging data test the ROP prediction model and real-time optimization method, and the results indicate that the ROP prediction model has high precision, small error, and high timeliness, which can fully meet the requirements of field engineering. This model can guide the selection of the bit, reamer, and drilling parameters in RWD, which is of considerable significance to RWD.

Split sleeve hole cold extrusion strengthening technology is one of the most commonly used fatigue resistance technology for metal structures. The residual stress field of the hole cold extrusion strengthening structure needs to be analysed, which is an important part of the fatigue life study. Finite element analysis for the 7075 aluminum alloy cold extrusion strengthening plate is carried out in this paper. The effects of split sleeve and reaming process are considered in the analysis process, and the residual stress field at the hole edge is obtained. The numerical results are verified by the experimental results, which show that the two are in good agreement. It is show that the residual stress is the compressive stress near the extrusion hole while the tensile stress far away from the extrusion hole. Additionally, the compressive stress value is the largest in the middle layer, the smallest in the squeeze layer, and the value in the extrude layer is between the two.

We exploit nanoscale mechanically induced switching of an artificially layered ferroelectric material, used as an active substrate, to achieve the local manipulation of the electrical transport properties of graphene. In Graphene Ferroelectric Field Effect Transistors (GFeFETs), the graphene channel's charge state is controlled by an underlying ferroelectric layer. The tip of an atomic force microscope (AFM) can be used to mechanically 'write' nanoscale regions of the graphene channel and 'read' off the modulation in the transport behavior. The written features associated with the switching of ferroelectric domains remain polarized until an electrical reset operation is carried out. Our result provides a method for flexible and reversible nano-scale manipulation of the transport properties of a broad class of 2D materials.

Separating the unit cell of YBa2Cu3O7-δ into perovskite and rock salt blocks and considering the interaction between the two blocks, a computer program has been developed to calculate the interaction called combinative energy, between the blocks. The combinative energy in YBa2Cu3O7-δ with different δ value from 0.07 to 0.62 has been calculated. A close relationship between the superconducting transition temperature and the combinative energy in YBa2Cu3O7-δ has been established, and the change of the combinative energy found to be closely related to the transformation from orthorhombic I to II. It is believed that the interaction between the two blocks in the unit cell is of great importance to the superconductivity in YBa2Cu3O7-δ.

Calculation of cohesive energy on Hg-system superconductors HgBa2CuOy(1201), HgBa2CaCu2Oy(1212), HgBa2 Ca2Cu3Oy(1223), HgBa2Ca3Cu4Oy(1234), and HgBa2Ca4Cu5Oy(1245) has been made. A program was developed to calculate the combinative energy between Cu-O planes and remaining parts, and between blocks in the superconductors. The result indicates that if the cell is considered as the two blocks combined together, a close relationship among the combinative energy of the two blocks, the value of Tc, and the number of the Cu-O planes in the Hg-system superconductors is established. The result gives a new way to understand the change of the value of Tc as the number of the Cu-O planes. In contrast, the combinative energy between the Cu-O planes and the remains got from the method separating all the Cu-O planes from the cell and leaving some discrete remaining parts does not show any relationship with the value of Tc. This means that considering the cell as the two blocks in more reasonable, and the interaction between the two blocks plays an important role in superconductivity.