F127 assisted fabrication of Ge/r GO/CNTs nanocomposites with three-dimensional network structure for efficient lithium storage

To solve the volume expansion and poor electrical conductivity of germanium-based anode materials,Ge/rGO/CNTs nanocomposites with three-dimensional network structure are fabricated through the dispersion of polyethylene-polypropylene glycol(F127)and reduction of hydrogen.An interesting phenomenon is discovered that F127 can break GeO_(2)polycrystalline microparticles into 100 nm nanoparticles by only physical interaction,which promotes the uniform dispersion of GeO_(2)in a carbon network structure composed of graphene(rGO)and carbon nanotubes(CNTs).As evaluated as anode material of Lithium-ion batteries,Ge/rGO/CNTs nanocomposites exhibit excellent lithium storage performance.The initial specific capacity is high to 1549.7 mAh/g at 0.2 A/g,and the reversible capacity still retains972.4 mAh/g after 100 cycles.The improved lithium storage performance is attributed to that Ge nanoparticles can effectively slow down the volume expansion during charge and discharge processes,and threedimensional carbon networks can improve electrical conductivity and accelerate lithium-ion transfer of anode materials.

Hot bend assisted gas forming of AA5083 sheet for making V-shaped trough containing deep uneven concavities

Employing low pressurized gas for shaping superplastic metal sheets into complex contours has long been adopted in the aero/auto industries and it is commonly recognized as superplastic forming （SPF）. The most undesired feature of SPF would be an uneven thickness distribution in the final formed part. However, there are techniques that lessen this disadvantage. Low pressurized gas was used to make a V-shaped trough containing deep uneven concavities using superplastic AA5083. The auxiliary yet influential procedure of mechanically hot bending the flat sheet into a V-shape precedes the gas-forming process. In this first quick hot-bending operation, buckling will occur if the depth of bending exceeds a certain level. The degree of buckling and associated contours will affect the thickness distribution as well as the wrinkling location in the gas-formed product. A better thickness distribution is obtainable at the cost of wrinkle formation. Wrinkling can be purposely arranged to achieve better uniform thickness distribution, but it needs to be located outside the trim line of the gas-formed semi-product. Therefore, it is critical to manipulate the hot bending procedure to yield a suitable pre-form allowing a successful sequential gas-forming process.

CO2 assisted steam flooding in late steam flooding in heavy oil reservoirs

To improve the oil recovery and economic efficiency in heavy oil reservoirs in late steam flooding,taking J6 Block of Xinjiang Oilfield as the research object,3D physical modeling experiments of steam flooding,CO2-foam assisted steam flooding,and CO2 assisted steam flooding under different perforation conditions are conducted,and CO2-assisted steam flooding is proposed for reservoirs in the late stage of steam flooding.The experimental results show that after adjusting the perforation in late steam flooding,the CO2 assisted steam flooding formed a lateral expansion of the steam chamber in the middle and lower parts of the injection well and a development mode for the production of overriding gravity oil drainage in the top chamber of the production well;high temperature water,oil,and CO2 formed stable low-viscosity quasi-single-phase emulsified fluid;and CO2 acted as a thermal insulation in the steam chamber at the top,reduced the steam partial pressure inside the steam chamber,and effectively improved the heat efficiency of injected steam.Based on the three-dimensional physical experiments and the developed situation of the J6 block in Xinjiang Oilfield,the CO2 assisted steam flooding for the J6 block was designed.The application showed that the CO2 assisted steam flooding made the oil vapor ratio increase from 0.12 to 0.16 by 34.0%,the oil recovery increase from 16.1%to 21.5%,and the final oil recovery goes up to 66.5%compared to steam flooding after perforation adjustment.

Modeling and Simulation of Laser Assisted Turning of Hard Steels

This research work is focused on simulation of laser assisted turning as a new solution for machining of hard steels. A transient, three-dimensional model was developed to predict the temperature distribution of a rotated cylindrical steel workpiece subjected to a localized heating using a moving Gaussian laser beam. In this regard, a User-Defined Function was created to overcome the problem of a moving Gaussian heat source’ definition. This User-Defined Function was compiled into a finite volume software package (Fluent), where three-dimensional single precision solver was used for analysis. Based on this model, simulation of the surface temperature of 32 mm diameter workpiece of AISI51 50H steel was performed as a function of time at a specific distance behind the laser beam spot, which is corresponding to 30° angle from the laser beam. The simulation results were compared with other published data of the same steel type where a close agreement was obtained. The verified model was used for simulation of laser assisted turning of 20 mm diameter workpiece of AISI D2 tool steel. The cutting depth, behind the laser beam, was set at a distance corresponding to 60° angle from the laser beam for having sufficient access for handling both laser head and cutting tool. This cutting depth was studied as a function of different lasers and machining parameters. The results indicated that the optimum parameters for successful laser-assisted turning process of the concerned steels are 800 W laser power, 5 mm laser beam spot diameter, 20 sec preheating time, 0.8 mm/sec laser scanning speed, 300 rpm rotational speed and 0.8 mm/sec feed rate. These parameters ensure easy/successful cutting of 1 mm depth in one pass without deteriorating the properties of the remaining bulk material. It can be deduced that the developed model might provide a useful tool for online process control of different steel types regardless of their physical properties and geometries.

Research on knowledge reasoning of TCM based on knowledge graphs

With the widespread use of Internet,the amount of data in the field of traditional Chinese medicine(TCM)is growing exponentially.Consequently,there is much attention on the collection of useful knowledge as well as its effective organization and expression.Knowledge graphs have thus emerged,and knowledge reasoning based on this tool has become one of the hot spots of research.This paper first presents a brief introduction to the development of knowledge graphs and knowledge reasoning,and explores the significance of knowledge reasoning.Secondly,the mainstream knowledge reasoning methods,including knowledge reasoning based on traditional rules,knowledge reasoning based on distributed feature representation,and knowledge reasoning based on neural networks are introduced.Then,using stroke as an example,the knowledge reasoning methods are expounded,the principles and characteristics of commonly used knowledge reasoning methods are summarized,and the research and applications of knowledge reasoning techniques in TCM in recent years are sorted out.Finally,we summarize the problems faced in the development of knowledge reasoning in TCM,and put forward the importance of constructing a knowledge reasoning model suitable for the field of TCM.

The Time and Cost Prediction of Tunnel Boring Machine in Tunnelling

Making use of microsoft visual studio. net platform, the assistant decision-making system of tunnel boring machine in tunnelling has been built to predict the time and cost. Computation methods of the performance parameters have been discussed. New time and cost prediction models have been depicted. The multivariate linear regression has been used to make the parameters more precise, which are the key factor to affect the prediction near to the reality.

Intelligent and connected vehicles： Current status and future perspectives

Intelligent connected vehicles(ICVs) are believed to change people's life in the near future by making the transportation safer,cleaner and more comfortable. Although many prototypes of ICVs have been developed to prove the concept of autonomous driving and the feasibility of improving traffic efficiency, there still exists a significant gap before achieving mass production of high-level ICVs. The objective of this study is to present an overview of both the state of the art and future perspectives of key technologies that are needed for future ICVs. It is a challenging task to review all related works and predict their future perspectives, especially for such a complex and interdisciplinary area of research. This article is organized to overview the ICV key technologies by answering three questions: what are the milestones in the history of ICVs; what are the electronic components needed for building an ICV platform; and what are the essential algorithms to enable intelligent driving? To answer the first question, the article has reviewed the history and the development milestones of ICVs. For the second question, the recent technology advances in electrical/electronic architecture, sensors, and actuators are presented. For the third question, the article focuses on the algorithms in decision making, as the perception and control algorithm are covered in the development of sensors and actuators. To achieve correct decision-making, there exist two different approaches: the principle-based approach and data-driven approach. The advantages and limitations of both approaches are explained and analyzed. Currently automotive engineers are concerned more with the vehicle platform technology, whereas the academic researchers prefer to focus on theoretical algorithms. However, only by incorporating elements from both worlds can we accelerate the production of high-level ICVs.