Simulation of T-junctions two phases separation characteristics

When the two phases pass through the bifurcated pipe of the T-shaped pipe, the ratio of the two-phase of the main pipe and the branch pipe generally changes. This paper uses FLUENT to simulate the separation characteristics of a two-phase mixture of high-viscosity oil and water in a T-pipe, and studies the effect of different structures (the height of the branch pipe, the number of branch pipes, and the spacing of the branch pipes) on the separation characteristics. The results show that the number of branch pipes and the spacing of the branch pipes have a great influence on the separation efficiency of the two phases

Mechanism design and kinematics analysis of multifunctional waist rehabilitation bed

A multifunctional waist rehabilitation bed is designed for the traction therapy of human spine and gait rehabilitation training. The rehabilitation bed has four degrees of freedom, the rotation in the x, y, and z axis, and the movement in the z axis, which realizes traction treatment of lumbar spine rotation around coronal axis, vertical axis, sagittal axis and gait rehabilitation training. Considering the stability and safety during the rehabilitation process, the kinematic model of coronal-axis-rotation part, vertical-axis-rotation part and rehabilitation bed are established. Using MATLAB, the model and numerical simulation were carried out to obtain the curve of joint change when the waist rehabilitation bed was used for different functions, which verifies the effectiveness of the mechanism

Organic Field-Effect Transistor: Device Physics, Materials, and Process

Organic field-effect transistors have received much attention in the area of low cost, large area, flexible, and printable electronic devices. Lots of efforts have been devoted to achieve comparable device performance with high charge carrier mobility and good air stability. Meanwhile, in order to reduce the fabrication costs, simple fabrication conditions such as the printing techniques have been frequently used. Apart from device optimization, developing novel organic semiconductor materials and using thin-film alignment techniques are other ways to achieve high-performance devices and functional device applications. It is expected that by combining proper organic semiconductor materials and appropriate fabrication techniques, high-performance devices for various applications could be obtained. In this chapter, the organic field-effect transistor in terms of device physics, organic materials, device process, and various thin-film alignment techniques will be discussed

Attitude Quantifier Based Possibility Distribution Generation Method for Hesitant Fuzzy Linguistic Group Decision Making

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The possibility distribution-based approach is one of the powerful tools available to manage hesitant fuzzy linguistic term set (HFLTS) information. However, existing possibility distribution studies have not considered the experts’ satisfied preference for HFLTSs in the process of generating the possibility distribution. This paper aims at filling this research gap. To achieve this goal, a novel possibility distribution generation method based on the concept of linguistic quantifier is proposed. This is accomplished by defining a new attitude linguistic quantifier, which is supported with theoretical results to analyze the relationship between the proposed attitude linguistic quantifier with the original linguistic quantifier, attitude indices and the expected linguistic term. The new possibility distribution generation method is proved to be (1) more general than the two main existing approaches, which are particular cases for specific linguistic quantifiers; and (2) useful to implement the concept of soft majority in the resolution process of the decision making situation. Additionally, a new two stages feedback mechanism of attitude adjustment and assessment adjustment is devised to guarantee the convergence of the consensus reaching process. Finally, a framework of group decision making with HFLTSs information is presented and an illustrative example is conducted to verify the proposed method

Microstructure Engineering of Metal-Halide Perovskite Films for Efficient Solar Cells

Photovoltaic (PV) devices with metal-halide perovskite films, namely perovskite solar cells, have become a rapidly rising star due to low cost of raw materials, simple solution processability, and swiftly increased power conversion efficiency (PCE). The PCEs so far certified have gone beyond 22% for perovskite solar cells and 23.6% for tandem devices with single crystalline silicon solar cells, which offer a promising PV technology for practical applications. In principle, performance of perovskite solar cells are largely dominated by the optoelectronic properties and stability of metal-halide perovskite films, which are determined by the microstructure features of the films in turns. In this chapter, we will describe the recently developed strategies on microstructure engineering of metal-halide perovskite films for efficient perovskite solar cells

How can sustainable public transport be improved? A traffic sign recognition approach using convolutional neural network

Sustainable public transport is an important factor to boost urban economic development, and it is also an important part of building a low-carbon environmental society. The application of driverless technology in public transport injects new impetus into its sustainable development. Road traffic sign recognition is the key technology of driverless public transport. It is particularly important to adopt innovative algorithms to optimize the accuracy of traffic sign recognition and build sustainable public transport. Therefore, this paper proposes a convolutional neural network (CNN) based on k-means to optimize the accuracy of traffic sign recognition, and it proposes a sparse maximum CNN to identify difficult traffic signs through hierarchical classification. In the rough classification stage, k-means CNN is used to extract features, and improved support vector machine (SVM) is used for classification. Then, in the fine classification stage, sparse maximum CNN is used for classification. The research results show that the algorithm improves the accuracy of traffic sign recognition more comprehensively and effectively, and it can be effectively applied in unmanned driving technology, which will also bring new breakthroughs for the sustainable development of public transport