Effects of WC-17Co Coating Combined with Shot Peening Treatment on Fatigue Behaviors of TC21 Titanium Alloy

The improvement and mechanism of the fatigue resistance of TC21 high-strength titanium alloy with a high velocity oxygen fuel (HVOF) sprayed WC-17Co coating was investigated. X-ray diffraction (XRD) and the corresponding stress measurement instrument, a surface roughness tester, a micro-hardness tester, and a scanning electron microscope (SEM) were used to determine the properties of the HVOF WC-17Co coating with or without shot peening. The fatigue behavior of the TC21 titanium alloy with or without the WC-17Co coating was determined by using a rotating bending fatigue testing machine. The results revealed that the polished HVOF sprayed WC-17Co coating had almost the same fatigue resistance as the TC21 titanium alloy substrate. This resulted from the polishing-induced residual surface compressive stress and a decrease in the stress concentration on the surface of the coating. Moderate-intensity shot peening of the polished WC-17Co coatings resulted in significant improvement of the fatigue resistance of the alloy. Furthermore, the fatigue life was substantially higher than that of the substrate, owing to the deep distribution of residual stress and high compressive stress induced by shot peening. The improved surface toughness of the coating can effectively delay the initiation of fatigue crack propagation

An Image Recognition Method for Coal Gangue Based on ASGS-CWOA and BP Neural Network

To improve the recognition accuracy of coal gangue images with the back propagation (BP) neural network, a coal gangue image recognition method based on BP neural network and ASGS-CWOA (ASGS-CWOA-BP) was proposed, which makes two key contributions. Firstly, a new feature extraction method for the unique features of coal and gangue images is proposed, known as “Encircle–City Feature”. Additionally, a method that applied ASGS-CWOA to optimize the parameters of the BP neural network was introduced to address to the issue of its low accuracy in coal gangue image recognition, and a BP neural network with a simple structure and reduced computational consumption was designed. The experimental results showed that the proposed method outperformed the other six comparison methods, with recognition of 95.47% and 94.37% in the training set and the test set, respectively, showing good symmetry

An Image Recognition Method for Coal Gangue Based on ASGS-CWOA and BP Neural Network

To improve the recognition accuracy of coal gangue images with the back propagation (BP) neural network, a coal gangue image recognition method based on BP neural network and ASGS-CWOA (ASGS-CWOA-BP) was proposed, which makes two key contributions. Firstly, a new feature extraction method for the unique features of coal and gangue images is proposed, known as “Encircle–City Feature”. Additionally, a method that applied ASGS-CWOA to optimize the parameters of the BP neural network was introduced to address to the issue of its low accuracy in coal gangue image recognition, and a BP neural network with a simple structure and reduced computational consumption was designed. The experimental results showed that the proposed method outperformed the other six comparison methods, with recognition of 95.47% and 94.37% in the training set and the test set, respectively, showing good symmetry

cooperative concept map based on cognitive model for visual analysis

China Computer Federation; ACM SIGCHI CHINA; Chinese Academy of Sciences, Institute of SoftwareThe ability to recognize users and their intention during the visual analysis process is important to interact intelligently and effortlessly in a cooperative environment. In this paper, we present the framework for creating and modifying a concept map that allows analysts to collaborate and utilize live collection of enterprise data in a visual interface. Based on modeling users and tasks in visual analysis, a user model supporting collaborative analysis is given. Furthermore, we propose the algorithm of concept map layout to facilitate the visual analysis. The interface presents the analyst with the dashboard configuration of certain data that users deems relevant, provides tools to facilitate the decision making process. Finally, we apply it to a collaborative visual decision support system. Experimental results show that it enhances the accessibility and the individualization of collaborative concept map for configuring enterprise data and helps to enhance user experience during the visual analysis process. Copyright © 2010 ACM

Impact of water on miscibility characteristics of the CO2/n-hexadecane system using the pendant drop shape analysis method

Miscible CO2 flooding has shown bright prospects for improving oil recovery from unconventional reservoirs as well as for storing greenhouse gas in underground formations. Although the favorable water presence effect has been reported in the near miscible CO2 flooding practices, there is still a lack of target research works on the impact of water on the miscibility characteristics of the oil/gas systems. Therefore in this paper, the effect of water presence on the Minimum Miscibility Pressure (MMP) of the CO2/n-Hexadecane (n-C16H34) system is experimentally investigated based on the Oil Droplet Volume Measurement (ODVM) method. By pre-saturating CO2 with water in the high-pressure high-temperature cell, the water component is introduced at the CO2/oil interface. Measurement results show the water presence could result in lower MMPs of the CO2/oil system. Under five temperature levels of 40 °C, 51 °C, 61 °C, 72 °C, and 82 °C, the water presence decreases the MMPs of the CO2/n-C16H34 system from 8.2 to 7.8 MPa, from 9.6 to 8.8 MPa, from 11.6 to 10.2 MPa, from 13.0 MPa to 12.2 MPa and from 14.6 MPa to 13.2 MPa respectively. Thermodynamic calculations provide consistent results as the experimental observations, indicating the main mechanism behind the lower MMPs of the water presence CO2/oil system could be the decreased CO2 molar fraction in the water presence system. This research is expected to provide an innovative viewpoint to understand the water presence effect in the CO2 flooding processes

Effect of Cryogenic Treatment on Internal Residual Stresses of Hydrogen-Resistant Steel

To reduce the influence of internal residual stress on the processing deformation of thin-walled hydrogen-resistant steel components, combined aging cryogenic and high-temperature treatment was used to eliminate the residual stress, and the effect of cryogenic process parameters on the initial residual stress of the specimens was compared and analyzed based on the contour method. X-ray diffraction, electron backscatter diffraction, and transmission electron microscopy were used to research the mechanism of the effect of cryogenic treatment on the internal residual stress of the specimen. After forging, the internal residual stress distribution of the hydrogen-resistant steel specimens without aging was characterized by tensile stress on the core and compressive stress on both sides, with a stress amplitude of −350–270 MPa. After compound treatment of −130 °C for 10 h and 350 °C for 2 h, the internal residual stress distribution remained unchanged, and the stresses decreased to −150–100 MPa. The internal residual stresses were reduced by 57–63% compared with the untreated specimens. The cryogenic treatment did not cause phase transformation and carbide precipitation of the hydrogen-resistant steel material. Instead, grain refinement and dislocation density depletion were the main reasons for the reduction in internal residual stresses in the specimens

Effects of Plasma ZrN Metallurgy and Shot Peening Duplex Treatment on Fretting Wear and Fretting Fatigue Behavior of Ti6Al4V Alloy

A metallurgical zirconium nitride (ZrN) layer was fabricated using glow metallurgy using nitriding with zirconiuming prior treatment of the Ti6Al4V alloy. The microstructure, composition and microhardness of the corresponding layer were studied. The influence of this treatment on fretting wear (FW) and fretting fatigue (FF) behavior of the Ti6Al4V alloy was studied. The composite layer consisted of an 8-μm-thick ZrN compound layer and a 50-μm-thick nitrogen-rich Zr–Ti solid solution layer. The surface microhardness of the composite layer is 1775 HK0.1. A gradient in cross-sectional microhardness distribution exists in the layer. The plasma ZrN metallurgical layer improves the FW resistance of the Ti6Al4V alloy, but reduces the base FF resistance. This occurs because the improvement in surface hardness results in lowering of the toughness and increasing in the notch sensitivity. Compared with shot peening treatment, plasma ZrN metallurgy and shot peening composite treatment improves the FW resistance and enhances the FF resistance of the Ti6Al4V alloy. This is attributed to the introduction of a compressive stress field. The combination of toughness, strength, FW resistance and fatigue resistance enhance the FF resistance for titanium alloy

an adaptive sketching user interface for education system in virtual reality

IEEE Beijing Sect, Shandong Normal Univ, Lanzhou Univ, Xiamen Univ, Henan Univ Technol, Wuhan Univ Technol, E China Normal Univ, Birmingham City Univ, Univ So QueenslandSketching user interface and virtual reality (VR) techniques to education application has become popular, promising to make the teaching and learning experience more natural and efficient for users. The adaptive support can improve the intelligence during the interaction process between user and systems to emphasize the individual needs. In this paper, we present the sketching user interface for geometry teaching and the VR class integrated with the corresponding adaptation support, which meet the requirements for the education application. Furthermore, we analylze the sketch context for adaptive mechanism in the education system with an instance. Finally, a prototype based on the methods above is developed An informal study is also done to show that it enhances the accessibility and individualization during the process of teaching and learning and helps to enhance user experience in human computer interaction