Effect of precipitate evolution on corrosion behavior of friction stir welded joints of AA2060-T8 alloy

Friction stir welding was used to join two AA2060-T8 plates,and then the effect of precipitate evolution on microstructure and corrosion behavior of the joint was investigated.The evolution of precipitates on the top surface of the joint was characterized by scanning electron microscopy and transmission electron microscopy.The corrosion behaviors of different regions in the joint were investigated by an electrochemistry method and an alternating salt spray exposure.The corrosion was mainly dependent on the nature of precipitates in each region of the joint.The shoulder affected zone had the worst corrosion resistance as a result of the re-dissolved ofθ′(Al2Cu),T1(Al2CuLi)andδ′(Al3Li)phases,the formation of intergranular precipitates and precipitate-free zones.However,the thermomechanically affected zone had a slightly improved corrosion resistance because it had no intergranular precipitates.The heat affected zone and base metal had the best corrosion resistance.

新型旋转挤出流变仪

聚合物加工是决定塑料制品最终结构性能的中心环节,其重要的理论基础是聚合物流变学,研究聚合物流变行为的关键仪器是流变仪.但现有流变仪大多基于简化的流动模型,与实际复杂加工条件不符,难有效揭示聚合物在复杂应力场/温度场作用下的流变行为.我们基于前期发明的聚合物管旋转挤出加工技术和装备,研制了新型旋转挤出流变仪,可实现挤出/旋转的不同组合和管内外壁双冷,实施和调控旋转挤出中多种运动模式和应力场及温度场,实时检测挤出/旋转速度、应力、温度场,显示记录有关数据,既可用于研究实际加工复杂条件下聚合物加工流变行为,也可用于制备高性能多功能聚合物微导管.本文综述了新型旋转挤出流变仪的结构特点和原理及其在流变测试与聚合物微导管制备方面的应用.

VR content creation and exploration with deep learning: A survey

Virtual reality(VR)offers an artificial,computer generated simulation of a real life environment.It originated in the 1960 s and has evolved to provide increasing immersion,interactivity,imagination,and intelligence.Because deep learning systems are able to represent and compose information at various levels in a deep hierarchical fashion,they can build very powerful models which leverage large quantities of visual media data.Intelligence of VR methods and applications has been significantly boosted by the recent developments in deep learning techniques.VR content creation and exploration relates to image and video analysis,synthesis and editing,so deep learning methods such as fully convolutional networks and general adversarial networks are widely employed,designed specifically to handle panoramic images and video and virtual 3 D scenes.This article surveys recent research that uses such deep learning methods for VR content creation and exploration.It considers the problems involved,and discusses possible future directions in this active and emerging research area.

Tensile properties and fracture behavior of friction stir welded joints of Fe-32Mn-7Cr-1Mo-0.3N steel at cryogenic temperature

This study investigates the cryogenic tensile properties and fracture behavior of fiction stir welded and post-weld heat-treated joints of 32Mn-7Cr-1Mo-0.3N steel. Cryogenic brittle fracture, which occurred in the as-welded joint, is related to the residual particles that contain tungsten in the joint band structure. Post-weld water toughening resulted in the cryogenic intergranular brittleness of the joint, which is related to the non-equilibrium segregation of solute atoms during the post-weld water toughening. Annealing at 55OC for 30rain can effectively inhibit the cryogenic intergranular brittleness of the post- weld water-toughened joint. The yield strength, ultimate tensile strength, and uniform elongation of the annealed joint are approximately 95%, 87%, and 94% of the corresponding data of the base metal.

A Comprehensive Review of Redirected Walking Techniques:Taxonomy,Methods,and Future Directions

Virtual reality(VR)allows users to explore and experience a computer-simulated virtual environment so that VR users can be immersed in a totally artificial virtual world and interact with arbitrary virtual objects.However,the limited physical tracking space usually restricts the exploration of large virtual spaces,and VR users have to use special locomotion techniques to move from one location to another.Among these techniques,redirected walking(RDW)is one of the most natural locomotion techniques to solve the problem based on near-natural walking experiences.The core idea of the RDW technique is to imperceptibly guide users on virtual paths,which might vary from the paths they physically walk in the real world.In a similar way,some RDW algorithms imperceptibly change the structure and layout of the virtual environment such that the virtual environment fits into the tracking space.In this survey,we first present a taxonomy of existing RDW work.Based on this taxonomy,we compare and analyze both contributions and shortcomings of the existing methods in detail,and find view manipulation methods offer satisfactory visual effect but the experience can be interrupted when users reach the physical boundaries,while virtual environment manipulation methods can provide users with consistent movement but have limited application scenarios.Finally,we discuss possible future research directions,indicating combining artificial intelligence with this area will be effective and intriguing.