To improve the tribocorrosion resistance of oil drill pipes used in deep-sea drilling,a Ti-based composite coating was successfully fabricated by laser direct energy deposition technology on the TC4 titanium alloy sur...To improve the tribocorrosion resistance of oil drill pipes used in deep-sea drilling,a Ti-based composite coating was successfully fabricated by laser direct energy deposition technology on the TC4 titanium alloy surface.The microstructure analysis showed that a new heterogeneous structure of multistage strength-ening phases(micron-sized TiN phases and nano-sized TiB phases)distributed on theβmatrix(soft Cu-rich phases and hard Mo-rich phases)was formed,and the size ofβgrain was refined to 2μm with the content of Cu higher than 12 wt.%.The microhardness of the composite coating was increased to more than 700 HV_(0.2)due to the solution strengthening of Mo elements and the formation of hard TiN phases.At the same time,the fracture toughness of 12Cu composite coating was significantly increased to 8.37 MPa m^(1/2),which was attributed to the combined effect of grain refining,high-density dislocations in Cu-rich phases,and nanoscale TiB phases.The synergistic enhancement of hardness and toughness of 12Cu composite coating promoted the generation of titano-molybdenum-copper composite oxide film on the worn surface,and the tribocorrosion resistance increased more than 7 times compared with TC4.展开更多
Ant colony optimization(ACO)is a random search algorithm based on probability calculation.However,the uninformed search strategy has a slow convergence speed.The Bayesian algorithm uses the historical information of t...Ant colony optimization(ACO)is a random search algorithm based on probability calculation.However,the uninformed search strategy has a slow convergence speed.The Bayesian algorithm uses the historical information of the searched point to determine the next search point during the search process,reducing the uncertainty in the random search process.Due to the ability of the Bayesian algorithm to reduce uncertainty,a Bayesian ACO algorithm is proposed in this paper to increase the convergence speed of the conventional ACO algorithm for image edge detection.In addition,this paper has the following two innovations on the basis of the classical algorithm,one of which is to add random perturbations after completing the pheromone update.The second is the use of adaptive pheromone heuristics.Experimental results illustrate that the proposed Bayesian ACO algorithm has faster convergence and higher precision and recall than the traditional ant colony algorithm,due to the improvement of the pheromone utilization rate.Moreover,Bayesian ACO algorithm outperforms the other comparative methods in edge detection task.展开更多
在全球变暖背景下,维持、提高和稳定土壤碳固存是助力“碳达峰、碳中和”(简称“双碳”)目标实现的重要手段。旨在为土壤碳固存的实践应用和全球气候变化的应对提供重要科学支持,以Web of Science核心合集数据库中收录的2107篇土壤碳固...在全球变暖背景下,维持、提高和稳定土壤碳固存是助力“碳达峰、碳中和”(简称“双碳”)目标实现的重要手段。旨在为土壤碳固存的实践应用和全球气候变化的应对提供重要科学支持,以Web of Science核心合集数据库中收录的2107篇土壤碳固存相关论文为数据源,通过文献计量工具VOSviewer和CiteSpace从合作网络、文献共被引、关键词等角度进行可视化计量分析。结果表明,2002年以来,土壤碳固存研究领域的发文数量不断增长,尤其是2016年以后相关文献快速增加。领域内高产国家主要集中于中国、美国和澳大利亚,中国总发文量第一,美国的国际影响力最大(中心度最高),并且中国与美国之间建立了密切的合作关系;研究机构发文数量以中国科学院最多,排名前10的机构中的5所(中国科学院、西北农林科技大学、中国农业科学院、中国农业大学、南京农业大学)均来自中国;目前形成了以LAL RATTAN、SMITH PETE、ZHAO Xin、TIAN Xiaohong和XU Minggang为核心的紧密学术团体。近年来,研究热点主要集中在“土壤微生物在土壤碳循环中的作用”“秸秆还田等农业实践对碳储存的影响”“有机碳转化效率”等。未来应加强不同管理措施对土壤碳固存的影响、土壤微生物与碳循环关系、改进土壤碳循环模型等方面的研究。展开更多
基金supported by the National Natural Science Foundation of China-Shandong Joint Fund for Marine Science Research Centers(CN)(No.U2106216)the National Natural Science Foundation of China(Nos.51971121 and 52331004)+4 种基金the Natural Science Foundation of Shandong Province(No.ZR2022ZD12)the Major-Special Science and Technology Projects in Shandong Province(No.2023ZLGX05)the Qingdao Marine Science and Technology Innovation Project(No.22-3-3-hygg-27-hy)the Key Research and Development Program of Shandong Province(No.2020CXGC010305)the Fundamental Research Funds for the Central Universities(Nos.202261105,202141027,202241012,202262011).
文摘To improve the tribocorrosion resistance of oil drill pipes used in deep-sea drilling,a Ti-based composite coating was successfully fabricated by laser direct energy deposition technology on the TC4 titanium alloy surface.The microstructure analysis showed that a new heterogeneous structure of multistage strength-ening phases(micron-sized TiN phases and nano-sized TiB phases)distributed on theβmatrix(soft Cu-rich phases and hard Mo-rich phases)was formed,and the size ofβgrain was refined to 2μm with the content of Cu higher than 12 wt.%.The microhardness of the composite coating was increased to more than 700 HV_(0.2)due to the solution strengthening of Mo elements and the formation of hard TiN phases.At the same time,the fracture toughness of 12Cu composite coating was significantly increased to 8.37 MPa m^(1/2),which was attributed to the combined effect of grain refining,high-density dislocations in Cu-rich phases,and nanoscale TiB phases.The synergistic enhancement of hardness and toughness of 12Cu composite coating promoted the generation of titano-molybdenum-copper composite oxide film on the worn surface,and the tribocorrosion resistance increased more than 7 times compared with TC4.
基金supported by the National Natural Science Foundation of China(62276055).
文摘Ant colony optimization(ACO)is a random search algorithm based on probability calculation.However,the uninformed search strategy has a slow convergence speed.The Bayesian algorithm uses the historical information of the searched point to determine the next search point during the search process,reducing the uncertainty in the random search process.Due to the ability of the Bayesian algorithm to reduce uncertainty,a Bayesian ACO algorithm is proposed in this paper to increase the convergence speed of the conventional ACO algorithm for image edge detection.In addition,this paper has the following two innovations on the basis of the classical algorithm,one of which is to add random perturbations after completing the pheromone update.The second is the use of adaptive pheromone heuristics.Experimental results illustrate that the proposed Bayesian ACO algorithm has faster convergence and higher precision and recall than the traditional ant colony algorithm,due to the improvement of the pheromone utilization rate.Moreover,Bayesian ACO algorithm outperforms the other comparative methods in edge detection task.
