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| 1 | Recent progresses on designing and manufacturing of bulk refractory alloys with high performances based on controlling interfaces显示文摘Refractory alloys such as tungsten and molybdenum based alloys with high strength,thermal/electrical conductivity,low coefficient of thermal expansion and excellent creep resistances are highly desirable for applications in nuclear facilities,critical components in aerospace and defense components.However,the serious embrittlement limits the engineering usability of some refractory alloys.A lot of research results indicate that the performances of refractory alloys are closely related to the physical/chemical status,such as the interface dimension,interface type,interface composition of their grain boundaries(GBs),phase boundaries(PBs)and other interface features.This paper reviewed the recent progress of simulations and experiments on interface design strategies that achieve high performance refractory alloys.These strategies include GB interface purifying/strengthening,PB interface strengthening and PB/GB synergistic strengthening.Great details are provided on the design/fabrication strategy such as GB interface controlling,PB interface controlling and synergistic control of multi-scaled interfaces.The corresponding performances such as the mechanical property,thermal conductivity,thermal load resistance,thermal stability,irradiation resistance,and oxidation resistance are reviewed in the aspect to the effect of interfaces.In addition,the relationships between these interfaces and material properties are discussed.Finally,future developments and potential new research directions for refractory alloys are proposed. | T.Zhang H.W.Deng Z.M.Xie R.Liu J.F.Yang C.S.Liu X.P.Wang Q.F.Fang Y.Xiong | 2020 | Journal of Materials Science & Technology2020，52，17： | 6 |
| 2 | OpenIFEM:A High Performance Modular Open-Source Software of the Immersed Finite Element Method for Fluid-Structure Interactions显示文摘We present a high performance modularly-built open-source software-OpenIFEM.OpenIFEM is a C++implementation of the modified immersed finite element method(mIFEM)to solve fluid-structure interaction(FSI)problems.This software is modularly built to perform multiple tasks including fluid dynamics(incompressible and slightly compressible fluid models),linear and nonlinear solid mechanics,and fully coupled fluid-structure interactions.Most of open-source software packages are restricted to certain discretization methods;some are under-tested,under-documented,and lack modularity as well as extensibility.OpenIFEM is designed and built to include a set of generic classes for users to adapt so that any fluid and solid solvers can be coupled through the FSI algorithm.In addition,the package utilizes well-developed and tested libraries.It also comes with standard test cases that serve as software and algorithm validation.The software can be built on cross-platform,i.e.,Linux,Windows,and Mac OS,using CMake.Efficient parallelization is also implemented for high-performance computing for large-sized problems.OpenIFEM is documented using Doxygen and publicly available to download on GitHub.It is expected to benefit the future development of FSI algorithms and be applied to a variety of FSI applications. | Jie Cheng Feimi Yu Lucy T.Zhang | 2019 | Computer Modeling in Engineering & Sciences2019，，4： | 2 |
| 3 | Ability to detect and locate gross errors on DEM matching algorithm显示文摘Digital elevation model(DEM)matching techniques have been extended to DEM deformation detection by substituting a robust estimator for the least squares estimator,in which terrain changes are treated as gross errors.However,all existing methods only emphasise their deformation detecting ability,and neglect another important aspect:only when the gross error can be detected and located,can this system be useful.This paper employs the gross error judgement matrix as a tool to make an in-depth analysis of this problem.The theoretical analyses and experimental results show that observations in the DEM matching algorithm in real applications have the ability to detect and locate gross errors.Therefore,treating the terrain changes as gross errors is theoretically feasible,allowing real DEM deformations to be detected by employing a surface matching technique. | T.Zhang M.Cen Z.Ren R.Yang Y.Feng J.Zhu | 2010 | International Journal of Digital Earth2010，3，1： | 2 |
| 4 | Simulation of vessel tissue remodeling with residual stress:an application to in-stent restenosis显示文摘We present a numerical procedure to model the artery wall remodeling stimulated by stenting considering varying degree of residual stresses.This framework sets up biological remodeling with the existence of residual stress.Previous studies suggest that the residual stress originates from the growth and remodeling of the premature tissue.Meanwhile,it is known that tissue remodeling can happen under mechanical loading.However,none of the existing research studies the impact of residual stress on the mechanical-driven growth of biomaterials.To fill this gap,we build a numerical framework that couples the residual stress with a growth model,and examine its impact on tissue remodeling.The proposed approach is applied to in-stent restenosis,where the tissue remodeling process is modeled with finite element method,and the residual stress is generated geometrically using open angle method.The result shows that residual stress reverses the radial distribution of stress concentration,which is ameliorated by tissue remodeling.The thickening of vessel wall tends to increase with residual stress,which links to more severe in-stent restenosis.The results demonstrate the important interplay between residual stress and tissue remodeling.The findings suggest that residual stress should be considered in the future simulation of tissue remodeling. | Jie Cheng Lucy T.Zhang | 2019 | International Journal of Smart and Nano Materials2019，10，1： | 1 |
| 5 | 查看详情显示文摘 | Y Fan Y.Q.Feng J T.Zhang | | 0，，： | 1 |
| 6 | Randomized clinical trial of intravenous soybean oil alone versus soybean oil plus fish oil emulsion after gastrointestinal cancer surgery显示文摘 | Z. M.Jiang D. W.Wilmore X. R.Wang J. M.Wei Z. T.Zhang Z. Y.Gu S.Wang S. M.Han H.Jiang K.Yu | 2010 | Br J Surg2010，，6： | 1 |
| 7 | COX‐2 mRNA expression in esophageal squamous cell carcinoma (ESCC) and effect by NSAID显示文摘 | X.Liu P.Li S.‐T.Zhang H.You J.‐D.Jia Z.‐L.Yu | 2007 | Diseases of the Esophagus2007，，1： | 1 |
| 8 | 查看详情显示文摘 | P.Cheng C.Song T.Zhang Y.Zhang Y.Wang J.F.Jia J.Wang Y.Wang B.F.Zhu X.Chen X.C.Ma K.He L.Wang X.Dai Z.Fang X.C.Xie X.L.Qi C.X.Liu S.-C.Zhang and Q.K.Xue | | 0，，07： | 1 |
| 9 | 查看详情显示文摘 | H.T.He G.Wang T.Zhang I.-K.Sou G.K.L.Wong and J.N.Wang | | 0，，16： | 1 |
| 10 | 查看详情显示文摘 | P.Cheng C.Song T.Zhang Y.Zhang Y.Wang J.F.Jia J.Wang Y.Wang B.F.Zhu X.Chen X.C.Ma K.He L.Wang X.Dai Z.Fang X.C.Xie X.L.Qi C.X.Liu S.C.Zhang and Q.K.Xue | | 0，，： | 1 |
| 11 | Politically Connected CEOs,Corporate Governance and Post-IPO Performance of China's Newly Partially Privatized Firms显示文摘 | Fan J.P.H T.J.Wong T.Zhang | | 0，，02： | 1 |
| 12 | Bulk glassy Ni(Co-)Nb-Ti-Zr alloys with high corrosion resistance and high strength显示文摘 | S.Pang T.Zhang K.Asami A.Inoue | | 0，，： | 1 |
| 13 | Perivascular spaces in the basal ganglia of the human brain: their relationship to lacunes显示文摘 | H.POLLOCK M.HUTCHINGS R. O.WELLER E‐T.ZHANG | 2002 | Journal of Anatomy2002，，3： | 1 |
| 14 | Fiscal Decentralization,Public Spending and Economic Growth in China显示文摘 | T.Zhang H.Zhou | | 0，，02： | 1 |
| 15 | Statistical behavior and consistency of classification methods based on convex risk minimization显示文摘 | T.Zhang | | 0，，： | 1 |
| 16 | Multiple Positive Solutions for Second-Order p-Laplacian Dynamic Equations with Integral Bounda-ry Conditions显示文摘 | Y.k.Li T.Zhang | | 0，，8676： | 1 |
| 17 | 查看详情显示文摘 | P.Cheng C.L.Song T.Zhang Y.Y.Zhang Y.L.Wang J.F.Jia J.Wang Y.Y.Wang B.F.Zhu X.Chen X.C.Ma K.He L.L.Wang X.Dai Z.Fang X.C.Xie X.L.Qi C.X.Liu S.C.Zhang and Q.K.Xue | | 0，，： | 1 |
| 18 | 查看详情显示文摘 | G.Wang X.G.Zhu Y.Y.Sun Y.Y.Li T.Zhang J.Wen X.Chen K.He L.L.Wang X.C.Ma J.F.Jia S.B.Zhang and Q.K.Xue | | 0，，： | 1 |
| 19 | Sparse online learning via truncated gradient显示文摘 | J.Langford L Li T.Zhang | | 0，，： | 1 |
| 20 | 查看详情显示文摘 | T.Zhang P.Cheng X.Chen J.F.Jia X.C.Ma K.He L.L.Wang H.J.Zhang X.Dai Z.Fang X.C.Xie and Q.K.Xue | | 0，，26： | 1 |
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