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      저자 : Quanyong Wang (검색결과 2 건)
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        Superwetting TiO2-decorated single-walled carbon nanotube composite membrane for highly efficient oil-in-water emulsion separation

        Yahong Sun,Ruiguang Zhao,Quanyong Wang,Yuanyuan Zheng,Gongrang Li,Dejun Sun,Tao Wu,Yujiang Li 한국화학공학회 2020 Korean Journal of Chemical Engineering Vol.37 No.11

        With the advantages of one-dimensional hollow structure, high porosity and prominent mechanical strength, single-walled carbon nanotubes (SWCNTs) have been extensively utilized to improve conventional filtration membranes for oil/water separation. Their intrinsic hydrophobicity, however, adversely affects the anti-fouling performance of the SWCNT membrane. Herein, a super-hydrophilic and underwater super-oleophobic hierarchical modified membrane with enhanced permeability and anti-fouling property was fabricated using the vacuum-assisted filtration technique by synergistically assembling SWCNTs and titanium dioxide (TiO2) nanoparticles on a cellulose acetate membrane. Highly dispersed SWCNTs were obtained by carboxylating treatment of agglomerate SWCNTs. The controlled stacking of SWCNTs fibers and a controllable amount of TiO2 rendered a modified membrane with high porosity and hierarchical structure, leading to an ultrahigh water flux up to 4,777.07 L·m2·h1, and excellent separation performance with efficiency greater than 99.47%. Most importantly, the membrane exhibited excellent anti-fouling ability during ten cycles with the aid of the super-wetting property of TiO2 nanoparticles. The results indicated that coating TiO2 nanoparticles on SWCNTs modified the surface topography of the obtained SWCNT/TiO2 membrane, which improved hydrophilicity, permeability and anti-fouling property, manifesting attractive potential applications in oil/water separation.

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        A joint probability distribution model of directional extreme wind speeds based on the t-Copula function

        Quan, Yong,Wang, Jingcheng,Gu, Ming Techno-Press 2017 Wind and Structures, An International Journal (WAS Vol.25 No.3

        The probabilistic information of directional extreme wind speeds is important for precisely estimating the design wind loads on structures. A new joint probability distribution model of directional extreme wind speeds is established based on observed wind-speed data using multivariate extreme value theory with the t-Copula function in the present study. At first, the theoretical deficiencies of the Gaussian-Copula and Gumbel-Copula models proposed by previous researchers for the joint probability distribution of directional extreme wind speeds are analysed. Then, the t-Copula model is adopted to solve this deficiency. Next, these three types of Copula models are discussed and evaluated with Spearman's rho, the parametric bootstrap test and the selection criteria based on the empirical Copula. Finally, the extreme wind speeds for a given return period are predicted by the t-Copula model with observed wind-speed records from several areas and the influence of dependence among directional extreme wind speeds on the predicted results is discussed.

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