| 1 | Numerical study and acceleration of LBM-RANS simulation of turbulent flow显示文摘The coupled models of LBM(Lattice Boltzmann Method) and RANS(Reynolds-Averaged Navier–Stokes) are more practical for the transient simulation of mixing processes at large spatial and temporal scales such as crude oil mixing in large-diameter storage tanks. To keep the efficiency of parallel computation of LBM, the RANS model should also be explicitly solved; whereas to keep the numerical stability the implicit method should be better for RANS model. This article explores the numerical stability of explicit methods in 2D cases on one hand, and on the other hand how to accelerate the computation of the coupled model of LBM and an implicitly solved RANS model in 3D cases. To ensure the numerical stability and meanwhile avoid the use of empirical artificial limitations on turbulent quantities in 2D cases, we investigated the impacts of collision models in LBM(LBGK, MRT)and the numerical schemes for convection terms(WENO, TVD) and production terms(FDM, NEQM) in an explicitly solved standard k–ε model. The combination of MRT and TVD or MRT and NEQM can be screened out for the 2D simulation of backward-facing step flow even at Re = 10~7. This scheme combination, however, may still not guarantee the numerical stability in 3D cases and hence much finer grids are required, which is not suitable for the simulation of industrial-scale processes. Then we proposed a new method to accelerate the coupled model of LBM with RANS(implicitly solved). When implemented on multiple GPUs, this new method can achieve 13.5-fold acceleration relative to the original coupled model and 40-fold acceleration compared to the traditional CFD simulation based on Finite Volume(FV) method accelerated by multiple CPUs. This study provides the basis for the transient flow simulation of larger spatial and temporal scales in industrial applications with LBM–RANS methods. | Shuli Shu Ning Yang | 2018 | Chinese Journal of Chemical Engineering2018，26，1： | 1 |
| 2 | High-throughput sequencing identifies salivary microbiota in Chinese caries-free preschool children with primary dentition显示文摘Objectives:The study aimed at identifying salivary microbiota in caries-free Chinese preschool children using highthroughput sequencing.Methods:Saliva samples were obtained from 35 caries-free preschool children(18 boys and 17 girls)with primary dentition,and 16 S ribosomal DNA(r DNA)V3–V4 hypervariable regions of the microorganisms were analyzed using Illumina MiSeq.Results:At 97%similarity level,all of these reads were clustered into 334 operational taxonomic units(OTUs).Among these,five phyla(Firmicutes,Proteobacteria,Actinobacteria,Bacteroidetes,and Candidate division TM7)and13 genera(Streptococcus,Rothia,Granulicatella,Prevotella,Enterobacter,Veillonella,Neisseria,Staphylococcus,Janthinobacterium,Pseudomonas,Brevundimonas,Devosia,and Gemella)were the most dominant,constituting 99.4%and 89.9%of the salivary microbiota,respectively.The core salivary microbiome comprised nine genera(Actinomyces,Capnocytophaga,Gemella,Granulicatella,Lachnoanaerobaculum,Neisseria,Porphyromonas,Rothia,and Streptococcus).Analysis of microbial diversity and community structure revealed a similar pattern between male and female subjects.The difference in microbial community composition between them was mainly attributed to Neisseria(P=0.023).Furthermore,functional prediction revealed that the most abundant genes were related to amino acid transport and metabolism.Conclusions:Our results revealed the diversity and composition of salivary microbiota in caries-free preschool children,with little difference between male and female subjects.Identity of the core microbiome,coupled with prediction of gene function,deepens our understanding of oral microbiota in cariesfree populations and provides basic information for associating salivary microecology and oral health. | Lei XU Zhifang WU Yuan WANG Sa WANG Chang SHU Zhuhui DUAN Shuli DENG | 2021 | Journal of Zhejiang University-Science B(Biomedicine & Biotechnology)2021，22，4： | 0 |
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