The gas leakage dynamic flow in nanoporous silica aerogel under different pressure

This paper was presented at the 4th Micro and Nano Flows Conference (MNF2014), which was held at University College, London, UK. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute, ASME Press, LCN London Centre for Nanotechnology, UCL University College London, UCL Engineering, the International NanoScience Community, www.nanopaprika.eu.The dynamic gas flow in silica aerogel caused by ambient pressure change is an important factor to influence the thermal conductivity performance. Due to the ultrafine pore size, the flow in the silica aerogel is non-continuum. The direct simulation Monte Carlo method is selected to simulate the transient behavior of gas dynamic flow in nanoporous silica aerogel caused by pressure difference. The influences of pressure ratio and porosity on the unsteady dynamic response and the magnitude of the macroscopic parameters are investigated. The results show that the response processes under different pressure ratio and porosity conditions are similar. The effect of the pressure ratio and porosity are mainly reflected on the magnitude of the macro parameters and response time

Three-dimensional multi-level heat transfer model of silica aerogel

This paper was presented at the 4th Micro and Nano Flows Conference (MNF2014), which was held at University College, London, UK. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute, ASME Press, LCN London Centre for Nanotechnology, UCL University College London, UCL Engineering, the International NanoScience Community, www.nanopaprika.eu.In this paper, a 3-D multi-level heat transfer model is developed in consideration of the tortuous path of heat conduction in solid skeleton and the fractal characteristic of silica aerogel. The heat conduction is analyzed for both the secondary particle model and the cluster model. The expression of effective thermal conductivity of a multi-level model is derived. The theoretical predictions from the proposed multi-level model are compared with three sets of experimental data with different densities and porosities. The results from the proposed model show good agreement with the experimental data

Predominant occurrence of apical cell divisions in Oedogoniam pakistanense and its phylogenetic significance

A rare terrestrial species, Oedogonium pakistanense, was first recorded from Hubei Province, south-central China. Morphological characters. including the predominant occurrence of apical cell division and unique lateral apical caps, are described. The growth of the filaments in O. pakistanense from China is usually the result of the repeated divisions of the apical cells and intercalary divisions are rare. It is suggested that this species may represent an evolutionary transition between Oedogonium and Oedocladium, the latter being a terrestrial genus with branched filaments and cell division more often terminal than intercalary.A rare terrestrial species, Oedogonium pakistanense, was first recorded from Hubei Province, south-central China. Morphological characters. including the predominant occurrence of apical cell division and unique lateral apical caps, are described. The growth of the filaments in O. pakistanense from China is usually the result of the repeated divisions of the apical cells and intercalary divisions are rare. It is suggested that this species may represent an evolutionary transition between Oedogonium and Oedocladium, the latter being a terrestrial genus with branched filaments and cell division more often terminal than intercalary

Genetic analysis of farmed and wild stocks of large yellow croaker Larimichthys crocea by using microsatellite markers

The large yellow croaker (Pseudosciaena crocea) is one of the most economically important mariculture fish species in China. In this study, the genetic diversity and relationship among a wild stock, four farmed stocks and a selectively bred strain of large yellow croaker were assessed by 14 microsatellite markers. A total of 108 different alleles were detected over all loci. The average number of allele per locus ranged from 5.57 to 7.93, with an average of 6.75; the observed and expected heterozygosity ranged from 0.572 to 0.665 and from 0.649 to 0.751, with an average of 0.621 and 0.694, respectively; the Shannon’s diversity index ranged from 1.34 to 1.64, with an average of 1.48. The selectively bred strain had the lowest genetic diversity; all farmed stocks showed a slight reduction of genetic variability contrasted with wild stock. All stocks suffered severe bottleneck. The pair-wise FST, the phylogenetic tree, the factor correspondence analysis and the model based clustering analysis revealed that, the Ningbo stock, which was from Zhejiang province, was different from the remaining stocks from Fujian province. This study suggested that (1) the farmed stocks were at relatively low level of genetic diversity compared with the wild stock; (2) samples from Ningbo investigated in this study have a distinct divergence with those from Fujian province; (3) there had emerged significant differentiation among farmed stocks.Key words: Pseudosciaena crocea, large yellow croaker, genetic structure, microsatellite markers

The lexical knowledge base of modern Chinese based on HNC theory

2013-2014 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Size-affected shear-band speed in bulk metallic glasses

2011-2012 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Semi-Supervised Overlapping Community Finding based on Label Propagation with Pairwise Constraints

Algorithms for detecting communities in complex networks are generally unsupervised, relying solely on the structure of the network. However, these methods can often fail to uncover meaningful groupings that reflect the underlying communities in the data, particularly when those structures are highly overlapping. One way to improve the usefulness of these algorithms is by incorporating additional background information, which can be used as a source of constraints to direct the community detection process. In this work, we explore the potential of semi-supervised strategies to improve algorithms for finding overlapping communities in networks. Specifically, we propose a new method, based on label propagation, for finding communities using a limited number of pairwise constraints. Evaluations on synthetic and real-world datasets demonstrate the potential of this approach for uncovering meaningful community structures in cases where each node can potentially belong to more than one community.Comment: Fix table