Effect of the heating rate on the thermal explosion behavior and oxidation resistance of 3D-structure porous NiAl intermetallic

Porous NiAl intermetallic compounds demonstrate great potential in various applications by their high porosity and excellent oxidation resistance. However, to obtain a controllable NiAl intermetallic structure by tuning different process parameters remains unclear. In this work, porous NiAl intermetallic compounds were fabricated by economic and energy-saving thermal explosion (TE) reaction. The relationship between microstructure and process parameters was revealed using three-dimensional X-ray microscopy (3D-XRM) with high resolution and non-destructive characteristics. The geometrical features and quantitative statistics of the porous NiAl obtained at different heating rates (2, 10, 20 \ub0C min−1) were compared. The result of the closed porosity calculation showed that a lower heating rate (2 \ub0C min−1) promoted the Kirkendall reaction between Ni and Al, resulting in a high closed porosity (5.25%). However, at a higher heating rate (20 \ub0C min−1), a homogeneous NiAl phase was observed using the threshold segmentation method, indicating uniform and complete TE reaction can be achieved at a high heating rate. The result of the 3D fluid simulation showed that the sample heated at 10 \ub0C min−1 had the highest permeability (2434.6 md). In this study, we systematically investigated the relationship between the heating rates and properties of the porous NiAl intermetallic, including the phase composition, porosity, exothermic mechanism, oxidation resistance, and compression resistance. Our work provides constructive directions for designing and tailoring the performance of porous NiAl intermetallic compounds

Estimation and uncertainty analyses of grassland biomass in Northern China: Comparison of multiple remote sensing data sources and modeling approaches

Accurate estimation of grassland biomass and its dynamics are crucial not only for the biogeochemical dynamics of terrestrial ecosystems, but also for the sustainable use of grassland resources. However, estimations of grassland biomass on large spatial scale usually suffer from large variability and mostly lack quantitative uncertainty analyses. In this study, the spatial grassland biomass estimation and its uncertainty were assessed based on 265 field measurements and remote sensing data across Northern China during 2001-2005. Potential sources of uncertainty, including remote sensing data sources (DATsrc), model forms (MODfrm) and model parameters (biomass allocation, BMallo, e.g. root:shoot ratio), were determined and their relative contribution was quantified. The results showed that the annual grassland biomass in Northern China was 1268.37 +/- 180.84Tg (i.e., 532.02 +/- 99.71 g/m(2)) during 2001-2005, increasing from western to eastern area, with a mean relative uncertainty of 19.8%. There were distinguishable differences among the uncertainty contributions of three sources (BMallo >DATsrc>MODfrm), which contributed 52%, 27% and 13%, respectively. This study highlighted the need to concern the uncertainty in grassland biomass estimation, especially for the uncertainty related to BMallo. (C) 2015 Elsevier Ltd. All rights reserved

M-Kernel Merging: Towards Density Estimation over Data Streams

Density estimation is a costly operation for computing distribution information of data sets underlying many important data mining applications, such as clustering and biased sampling. However, traditional density estimation methods are inapplicable for streaming data, which are continuous arriving large volume of data, because of their request for linear storage and square size calculation. The shortcoming limits the application of many existing effective algorithms on data streams, for which the mining problem is an emergency for applications and a challenge for research. In this paper, the problem of computing density functions over data streams are examined. A novel method attacking this shortcoming of existing methods is developed to enable density estimation for large volume of data in linear time, fixed size memory, and without lose of accuracy. The method is based on M-Kernel merging, so that limited kernel functions to be maintained are determined intelligently. The application of the new method on different streaming data models are discussed, and the result of intensive experiments is presented. The analytical and empirical result show that this new density estimation algorithm for data streams can calculate density functions on demand at any time with high accuracy for different streaming data models.

Effects of liquids immersion and drying on the surface properties of HTV silicone rubber: characterisation by contact angle and surface physical morphology

High-temperature vulcanised (HTV) silicone rubber composite insulator has been widely used in extra-high and ultra-high transmission lines due to its excellent electrical and mechanical performance. In practice use, liquids may encounter the composite insulator intermittently and can lead to the degradation and deterioration of silicone rubber. In the present research, the effects of liquids immersion and subsequent drying on the surface properties of HTV silicone rubber were investigated by means of the contact angle measurement and surface physical morphology measurement which was further analysed in terms of the discrete wavelet transform method, multiresolution signal decomposition algorithm, and three-dimensional fractal dimension calculation. Based on the experimental results, the mechanism of the loss and recovery of the hydrophobicity of HTV silicone rubber surface during the liquids immersion and subsequent drying processes were further explained by taking into consideration the embedded water molecules (and/or hydrated ions) on the HTV silicone rubber surface and the synergy of the increase in roughness/fractal dimension and low molecular weight siloxanes diffusion. This study is helpful for better understanding of the change of surface properties of HTV silicone rubber caused by environmental and electrical stresses

Axial compressive behaviour of square through-beam joints between CFST columns and RC beams with multi-layers of steel meshes

The axial compressive behaviour of an innovative type of square concrete filled steel tube (CFST) column to reinforced concrete (RC) beam joint was experimentally investigated in this paper. The innovative joint was designed such that (i) the steel tubes of the CFST columns were completely interrupted in the joint region, (ii) the longitudinal reinforcements from the RC beams could easily pass through the joint area and (iii) a reinforcement cage, including a series of reinforcement meshes and radial stirrups, was arranged in the joint area to strengthen the mechanical performance of the joint. A twostage experimental study was conducted to investigate the behaviour of the innovative joint under axial compression loads, where the first stage of the tests included three fullscale innovative joint specimens subjected to axial compression to assess the feasibility of the joint detailing and propose measures to further improve its axial compressive behaviour, and the second stage of the tests involved 14 innovative joint specimens with the improved detailing to study the effect of the geometric size of the joint, concrete strength and volume ratio of the steel meshes on the bearing strengths of the joints. It was generally found from the experiments that (i) the innovative joint is capable of achieving the design criterion of the 'strong jointweak member' with appropriate designs, and (ii) by decreasing the height factor and increasing the volume ratio of the steel meshes, the axial compressive strengths of the joints significantly increased, while the increase of the length factor is advantageous but limited to the resistances of the joint specimens. Because of the lack of existing design methods for the innovative joints, new design expressions were proposed to calculate the axial compression resistances of the innovative joints subjected to bearing loads, with the local compression effect, the confinement effect provided by the multilayers of steel meshes and the height effect of concrete considered. It was found that the proposed design methods were capable of providing accurate and safe resistance predictions for the innovative joints.Published versio

Estimation and uncertainty analyses of grassland biomass in Northern China: Comparison of multiple remote sensing data sources and modeling approaches

Accurate estimation of grassland biomass and its dynamics are crucial not only for the biogeochemical dynamics of terrestrial ecosystems, but also for the sustainable use of grassland resources. However, estimations of grassland biomass on large spatial scale usually suffer from large variability and mostly lack quantitative uncertainty analyses. In this study, the spatial grassland biomass estimation and its uncertainty were assessed based on 265 field measurements and remote sensing data across Northern China during 2001-2005. Potential sources of uncertainty, including remote sensing data sources (DATsrc), model forms (MODfrm) and model parameters (biomass allocation, BMallo, e.g. root:shoot ratio), were determined and their relative contribution was quantified. The results showed that the annual grassland biomass in Northern China was 1268.37 +/- 180.84Tg (i.e., 532.02 +/- 99.71 g/m(2)) during 2001-2005, increasing from western to eastern area, with a mean relative uncertainty of 19.8%. There were distinguishable differences among the uncertainty contributions of three sources (BMallo >DATsrc>MODfrm), which contributed 52%, 27% and 13%, respectively. This study highlighted the need to concern the uncertainty in grassland biomass estimation, especially for the uncertainty related to BMallo. (C) 2015 Elsevier Ltd. All rights reserved

Whole-genome resequencing reveals world-wide ancestry and adaptive introgression events of domesticated cattle in East Asia

Cattle domestication and the complex histories of East Asian cattle breeds warrant further investigation. Through analysing the genomes of 49 modern breeds and eight East Asian ancient samples, worldwide cattle are consistently classified into five continental groups based on Y-chromosome haplotypes and autosomal variants. We find that East Asian cattle populations are mainly composed of three distinct ancestries, including an earlier East Asian taurine ancestry that reached China at least ~3.9 kya, a later introduced Eurasian taurine ancestry, and a novel Chinese indicine ancestry that diverged from Indian indicine approximately 36.6–49.6 kya. We also report historic introgression events that helped domestic cattle from southern China and the Tibetan Plateau achieve rapid adaptation by acquiring ~2.93% and ~1.22% of their genomes from banteng and yak, respectively. Our findings provide new insights into the evolutionary history of cattle and the importance of introgression in adaptation of cattle to new environmental challenges in East Asia