The effects of a porous fence with a nonuniform porosity on flow fields are investigated numerically. First, an experiment with a non-uniform porous fence located in a wind tunnel is performed to obtain a reference data set. Then, a numerical model that utilizes the finite volume scheme with a weakly compressible-flow method to solve the continuity and momentum equations is developed. The numerical simulation is compared to experimental measurements for validation purposes. As a result, the numerical predictions show good agreements with the experimental data. Finally, the numerical investigations of the flow fields around porous fences with various combinations of upper and lower fence porosity are also presented. When the upper porosity is greater than the lower porosity, the Protection Index PI 0.1 , PI 0.3 and PI 0.5 , representing the adverse sheltering effect, decreases compared to that of the uniform porous fence. When the upper porosity is less than the lower porosity, the PI 0.5 increases and the variations of the PI 0.1 and PI 0.3 , depend on the upper porosity, compared to that of the uniform porous fence. The results show that the porous fence with the upper fence porosity ε U 0% and the lower fence porosity ε L 30% gives the best sheltering effect among the porous fences in this study.
A novel microbial transglutaminase (TGase) from the cultural filtrate of Streptomyces netropsis BCRC 12429 (Sn) was purified. The specific activity of the purified TGase was 18.2 U/mg protein with an estimated molecular mass of 38 kDa by sodium dodecyl sulfate polyacrylamide gel electrophoresis analysis. The TGase gene of S. netropsis was cloned and an open reading frame of 1,242 bp encoding a protein of 413 amino acids was identified. The Sn TGase was synthesized as a precursor protein with a preproregion of 82 amino acid residues. The deduced amino acid sequence of the mature S. netropsis TGase shares 78.9-89.6% identities with TGases from Streptomyces spp. A high level of soluble Sn TGase with its N-terminal propeptide fused with thioredoxin was expressed in E. coli. A simple and efficient process was applied to convert the purified recombinant protein into an active enzyme and showed activity equivalent to the authentic mature TGase.
A new type of collar, the hooked-collar, was studied through experiments and numerical methods. Tests were conducted using a hooked collar of a width of 1.25b and a height of 0.25b, where b is the bridge-pier width. The hooked-collar efficiency was evaluated by testing different hooked-collar placements within the bridge-pier, which were compared to the bridge-pier without any collar. A double hooked-collar configuration, one placed at the bed level and the other buried 0.25b, was the most efficient at reducing the scour hole. In other cases, a hooked-collar positioned 0.25b above the bed slightly reduced the scour hole and had similar scour patterns when compared to the pier without the hooked-collar. The flow fields along the vertical symmetrical plane in the experiments are also presented. Laboratory experiments and numerical tests show that maximal downflow is highly reduced along with a corresponding decrease in horseshoe vortex strength for the experiments with the hooked-collar, compared to cases without the hooked-collar. The flow fields reveal that the maximum turbulent kinetic energy decreases with the installation of the hooked-collar.
Conventional landslide susceptibility analysis adopted rainfall depth or maximum rainfall intensity as the hydrological factor. However, using these factors cannot delineate temporal variations of landslide in a rainfall event. In the hydrological cycle, runoff quantity reflects rainfall characteristics and surface feature variations. In this study, a rainfall–runoff model was adopted to simulate the runoff produced by rainfall in various periods of a typhoon event. To simplify the number of factors in landslide susceptibility analysis, the runoff depth was used to replace rainfall factors and some topographical factors. The proposed model adopted the upstream area of the Alishan River in southern Taiwan as the study area. The landslide susceptibility analysis of the study area was conducted by using a logistic regression model. The results indicated that the overall accuracy of predicted events exceeded 80%, and the area under the receiver operating characteristic curve (AUC) closed to 0.8. The results revealed that the proposed landslide susceptibility simulation performed favorably in the study area. The proposed model could predict the evolution of landslide susceptibility in various periods of a typhoon and serve as a new reference for landslide hazard prevention.
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