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Fast and efficient mixing of high-speed shear flow formed by fuel and oxidizer is of great importance for the improvement of rocket-based combined cycle engine performance. Nevertheless, the existence of compressibility effects of high-speed flow significantly inhibits the growth process of a mixing layer. Moreover, a finite-length combustor of the engine calls for more effective enhanced-mixing strategies to complete mixing in a shorter streamwise distance. To this end, in present paper, the strategy called dual plate cavity (DPC) is proposed to promote mixing. Three cases including the benchmark, front-DPC and back-DPC cases are selected to perform the comparative study. By means of high-order direct numerical simulations, the structure evolution characteristics and turbulence intensity distributions are researched. The index of velocity thickness is utilized to assess the mixing layer growth. The results indicate that with the introduction of DPC, the mixing process is dramatically promoted. The penetration behavior of newly found T-shaped structures into the upper main stream can engulf more fluid into the mixing region. Specifically, in the back-DPC case, the coexistence of both large-scale and small-scale structures in the far flow field can improve the turbulence intensity. The spatial correlation analysis results show that with the influence of DPC, the structure sizes are much larger than that of the benchmark case in the same streamwise position. Meanwhile, the contour line equal to 0.5 possesses property of distortion for the back-DPC case. The drastic pulsation of a mixing layer edge can obviously promote the mixing process. Through exploration of the enhanced-mixing mechanisms, this work indicates that the proposed DPC strategy is a good candidate for efficient mixing, and in the future, more detailed work including three-dimensional simulations concerning the strategy optimization is suggested to be performed. [ABSTRACT FROM AUTHOR]

Avalanche susceptibility assessment is a core aspect of regional avalanche early warning and risk analysis and is of great significance for disaster prevention and mitigation on proposed highways. Using sky–ground integration investigation, 83 avalanche points within the G219 Wen Quan to Horgos transportation corridor were identified, and the avalanche hazard susceptibility of the transportation corridor was partitioned using the certainty factor (CF) model and the coupled coefficient of the certainty factor–Geodetector (CF-GD) model. The CF model analysis presented nine elements of natural conditions which influence avalanche development; then, by applying the Geodetector for each of the factors, a weighting coefficient was given depending on its importance for avalanche occurrence. The results demonstrate the following: (1) According to the receiver operating characteristic (ROC) curve used to verify the accuracy, the area under the ROC curve (AUC) value for the CF-GD coupled model is 0.889, which is better than the value of 0.836 of the CF model's evaluation accuracy, and the coupled model improves the accuracy by about 6.34% compared with the single model, indicating that the coupled model is more accurate. The results provide avalanche prevention and control recommendations for the G219 Wen Quan to Horgos transportation corridor. (2) The slope orientation, slope gradient, and mean winter temperature gradient are the main factors for avalanche development in the study area. (3) The results were validated based on the AUC values. The AUCs of the CF-GD coupled model and the CF model were 0.889 and 0.836, respectively. The accuracy of the coupled model was improved by about 6.34% compared to the single model, and the coupled CF-GD model was more accurate. The results provide avalanche control recommendations for the G219 Wen Quan to Horgos transportation corridor. [ABSTRACT FROM AUTHOR]

Biochar return to the field has been widely explored, but there is a problematic disconnect between biochar preparation and biochar return to the field. In this study, soybean straw is used as a raw material and is sieved into two components: 60-mesh (0.250 mm) and 110-mesh (0.130 mm). Four kinds of biochar were obtained by pyrolysis under the condition of no heat preservation and heat preservation for 60 min. The biochar was applied to the soil, and the effects of biochar on soil and capsicum growth were analyzed by Spearman correlation. Compared with the control group, soil pH, soil electrical conductivity, and soil organic matter decomposition were increased by 0.58, 101 μs/cm, and 9.48%, respectively. The fruit quantity, plant height, water, fat, soluble solid, and titrable acidity of capsicum were increased by 1, 0.55, 0.08, 0.62, 0.67, and 0.7 times, respectively. Spearman correlation analysis showed that soil properties and capsicum growth were most affected by biochar's specific surface area (SSA). Therefore, increasing the biomass mesh number and heat preservation time is beneficial to increasing the SSA of biochar and facilitating the return of biochar to the field and the best preparation conditions are 110-mesh soybean straw biomass pyrolysis and heat preservation for 60 min. [ABSTRACT FROM AUTHOR]

In this study, a yeast strain with an outstanding NH3-N degradation ability was isolated from the sediment of a black-odor water channel in Guangdong Province, China. Based on phenotypic and phylogenetic analysis, this strain was identified as Pichia kudriavzevii GW1. The optimum conditions for NH3-N degradation by the GW1 strain were as follows: 0.3% inoculum concentration, 1.5 L/min aeration, pH 7, and a temperature of 35°C. Under optimized conditions, the GW1 strain degraded 95.5% of the NH3-N. The strain was then added to simulated black-odor water under optimal degradation conditions to investigate changes to the bacterial community over time. 16S rRNA sequencing of samples collected on days 0, 7, 14, and 21 showed that, in the presence of the GW1 strain, the relative abundances of the phyla Proteobacteria, Bacteroidetes, Chloroflexi, and Firmicutes increased in the black-odor water. In addition, the relative abundance of Propionivibrio, a known NH3-N degrading genus, increased. This study will facilitate the use of microbiological methods to repair black-odor water. [ABSTRACT FROM AUTHOR]

With the improvement of operation monitoring and data acquisition levels of smart meters, mining data associated with smart meters becomes possible. Besides, precisely assessing the operation quality of smart meters plays an important role in purchasing metering equipment and improving the economic benefits of power utilities. First, seven indexes for assessing operation quality of smart meters are defined based on the metering data and the Gaussian mixture model (GMM) clustering algorithm is applied to extract the typical index data from the massive data of smart meters. Then, the combination optimization model of index's weight is presented with the subject experience of experts and object difference of data considered; and the comprehensive assessment algorithm based on the revised technique for order preference by similarity to an ideal solution (TOPSIS) is proposed to evaluate the operation quality of smart meters. Finally, the proposed data-driven assessment algorithm is illustrated by the actual metering data from Zhejiang Ningbo power supply company of China and practical application is briefly introduced. The results show that the proposed algorithm is effective for assessing the operation quality of smart meters and could be helpful for energy measurement and asset management. [ABSTRACT FROM AUTHOR]

In this study, a yeast strain with an outstanding NH 3 -N degradation ability was isolated from the sediment of a black-odor water channel in Guangdong Province, China. Based on phenotypic and phylogenetic analysis, this strain was identified as Pichia kudriavzevii GW1. The optimum conditions for NH 3 -N degradation by the GW1 strain were as follows: 0.3% inoculum concentration, 1.5 L/min aeration, pH 7, and a temperature of 35°C. Under optimized conditions, the GW1 strain degraded 95.5% of the NH 3 -N. The strain was then added to simulated black-odor water under optimal degradation conditions to investigate changes to the bacterial community over time. 16S rRNA sequencing of samples collected on days 0, 7, 14, and 21 showed that, in the presence of the GW1 strain, the relative abundances of the phyla Proteobacteria, Bacteroidetes, Chloroflexi, and Firmicutes increased in the black-odor water. In addition, the relative abundance of Propionivibrio , a known NH 3 -N degrading genus, increased. This study will facilitate the use of microbiological methods to repair black-odor water., Competing Interests: The authors have no conflicts of interest to declare., (Copyright © 2020 Haiwei Xie et al.)