48 research outputs found

    Application of Fibonacci Sequence and Lucas Sequence on the Design of the Toilet Siphon Pipe Shape

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    The purpose of this study was to explore the method for designing the toilet siphon pipe shape to improve flushing performance. The Fibonacci sequence and the Lucas sequence were used to design the structural parameters of the siphon pipe. The flushing processes of the toilet were simulated using the computational fluid dynamics (CFD) method to analyze the flushing performance under different siphon pipe shapes. Experimental studies were conducted to verify the reliability of the simulation results. The results indicated that when the Lucas numbers and the Fibonacci numbers were utilized to regulate the curvature of the siphon pipe in the Xi direction and the Yj direction respectively, the flushing performance of the toilet was optimal. In order to obtain better flushing performance, the curvature of the siphon pipe should be smooth and have obvious transitions at the connections of different sections. When the overall size of the siphon pipe is kept constant, a short siphon pipe length is helpful for the improvement of toilet flushing performance

    Study on the Influence of Toilet Siphon Pipe Shape on Flushing Performance

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    The goal of this work was to explore the influence of toilet siphon pipe shape on flushing performance. The flushing processes of a toilet under different shape parameters were simulated by using computational fluid dynamics (CFD) with a volume of fluid (VOF) multiphase model. The effects of siphon pipe shape on flushing performance were analyzed in detail. The interpretation of the simulation results was experimentally validated. The results reveal that a toilet may obtain good flushing performance under one single shape parameter when the climbing angle, the arc width, the arc height, the pipe diameter, the climbing width, and the climbing height are about 48°, 45 mm, 210 mm, 50 mm, 90 mm and 30 mm, respectively. With the increase of the siphon pipe diameter, the toilet flushing performance peaks in the range between 50 and 53 mm rather than continuing to improve. In order to reasonably evaluate the flushing effect of the toilet, all flow parameters on a characteristic cross section of the siphon pipe, including the average velocity, the average pressure and the average mass flow rate, should be comprehensively considered instead of one single parameter. The findings of this study provide a reference for the pipe shape design of toilets

    Performance optimization of banana vibrating screens based on PSO-SVR under DEM simulations

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    This paper carried out the numerical simulation about the movement of non-spherical particles on banana vibrating screen using direct element method (DEM) considering the complexity of particle collision and avoiding obtaining motion information with difficulty. Experimental prototype of banana vibrating screen under variable parameters was manufactured to verify the feasibility of simulations. Because the complex non-linear mathematical model is the basis of optimization. Based on the simulation data this paper applied the least squares support vector machines (LS-SVM) to establish relationships between vibrating parameters of banana screen and screening performance. LS-SVM based on statistical theory can effectively solve the mapping problem of small sample. At same time, in order to improving the quality of modeling, the kernel parameters of SVM were optimized by particle swarm optimization (PSO). Considering multi-extremum, large-scale, and non-differentiable of this computational model, the artificial fish-swarm algorithm (AFSA) with strong robustness and global convergence was applied to vibration parameters optimization. Finally, the optimal vibration parameters were: vibration amplitude 2.4 mm, vibration frequency 21 Hz, vibration direction angle 40 degrees

    Impact of biogenic SOA loading on the molecular composition of wintertime PM2.5 in urban Tianjin: an insight from Fourier transform ion cyclotron resonance mass spectrometry

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    Biomass burning is one of the key sources of urban aerosols in the North China Plain, especially in winter when the impact of secondary organic aerosols (SOA) formed from biogenic volatile organic compounds (BVOCs) is generally considered to be minor. However, little is known about the influence of biogenic SOA loading on the molecular composition of wintertime organic aerosols. Here, we investigated the water-soluble organic compounds in fine particles (PM2.5) from urban Tianjin by ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Our results show that most of the CHO and CHON compounds were derived from biomass burning; they contain O-poor and highly unsaturated compounds with aromatic rings, which are sensitive to photochemical reactions, and some of which probably contribute to light-absorbing chromophores. Under moderate to high SOA loading conditions, the nocturnal chemistry is more efficient than photooxidation to generate secondary CHO and CHON compounds with high oxygen content. Under low SOA-loading, secondary CHO and CHON compounds with low oxygen content are mainly formed by photochemistry. Secondary CHO compounds are mainly derived from oxidation of monoterpenes. But nocturnal chemistry may be more productive to sesquiterpene-derived CHON compounds. In contrast, the number- and intensity-weight of S-containing groups (CHOS and CHONS) increased significantly with the increase of biogenic SOA-loading, which agrees with the fact that a majority of the S-containing groups are identified as organosulfates and nitrooxy-organosulfates that are derived from the oxidation of BVOCs. Terpenes may be potential major contributors to the chemical diversity of organosulfates and nitrooxy-organosulfates under photo-oxidation. While the nocturnal chemistry is more beneficial to the formation of organosulfates and nitrooxy-organosulfates under low SOA-loading. The SOA-loading is an important factor associating with the oxidation degree, nitrate group content and chemodiversity of nitrooxy-organosulfates. Furthermore, our study suggests that the hydrolysis of nitrooxy-organosulfates is a possible pathway for the formation of organosulfates.</p

    Selection for antimicrobial resistance is reduced when embedded in a natural microbial community

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    This is the final version. Available from Springer Nature via the DOI in this record.Antibiotic resistance has emerged as one of the most pressing, global threats to public health. In single-species experiments selection for antibiotic resistance occurs at very low antibiotic concentrations. However, it is unclear how far these findings can be extrapolated to natural environments, where species are embedded within complex communities. We competed isogenic strains of Escherichia coli, differing exclusively in a single chromosomal resistance determinant, in the presence and absence of a pig faecal microbial community across a gradient of antibiotic concentration for two relevant antibiotics: gentamicin and kanamycin. We show that the minimal selective concentration was increased by more than one order of magnitude for both antibiotics when embedded in the community. We identified two general mechanisms were responsible for the increase in minimal selective concentration: an increase in the cost of resistance and a protective effect of the community for the susceptible phenotype. These findings have implications for our understanding of the evolution and selection of antibiotic resistance, and can inform future risk assessment efforts on antibiotic concentrations.Medical Research Council (MRC)European Commissio

    Tracking antibiotic resistance gene pollution from different sources using machine-learning classification

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    Abstract Background Antimicrobial resistance (AMR) has been a worldwide public health concern. Current widespread AMR pollution has posed a big challenge in accurately disentangling source-sink relationship, which has been further confounded by point and non-point sources, as well as endogenous and exogenous cross-reactivity under complicated environmental conditions. Because of insufficient capability in identifying source-sink relationship within a quantitative framework, traditional antibiotic resistance gene (ARG) signatures-based source-tracking methods would hardly be a practical solution. Results By combining broad-spectrum ARG profiling with machine-learning classification SourceTracker, here we present a novel way to address the question in the era of high-throughput sequencing. Its potential in extensive application was firstly validated by 656 global-scale samples covering diverse environmental types (e.g., human/animal gut, wastewater, soil, ocean) and broad geographical regions (e.g., China, USA, Europe, Peru). Its potential and limitations in source prediction as well as effect of parameter adjustment were then rigorously evaluated by artificial configurations with representative source proportions. When applying SourceTracker in region-specific analysis, excellent performance was achieved by ARG profiles in two sample types with obvious different source compositions, i.e., influent and effluent of wastewater treatment plant. Two environmental metagenomic datasets of anthropogenic interference gradient further supported its potential in practical application. To complement general-profile-based source tracking in distinguishing continuous gradient pollution, a few generalist and specialist indicator ARGs across ecotypes were identified in this study. Conclusion We demonstrated for the first time that the developed source-tracking platform when coupling with proper experiment design and efficient metagenomic analysis tools will have significant implications for assessing AMR pollution. Following predicted source contribution status, risk ranking of different sources in ARG dissemination will be possible, thereby paving the way for establishing priority in mitigating ARG spread and designing effective control strategies

    Polycyclic aromatic hydrocarbon (PAH) biodegradation capacity revealed by a genome-function relationship approach

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    Abstract Background Polycyclic aromatic hydrocarbon (PAH) contamination has been a worldwide environmental issue because of its impact on ecosystems and human health. Biodegradation plays an important role in PAH removal in natural environments. To date, many PAH-degrading strains and degradation genes have been reported. However, a comprehensive PAH-degrading gene database is still lacking, hindering a deep understanding of PAH degraders in the era of big data. Furthermore, the relationships between the PAH-catabolic genotype and phenotype remain unclear. Results Here, we established a bacterial PAH-degrading gene database and explored PAH biodegradation capability via a genome-function relationship approach. The investigation of functional genes in the experimentally verified PAH degraders indicated that genes encoding hydratase-aldolase could serve as a biomarker for preliminarily identifying potential degraders. Additionally, a genome-centric interpretation of PAH-degrading genes was performed in the public genome database, demonstrating that they were ubiquitous in Proteobacteria and Actinobacteria. Meanwhile, the global phylogenetic distribution was generally consistent with the culture-based evidence. Notably, a few strains affiliated with the genera without any previously known PAH degraders (Hyphomonas, Hoeflea, Henriciella, Saccharomonospora, Sciscionella, Tepidiphilus, and Xenophilus) also bore a complete PAH-catabolic gene cluster, implying their potential of PAH biodegradation. Moreover, a random forest analysis was applied to predict the PAH-degrading trait in the complete genome database, revealing 28 newly predicted PAH degraders, of which nine strains encoded a complete PAH-catabolic pathway. Conclusions Our results established a comprehensive PAH-degrading gene database and a genome-function relationship approach, which revealed several potential novel PAH-degrader lineages. Importantly, this genome-centric and function-oriented approach can overcome the bottleneck of conventional cultivation-based biodegradation research and substantially expand our current knowledge on the potential degraders of environmental pollutants

    Siphon pipe Parameter Optimization of the Toilet Using CFD-DEM Coupling Method

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    The computational fluid dynamics (CFD) and discrete element method (DEM) coupling method is used to simulate the flushing process of the toilet and this paper analyzes the influence of different structural parameters of siphon pipe on the flushing performance of the toilet. And through the adjusted-parameters toilet, tlushing experments were carried out to verify the simulations. Meanwhile the orthogonal test of different structural parameters of siphon pipes were conducted to study the flushing Performance. The research results show that the CFD-DEM coupling method can be used to study the regularity of the toilet flushing performance. The toilet can get the better flushing performance when the&nbsp;tilt&nbsp;angle&nbsp;of&nbsp;the&nbsp;angle of inclination&nbsp;is&nbsp;50&deg;, the curvature width and length are 50 mm and 220 mm, the width and height of the secondary water seal are 100 mm and 25 mm and pipe diameter is 53 mm. The method in this paper can provide a new idea for the study and design of the flushing performance of the toilet. &#39;&#39;&#39;Keyword:&#39;&#39;&#39; CFD-DEM, flushing performance, structural parameters, coupling method, adjusted-parameters toile
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