Analysis of the Hydraulic Performances of a New Liquid Emitter Based on a Leaf Vein Concept

The leaf-vein drip irrigation emitter is a new type of drip emitter based on a bionic structure able to support shunting,sharp turns,and increased dissipation.In the present work,the results of twenty-five tests executed in the framework of an orthogonal design strategy are presented in order to clarify the influence of the geometrical parameters of the flow channel on the hydraulic characteristics of such emitter.The corresponding flow index and head loss coefficient are determined through numerical simulations and model testing.The results show that the flow index of the flow channel is 0.4970∼0.5461,which corresponds to good hydraulic performances.The head loss coefficient of the flow channel is 572.74∼3933.05,which in turn indicates a good energy dissipation effect.The order of influence of the leaf vein flow channel parameters on the flow index can be represented in a synthetic way as a>b>c>d>e,where(a)is the width of the inlet,(b)is the horizontal distance of the front water inlet,(c)is the vertical distance of the inner edge of the front end,(d)is the horizontal distance of the rear water outlet and(e)is the vertical distance of the outer edge of the front end.The flow index increases with d,decreases with a,first decreases,and then increases with b,and first increases and then decreases with the increase of c and e.The coefficient(R^(2))of the fitted model related to geometric parameters and flow index is 0.9986-0.9999.The relative errors among experimental testing,simulation calculation and predictive estimates are shown to be less than 5%.

Simulation of the Hydraulic Behavior of a Bionic-Structure Drip Irrigation Emitter

The bionic structure drip irrigation emitter(BSDE)is a new-type emitter,by which better hydraulic performances can be obtained.In the present work,twenty-five sets of orthogonal test schemes were implemented to analyze the influence of the geometric parameters of the flow channel on the hydraulic characteristics and energy dissipation efficiency of this emitter.Through numerical simulations and verification tests,the flow index and energy dissipation coefficient were obtained.According to the results,the flow index of the BSDE is 0.4757-0.5067.The energy dissipation coefficient under the pressure head of 5-15 m is 584-1701.The verification test has shown that the relative errors among measured values,simulated values and estimated values are less than 3%,which indicates that the flow index can be estimated reliably.

Analysis of Water Transport inside a Plant Xylem Vessel with Pitted Thickening

In this article,computational fluid dynamics(CFD)are used to explore the dynamics of water transport inside the pitted thickening of a plant xylem vessel.A pitted thickening model combined with the Bernoulli equation is used to analyze the influence of various factors(namely,the inner diameter,thickening width,thickening height,thickening spacing,number of laps and adjacent pit axial rotation).The pressure drop and the flow resistance coefficient are the variable parameters for our analysis.The results show that these two parameters are proportional to the thickening height and thickening width,and inversely proportional to the inner diameter,thickening spacing and number of laps.Three different wall thickening structures of the vessel are compared and the pitted thickening vessel is shown to provide the largest structural flow resistance,the annular thickening vessel has the second largest resistance and the helical thickening vessel corresponds to the smallest resistance of the three structures.

The role and challenge of artificial intelligence in new coronavirus pneumonia CT diagnosis

In early 2020,the new coronavirus pneumonia(COVID-19)broke out in China.Many medical-related products have rapidly appeared in the Artificial Intelligence(AI)field,which have played an important role in fighting against the pandemic.This article summarizes the current research and application status of AI in radiology and pandemic control and analyzes the common problems of AI technology in the research of COVID-19 diagnosis.It mainly includes the thoughts on clinical study design,difficulties in research implementation and challenges in the reliability verification of AI models.In response to the above difficulties,suggestions are proposed for optimizing the scientificity and quality of AI diagnostic research.

Analysis of Dust Weather Process in Most Areas of China from January 11 to 16, 2021

The DERF2.0 model of China National Climate Center and NCEP (National Centers for Environmental Prediction) data were used in this paper. Using the knowledge of synoptic principles, the process of dust weather in most parts of China from January 11 to 16, 2021 was analyzed. The results show that: 1) Compared with previous years, this process has a large impact scope and appears earlier. 2) The continuous cold air caused the dust weather process. 3) The surface cold front is conducive to the development of dust. 4) Surface cyclone is conducive to the transport and diffusion of dust.

Fe2O3/AC催化剂的低温选择性催化还原脱硝性能

以活性焦（AC）为载体、Fe2O3为活性组分,采用等体积浸渍法制备Fe2O3/AC催化剂,研究了Fe含量对Fe2O3/AC催化剂低温脱硝性能的影响.结果表明,当Fe负载量为6wt%时能获得比其它负载量更佳的NOx转化率,尤其在240℃时NOx转化率达93.9%,当分别有120′10-6（vol）SO2和3.5vol H2O存在时,脱硝率分别稳定在约86%和74%;催化剂孔径≤4 nm,随Fe负载量增加,孔径呈增大趋势;催化剂较稳定;Fe主要以γ-Fe2O3分散在催化剂表面,负载适量Fe2O3使表面吸附氧Oβ和Fe3＋增多,为催化剂提供更多活性位,提高了Fe2O3/AC催化剂的低温选择性催化还原脱硝活性.