Design And Optimization Of Annular Ejector For Conveying Latex Products

Owning to the fact that the power source can be obtainable conveniently and the environmental requirements are relatively low,as a material conveyor,ejectors are widely applied in coal chemical industry,animal husbandry,fishery,industrial automation,etc.Compared with the central ejector commonly used in the transport of particle materials,annular ejectors possess unimpeded suction channels which are beneficial to transporting bulk materials.Accordingly,annular ejectors applied to convey the latex products are designed and optimized in this work.Expectable goals,including revealing the internal flow characteristics of the annual ejector,realizing the smooth delivery of condoms,designing a high-performance annular ejector,need to be achieved.Around these goals above,some studying results are listed as follows:Firstly,a 3D numerical calculation model of the annual ejector is set up and then the flow field characteristic of the ejector working under variable conditions is analyzed.Results show that the vacuum in the suction mouth increases gradually while the injection coefficient decreases with the increase of gas pressure.Then experiments are conducted to testify the effectiveness of the model and the feasibility of gesture adjustment of latex products during the conveying process.For the reason that some test samples are easily adhered to the inner wall,the subsequent optimization objectives are to improve the velocity distribution uniformity and increase the vacuum degree in the suction mouth.Secondly,the flow structure is improved so that the flow filed is uniform,and the vacuum degree in the suction mouth under the same working condition is increased as well.The effects of structural parameters on the ejector performance are studied and a series of optimal structural parameters are obtained when the flow structure is determined.Both the injection coefficient and the vacuum degree decrease accompanying with the increase of jet angle ranging from 7°,15°,23°to 30°.However,the injection coefficient decreases with the annular nozzle gap increasing from 0.5 mm to 3 mm,while the vacuum degree reaches up to its peak value when the gap is 1.5 mm.When the structural requirements are met,the larger the mixing tube diameter is,the greater the injection coefficient and the vacuum degree become.When the length to diameter ratio is around 2.5,the suction characteristic of the mixing tube is optimal as the working and ejector media are fully mixed.Finally,the nonlinear relationship between structural parameters and the vacuum degree is built by combing the orthogonal experiment with BP neural network method in a range including approximately optimal values.The new samples obtained by numerical simulation of Fluent are compared with those predicted by BP neural network.The maximum relative error is 7.16%,which satisfies the engineering demand.Combined with the established BP neutral network,the step length is controlled to search for the maximum of the vacuum degree,with the optimal structure parameters of the injector achieved as well.Compared with the single parameter optimization results,the vacuum degree value is increased by 10.6%after the neural network optimization.