Cavitation is a destructive phenomenon in control valves.In order to delay cavitation,a multi-series of perforated cylindrical plates,called trims,are used.Previously,the effects of orifice diameter and different type...Cavitation is a destructive phenomenon in control valves.In order to delay cavitation,a multi-series of perforated cylindrical plates,called trims,are used.Previously,the effects of orifice diameter and different types of trims have been investigated.In this study,by numerical analysis,a globe control valve was investigated by employing four different cases(without trim,with one trim,with two and three trims)and the impact of the number of these trims on the intensity,formation region and the initiation point of cavitation was analyzed.It was found that the addition of one stage or two stages of trims reduces the intensity and delays the onset of cavitation,relative to the valve without trim.However,no significant differences in terms of intensity and initiation point of cavitation were observed in the cases where two or three trims were used.Therefore,due to the high cost of producing the trims,and the severe drop in flow coefficient,it is not economically and technically justified to increase the number of trims to more than three.展开更多
When detecting deletions in complex human genomes,split-read approaches using short reads generated with next-generation sequencing still face the challenge that either false discovery rate is high,or sensitivity is l...When detecting deletions in complex human genomes,split-read approaches using short reads generated with next-generation sequencing still face the challenge that either false discovery rate is high,or sensitivity is low.To address the problem,an integrated strategy is proposed.It organically combines the fundamental theories of the three mainstream methods(read-pair approaches,split-read technologies and read-depth analysis) with modern machine learning algorithms,using the recipe of feature extraction as a bridge.Compared with the state-of-art split-read methods for deletion detection in both low and high sequence coverage,the machine-learning-aided strategy shows great ability in intelligently balancing sensitivity and false discovery rate and getting a both more sensitive and more precise call set at single-base-pair resolution.Thus,users do not need to rely on former experience to make an unnecessary trade-off beforehand and adjust parameters over and over again any more.It should be noted that modern machine learning models can play an important role in the field of structural variation prediction.展开更多
文摘Cavitation is a destructive phenomenon in control valves.In order to delay cavitation,a multi-series of perforated cylindrical plates,called trims,are used.Previously,the effects of orifice diameter and different types of trims have been investigated.In this study,by numerical analysis,a globe control valve was investigated by employing four different cases(without trim,with one trim,with two and three trims)and the impact of the number of these trims on the intensity,formation region and the initiation point of cavitation was analyzed.It was found that the addition of one stage or two stages of trims reduces the intensity and delays the onset of cavitation,relative to the valve without trim.However,no significant differences in terms of intensity and initiation point of cavitation were observed in the cases where two or three trims were used.Therefore,due to the high cost of producing the trims,and the severe drop in flow coefficient,it is not economically and technically justified to increase the number of trims to more than three.
基金Project(61472026)supported by the National Natural Science Foundation of ChinaProject(2014J410081)supported by Guangzhou Scientific Research Program,China
文摘When detecting deletions in complex human genomes,split-read approaches using short reads generated with next-generation sequencing still face the challenge that either false discovery rate is high,or sensitivity is low.To address the problem,an integrated strategy is proposed.It organically combines the fundamental theories of the three mainstream methods(read-pair approaches,split-read technologies and read-depth analysis) with modern machine learning algorithms,using the recipe of feature extraction as a bridge.Compared with the state-of-art split-read methods for deletion detection in both low and high sequence coverage,the machine-learning-aided strategy shows great ability in intelligently balancing sensitivity and false discovery rate and getting a both more sensitive and more precise call set at single-base-pair resolution.Thus,users do not need to rely on former experience to make an unnecessary trade-off beforehand and adjust parameters over and over again any more.It should be noted that modern machine learning models can play an important role in the field of structural variation prediction.
