The liquid loading is one of the most frequently encountered phenomena in the transportation of gas pipeline,reducing the transmission efficiency and threatening the flow assurance.However,most of the traditional mech...The liquid loading is one of the most frequently encountered phenomena in the transportation of gas pipeline,reducing the transmission efficiency and threatening the flow assurance.However,most of the traditional mechanism models are semi-empirical models,and have to be resolved under different working conditions with complex calculation process.The development of big data technology and artificial intelligence provides the possibility to establish data-driven models.This paper aims to establish a liquid loading prediction model for natural gas pipeline with high generalization ability based on machine learning.First,according to the characteristics of actual gas pipeline,a variety of reasonable combinations of working conditions such as different gas velocity,pipe diameters,water contents and outlet pressures were set,and multiple undulating pipeline topography with different elevation differences was established.Then a large number of simulations were performed by simulator OLGA to obtain the data required for machine learning.After data preprocessing,six supervised learning algorithms,including support vector machine(SVM),decision tree(DT),random forest(RF),artificial neural network(ANN),plain Bayesian classification(NBC),and K nearest neighbor algorithm(KNN),were compared to evaluate the performance of liquid loading prediction.Finally,the RF and KNN with better performance were selected for parameter tuning and then used to the actual pipeline for liquid loading location prediction.Compared with OLGA simulation,the established data-driven model not only improves calculation efficiency and reduces workload,but also can provide technical support for gas pipeline flow assurance.展开更多
Traditional modifications to hydroxyapatite （HA） nanoparticles usually occurred after HA synthesis and thus are insufficient to avoid particle agglomeration. In this study, a new heterofunctional poly（ethylene gly...Traditional modifications to hydroxyapatite （HA） nanoparticles usually occurred after HA synthesis and thus are insufficient to avoid particle agglomeration. In this study, a new heterofunctional poly（ethylene glycol） （PEG） with phosphoric acid and carboxyl end groups, Le., a-（N-2-phosphoethyl phosphoric acid）- amide, w-carboxyl-bismethyoxy poly（ethylene glycol） （ADP-PEG-COOH）, was synthesized as an in situ surface modifier to HA nanoparticles. The resulting modified HA （ADP-PEG-HA） can disperse in methanol, forming a colloid stabilized by peripheral carboxyl-endcapped PEG chains. The colloidal particles resembled nanospheres which agglomerated to some extent under examination by transmission electron microscope. This highly dispersible HA nanoparticles in organic solvent might find application in preparing new HA nanocomposites.展开更多
A series of novel, azasugar-modified 2-monosubstituted, 2,6- and 2,7-bissubstituted anthraquinone derivatives have been synthesized by the nucleophilic substitution of N-alkylamino azasugar with mono-, bis（2-chloroac...A series of novel, azasugar-modified 2-monosubstituted, 2,6- and 2,7-bissubstituted anthraquinone derivatives have been synthesized by the nucleophilic substitution of N-alkylamino azasugar with mono-, bis（2-chloroacetamido）anthraquinones. Their cytotoxic activities against HeLa and MCF-7 ceils were preliminarily evaluated and compound 9a with mono-azasugar pendant at 2-position showed similar activity to the control drug （Cisplatin）.展开更多
C(sp^2)‐centered homo‐ and hetero‐nuclear gold complexes have attracted widespread interests in recent decades. Studies of this type of complexes may deepen the understandings of the intermediates in Au‐catalyzed ...C(sp^2)‐centered homo‐ and hetero‐nuclear gold complexes have attracted widespread interests in recent decades. Studies of this type of complexes may deepen the understandings of the intermediates in Au‐catalyzed organic reactions and explore new applications in catalytic and material science. The focuses of this review include the synthesis, structural characteristics, properties and applications of C(sp^2)‐centered homo‐ and hetero‐nuclear gold complexes according to different structural classifications.展开更多
基金supported by the National Science and Technology Major Project of China(2016ZX05066005-001)Zhejiang Province Key Research and Development Plan(2021C03152)Zhoushan Science and Technology Project(2021C21011)
文摘The liquid loading is one of the most frequently encountered phenomena in the transportation of gas pipeline,reducing the transmission efficiency and threatening the flow assurance.However,most of the traditional mechanism models are semi-empirical models,and have to be resolved under different working conditions with complex calculation process.The development of big data technology and artificial intelligence provides the possibility to establish data-driven models.This paper aims to establish a liquid loading prediction model for natural gas pipeline with high generalization ability based on machine learning.First,according to the characteristics of actual gas pipeline,a variety of reasonable combinations of working conditions such as different gas velocity,pipe diameters,water contents and outlet pressures were set,and multiple undulating pipeline topography with different elevation differences was established.Then a large number of simulations were performed by simulator OLGA to obtain the data required for machine learning.After data preprocessing,six supervised learning algorithms,including support vector machine(SVM),decision tree(DT),random forest(RF),artificial neural network(ANN),plain Bayesian classification(NBC),and K nearest neighbor algorithm(KNN),were compared to evaluate the performance of liquid loading prediction.Finally,the RF and KNN with better performance were selected for parameter tuning and then used to the actual pipeline for liquid loading location prediction.Compared with OLGA simulation,the established data-driven model not only improves calculation efficiency and reduces workload,but also can provide technical support for gas pipeline flow assurance.
基金sponsored by the National Natural Science Foundation of China(No.50973069)the Scientific Research Foundation for the Returned Overseas Chinese Scholars,State Education Ministry(No.20101561-3-3)
文摘Traditional modifications to hydroxyapatite （HA） nanoparticles usually occurred after HA synthesis and thus are insufficient to avoid particle agglomeration. In this study, a new heterofunctional poly（ethylene glycol） （PEG） with phosphoric acid and carboxyl end groups, Le., a-（N-2-phosphoethyl phosphoric acid）- amide, w-carboxyl-bismethyoxy poly（ethylene glycol） （ADP-PEG-COOH）, was synthesized as an in situ surface modifier to HA nanoparticles. The resulting modified HA （ADP-PEG-HA） can disperse in methanol, forming a colloid stabilized by peripheral carboxyl-endcapped PEG chains. The colloidal particles resembled nanospheres which agglomerated to some extent under examination by transmission electron microscope. This highly dispersible HA nanoparticles in organic solvent might find application in preparing new HA nanocomposites.
基金supported by the National Natural Science Foundation of China(Nos.21372059 and 21172051)the Hebei Key Basic Research(No.12966417D)+1 种基金the Hebei Natural Science Foundation(No.B2012201041)the Foundation of Hebei Education Department(No.YQ2013006)
文摘A series of novel, azasugar-modified 2-monosubstituted, 2,6- and 2,7-bissubstituted anthraquinone derivatives have been synthesized by the nucleophilic substitution of N-alkylamino azasugar with mono-, bis（2-chloroacetamido）anthraquinones. Their cytotoxic activities against HeLa and MCF-7 ceils were preliminarily evaluated and compound 9a with mono-azasugar pendant at 2-position showed similar activity to the control drug （Cisplatin）.
文摘C(sp^2)‐centered homo‐ and hetero‐nuclear gold complexes have attracted widespread interests in recent decades. Studies of this type of complexes may deepen the understandings of the intermediates in Au‐catalyzed organic reactions and explore new applications in catalytic and material science. The focuses of this review include the synthesis, structural characteristics, properties and applications of C(sp^2)‐centered homo‐ and hetero‐nuclear gold complexes according to different structural classifications.
