At present,the optimization of the plunger mechanism is shale gas wells is mostly based on empirical methods,which lack a relevant rationale and often are not able to deal with the quick variations experienced by the ...At present,the optimization of the plunger mechanism is shale gas wells is mostly based on empirical methods,which lack a relevant rationale and often are not able to deal with the quick variations experienced by the production parameters of shale gas wells in comparison to conventional gas wells.In order to mitigate this issue,in the present work,a model is proposed to loosely couple the dynamics of gas inflow into shale gas wells with the dynamics of the liquid inflow.Starting from the flow law that accounts for the four stages of movement of the plunger,a dynamic model of the plunger lift based on the real wellbore trajectory is introduced.The model is then tested against 5 example wells,and it is shown that the accuracy level is higher than 90%.The well‘switch’,optimized on the basis of simulations based on such a model,is tested through on-site experiments.It is shown that,compared with the original switch configuration,the average production of the sample well can be increased by about 15%.展开更多
For accurate aeroelastic analysis,the unsteady rotor flowfield is solved by computational fluid dynamics(CFD)module based on RANS/Euler equations and moving-embedded grid system,while computational structural dynamics...For accurate aeroelastic analysis,the unsteady rotor flowfield is solved by computational fluid dynamics(CFD)module based on RANS/Euler equations and moving-embedded grid system,while computational structural dynamics(CSD)module is introduced to handle blade flexibility.In CFD module,dual time-stepping algorithm is employed in temporal discretization,Jameson two-order central difference(JST)scheme is adopted in spatial discretization and B-L turbulent model is used to illustrate the viscous effect.The CSD module is developed based on Hamilton′s variational principles and moderate deflection beam theory.Grid deformation is implemented using algebraic method through coordinate transformations to achieve deflections with high quality and efficiency.A CFD/CSD loose coupling strategy is developed to transfer information between rotor flowfield and blade structure.The CFD and the CSD modules are verified seperately.Then the CFD/CSD loose coupling is adopted in airloads prediction of UH-60A rotor under high speed forward flight condition.The calculated results agree well with test data.Finally,effects of torsional stiffness properties on airloads of rotors with different tip swept angles(from 10° forward to 30° backward)are investigated.The results are evaluated through pressure distribution and airloads variation,and some meaningful conclusions are drawn the moderated shock wave strength and pressure gradient caused by varied tip swept angle and structural properties.展开更多
The simulations and potential forecasting of dust storms are of significant interest to public health and environment sciences.Dust storms have interannual variabilities and are typical disruptive events.The computing...The simulations and potential forecasting of dust storms are of significant interest to public health and environment sciences.Dust storms have interannual variabilities and are typical disruptive events.The computing platform for a dust storm forecasting operational system should support a disruptive fashion by scaling up to enable high-resolution forecasting and massive public access when dust storms come and scaling down when no dust storm events occur to save energy and costs.With the capability of providing a large,elastic,and virtualized pool of computational resources,cloud computing becomes a new and advantageous computing paradigm to resolve scientific problems traditionally requiring a large-scale and high-performance cluster.This paper examines the viability for cloud computing to support dust storm forecasting.Through a holistic study by systematically comparing cloud computing using Amazon EC2 to traditional high performance computing(HPC)cluster,we find that cloud computing is emerging as a credible solution for(1)supporting dust storm forecasting in spinning off a large group of computing resources in a few minutes to satisfy the disruptive computing requirements of dust storm forecasting,(2)performing high-resolution dust storm forecasting when required,(3)supporting concurrent computing requirements,(4)supporting real dust storm event forecasting for a large geographic domain by using recent dust storm event in Phoniex,05 July 2011 as example,and(5)reducing cost by maintaining low computing support when there is no dust storm events while invoking a large amount of computing resource to perform high-resolution forecasting and responding to large amount of concurrent public accesses.展开更多
基金The authors would like to acknowledge the National Natural Science Fund Project(62173049)for Key Projectthe Open Fund Project“Study on Transient Flow Mechanism of Fluid Accumulation in Shale Gas Wells”of the Sinopec Key Laboratory of Shale Oil/Gas Exploration and Production Technology.
文摘At present,the optimization of the plunger mechanism is shale gas wells is mostly based on empirical methods,which lack a relevant rationale and often are not able to deal with the quick variations experienced by the production parameters of shale gas wells in comparison to conventional gas wells.In order to mitigate this issue,in the present work,a model is proposed to loosely couple the dynamics of gas inflow into shale gas wells with the dynamics of the liquid inflow.Starting from the flow law that accounts for the four stages of movement of the plunger,a dynamic model of the plunger lift based on the real wellbore trajectory is introduced.The model is then tested against 5 example wells,and it is shown that the accuracy level is higher than 90%.The well‘switch’,optimized on the basis of simulations based on such a model,is tested through on-site experiments.It is shown that,compared with the original switch configuration,the average production of the sample well can be increased by about 15%.
文摘For accurate aeroelastic analysis,the unsteady rotor flowfield is solved by computational fluid dynamics(CFD)module based on RANS/Euler equations and moving-embedded grid system,while computational structural dynamics(CSD)module is introduced to handle blade flexibility.In CFD module,dual time-stepping algorithm is employed in temporal discretization,Jameson two-order central difference(JST)scheme is adopted in spatial discretization and B-L turbulent model is used to illustrate the viscous effect.The CSD module is developed based on Hamilton′s variational principles and moderate deflection beam theory.Grid deformation is implemented using algebraic method through coordinate transformations to achieve deflections with high quality and efficiency.A CFD/CSD loose coupling strategy is developed to transfer information between rotor flowfield and blade structure.The CFD and the CSD modules are verified seperately.Then the CFD/CSD loose coupling is adopted in airloads prediction of UH-60A rotor under high speed forward flight condition.The calculated results agree well with test data.Finally,effects of torsional stiffness properties on airloads of rotors with different tip swept angles(from 10° forward to 30° backward)are investigated.The results are evaluated through pressure distribution and airloads variation,and some meaningful conclusions are drawn the moderated shock wave strength and pressure gradient caused by varied tip swept angle and structural properties.
基金Research reported is supported by NSF(CSR-1117300 and IIP-1160979)NASA(NNX07AD99G)Microsoft Research.
文摘The simulations and potential forecasting of dust storms are of significant interest to public health and environment sciences.Dust storms have interannual variabilities and are typical disruptive events.The computing platform for a dust storm forecasting operational system should support a disruptive fashion by scaling up to enable high-resolution forecasting and massive public access when dust storms come and scaling down when no dust storm events occur to save energy and costs.With the capability of providing a large,elastic,and virtualized pool of computational resources,cloud computing becomes a new and advantageous computing paradigm to resolve scientific problems traditionally requiring a large-scale and high-performance cluster.This paper examines the viability for cloud computing to support dust storm forecasting.Through a holistic study by systematically comparing cloud computing using Amazon EC2 to traditional high performance computing(HPC)cluster,we find that cloud computing is emerging as a credible solution for(1)supporting dust storm forecasting in spinning off a large group of computing resources in a few minutes to satisfy the disruptive computing requirements of dust storm forecasting,(2)performing high-resolution dust storm forecasting when required,(3)supporting concurrent computing requirements,(4)supporting real dust storm event forecasting for a large geographic domain by using recent dust storm event in Phoniex,05 July 2011 as example,and(5)reducing cost by maintaining low computing support when there is no dust storm events while invoking a large amount of computing resource to perform high-resolution forecasting and responding to large amount of concurrent public accesses.
