Background Understanding the volume fraction of water-oil-gas three-phase flow is of significant importance in oil and gas industry.Purpose The current research attempts to indicate the ability of adaptive network-bas...Background Understanding the volume fraction of water-oil-gas three-phase flow is of significant importance in oil and gas industry.Purpose The current research attempts to indicate the ability of adaptive network-based fuzzy inference system(ANFIS)to forecast the volume fractions in a water-oil-gas three-phase flow system.Method The current investigation devotes to measure the volume fractions in the stratified three-phase flow,on the basis of a dual-energy metering system consisting of the 152Eu and 137Cs and one NaI detector using ANFIS.The summation of volume fractions is equal to 100%and is also a constant,and this is enough for the ANFIS just to forecast two volume fractions.In the paper,three ANFIS models are employed.The first network is applied to forecast the oil and water volume fractions.The next to forecast the water and gas volume fractions,and the last to forecast the gas and oil volume fractions.For the next step,ANFIS networks are trained based on numerical simulation data from MCNP-X code.Results The accuracy of the nets is evaluated through the calculation of average testing error.The average errors are then compared.The model in which predictions has the most consistency with the numerical simulation results is selected as the most accurate predictor model.Based on the results,the best ANFIS net forecasts the water and gas volume fractions with the mean error of less than 0.8%.Conclusion The proposed methodology indicates that ANFIS can precisely forecast the volume fractions in a water-oil-gas three-phase flow system.展开更多
How to solve the hypersonic aerothermodynamics around large-scale uncontrolled spacecraft during falling disintegrated process from outer space to earth,is the key to resolve the problems of the uncontrolled Tiangong-...How to solve the hypersonic aerothermodynamics around large-scale uncontrolled spacecraft during falling disintegrated process from outer space to earth,is the key to resolve the problems of the uncontrolled Tiangong-No.1 spacecraft reentry crash.To study aerodynamics of spacecraft reentry covering various flow regimes,a Gas-Kinetic Unified Algorithm(GKUA)has been presented by computable modeling of the collision integral of the Boltzmann equation over tens of years.On this basis,the rotational and vibrational energy modes are considered as the independent variables of the gas molecular velocity distribution function,a kind of Boltzmann model equation involving in internal energy excitation is presented by decomposing the collision term of the Boltzmann equation into elastic and inelastic collision terms.Then,the gas-kinetic numerical scheme is constructed to capture the time evolution of the discretized velocity distribution functions by developing the discrete velocity ordinate method and numerical quadrature technique.The unified algorithm of the Boltzmann model equation involving thermodynamics non-equilibrium effect is presented for the whole range of flow regimes.The gas-kinetic massive parallel computing strategy is developed to solve the hypersonic aerothermodynamics with the processor cores 500~45,000 at least 80%parallel efficiency.To validate the accuracy of the GKUA,the hypersonic flows are simulated including the reentry Tiangong-1 spacecraft shape with the wide range of Knudsen numbers of 220~0.00005 by the comparison of the related results from the DSMC and N-S coupled methods,and the low-density tunnel experiment etc.For uncontrolling spacecraft falling problem,the finite-element algorithm for dynamic thermalforce coupling response is presented,and the unified simulation of the thermal structural response and the hypersonic flow field is tested on the Tiangong-1 shape under reentry aerodynamic environment.Then,the forecasting analysis platform of end-of-life largescale spacecraft flying track is established on the basis of ballistic computation combined with reentry aerothermodynamics and deformation failure/disintegration.展开更多
文摘Background Understanding the volume fraction of water-oil-gas three-phase flow is of significant importance in oil and gas industry.Purpose The current research attempts to indicate the ability of adaptive network-based fuzzy inference system(ANFIS)to forecast the volume fractions in a water-oil-gas three-phase flow system.Method The current investigation devotes to measure the volume fractions in the stratified three-phase flow,on the basis of a dual-energy metering system consisting of the 152Eu and 137Cs and one NaI detector using ANFIS.The summation of volume fractions is equal to 100%and is also a constant,and this is enough for the ANFIS just to forecast two volume fractions.In the paper,three ANFIS models are employed.The first network is applied to forecast the oil and water volume fractions.The next to forecast the water and gas volume fractions,and the last to forecast the gas and oil volume fractions.For the next step,ANFIS networks are trained based on numerical simulation data from MCNP-X code.Results The accuracy of the nets is evaluated through the calculation of average testing error.The average errors are then compared.The model in which predictions has the most consistency with the numerical simulation results is selected as the most accurate predictor model.Based on the results,the best ANFIS net forecasts the water and gas volume fractions with the mean error of less than 0.8%.Conclusion The proposed methodology indicates that ANFIS can precisely forecast the volume fractions in a water-oil-gas three-phase flow system.
基金The National Key Basic Research and Development Program(2014CB744100)and the National Natural Science Foundation of China(91530319 and 11325212)support the present researches in the design of the study and collection,analysis,and interpretation of data and in writing the manuscript.
文摘How to solve the hypersonic aerothermodynamics around large-scale uncontrolled spacecraft during falling disintegrated process from outer space to earth,is the key to resolve the problems of the uncontrolled Tiangong-No.1 spacecraft reentry crash.To study aerodynamics of spacecraft reentry covering various flow regimes,a Gas-Kinetic Unified Algorithm(GKUA)has been presented by computable modeling of the collision integral of the Boltzmann equation over tens of years.On this basis,the rotational and vibrational energy modes are considered as the independent variables of the gas molecular velocity distribution function,a kind of Boltzmann model equation involving in internal energy excitation is presented by decomposing the collision term of the Boltzmann equation into elastic and inelastic collision terms.Then,the gas-kinetic numerical scheme is constructed to capture the time evolution of the discretized velocity distribution functions by developing the discrete velocity ordinate method and numerical quadrature technique.The unified algorithm of the Boltzmann model equation involving thermodynamics non-equilibrium effect is presented for the whole range of flow regimes.The gas-kinetic massive parallel computing strategy is developed to solve the hypersonic aerothermodynamics with the processor cores 500~45,000 at least 80%parallel efficiency.To validate the accuracy of the GKUA,the hypersonic flows are simulated including the reentry Tiangong-1 spacecraft shape with the wide range of Knudsen numbers of 220~0.00005 by the comparison of the related results from the DSMC and N-S coupled methods,and the low-density tunnel experiment etc.For uncontrolling spacecraft falling problem,the finite-element algorithm for dynamic thermalforce coupling response is presented,and the unified simulation of the thermal structural response and the hypersonic flow field is tested on the Tiangong-1 shape under reentry aerodynamic environment.Then,the forecasting analysis platform of end-of-life largescale spacecraft flying track is established on the basis of ballistic computation combined with reentry aerothermodynamics and deformation failure/disintegration.
