In this paper, the convergence turbulent flow equations are considered. By rates of solutions to the three-dimensional combining the LP-Lq estimate for the linearized equations and an elaborate energy method, the conv...In this paper, the convergence turbulent flow equations are considered. By rates of solutions to the three-dimensional combining the LP-Lq estimate for the linearized equations and an elaborate energy method, the convergence rates are obtained in various norms for the solution to the equilibrium state in the whole space when the initial perturbation of the equilibrium state is small in the H3-framework. More precisely, the optimal convergence rates of the solutions and their first-order derivatives in the L2-norm are obtained when the LP-norm of the perturbation is bounded for some p ε [1, 6）.展开更多
The Sulige tight gas reservoir is characterized by low-pressure, low-permeability and lowabundance. During production, gas flow rate and reservoir pressure decrease sharply; and in the shut- in period, reservoir press...The Sulige tight gas reservoir is characterized by low-pressure, low-permeability and lowabundance. During production, gas flow rate and reservoir pressure decrease sharply; and in the shut- in period, reservoir pressure builds up slowly. Many conventional methods, such as the indicative curve method, systematic analysis method and numerical simulation, are not applicable to determining an appropriate gas flow rate. Static data and dynamic performance show permeability capacity, kh is the most sensitive factor influencing well productivity, so criteria based on kh were proposed to classify vertical wells. All gas wells were classified into 4 groups. A multi-objective fuzzy optimization method, in which dimensionless gas flow rate, period of stable production, and recovery at the end of the stable production period were selected as optimizing objectives, was established to determine the reasonable range of gas flow rate. In this method, membership functions of above-mentioned optimizing factors and their weights were given. Moreover, to simplify calculation and facilitate field use, a simplified graphical illustration （or correlation） was given for the four classes of wells. Case study illustrates the applicability of the proposed method and graphical correlation, and an increase in cumulative gas production up to 37% is achieved and the well can produce at a constant flow rate for a long time.展开更多
Oilfield treated oil pipeline network is the link connecting the upstream oilfields and the downstream refineries.Due to the differences in operating costs and transportation fee between different pipelines and the fl...Oilfield treated oil pipeline network is the link connecting the upstream oilfields and the downstream refineries.Due to the differences in operating costs and transportation fee between different pipelines and the fluctuation in the demand and sales prices of the treated oil,there is an optimal flow allocation plan for the pipeline network to make the oilfield company obtain the highest social and economic benefit.In this study,a mixed integer nonlinear programming(MINLP)model is developed to determine the optimal flow rate allocation plan of the large-scale and complex treated oil pipeline network,and both the social and economic benefits are considered simultaneously.The optimization objective is the multi-objective which includes the largest user satisfaction and the highest economic benefit.The model constraints include the oilfield production capacity,refinery demand,pipeline transmission capacity,flow,pressure,and temperature of the node and station,and the pipeline hydraulic and thermal calculations.Python 3.7 is utilized for the programming of the off-line calculation procedure and the MINLP model,and GUROBI 9.0.2 is served as the MINLP solver.Moreover,the model is applied to a real treated oil pipeline network located in China,and three optimization scenarios are analyzed.For social benefit,the values of the user satisfaction of each refinery and the total network are 1 before and after optimization for scenarios 1,2,and 3.For economic benefit,the annual revenue can be increased by 0.227,0.293,and 0.548 billion yuan after the optimization in scenario 1,2,and 3,respectively.展开更多
The application of a novel Particle Swarm Optimization (PSO) method called Fitness Distance Ratio PSO (FDR PSO) algorithm is described in this paper to determine the optimal power dispatch of the Independent Power Pro...The application of a novel Particle Swarm Optimization (PSO) method called Fitness Distance Ratio PSO (FDR PSO) algorithm is described in this paper to determine the optimal power dispatch of the Independent Power Producers (IPP) with linear ramp model and transient stability constraints of the power producers. Generally the power producers must respond quickly to the changes in load and wheeling transactions. Moreover, it becomes necessary for the power producers to reschedule their power generation beyond their power limits to meet vulnerable situations like credible contingency and increase in load conditions. During this process, the ramping cost is incurred if they violate their permissible elastic limits. In this paper, optimal production costs of the power producers are computed with stepwise and piecewise linear ramp rate limits. Transient stability limits of the power producers are also considered as addi-tional rotor angle inequality constraints while solving the Optimal Power Flow (OPF) problem. The proposed algo-rithm is demonstrated on practical 10 bus and 26 bus systems and the results are compared with other optimization methods.展开更多
This paper is a redevelopment result of liftoff rates of saltating sand grains based on our previous work.Aeolian sand flow is a complex multi-phase flow because of a special two-phase gas-solid flow near ground surfa...This paper is a redevelopment result of liftoff rates of saltating sand grains based on our previous work.Aeolian sand flow is a complex multi-phase flow because of a special two-phase gas-solid flow near ground surface.Despite extensive research on the movement of blowing sand,no model fully characterizes aeolian sand flow,and large differences often exist between simulations of aeolian sand movement and field observations.One key problem is a few of sufficient research on liftoff rates of saltating sand grains(also called the number of liftoff sand grains per unit time and per unit bed area).It is necessary to re-search in advance liftoff rates of saltating sand grains.We redeveloped liftoff rates of saltating sand grains by establishing an optimization model based on the flux of aeolian sand flow at different heights of the sampler in wind tunnel and the simulated capture of saltating sand grains by different heights of the sampler that are from different liftoff position(distance from the sampler) in order to revise previous inversion condition of liftoff rates of saltating sand grains.Liftoff rates increased rapidly with increasing wind speed.For frictional wind velocities of u=0.67,0.77,0.82,0.83,and 0.87 m s-1,liftoff rates were 3840,954502,5235114,5499407,and 7696291 sand grain s-1 m-2,respectively.These rates could be expressed as the square of the instantaneous frictional wind velocity and a constant(0.663) that differs from the critical(threshold) frictional wind velocity at which saltation begins.Although our results require additional experimental validation and the simple optimization model must be improved,they nonetheless provide a strong basis for future research.展开更多
基金supported by the National Natural Science Foundation of China(Nos.11071057 and 11271052)the Special Fund Project of Mathematical Tian Yuan Fund(No.11226029)
文摘In this paper, the convergence turbulent flow equations are considered. By rates of solutions to the three-dimensional combining the LP-Lq estimate for the linearized equations and an elaborate energy method, the convergence rates are obtained in various norms for the solution to the equilibrium state in the whole space when the initial perturbation of the equilibrium state is small in the H3-framework. More precisely, the optimal convergence rates of the solutions and their first-order derivatives in the L2-norm are obtained when the LP-norm of the perturbation is bounded for some p ε [1, 6）.
基金National Natural Science Foundation of China (NO. Z02047)CNPC Program (NO.Z03014).
文摘The Sulige tight gas reservoir is characterized by low-pressure, low-permeability and lowabundance. During production, gas flow rate and reservoir pressure decrease sharply; and in the shut- in period, reservoir pressure builds up slowly. Many conventional methods, such as the indicative curve method, systematic analysis method and numerical simulation, are not applicable to determining an appropriate gas flow rate. Static data and dynamic performance show permeability capacity, kh is the most sensitive factor influencing well productivity, so criteria based on kh were proposed to classify vertical wells. All gas wells were classified into 4 groups. A multi-objective fuzzy optimization method, in which dimensionless gas flow rate, period of stable production, and recovery at the end of the stable production period were selected as optimizing objectives, was established to determine the reasonable range of gas flow rate. In this method, membership functions of above-mentioned optimizing factors and their weights were given. Moreover, to simplify calculation and facilitate field use, a simplified graphical illustration （or correlation） was given for the four classes of wells. Case study illustrates the applicability of the proposed method and graphical correlation, and an increase in cumulative gas production up to 37% is achieved and the well can produce at a constant flow rate for a long time.
基金the Natural Science Foundation of Chongqing,China (No.cstc2021jcyj-msxmX0918)the Science and Technology Research Program of Chongqing Municipal Education Commission (No.KJQN202101545)+1 种基金the National Natural Science Foundation of China (52302402)the Research Foundation of Chongqing University of Science and Technology (ckrc2021003)for providing support for this work.
文摘Oilfield treated oil pipeline network is the link connecting the upstream oilfields and the downstream refineries.Due to the differences in operating costs and transportation fee between different pipelines and the fluctuation in the demand and sales prices of the treated oil,there is an optimal flow allocation plan for the pipeline network to make the oilfield company obtain the highest social and economic benefit.In this study,a mixed integer nonlinear programming(MINLP)model is developed to determine the optimal flow rate allocation plan of the large-scale and complex treated oil pipeline network,and both the social and economic benefits are considered simultaneously.The optimization objective is the multi-objective which includes the largest user satisfaction and the highest economic benefit.The model constraints include the oilfield production capacity,refinery demand,pipeline transmission capacity,flow,pressure,and temperature of the node and station,and the pipeline hydraulic and thermal calculations.Python 3.7 is utilized for the programming of the off-line calculation procedure and the MINLP model,and GUROBI 9.0.2 is served as the MINLP solver.Moreover,the model is applied to a real treated oil pipeline network located in China,and three optimization scenarios are analyzed.For social benefit,the values of the user satisfaction of each refinery and the total network are 1 before and after optimization for scenarios 1,2,and 3.For economic benefit,the annual revenue can be increased by 0.227,0.293,and 0.548 billion yuan after the optimization in scenario 1,2,and 3,respectively.
文摘The application of a novel Particle Swarm Optimization (PSO) method called Fitness Distance Ratio PSO (FDR PSO) algorithm is described in this paper to determine the optimal power dispatch of the Independent Power Producers (IPP) with linear ramp model and transient stability constraints of the power producers. Generally the power producers must respond quickly to the changes in load and wheeling transactions. Moreover, it becomes necessary for the power producers to reschedule their power generation beyond their power limits to meet vulnerable situations like credible contingency and increase in load conditions. During this process, the ramping cost is incurred if they violate their permissible elastic limits. In this paper, optimal production costs of the power producers are computed with stepwise and piecewise linear ramp rate limits. Transient stability limits of the power producers are also considered as addi-tional rotor angle inequality constraints while solving the Optimal Power Flow (OPF) problem. The proposed algo-rithm is demonstrated on practical 10 bus and 26 bus systems and the results are compared with other optimization methods.
基金supported by National Natural Science Foundation of China (Grant Nos.40601011,10532030)Key Technology Research and Development Program of China (Grant No.2006BAD26B03)+1 种基金the Beijing Nova Program (Grant No.2006A31)State Key Laboratory of Earth Surface Processes and Resource Ecology (Grant No.2008-ZY-02)
文摘This paper is a redevelopment result of liftoff rates of saltating sand grains based on our previous work.Aeolian sand flow is a complex multi-phase flow because of a special two-phase gas-solid flow near ground surface.Despite extensive research on the movement of blowing sand,no model fully characterizes aeolian sand flow,and large differences often exist between simulations of aeolian sand movement and field observations.One key problem is a few of sufficient research on liftoff rates of saltating sand grains(also called the number of liftoff sand grains per unit time and per unit bed area).It is necessary to re-search in advance liftoff rates of saltating sand grains.We redeveloped liftoff rates of saltating sand grains by establishing an optimization model based on the flux of aeolian sand flow at different heights of the sampler in wind tunnel and the simulated capture of saltating sand grains by different heights of the sampler that are from different liftoff position(distance from the sampler) in order to revise previous inversion condition of liftoff rates of saltating sand grains.Liftoff rates increased rapidly with increasing wind speed.For frictional wind velocities of u=0.67,0.77,0.82,0.83,and 0.87 m s-1,liftoff rates were 3840,954502,5235114,5499407,and 7696291 sand grain s-1 m-2,respectively.These rates could be expressed as the square of the instantaneous frictional wind velocity and a constant(0.663) that differs from the critical(threshold) frictional wind velocity at which saltation begins.Although our results require additional experimental validation and the simple optimization model must be improved,they nonetheless provide a strong basis for future research.
