The distribution of droplet surface pressure is uneven?under the action of high velocity gas streams in gas wells, and there exists a pressure difference which leads to droplet deformation before and after the droplet...The distribution of droplet surface pressure is uneven?under the action of high velocity gas streams in gas wells, and there exists a pressure difference which leads to droplet deformation before and after the droplet. Moreover, it affects the critical liquid carrying rate. The pressure difference prediction model must be determined, because of the existing one lacking theoretical basis. Based on the droplet surface pressure distribution in high velocity gas streams, a new model is established to predict the average differential pressure of droplets. Compared with the new differential pressure prediction results, the existing pressure difference prediction results were overvalued by 46.0%. This article also improves four gas-well critical liquid carrying models using the proposed pressure difference prediction model, and compares with the original one. The result indicates that the critical velocity of the original models is undervalued by 10% or so, due to the overestimate to the pressuredifference. In addition, comparisons of the improved model with original models show that it is necessary to consider the adaptability, because the models have significant differences in results, and different suitability for different well conditions.展开更多
In this article,a procedure for estimating the coefficient functions on the functional-coefficient regression models with different smoothing variables in different coefficient functions is defined.First step,by the l...In this article,a procedure for estimating the coefficient functions on the functional-coefficient regression models with different smoothing variables in different coefficient functions is defined.First step,by the local linear technique and the averaged method,the initial estimates of the coefficient functions are given.Second step,based on the initial estimates,the efficient estimates of the coefficient functions are proposed by a one-step back-fitting procedure.The efficient estimators share the same asymptotic normalities as the local linear estimators for the functional-coefficient models with a single smoothing variable in different functions.Two simulated examples show that the procedure is effective.展开更多
文摘The distribution of droplet surface pressure is uneven?under the action of high velocity gas streams in gas wells, and there exists a pressure difference which leads to droplet deformation before and after the droplet. Moreover, it affects the critical liquid carrying rate. The pressure difference prediction model must be determined, because of the existing one lacking theoretical basis. Based on the droplet surface pressure distribution in high velocity gas streams, a new model is established to predict the average differential pressure of droplets. Compared with the new differential pressure prediction results, the existing pressure difference prediction results were overvalued by 46.0%. This article also improves four gas-well critical liquid carrying models using the proposed pressure difference prediction model, and compares with the original one. The result indicates that the critical velocity of the original models is undervalued by 10% or so, due to the overestimate to the pressuredifference. In addition, comparisons of the improved model with original models show that it is necessary to consider the adaptability, because the models have significant differences in results, and different suitability for different well conditions.
文摘In this article,a procedure for estimating the coefficient functions on the functional-coefficient regression models with different smoothing variables in different coefficient functions is defined.First step,by the local linear technique and the averaged method,the initial estimates of the coefficient functions are given.Second step,based on the initial estimates,the efficient estimates of the coefficient functions are proposed by a one-step back-fitting procedure.The efficient estimators share the same asymptotic normalities as the local linear estimators for the functional-coefficient models with a single smoothing variable in different functions.Two simulated examples show that the procedure is effective.
