In this paper, solutions to the 3D transient flow mathematical model for horizontal wells in box-rounded reservoirs are presented. The solutions are derived in Laplace transform domain by employing integral transform ...In this paper, solutions to the 3D transient flow mathematical model for horizontal wells in box-rounded reservoirs are presented. The solutions are derived in Laplace transform domain by employing integral transform and point-source superposition. Both efficient computation of pressure responses and practical technology of oil field application mentioned here may be used to interpret the data from unsteady-state horizontal well testing.展开更多
In this paper, we consider an SIR-model for which the interaction term is the square root of the susceptible and infected individuals in the form of fractional order differential equations. First the non-negative solu...In this paper, we consider an SIR-model for which the interaction term is the square root of the susceptible and infected individuals in the form of fractional order differential equations. First the non-negative solution of the model in fractional order is presented. Then the local stability analysis of the model in fractional order is discussed. Finally, the general solutions are presented and a discrete-time finite difference scheme is constructed using the nonstandard finite difference (NSFD) method. A comparative study of the classical Runge-Kutta method and ODE45 is presented in the case of integer order derivatives. The solutions obtained are presented graphically.展开更多
The work address the problem of modeling the dynamical oscillating behavior during both unstable and stable operations, of an experimental thermosyphon. A standard RBF artificial neural network-based prediction model ...The work address the problem of modeling the dynamical oscillating behavior during both unstable and stable operations, of an experimental thermosyphon. A standard RBF artificial neural network-based prediction model was developed for predicting the oscillating heat transfer of thermosyphon by means of input-output experimental measurements with the characteristics of time series. A comparison of prediction values between the RBF network and the MLP network was giving.The precision of RBF network was higher than that of the other neural networks such as BP-MLP network etc . The dynamical model of RBF network could be used to describe, predict and control the heat transfer process of a thermosyphon or a heat pipe system.展开更多
文摘In this paper, solutions to the 3D transient flow mathematical model for horizontal wells in box-rounded reservoirs are presented. The solutions are derived in Laplace transform domain by employing integral transform and point-source superposition. Both efficient computation of pressure responses and practical technology of oil field application mentioned here may be used to interpret the data from unsteady-state horizontal well testing.
文摘In this paper, we consider an SIR-model for which the interaction term is the square root of the susceptible and infected individuals in the form of fractional order differential equations. First the non-negative solution of the model in fractional order is presented. Then the local stability analysis of the model in fractional order is discussed. Finally, the general solutions are presented and a discrete-time finite difference scheme is constructed using the nonstandard finite difference (NSFD) method. A comparative study of the classical Runge-Kutta method and ODE45 is presented in the case of integer order derivatives. The solutions obtained are presented graphically.
文摘The work address the problem of modeling the dynamical oscillating behavior during both unstable and stable operations, of an experimental thermosyphon. A standard RBF artificial neural network-based prediction model was developed for predicting the oscillating heat transfer of thermosyphon by means of input-output experimental measurements with the characteristics of time series. A comparison of prediction values between the RBF network and the MLP network was giving.The precision of RBF network was higher than that of the other neural networks such as BP-MLP network etc . The dynamical model of RBF network could be used to describe, predict and control the heat transfer process of a thermosyphon or a heat pipe system.
