A numerical method is developed to obtain two-dimensional velocity and pressure distribution through a cylindrical pipe with cross jet flows. The method is based on solving partial differential equations for the conservation of mass and momentum by finite difference method to convert them into algebraic equations. This well-known problem is used to introduce the basic concepts of CFD including: the finite- difference mesh, the discrete nature of the numerical solution, and the dependence of the result on the mesh refinement. Staggered grid implementation of the numerical model is used. The set of algebraic equations is solved simultaneously by “SIMPLE” algorithm to obtain velocity and pressure distribution within a pipe. In order to

Heat transfer process and fluid flow in a solar chimney used for natural ventilation are investigated numerically in the present work. Solar chimney was tested by selecting different positions of absorber namely: at the back side, front side, and at the middle of the air gap. CFD analysis based on finite volume method is used to predict the thermal performance, and air flow in two dimensional solar chimney under unsteady state condition, to identify the effect of different parameters such as solar radiation. Results show that a solar chimney with absorber at the middle of the air gap gives better ventilation performance. A comparison between the numerical and previous experimental results shows fair agreement.

      Negotiations are distinguished in that they are an easy and simple means between the conflicting parties, and it is an effective means at the same time as the conflicting parties seek understanding on the most effective way to solve their dispute, but negotiations are not always appropriate to resolve international disputes, especially when there is a disparity in power between the negotiating countries, or when it is missing Goodwill, or even when one of the parties is absent or less flexible, and the internal circumstances of one of the conflicting countries may play a negative or positive role in the success of the negotiations, away from the influence of the role of external variables in that, a

Abstract

Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n^-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.

A range of batch experiments were carried out for the estimation of the key process parameters in adsorption of Furfural from aqueous solution onto activated carbon in fixed-bed adsorber. A batch absorber model has been used to determine the external mass transfer coefficient (kf) which equal to 6.24*10-5 m/s and diffusion coefficient (Dp) which equal to 9.875*10-10 m2/s for the Furfural system. The Langmuir model gave the best fit for the data at constant temperature (30oC). The pore diffusion mathematical model using nonlinear isotherm provides a good description of the adsorption of Furfural onto activated carbon.

Due to its importance in physics and applied mathematics, the non-linear Sturm-Liouville problems
witnessed massive attention since 1960. A powerful Mathematical technique called the Newton-Kantorovich
method is applied in this work to one of the non-linear Sturm-Liouville problems. To the best of the authors’
knowledge, this technique of Newton-Kantorovich has never been applied before to solve the non-linear
Sturm-Liouville problems under consideration. Accordingly, the purpose of this work is to show that this
important specific kind of non-linear Sturm-Liouville differential equations problems can be solved by
applying the well-known Newton-Kantorovich method. Also, to show the efficiency of appl

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to