In this paper investigate the influences of dissolved CO₂/H₂S gases, crude oil velocity and temperature on the rate of corrosion of crude oil transmission pipelines of Maysan oil fields southern Iraq. The Potentiostatic corrosion test technique was conducted into two types of carbon steel pipeline (materials API 5L X60 and API 5L X80). The computer software ECE electronic corrosion engineer was used to predict the influences of CO₂ partial pressure, the composition of crude oil, flow velocity of crude oil and percentage of material elements of carbon steel on the rate of corrosion. As a result, the carbon steel API 5L X80 indicates good and appropriate resistance to corrosion compared to carbon steel API

This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

A theoretical study has been proposed to investigate the effects of different laser radiations (Nd - glass, DF and C02) as a heating source on different glass samples (Optical glass, Bk - 7 and Soda - lime glass) and different waves lengths (10.6, 3.8, 1.6) ???. The heat changes as which are resulted due irradiation with laser sources have been determined by using the one dimension mathematical relation as a function of time (t) and depth (z). The results of the study show ed that the irradiation with C02 laser had a greater effect than DF laser, while the effects of Nd - glass laser were minimal with a power density of (1.8*10?? w/m2) within atime(l^sec).(Forboth Kinds) The change in the temperatures were not exceeded than (70"K) in all sa

In this review of literature, the light will be concentrated on the local drugs delivery systems for treating the periodontal diseases. Principles, types, advantages and indications of each type will be discussed in this paper.