Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : Modelling


Neural Network Modelling of Tds Concentrations in Shatt Al-Arab River Water

Ahmed Naseh Ahmed; Ammar S. Dawood

Engineering and Technology Journal, 2016, Volume 34, Issue 2, Pages 334-345

River water salinity is a big concern in many countries, considering agricultural and drinking usages. Therefore, prediction of amount of Total Dissolved Solid (TDS) is a necessary tool for planning and management of water resources. Shatt Al-Arab river basin in Basrah which is located in south of Iraq suffer from high salinity, therefore use of the water for irrigation and drinking has become problematic. In this regard, prediction of future TDS of Shatt Al-Arab river basin was studied using Artificial Neural Network (ANN).
Data measured monthly from January 2007 up to December 2012 at monitoring station in the middle point along to the Shatt Al-Arab river has been used for training of the selected ANN.
Some of water quality parameters such as, power of hydrogen (pH), Total Hardness (TH), Magnesium hardness (MgSO4), Calcium hardness (CaSO4), Chlorides (Cl), Sulphates (SO4), turbidity (TU) and electrical conductivity (EC) were considered as inputs for the ANN and Total Dissolved Solid (TDS) was the output of the model.
The validation of the neural network model showed very good agreement for predictions of the TDS concentrations between observed and simulated values.
The coefficient of correlation (R), during the validation process was found to be (1), and the mean squared error (MSE) was (0.075). This work supports the concept that the neural network approach is a successful method of modelling such complex and nonlinear behavior of TDS in the rivers with different environmental conditions.

Unscented Kalman Estimator for Estimating the State of Two-phase Permanent Magnet Synchronous Motor

Ayad Qasim Hussein

Engineering and Technology Journal, 2010, Volume 28, Issue 15, Pages 5071-5078

This paper presents the unscented Kalman filters (UKF) for estimating the states (winding currents, rotor speed and rotor angular position) of two-phase Permanent Magnet Synchronous Motor (PMSM). The UKF is based on firstly specifying a minimal set of carefully chosen sample points. These sample points completely capture the true mean and covariance of the Gaussian Random Variable (GRV), and when propagated through the true nonlinear system (motor model), capture the posterior mean and covariance accurately to the second order (Taylor series expansion). The results showed that the UK estimator could successively estimate the states of PMSM without need any Jacobian matrix.

State Estimation of Two-Phase Permanent Magnet Synchronous Motor

Amjed J. Hamidi; Ahmed Alaa Ogla; Yaser Nabeel Ibrahem

Engineering and Technology Journal, 2009, Volume 27, Issue 7, Pages 1435-1443

The goal of this paper is to estimate the states of two-phase permanent magnet synchronous
motor (PMSM). The system is highly nonlinear and one therefore cannot directly use any linear
system tools for estimation. However, if one can linearize the system around a nominal
(possibly time-varying) operating point then linear system tools could be used for control and
estimation. Firstly, the error covariance matrices of measurement and process would be derived
when the system inputs and outputs are subjected to uncertain variations. Then, the corruptednoise
nonlinear model of the system will be discretized and extended to be suitable for applying
standard discrete Kalman filter (KF) for state estimation purpose. The entire state estimated
system has been modeled using MATLAB/SIMULINK blocks. The state estimation algorithm
and the motor discretized model are coded inside special S-functions of m-file type.

Numerical Study of Forced Convection in Wavy and Diverged-Converged Ducts

Anmar M. Basheer; Sattar J. Habeeb; Waheed S. Mohamad; Qutaiba G. Majeed; Mohammed Y. Fattah; Jawad K.Oleiwi; Mohammed S. Hamza; Mayyadah Sh. Abed; Amjed J. Hamidi; Ahmed Alaa Ogla; Yaser Nabeel Ibrahem

Engineering and Technology Journal, 2009, Volume 27, Issue 7, Pages 1385-1403

A three-dimensional study of developing fluid flow and heat transfer through
wavy and diverged-converged ducts were studied numerically for a Prandlt number 0.7
and 5.85 and compared with flow through corresponding straight duct. The Navier-
Stokes and energy equations are solved by using control finite volume method.
Development of the Nusselt number in wavy and diverged-converged ducts are
presented for different flow rates (50

Keywords

forced convection
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numerical study
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wavy duct
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diverged-converged duct

Indirect Field Orientation Control of Induction Machine with Detuning Effect

Rami A. Mahir; Ziad M. Ahmed; Amjad J. H

Engineering and Technology Journal, 2008, Volume 26, Issue 2, Pages 265-277

Field orientation control (FOC) methods of an induction machine achieve
decoupled torque and flux dynamics leading to independent control of torque and
flux as for separately excited DC motor, but they are sensitive to motor parameter
variations. The has present work selects the indirect field orientation control
(IFOC) as an effective method for eliminating the coupling effect. The results
show how well the drive performance has been improved by this control strategy.
However, to which extent the control strategy can perform the decoupling relies on
the accuracy of the slip frequency calculation. Unfortunately, the slip frequency
depends on the rotor time constant that varies continuously according to the
operational conditions and, then, the coupling effect may again arise.
This paper investigates the improvement in the performance of the
induction machine dynamics as the IFOC technique is utilized, also, it
investigatesthe degradation in dynamic performance when the rotor resistance is
deviated from its nominal value.