The aerodynamic characteristics of the forward swept wing aircraft have been studied theoretically and experimentally. Low order panel method with the Dirichlet boundary condition have been used to solve the case of the steady, inviscid and compressible flow. Experimentally, a model was manufactured from wood to carry out the tests. The primary objective of the experimental work was the measurements of the wake dimensions and orientation, velocity defect along the wake and the wake thickness. A blower type low speed (open jet) wind tunnel was used in the experimental work. The mean velocity at the test section was (9.3 m/s) and the Reynolds number based on the mean aerodynamic chord and the mean velocity was (0.46x105). The measurements showed the existence of a three-dimensionality behavior in the wake flow field. Interference between the canard wake and the wing wake was observed. The canard effect on the wing root area was detected as the separation at the wing root was delayed due to the canard downwash. The aerodynamic coefficients for the forward swept wing aircraft were calculated using the measured wake shape from the experimental work. Numerical results showed that the canard extended the range of the angle of attack for the aircraft with a significant improvement for the lift curve slope compared to the aircraft without the canard.
The research addresses the role of the digital economy in the growth of the Iraqi economy during the period from 2010 to 2022. The research is based on the hypothesis that the digital economy has become one of the primary growth drivers worldwide and has a close relationship with economic development. Therefore, the digital transformation in Iraq can accelerate bridging developmental gaps with other countries.
It has become evident that the Iraqi economy suffers from structural imbalances for various reasons, hindering economic growth. These reasons include political and economic factors, as well as the absence of a well-thought-out policy to promote the agricultural sector, which is considered one of the fundamental sectors capa
... Show MoreThis work was conducted to study the ability of locally prepared Zeolite NaY for the reduction of sulfur compounds from Iraqi natural gas by a continuous mode adsorption unit. Zeolite Y was hydrothermally synthesized using abundant kaolin clay as aluminum precursor. Characterization was made using chemical analysis, XRD and BET surface area. Results of the adsorption experiments showed that zeolite Y is an active adsorbent for removal H2S from natural gas and other gas streams. The effect of temperature was found inversely related to the removal efficiency. Increasing bed height was found to increase the removal efficiency at constant flow rate of natural gas. The adsorption capacity was evaluated and its maximum uptake was 5.345 mg H2S/g z
... Show MoreThe responsibility of the Central Bank through the implementation of its monetary policy to maintain the integrity and stability of the financial system and the economic system, because any shock, whether internal or external, may endanger the financial system and instability, so the research sheds light on the effectiveness of monetary policy in maintaining financial stability, The most important conclusion is that there is an increase in capital, which gives banks the possibility to face the risks to which they are exposed, as well as a rise in the total bad debts, which weakens its financial position, which constitutes a decline in the financial stability of these banks.
The study aimed to identify the degree of academic leaders practices at the University of Northern Border for creative leadership, which attribute to different variables (nature of work, employer, gender, years of experience in administrative work at the university). To achieve the goal of the study, the researcher used the descriptive approach survey. Therefore, the researcher used a questionnaire as a study tool, which consisted of (40) items that included dimensions (sensitivity to problems, initiative, originality, flexibility). The study sample consisted of (240) participants included (agents of colleges, and supporting deanships, and their employees) during the second semester of the academic year 1439/1440 AH. The results showed t
... Show MoreThis paper attempts to shed light on the most influential factors in the importance of religious buildings were destroyed because of the recent war due to the control of terrorist gangs of ISIS over the city of Mosul, and to prioritize their reconstruction and their role in reviving the historical center of Mosul.
The research’s problem emerged in the lack of knowledge about the identifying the most influential factors in the importance of religious buildings and utilizing them to prioritize their reconstruction. This study aims to analyze the factors influencing the importance of religious buildings using the Expert Choice software through the Analytic Hierarchy Process (AHP) to reach an analysis of their weights and propose p
... Show MoreThe current study aims at identifying the impact of using learning acceleration model on the achievement of mathematics for third intermediategrade students. Forachieving this, the researchers chose the School (Al-Kholood Secondary School for Girls) affiliated to the General Directorate of Babylon Education / Hashemite Education Department for the academic year (2021/2021), The sample reached to (70) female students from the third intermediate grade, with (35) female students for each of the two research groups. The two researchers prepared an achievement test consisting of (25) objective items of multiple choice type, The psychometric properties of the test were confirmed, and after the completion of the experiment, the achievement test wa
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In this work, a novel technique to obtain an accurate solutions to nonlinear form by multi-step combination with Laplace-variational approach (MSLVIM) is introduced. Compared with the traditional approach for variational it overcome all difficulties and enable to provide us more an accurate solutions with extended of the convergence region as well as covering to larger intervals which providing us a continuous representation of approximate analytic solution and it give more better information of the solution over the whole time interval. This technique is more easier for obtaining the general Lagrange multiplier with reduces the time and calculations. It converges rapidly to exact formula with simply computable terms wit
... Show MoreThis work is concerned with the vibration attenuation of a smart beam interacting with fluid using proportional-derivative PD control and adaptive approximation compensator AAC. The role of the AAC is to improve the PD performance by compensating for unmodelled dynamics using the concept of function approximation technique FAT. The key idea is to represent the unknown parameters using the weighting coefficient and basis function matrices/vectors. The weighting coefficient vector is updated using Lyapunov theory. This controller is applied to a flexible beam provided with surface bonded piezo-patches while the vibrating beam system is submerged in a fluid. Two main effects are considered: 1) axial stretching of the vibrating beam that leads
... Show MoreThis paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul
... Show MoreA three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an
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