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On modelling and adaptive control of a linear smart beam model interacting with fluid
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Abstract<p>This paper deals with modelling and control of Euler-Bernoulli smart beam interacting with a fluid medium. Several distributed piezo-patches (actuators and/or sensors) are bonded on the surface of the target beam. To model the vibrating beam properly, the effect of the piezo-patches and the hydrodynamic loads should be taken into account carefully. The partial differential equation PDE for the target oscillating beam is derived considering the piezo-actuators as input controls. Fluid forces are decomposed into two components: 1) hydrodynamic forces due to the beam oscillations, and 2) external (disturbance) hydrodynamic loads independent of beam motion. Then the PDE is discretized using the Galerkin approach to obtain standard multi-modal equations. An adaptive approximation control structure is proposed to suppress the beam vibration. The controller consists of a proportional-derivative PD control plus an adaptive approximation compensator AAC with guaranteed stability. A simply supported beam with 2 piezo-patches interacting with fluid is simulated. The disturbance hydrodynamic force that excites the beam vibration is assumed as a harmonic force with 50 Hz frequency and 1 N amplitude. The results prove the efficacy of the proposed control architecture.</p>
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Publication Date
Mon Nov 01 2021
Journal Name
International Journal Of Hydrogen Energy
Experimental study on combustion stability and performance of hydrogen-enriched compressed natural gas of a free-piston linear generator
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Publication Date
Mon Dec 08 2025
Journal Name
Engineering, Technology &amp; Applied Science Research
Multi-Layer Feedforward Neural Network Modelling of a Kinematics Solution of A 3-DoF Manipulator Robot
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Modeling forward kinematics with neural networks allows for efficient handling of nonlinear relationships and realistic error correction in time-critical applications by relying on accurate training data. This paper presents a Multi-Layer Feed-Forward Neural Network (MLFFNN) to solve the forward kinematics of a 3-DOF robot. The proposed MLFFNN consists of 50 hidden neurons and was trained using 628319 samples to find only the position (x, y, z) of the end-effector. Data were generated by MATLAB, assuming an incremental motion of joints. The joint variables ( , , and ) are the inputs of the NN, which outputs the positions of the end effector (x, y, z) calculated using the Denavit-Hartenberg (DH) method. The results demonstrate that t

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Publication Date
Wed Jun 01 2022
Journal Name
Political Sciences Journal
US-Russian Interventions in the Caspian-Caucasus Basin Countries after 2001: (Strategies to Re-Impose Control and Influence as a Model)
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Today, the five Caspian riparian states on the shores of the Caspian Sea (Kazakhstan, Turkmenistan, Azerbaijan, Russia, and Iran) have become a front for ambitions and international and regional competition, especially in light of the features and characteristics that natural geography has endowed them with and their enjoyment of a group of economic and mineral wealth that are not optimally exploited so far which made it a strategic attraction area for international trends and interventions, especially Western ones. It is a battleground for major international companies aiming to monopolize promising industrial investments in order to impose control and influence on the region’s resources and economic wealth and thus impose their forei

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Publication Date
Sun Jun 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
The Convective Heat Transfer of Fluid Flowing Across a Vertical Plate
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Publication Date
Mon Jan 01 2018
Journal Name
Ournal Of Advanced Research In Dynamical And Control System
Effect of magnetic field on peristaltic transport of bingham plastic fluid
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Publication Date
Tue Aug 19 2025
Journal Name
Journal Of Engineering Research
Development of a memory-efficient and computationally cost-effective CNN for smart waste classification
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Summary The paper proposes a small custom CNN for classifying solid waste into four classes: aluminum, cardboard, plastic, and glass. It is designed for real-time use on limited hardware such as a Raspberry Pi or Jetson.

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Comparison between RSA and CAST-128 with Adaptive Key for Video Frames Encryption with Highest Average Entropy
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Encryption of data is translating data to another shape or symbol which enables people only with an access to the secret key or a password that can read it. The data which are encrypted are generally referred to as cipher text, while data which are unencrypted are known plain text. Entropy can be used as a measure which gives the number of bits that are needed for coding the data of an image. As the values of pixel within an image are dispensed through further gray-levels, the entropy increases. The aim of this research is to compare between CAST-128 with proposed adaptive key and RSA encryption methods for video frames to determine the more accurate method with highest entropy. The first method is achieved by applying the "CAST-128" and

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Publication Date
Tue Oct 13 2026
Journal Name
Journal Of Physical Education
The impact of a computerized program (cogniplus) to develop the strength to focus and perform kinetic chain on the balance beam
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Publication Date
Tue Jan 01 2019
Journal Name
Opcion- Universidad Del Zulia
Sample for the inner control on the quality in accordance with standard
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Scopus
Publication Date
Tue Sep 01 2020
Journal Name
Ain Shams Engineering Journal
Estimating server utilization rate in single server queuing models using an approximate solution of stiff fluid flow model
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