The present study focused mainly on the buckling behavior of composite laminated plates subjected to mechanical loads. Mechanical loads are analyzed by experimental analysis, analytical analysis (for laminates without cutouts) and numerical analysis by finite element method (for laminates with and without cutouts) for different type of loads which could be uniform or non-uniform, uniaxial or biaxial. In addition to many design parameters of the laminates such as aspect ratio, thickness ratio, and lamination angle or the parameters of the cutout such as shape, size, position, direction, and radii rounding) which are changed to studytheir effects on the buckling characteristics with various boundary conditions. Levy method of classical lam

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

The distribution of the expanded exponentiated power function EEPF with four parameters, was presented by the exponentiated expanded method using the expanded distribution of the power function, This method is characterized by obtaining a new distribution belonging to the exponential family, as we obtained the survival rate and failure rate function for this distribution, Some mathematical properties were found, then we used the developed least squares method to estimate the parameters using the genetic algorithm, and a Monte Carlo simulation study was conducted to evaluate the performance of estimations of possibility using the Genetic algorithm GA.

     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai

Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use

Schiff base N,N'-Bis-(4-dimethylamino-benzylidene)-benzene-1,4-diamine has been synthesized from 4-dimethylaminobenzenaldehyde and benzene-1,4-diamine. The structure of Schiff base was obtained by (C.H.N.) microanalysis, Mass, 1HNMR, FT-IR and UV-Vis spectral methods and thermal analysis. Metal mixed ligand complexes of some metal(II) salts with Schiff base ligand and anthranilic acid were prepared in the molar ratio (1:2:2), (Metal):(SBL)2:(Anthra)2, (SBL)= Schiff base ligand, (Anthra) =anthranilic acid and Metal= Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and Hg(II). The thermal behaviour (TGA) of the complexes was studied. The prepared complexes identified by using mass, thermal analysis, FT.IR and UV-Vis spectrum methods, on otherwise flame