In earthquake engineering problems, uncertainty exists not only in the seismic excitations but also in the structure's parameters. This study investigates the influence of structural geometry, elastic modulus, mass density, and section dimension uncertainty on the stochastic earthquake response of a multi-story moment resisting frame subjected to random ground motion. The North-south component of the Ali Gharbi earthquake in 2012, Iraq, is selected as ground excitation. Using the power spectral density function (PSD), the two-dimensional finite element model of the moment resisting frame's base motion is modified to account for random ground motion. The probabilistic study of the moment resisting frame structure using stochastic finite element utilizing Monte Carlo simulation was presented using the finite element program ABAQUS. The dynamic reliability and probability of failure of the stochastic and deterministic structure based on the first passage failure were checked and evaluated. Results revealed that the probability of failure increased due to randomness in stiffness and mass of the structure. Generally, natural frequencies for the lower modes of vibration and relative displacements for the lower stories were more sensitive to the randomness in system parameters.
In study carried out in the cold storage in college of Agric./Univ. of Baghdad at 8 ? C. shows that Alternaria , Pencillium , Rhizoctonia , Mucor , are the fungi that causes tomato fruits decay. This is the first record of Rhizoctonia and Mucor as a Tomato fruits rot under 8º c in Iraq. There is no fungal infection on cucumber fruits under 8 ? C. . Waxing tomato fruits reduced the severity of the fungi infection and gave shelflife (19 days) under 8 ? C. There is an infection with Mucor was found in tomato fruits kept in perforated polyethylene bages with 16 bores prevent the infection and the lowest severity and frequency of infection was found in waxed tomato fruits. Part of M.Sc thesis of the Second author.
In this research, the problem of multi- objective modal transport was formulated with mixed constraints to find the optimal solution. The foggy approach of the Multi-objective Transfer Model (MOTP) was applied. There are three objectives to reduce costs to the minimum cost of transportation, administrative cost and cost of the goods. The linear membership function, the Exponential membership function, and the Hyperbolic membership function. Where the proposed model was used in the General Company for the manufacture of grain to reduce the cost of transport to the minimum and to find the best plan to transfer the product according to the restrictions imposed on the model.
Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
... Show MoreThis study provides an empirical and strategic contribution to the revenue management literature by investigating the transition from static cost-plus pricing to a dynamic, elasticity-based framework within state-owned extractive industries (SOEs). While dynamic pricing is extensively studied in flexible, data-rich private markets, its application in structurally rigid SOEs within transitional economies remains a critical research gap. Drawing on primary fiscal and production data from the 2024 fiscal year of the General Company for Mining Industries (SCMI), we developed a mathematical model to determine optimal pricing ( ) based on marginal cost principles and demand elasticity. The findings demonstrate that replacing rigid accounting rout
... Show MoreModeling 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
... Show MoreFrictional heat is generated when the clutch starts to engag. As a result of this operation the surface temperature is increased rapidly due to the difference in speed between the driving and driven parts. The influence of the thickness of frictional facing on the distribution of the contact pressure of the multi-disc clutches has been investigated using a numerical approach (the finite element method). The analysis of contact problem has been carried out for a multiple disc dry clutch (piston, clutch discs, separators and pressure plate). The results present the distribution of the contact pressure on all tShe surfaces of friction discs that existed in the friction clutch system. Axisymmetric finite element models have been developed to ac
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