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Buckling Loads and Effective Length Factor for Non-Prismatic Columns
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Based on a finite element analysis using Matlab coding, eigenvalue problem has been formulated and solved for the buckling analysis of non-prismatic columns. Different numbers of elements per column length have been used to assess the rate of convergence for the model. Then the proposed model has been used to determine the critical buckling load factor () for the idealized supported columns based on the comparison of their buckling loads with the corresponding hinge supported columns . Finally in this study the critical buckling factor () under end force (P) increases by about 3.71% with the tapered ratio increment of 10% for different end supported columns and the relationship between normalized critical load and slenderness ratio was generalized.

 

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Publication Date
Mon Mar 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of bubble size in Bubble columns using Artificial Neural Network
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In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

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Publication Date
Fri Nov 13 2020
Journal Name
Mechanics Of Advanced Materials And Structures
Enhancing the strength of reinforced concrete columns using steel embedded tubes
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This paper demonstrates an experimental and numerical study on the behavior of reinforced concrete (RC) columns with longitudinal steel embedded tubes positioned at the center of the column cross-section. A total of 12 pin-ended square sectional columns of 150 × 150 mm having a total height of 1400 mm were investigated. The considered variables were the steel tube diameters of 29, 58, and 76 mm and the load eccentricity (0, 50, and 150) mm. Accordingly, these columns were divided into three groups (four columns in each group) depending on the load eccentricity (e) to column depth (h) ratio (e/h = 0, 1/3, and 1). For each group, one column was solid (reference), and the other three columns contained steel tubes with hollow rat

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Publication Date
Sat Oct 10 2026
Journal Name
Journal Of Composites Science
The Structural Behavior of Encased Composite Columns Under Biaxial Loading Conditions
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This study presents a theoretical investigation of encased composite columns under biaxial loading. The EUROCODE 4 theoretical model for generating the uniaxial interaction diagram was developed and used to meet biaxial requirements. The primary objective was to evaluate how internal steel ratios and configurations and concrete compressive strength influence the axial and biaxial flexural performance of the composite column. Ten models were analyzed, and the results were validated against previous experimental and analytical data. The results indicate that internal reinforcement is the primary driver of stiffness. Changing from an I-section to equivalent reinforcing bars or four steel angles significantly improves the y-axis stiffne

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Publication Date
Mon Jan 16 2023
Journal Name
Journal Of Medical And Health Studies
Is Mometasone Effective in Treating Otitis Media with Effusion?
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Otitis media with effusion (OME) is the long-term deposition of mucus in the middle ear cleft. It is the leading cause of childhood hearing loss and a common childhood infection. It can impair communication and life quality. OME's direct and indirect costs are also crucial. Improving OME care is crucial. This study examines intranasal mometasone's efficacy in treating otitis media with effusion. A clinical trial study was conducted during a period from January 2021 to June 2022. It included 80 patients suffering from otitis media with effusion bilaterally (160 ears) who had an intact tympanic membrane and tympanometry type B. These patients were included only if they had a hearing change or loss noted by the parents or by the patien

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Publication Date
Thu Jul 04 2019
Journal Name
International Journal Of Automotive And Mechanical Engineering
Nonlinear Buckling Analysis of Steel Cylindrical Shell with Elliptical Cut-out Subjected to Longitudinal Compressive Load
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The current paper investigates the effect of cut-out design parameters on load-bearing capacity and buckling behaviour of steel cylindrical shell using a nonlinear finite element analysis in modelling cylinder buckling under longitudinal compressive load. The effect of four geometry design parameters: shell diameter to thickness ratio, cut-out location, orientation, and size were investigated in this study. To enhance the prediction of buckling behaviour, both geometrical and material nonlinearities were considered. An ANSYS APDL code was written and tested by verifying its validity through comparison with former buckling study. The results showed that changing the cut-out location from mid-height of the cylindrical shell towards a

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Publication Date
Sat Oct 01 2022
Journal Name
Advances In Structural Engineering
Experimental and FE analysis of composite RC beams with encased pultruded GFRP I-beam under static loads
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Publication Date
Sat Oct 01 2022
Journal Name
Advances In Structural Engineering
Experimental and FE analysis of composite RC beams with encased pultruded GFRP I-beam under static loads
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Encasing glass fiber reinforced polymer (GFRP) beam with reinforced concrete (RC) improves stability, prevents buckling of the web, and enhances the fire resistance efficiency. This paper provides experimental and numerical investigations on the flexural performance of RC specimens composite with encased pultruded GFRP I-sections. The effect of using shear studs to improve the composite interaction between the GFRP beam and concrete was explored. Three specimens were tested under three-point loading. The deformations, strains in the GFRP beams, and slippages between the GFRP beams and concrete were recorded. The embedded GFRP beam enhanced the peak loads by 65% and 51% for the composite specimens with and without shear connectors,

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Publication Date
Fri Sep 09 2022
Journal Name
Journal Of Ovonic Research
Confinement factor and carrier recombination of InGaAsP/InP quantum well lasers
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Low-dimensional materials have attracted significant attention in developing and enhancing the performance of quantum well lasers due to their extraordinary unique properties. The optical confinement factor is one of the most effective parameters for evaluating the optimal performance of a semiconductor laser diode when used to measure the optical gain and current threshold. The optical confinement factor and the radiative recombination of single quantum wells (SQW) and multi-quantum wells (MQW) for InGaAsP/InP have been theoretically studied using both radiative and Auger coefficients. Quantum well width, barrier width, and number of quantum wells were all looked at to see how these things changed the optical confinement factor and

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Publication Date
Sat Oct 01 2022
Journal Name
Nuclear Instruments And Methods In Physics Research Section B: Beam Interactions With Materials And Atoms
Shielding properties and buildup factor of Al2O3/PbO-based ceramic materials
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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A 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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