This paper presents a nonlinear finite element modeling and analysis of steel fiber reinforced concrete (SFRC) deep beams with and without openings in web subjected to two- point loading. In this study, the beams were modeled using ANSYS nonlinear finite element
software. The percentage of steel fiber was varied from 0 to 1.0%.The influence of fiber content in the concrete deep beams has been studied by measuring the deflection of the deep beams at mid- span and marking the cracking patterns, compute the failure loads for each deep beam, and also study the shearing and first principal stresses for the deep beams with and without openings and with different steel fiber ratios. The above study indicates that the location of openings and the amount steel fiber are affects to the behavior and strength of deep beams. And also when the results of the experiments taken from the literature were compared with the results obtained from the beam modeled with ANSYS finite element program, it was shown that the results of computer model gave similar results to the experimental behavior.
In this paper, the author established some new integral conditions for the oscillation of all solutions of nonlinear first order neutral delay differential equations. Examples are inserted to illustrate the results.
Linear and nonlinear optical properties of epoxy/ Al2O3 nanocomposites system were studied for epoxy neat and (0.5, 1.5, 3, and 5) % Al2O3 nanocomposites.The band gap of epoxy and its nanocomposites was obtained at these weight ratios. Nonlinear optical properties experiments were performed using Q-switched Nd:YAG laser z-scan system.These experiments were carried out for different parameters: wavelengths (1064 nm and 532 nm), laser intensities (0.530, 0.679, and 0.772) GW/cm2 and weight ratio of Al2O3 nanocomposites. The results showed that the band gaps were decreased with increasing the weight ratio of nanoalumina except at 5wt% and the nonlinear refractive index coefficient is directly proportional to the incident intensities while o
... Show MoreExperimental activity coefficients at infinite dilution are particularly useful for calculating the parameters needed in an expression for the excess Gibbs energy. If reliable values of γ∞1 and γ∞2 are available, either from direct experiment or from a correlation, it is possible to predict the composition of the azeotrope and vapor-liquid equilibrium over the entire range of composition. These can be used to evaluate two adjustable constants in any desired expression for G E. In this study MOSCED model and SPACE model are two different methods were used to calculate γ∞1 and γ∞2
In this ˑwork, we present theˑ notion of the ˑgraph for a KU-semigroup as theˑundirected simple graphˑ with the vertices are the elementsˑ of and weˑˑstudy the ˑgraph ofˑ equivalence classesˑofˑ which is determinedˑ by theˑ definition equivalenceˑ relation ofˑ these verticesˑ, andˑ then some related ˑproperties areˑ given. Several examples are presented and some theorems are proved. Byˑ usingˑ the definitionˑ ofˑ isomorphicˑ graph, ˑwe showˑ thatˑ the graphˑ of equivalence ˑclasses ˑand the ˑgraphˑof ˑa KU-semigroup ˑ areˑ theˑ sameˑ, in special cases.
This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number
... Show MoreGeneral Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k
... Show MoreThe aim of this work is to evaluate some mechanical and physical
properties (i.e. the impact strength, hardness, flexural strength,
thermal conductivity and diffusion coefficient) of
(epoxy/polyurethane) blend reinforced with nano silica powder (2%
wt.). Hand lay-up technique was used to manufacture the composite
and a magnetic stirrer for blending the components. Results showed
that water had affected the bending flexural strength and hardness,
while impact strength increased and thermal conductivity decreased.
In addition to the above mentioned tests, the diffusion coefficient
was calculated using Fick’s 2nd law.
Roller compacted concrete (RCC) is a type of rigid pavement that is designed in a similar way to conventional concrete pavements reflecting its mode of failure. The thickness design of RCC pavements is based on keeping the flexural stresses and fatigue damage in the pavement caused by wheel loads within allowable limits. As in all jointed concrete pavements, there is a greater effect from loads placed along edges and less at interior locations in the pavement. Joints in RCC pavement are clearly critical areas and form weak points. RCC is typically constructed with saw-cut joints to prevent random cracking, improve the appearance of the pavement surface, and maintain the highest possible load transfer across the joints. This paper pr
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