• Steel and Composite Structures
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• v.47 no.3
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• pp.383-393
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• 2023

Conventional reinforced concrete design codes assume ideal strain evolution in semi-deep beams with externally bonded fiber-reinforced polymer (EB-FRP) web strips. However, there is a strain interaction between internal stirrups and web strips, leading to a notable difference between code-based and experimental shear strengths. Current study provides an experiment-verified detailed numerical framework to assess the potential strain interaction under quasi-static monotonic load. Based on the observations, steel stirrups are effective only for low EB-FRP amounts and the over-strengthening of semi-deep beams prevents the stirrups from yielding, reducing its shear strength contribution. A notable difference is detected between the code-based and the study-based EB-FRP strain values, which is a function of the normalized FRP stress parameter. Semi-analytical relations are proposed to estimate the effective strain and stress of the components considering the potential strain interaction. For the sake of simplification, a linearized correction factor is proposed for the EB-FRP web strip strain, assuming its restraining effect as constant for all steel stirrup amounts.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.66.2-66.2
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• 2020

We propose a deep learning analysis technique with a convolutional neural network (CNN) to predict the evolutionary track of the Epoch of Reionization (EoR) from the 21-cm differential brightness temperature tomography images. We use 21cmFAST, a fast semi-numerical cosmological 21-cm signal simulator, to produce mock 21-cm maps between z = 6 ~ 13. We then apply two observational effects, such as instrumental noise and limit of (spatial and depth) resolution somewhat suitable for realistic choices of the Square Kilometre Array (SKA), into the 21-cm maps. We design our deep learning model with CNN to predict the sliced-averaged neutral hydrogen fraction from the given 21-cm map. The estimated neutral fraction from our CNN model has great agreement with the true value even after coarsely smoothing with broad beam size and frequency bandwidth and heavily covered by noise with narrow beam size and frequency bandwidth. Our results show that the deep learning analyzing method has the potential to reconstruct the EoR history efficiently from the 21-cm tomography surveys in future.

• Computers and Concrete
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• v.10 no.6
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• pp.609-630
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• 2012

Currently, the design of reinforced concrete deep beams with web openings is carried out using empirical or semi-empirical methods and hence their scope of application is limited. In particular, high strength concrete deep beams with various web opening configurations have been given little treatment. In view of this, a nonlinear layered finite element method (LFEM) for cracking and failure analysis of reinforced concrete structures is used to conduct a parametric study to investigate reinforced concrete deep beams various web opening behaviours. This paper initially presents comparisons of LFEM output with published test results to numerical techniques. The paper then focuses on a parametric study on the shear strengths of deep beams with varying web opening configurations such as opening sizes and locations. The results confirm that the current design methods are inadequate in predicting the maximum shear strength when web openings are present. A series of parametric study offers insight into the maximum shear strength of the deep beams being critically influenced by the size and location of web openings.

• Structural Engineering and Mechanics
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• v.77 no.2
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• pp.273-291
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• 2021

The strut-and-tie method (STM) has been widely accepted and used as a rational approach for the design of disturbed regions ('D' regions) of reinforced concrete members such as in corbels and deep beams, where traditional flexure theory does not apply. This paper evaluates the applicability of the equilibrium based STM in strength predictions of deep beams (with rectangular and circular cross-section) and corbels using the available experiments in literature. STM is found to give fairly good results for corbel and deep beams. The failure modes of these deep members are also studied, and an optimum amount of distribution reinforcement is suggested to eliminate the premature diagonal splitting failure. A comparison with existing empirical and semi empirical methods also show that STM gives more reliable results. The nonlinear finite element analysis (NLFEA) of 50 deep beams and 20 corbels could capture the complete behaviour of deep members including crack pattern, failure load and failure load accurately.

• Steel and Composite Structures
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• v.29 no.4
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• pp.483-491
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• 2018

Timoshenko beam model is widely exploited in the literature to examine the mechanical behavior of stubby beam-like components. Timoshenko beam theory is well-known to require the shear correction factor in order to recognize the nonuniform shear distribution at a section. While a variety of shear correction factors are appeared in the literature so far, there is still no consensus on the most appropriate form of the shear correction factor. The Saint-Venant's flexure problem is first revisited in the frame work of the classical theory of elasticity and a highly accurate approximate closed-form solution is presented employing the extended Kantorovich method. The resulted approximate solution for the elasticity field is then employed to introduce two shear correction factors consistent with the Cowper's and energy approaches. The mathematical form of the proposed shear correction factors are then simplified and compared with the results available in the literature over an extended range of Poisson's and aspect ratios. The proposed shear correction factors do not exhibit implausible issue of negative values and do not result in numerical instabilities too. Based on the comprehensive discussion on the shear correction factors, a piecewise definition of shear correction factor is introduced for rectangular cross-sections having excellent agreement with the numerical results in the literature for both shallow and deep cross-sections.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.78.3-78.3
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• 2019

We develop a novel technique that can constrain the evolutionary track of the epoch of reionization (EoR) by applying the convolutional neural network (CNN) to the 21-cm differential brightness temperature. We use 21cmFAST, a fast semi-numerical cosmological 21-cm signal simulator, to produce mock 21-cm map between z=6-13. We design a CNN architecture that predicts the volume-averaged neutral hydrogen fraction from the given 21-cm map. The estimated neutral fraction has a good agreement with its truth value even after smoothing the 21-cm map with somewhat realistic choices of beam size and the frequency bandwidth of the Square Kilometre Array (SKA). Our technique could be further utilized to denoise the 21-cm map or constrain the properties of the radiation sources.

• Steel and Composite Structures
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• v.49 no.6
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• pp.603-614
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• 2023

In this paper, frequency analysis of curved functionally graded (FG) nanobeam by consideration of deepness effect has been studied. Differential transform method (DTM) has been used to obtain frequency responses. The nonlocal theory of Eringen has been applied to consider nanoscales. Material properties are supposed to vary in radial direction according to power-law distribution. Differential equations and related boundary conditions have been derived using Hamilton's principle. Finally, by consideration of nonlocal theory, the governing equations have been derived. Natural frequencies have been obtained using semi analytical method (DTM) for different boundary conditions. In order to study the effect of deepness, the deepness term is considered in strain field. The effects of the gradient index, radius of curvature, the aspect ratio, the nonlocal parameter and interaction of aforementioned parameters on frequency value for different boundary conditions such as clamped-clamped (C-C), clamped-hinged (C-H), and clamped-free (C-F) have been investigated. In addition, the obtained results are compared with the results in previous literature in order to validate present study, a good agreement was observed in the present results.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.4 no.1
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• pp.11-20
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• 1994

GaAs and AlGaAs epi-layers were grown on semi-insulating (100) GaAs substrate by molecular beam epitaxy (MBE) and their electrical and optical properties have been investigated by several measurements. In undoped GaAs, the p-type GaAs layers with the good surface morphology were obtained under the growth conditions of the substrate temperatures ranging from 570 to $585^{\circ}C$ and the $As_4$/Ga ratios from 17 to 22. In the samples with the growth rates of the ranges of $0.9~1.1 {\mu}m/h$, the impurity concentrations were in the ranges of $1.5{\times}10^{14}~5.6{\times}10^{14}cm^{-3}$ with the Hall mobilities of $590~410cm^2/V-s$. In the Si-doped GaAs, the n-type GaAs layers with low electro trap, only two hole deep levels were observed with uniform doping profiles (<1%). AlGaAs layers with good surface morphology and crystallinity were grown under an optimum condition of the substrate temperature, $600^{\circ}C $. 8 deep level defects were observed between 0.17~0.85eV in undoped AlGaAs layers.