• Steel and Composite Structures
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• v.47 no.1
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• pp.19-36
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• 2023

An experimental study of eleven PVC-FRP Confined Concrete (PFCC) column-Reinforced Concrete (RC) beam joints reinforced with Core Steel Tube (CST) under axial compression is carried out. All specimens are designed in accordance with the principle of "weak column and strong joint". The influences of FRP strips spacing, length and steel ratio of CST, height and stirrup ratio of joint on mechanical behavior are investigated. As the design anticipated, all specimens are destroyed by column failure. The failure mode of PFCC column-RC beam joint reinforced with CST is the yielding of longitudinal steel bars, CST and stirrups of column as well as the fracture of FRP strips and PVC tube. The ultimate bearing capacity decreases as FRP strips spacing or joint height increases. The effects of other three studied parameters on ultimate bearing capacity are not obvious. The strain development rules of longitudinal steel bars, PVC tube, FRP strips, column stirrups and CST are revealed. The effects of various studied parameters on stiffness are also examined. Additionally, an influence coefficient of joint height is introduced based on the regression analysis of test data, a theoretical formula for predicting bearing capacity is proposed and it agrees well with test data.

• Journal of ILASS-Korea
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• v.27 no.1
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• pp.1-10
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• 2022

In this study, an experimental investigation on the effects of the pressure ratio on the wall-impingement spray characteristics of nitrogen gas using a compressed natural gas (CNG) injector was conducted. The transient development of the impingement spray was recorded by a high speed camera with Z-type Schlieren visualization method. The spray behavior under various pressure ratio conditions were analyzed. The experimental results showed that the pressure ratio has positive effect on the development of spray wall-impingement. The effects of the above factor were evaluated in a constant volume chamber at atmospheric conditions. The data from test showed that, with the increase of the pressure ratio, the spray tip penetration (STP) quickly increases before the impingement and gradually increases after the impingement. Additionally, the spray velocity first increases and then sharply decreases on regardless of the injection pressure level. As the spray spreading angle increases, spray area and volume increases rapidly with the increase in STP at the beginning of injection, and finally entered a stable range, has a great correlation with the increase of pressure ratios.

• Computers and Concrete
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• v.31 no.6
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• pp.527-536
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• 2023

Fiber Reinforced Polymer (FRP) bar has emerged as a viable and sustainable replacement to steel in reinforced concrete (RC) under severe corrosive environment. The behavior of concrete columns reinforced with FRP bars, spirals, and hoops is an ongoing area of research. In this study, 3D nonlinear numerical modelling of circular concrete columns reinforced with Glass Fiber Reinforced Polymer (GFRP) bars and transversely confined with GFRP spirals were conducted using fracture-plastic model. The numerical models and experimental results are found to be in good agreement. The effectiveness of confinement was accessed through von-mises stresses, and it was found that the stresses in the concrete's core are higher with a 30 mm pitch (46 MPa) compared to a 60 mm pitch (36 MPa). The validated models are used to conduct parametric studies. In terms of axial load carrying capacity and member ductility, the effect of concrete strength, spiral pitch, and longitudinal reinforcement ratio are thoroughly investigated. The confinement effect and member ductility of a GFRP RC column increases as the spiral pitch decreases. It is also found that the confinement effect and member ductility decreased with increase in strength of concrete.

• Steel and Composite Structures
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• v.46 no.3
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• pp.293-318
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• 2023

This study aims to examine the elastic stiffness properties of Elliptic-Braced Moment Resisting Frame (EBMRF) subjected to lateral loads. Installing the elliptic brace in the middle span of the frames in the facade of a building, as a new lateral bracing system not only it can improve the structural behavior, but it provides sufficient space to consider opening it needed. In this regard, for the first time, an accurate theoretical formulation has been developed in order that the elastic stiffness is investigated in a two-dimensional single-story single-span EBMRF. The concept of strain energy and Castigliano's theorem were employed to perform the analysis. All influential factors were considered, including axial and shearing loads in addition to the bending moment in the elliptic brace. At the end of the analysis, the elastic lateral stiffness could be calculated using an improved relation through strain energy method based on geometric properties of the employed sections as well as specifications of the utilized materials. For the ease of finite element (FE) modeling and its use in linear design, an equivalent element was developed for the elliptic brace. The proposed relation was verified by different examples using OpenSees software. It was found that there is a negligible difference between elastic stiffness values derived by the developed equations and those of numerical analysis using FE method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4A
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• pp.577-585
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• 2006

In this research, nonlinear Timoshenko beam element that is able to capture nonlinear shear deformation is developed. The proposed model shows more reasonable prediction than Bernoulli beam theory in short columns or strong shear column due to the consideration of shear deformation. The cross-section is modeled as fiber approach. Since the model is based on the fiber approach for section discretization, the plastic progress of the section can be traced and the coupling effect of the axial and flexural response. The developed element is implemented into the finite element program to analysis general reinforced concrete structures. As parametric study, reinforced concrete columns are analyzed and compared with experimental results, analyzed the property of behavior for reinforced concrete columns.

• Journal of the Earthquake Engineering Society of Korea
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• v.28 no.2
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• pp.113-119
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• 2024

Existing reinforced concrete buildings with seismically deficient column details affect the overall behavior depending on the failure type of column. This study aims to develop and validate a machine learning-based prediction model for the column failure modes (shear, flexure-shear, and flexure failure modes). For this purpose, artificial neural network (ANN), K-nearest neighbor (KNN), decision tree (DT), and random forest (RF) models were used, considering previously collected experimental data. Using four machine learning methodologies, we developed a classification learning model that can predict the column failure modes in terms of the input variables using concrete compressive strength, steel yield strength, axial load ratio, height-to-dept aspect ratio, longitudinal reinforcement ratio, and transverse reinforcement ratio. The performance of each machine learning model was compared and verified by calculating accuracy, precision, recall, F1-Score, and ROC. Based on the performance measurements of the classification model, the RF model represents the highest average value of the classification model performance measurements among the considered learning methods, and it can conservatively predict the shear failure mode. Thus, the RF model can rapidly predict the column failure modes with simple column details.

• Computers and Concrete
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• v.33 no.3
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• pp.285-299
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• 2024

Recently, many engineering computations have realized their digital transformation to Machine Learning (ML)-based systems. Predicting the behavior of a structure, which is mainly computed with structural analysis software, is an essential step before construction for efficient structural analysis. Especially in the seismic-based design procedure of the structures, predicting the lateral load capacity of reinforced concrete (RC) columns is a vital factor. In this study, a novel ML-based model is proposed to predict the maximum lateral load capacity of RC columns under varying axial loads or cyclic loadings. The proposed model is generated with a Deep Neural Network (DNN) and compared with traditional ML techniques as well as a popular commercial structural analysis software. In the design and test phases of the proposed model, 319 columns with rectangular and square cross-sections are incorporated. In this study, 33 parameters are used to predict the maximum lateral load capacity of each RC column. While some traditional ML techniques perform better prediction than the compared commercial software, the proposed DNN model provides the best prediction results within the analysis. The experimental results reveal the fact that the performance of the proposed DNN model can definitely be used for other engineering purposes as well.

• Steel and Composite Structures
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• v.52 no.1
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• pp.89-107
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• 2024

This article focuses on the static and dynamic analysis and optimization of an anisogrid lattice plate subjected to axial compressive load with simply supported boundary conditions. The lattice plate includes diagonal and transverse ribs and is modeled as an orthotropic plate with effective stiffness properties. The study employs the first-order shear deformation theory and the Ritz method with a Legendre approximation function. In the realm of optimization, the Non-dominated Sorting Genetic Algorithm-II is utilized as an evolutionary multi-objective algorithm to optimize. The research findings are validated through finite element analysis. Notably, this study addresses the less-explored areas of optimizing the geometric parameters of the plate by maximizing the buckling load and natural frequency while minimizing mass. Furthermore, this study attempts to fill the gap related to the analysis of the post-buckling behavior of lattice plates, which has been conspicuously overlooked in previous research. This has been accomplished by conducting nonlinear analyses and scrutinizing post-buckling diagrams of this type of lattice structure. The efficacy of the continuous methods for analyzing the natural frequency, buckling, and post-buckling of these lattice plates demonstrates that while a degree of accuracy is compromised, it provides a significant amount of computational efficiency.

• Journal of Korean Society of Steel Construction
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• v.22 no.1
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• pp.1-12
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• 2010

According to the capacity design concept which forms the basis of the current steel seismic codes, the braces in concentrically braced frames (CBFs) should dissipate seismic energy through cyclic tension yielding and cyclic compression buckling while the beams and the columns should remain elastic. Brace buckling in inverted V-braced frames induces unbalanced vertical forces which, in turn, impose the additional beam moments and column axial forces. However, due to difficulty in predicting the location of buckling stories, the most conservative approach implied in the design code is to estimate the column axial forces by adding all the unbalanced vertical forces in the upper stories. One alternative approach, less conservative and recommended by the current code, is to estimate the column axial forces based on the amplified seismic load expected at the mechanism-level response. Both are either too conservative or lacking technical foundation. In this paper, three combination rules for a rational estimation of the column axial forces were proposed. The idea central to the three methods is to detect the stories of high buckling potential based on pushover analysis and dynamic behavior. The unbalanced vertical forces in the stories detected as high buckling potential are summed in a linear manner while those in other stories are combined by following the SRSS(square root of sum of squares) rule. The accuracy and design advantage of the three methods were validated by comparing extensive inelastic dynamic analysis results. The mode-shape based method(MSBM), which is both simple and accurate, is recommended as the method of choice for practicing engineers among the three.

• Korean Chemical Engineering Research
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• v.60 no.4
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• pp.535-543
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• 2022

A CPFD (Computational particle fluid dynamics) model of solar fluidized bed receiver of silicon carbide (SiC: average d_p=123 ㎛) particles was established, and the model was verified by comparing the simulation and experimental results to analyze the effect of particle behavior on the performance of the receiver. The relationship between the heat-absorbing performance and the particles behavior in the receiver was analyzed by simulating their behavior near bed surface, which is difficult to access experimentally. The CPFD simulation results showed good agreement with the experimental values on the solids holdup and its standard deviation under experimental condition in bed and freeboard regions. The local solid holdups near the bed surface, where particles primarily absorb solar heat energy and transfer it to the inside of the bed, showed a non-uniform distribution with a relatively low value at the center related with the bubble behavior in the bed. The local solid holdup increased the axial and radial non-uniformity in the freeboard region with the gas velocity, which explains well that the increase in the RSD (Relative standard deviation) of pressure drop across the freeboard region is responsible for the loss of solar energy reflected by the entrained particles in the particle receiver. The simulation results of local gas and particle velocities with gas velocity confirmed that the local particle behavior in the fluidized bed are closely related to the bubble behavior characterized by the properties of the Geldart B particles. The temperature difference of the fluidizing gas passing through the receiver per irradiance (∆T/I_DNI) was highly correlated with the RSD of the pressure drop across the bed surface and the freeboard regions. The CPFD simulation results can be used to improve the performance of the particle receiver through local particle behavior analysis.