• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.141-144
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• 2008

Deflection in terms of serviceability of reinforced concrete structures is considered as one of significant factor. Domestic concrete specification offers a procedure to evaluate deflection using effective moment of inertia at cracked section, which has been known as Branson's equation in ACI. Branson's equation was derived from statistical analysis of maximum deflection of flexural members, but is somewhat weak in no reflection of bond characteristics between reinforced bars and concrete, such as tension stiffening effect. Therefore, present code creates difference from actual deflection. In this study, experiments about deflection of RC beams was completed to compare domestic standard and Eurocode 2, which calculates deflection considering tension stiffening effect. Four RC beams were built and tested, and initial modulus of elasticity and tensile strength of concrete used in the test was calculated by each design standard.

• Structural Engineering and Mechanics
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• v.69 no.3
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• pp.257-268
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• 2019

Infills are as important members in structural design as beams, columns and braces. They have significant effect on structural behavior. Because of lots of variables in infills like material non-linear behavior, the interaction between frames and infill, etc., the infills performance during an earthquake is complicated, so have led designers do not consider the effect of infills in designing the structure. However, the experimental studies revealed that the infills have the remarkable effect on structure behavior. As if these effects ignored, it might occur soft-story phenomena, torsion or short-column effects on the structures. One simple and appropriate method for considering the infills effects in analyzing, is replacing the infills with diagonal compression strut with the same performance of real infill, instead of designing the whole infill. Because of too many uncertainties, codes and researchers gave many expressions that were not as the same as the others. The major intent of this paper is calculation the width of this diagonal strut, which has the most characteristics of infill. This paper by comprehensive on different parameters like the modulus of young or moment of inertia of columns presents a new formula for achieving the equivalent strut width. In fact, this new formula is extracted from about 60 FEM analyses models. It can be said that this formula is very efficient and accurate in estimating the equivalent strut width, considering the large number of effective parameters relative to similar relationships provided by other researchers. In most cases, the results are so close to the values obtained by the FEM. In this formula, the effect of out of plane buckling is neglected and this formula is used just in steel structures. Also, the thickness of infill panel, and the lateral force applied to frame are constant. In addition, this new formula is just for modeling the lateral stiffness. Obtaining the nearest response in analyzing is important to the designers, so this new formula can help them to reach more accurate response among a lot of experimental equations proposed by researchers.

• Structural Engineering and Mechanics
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• v.85 no.4
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• pp.469-484
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• 2023

A deep recursive bidirectional Cuda Deep Neural Network Long Short Term Memory (Bi-CuDNNLSTM) layer is recruited in this paper to predict the entire force time histories, and the corresponding hysteresis and backbone curves of reinforced concrete (RC) bridge piers using experimental fast and slow cyclic tests. The proposed stacked Bi-CuDNNLSTM layers involve multiple uncertain input variables, including horizontal actuator displacements, vertical actuators axial loads, the effective height of the bridge pier, the moment of inertia, and mass. The functional application programming interface in the Keras Python library is utilized to develop a deep learning model considering all the above various input attributes. To have a robust and reliable prediction, the dataset for both the fast and slow cyclic tests is split into three mutually exclusive subsets of training, validation, and testing (unseen). The whole datasets include 17 RC bridge piers tested experimentally ten for fast and seven for slow cyclic tests. The results bring to light that the mean absolute error, as a loss function, is monotonically decreased to zero for both the training and validation datasets after 5000 epochs, and a high level of correlation is observed between the predicted and the experimentally measured values of the force time histories for all the datasets, more than 90%. It can be concluded that the maximum mean of the normalized error, obtained through Box-Whisker plot and Gaussian distribution of normalized error, associated with unseen data is about 10% and 3% for the fast and slow cyclic tests, respectively. In recapitulation, it brings to an end that the stacked Bi-CuDNNLSTM layer implemented in this study has a myriad of benefits in reducing the time and experimental costs for conducting new fast and slow cyclic tests in the future and results in a fast and accurate insight into hysteretic behavior of bridge piers.

• Journal of Korean Society of Steel Construction
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• v.22 no.2
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• pp.139-150
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• 2010

Reinforced-concrete (RC) columns are frequently designed and constructed. other types of columns includes composite types such as concrete-filled tube columns (CFT). Hollow RC columns may be effective in reducing both the self weight of columns and total amount of materials used. This is due to the fact that a hollow RC column possesses larger moment of inertia than that of solid RC columns of same cross sectional area. Despite the effectiveness the hollow RC column has not been popular because of its poor ductility performance. While the transverse reinforcements are effective in controlling the brittle failure of the outside concrete, they are not capable of resisting the failure of concrete of inner face which is in unconfined state of stress. To overcome these drawbacks, the internally confined hollow reinforced concrete (ICH RC), a new column type, was proposed in the previous researches. In this study, the fire resistance performance of the ICH RC columns was analyzed through a series of extensive heat transfer analyses using the nonlinear-material model program. Also, effect of factors such as the hollowness ratio, thickness of the concrete, and thickness of the internal tube on the fire resistance performance were extensively studied. Then the factors that enhance the fire-resistant performance of ICH RC were presented and analyzed.