• Steel and Composite Structures
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• v.16 no.5
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• pp.481-489
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• 2014

The function of carbon fibre reinforced polymer (CFRP) reinforcement in increasing the ductility of reinforced concrete (RC) deep beam is important in such shear-sensitive RC member. This paper aims to investigate the effect of CFRP-strengthening on the energy absorption of RC deep beams. Six ordinary RC deep beams and six CFRP-strengthened RC deep beams with shear span to the effective depth ratio of 0.75, 1.00, 1.25, 1.50, 1.75, and 2.00 were tested till failure in this research. An empirical relationship was established to obtain the energy absorption of CFRP-strengthened RC deep beams. The shear span to the effective depth ratio and growth of energy absorption of CFRP-strengthened deep beam were the significant factors to establish this relationship.

• Advances in concrete construction
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• v.13 no.3
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• pp.243-254
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• 2022

Reinforced concrete (RC) deep beams are critical structural elements used in offshore pile caps, rectangular cross-section water tanks, silo structures, transfer beams in high-rise buildings, and bent caps. As a result of the low shear span ratio to effective depth (a/d) in deep beams, arch action occurs, which leads to shear failure. Several studies have been carried out to improve the shear resistance of RC deep beams and avoid brittle fracture behavior in recent years. This study was performed to investigate the behavior of RC deep beams numerically and experimentally with different reinforcement arrangements. Deep beams with four different reinforcement arrangements were produced and tested under monotonic static loading in the study's scope. The horizontal and vertical shear reinforcement members were changed in the test specimens to obtain the effects of different reinforcement arrangements. However, the rebars used for tension and the vertical shear reinforcement ratio were constant. In addition, the behavior of each deep beam was obtained numerically with commercial finite element analysis (FEA) software ABAQUS, and the findings were compared with the experimental results. The results showed that the reinforcements placed diagonally significantly increased the load-carrying and energy absorption capacities of RC deep beams. Moreover, an apparent plastic plateau was seen in the load-displacement curves of these test specimens in question (DE-2 and DE-3). This finding also indicated that diagonally located reinforcements improve displacement ductility. Also, the numerical results showed that the FEM method could be used to accurately predict RC deep beams'behavior with different reinforcement arrangements.

• Structural Engineering and Mechanics
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• v.57 no.4
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• pp.657-680
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• 2016

Reinforced concrete (RC) deep beams are structural members that predominantly fail in shear. Therefore, determining the shear strength of these types of beams is very important. The strut-and-tie method is commonly used to design deep beams, and this method has been adopted in many building codes (ACI318-14, Eurocode 2-2004, CSA A23.3-2004). In this study, the efficiency of artificial neural networks (ANNs) in predicting the shear strength of RC deep beams is investigated as a different approach to the strut-and-tie method. An ANN model was developed using experimental data for 214 normal and high-strength concrete deep beams from an existing literature database. Seven different input parameters affecting the shear strength of the RC deep beams were selected to create the ANN structure. Each parameter was arranged as an input vector and a corresponding output vector that includes the shear strength of the RC deep beam. The ANN model was trained and tested using a multi-layered back-propagation method. The most convenient ANN algorithm was determined as trainGDX. Additionally, the results in the existing literature and the accuracy of the strut-and-tie model in ACI318-14 in predicting the shear strength of the RC deep beams were investigated using the same test data. The study shows that the ANN model provides acceptable predictions of the ultimate shear strength of RC deep beams (maximum $R^2{\approx}0.97$). Additionally, the ANN model is shown to provide more accurate predictions of the shear capacity than all the other computed methods in this study. The ACI318-14-STM method was very conservative, as expected. Moreover, the study shows that the proposed ANN model predicts the shear strengths of RC deep beams better than does the strut-and-tie model approaches.

• Steel and Composite Structures
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• v.20 no.2
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• pp.337-355
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• 2016

Steel coupling beam in reinforced concrete (RC) coupled shear wall system is a proper substitute for deep concrete coupling beam. Previous studies have shown that RC coupled walls with steel or concrete coupling beam designed with strength-based design approach, may not guarantee a ductile behavior of a coupled shear wall system. Therefore, seismic performance evaluation of RC coupled shear wall with steel or concrete coupling beam designed based on a strength-based design approach is essential. In this paper first, buildings with 7, 14 and 21 stories containing RC coupled shear wall system with concrete and steel coupling beams were designed with strength-based design approach, then performance level of these buildings were evaluated under two spectrum; Design Basis Earthquake (DBE) and Maximum Considered Earthquake (MCE). The performance level of LS and CP of all buildings were satisfied under DBE and MCE respectively. In spite of the steel coupling beam, concrete coupling beam in RC coupled shear wall acts like a fuse under strong ground motion.

• Journal of Korean Association for Spatial Structures
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• v.23 no.2
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• pp.29-36
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• 2023

Reinforcement learning (RL) is widely applied to various engineering fields. Especially, RL has shown successful performance for control problems, such as vehicles, robotics, and active structural control system. However, little research on application of RL to optimal structural design has conducted to date. In this study, the possibility of application of RL to structural design of reinforced concrete (RC) beam was investigated. The example of RC beam structural design problem introduced in previous study was used for comparative study. Deep q-network (DQN) is a famous RL algorithm presenting good performance in the discrete action space and thus it was used in this study. The action of DQN agent is required to represent design variables of RC beam. However, the number of design variables of RC beam is too many to represent by the action of conventional DQN. To solve this problem, multi-agent DQN was used in this study. For more effective reinforcement learning process, DDQN (Double Q-Learning) that is an advanced version of a conventional DQN was employed. The multi-agent of DDQN was trained for optimal structural design of RC beam to satisfy American Concrete Institute (318) without any hand-labeled dataset. Five agents of DDQN provides actions for beam with, beam depth, main rebar size, number of main rebar, and shear stirrup size, respectively. Five agents of DDQN were trained for 10,000 episodes and the performance of the multi-agent of DDQN was evaluated with 100 test design cases. This study shows that the multi-agent DDQN algorithm can provide successfully structural design results of RC beam.

• Advances in concrete construction
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• v.13 no.1
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• pp.1-10
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• 2022

Concrete is a brittle material and weak in tension. Traditionally, web reinforcement in the form of vertical stirrups is used in reinforced concrete (RC) beams to take care of principal stresses that may cause failure when they are subjected to shear stresses. In recent decades, the potential of various types of fibers for improving post-cracking behavior of RC beams and replacing stirrups completely or partially have been studied. It has been shown that the use of steel fibers randomly dispersed and oriented in concrete has a significant potential for enhancing mechanical properties of RC beams. However, the studies on deep steel fiber reinforced concrete (SFRC) beams are limited when compared to those focusing on slender beams. An experimental program consisting of three RC and nine SFRC deep beams without stirrups were conducted in this study. Besides, various models developed for predicting the ultimate shear strength and diagonal cracking strength of SFRC deep beams without stirrups were applied to experimental data obtained from the literature and this study.

• Computers and Concrete
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• v.13 no.1
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• pp.135-147
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• 2014

Strut-and-tie model (STM) has been recommended by many codes and standards as a rational model for discontinuity regions in structural members. STM has been adopted in ACI building code for analysis of reinforced concrete (RC) deep beams since 2002. However, STM recommended by ACI 318-11 is only applicable for analysis of ordinary RC deep beams. This paper aims to develop the STM for CFRP strengthened RC deep beams through the strut effectiveness factor recommended by ACI 318-11. Two sets of RC deep beams were cast and tested in this research. Each set consisted of six simply-supported specimens loaded in four-point bending. The first set had no CFRP strengthening while the second was strengthened by means of CFRP sheets using two-side wet lay-up system. Each set consisted of six RC deep beams with shear span to effective depth ratio of 0.75, 1.00, 1.25, 1.50, 1.75, and 2.00.The value of strut effectiveness factor recommended by ACI 318-11 is modified using a proposed empirical relationship in this research. The empirical relationship is established based on shear span to effective depth ratio.

• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.3
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• pp.149-158
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• 2004

In this study, deep beam specimens are designed to have the effective shear span to depth ratio 1.0 and web opening within effective shear region. The purpose of this study is to investigate experimentally the shear strengthening effect between before failure and after failure upon using fiber sheets for RC deep beam with opening in web. The results can be summarized as follows; 1)When deep beams with web opening were failed in shear, their initial diagonal crack load and crack width were not influenced by their types of the arranged steel bars. 2)Deep beam with the horizontal reinforced bar was effective in the ultimate load of deep beam with web opening in shear failure 3)There were the approximate values between the experimental values and the analysis of finite element method. 4)The ultimate failure strengths of the repaired and strengthened specimens were increased about 34.4%~83.8% in comparison with specimens not to be strengthened.

• International Journal of Concrete Structures and Materials
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• v.7 no.2
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• pp.127-133
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• 2013

After reviewing the background and motivations for using modern computational methods for the design of reinforced concrete structures, an algorithm making use of the object oriented programming language Python and professionally developed finite element software is presented for the sizing and placement of the reinforcement in RC structures. The developed method is then used to design the reinforcement of a deep beam. To validate the design, two identical deep beam specimens were manufactured with the obtained steel, and then tested in the laboratory. It was found that the experimental results corroborated those predicted with the finite element design method.

• Earthquakes and Structures
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• v.12 no.1
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• pp.23-34
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• 2017

Composite steel plate deep beam (CDB) is proposed as a lateral resisting member, which is constructed by steel plate and reinforced concrete (RC) panel, and it is connected with building frame through high-strength bolts. To investigate the seismic performance of the CDB, tests of two 1/3 scaled specimens with different length-to-height ratio were carried out under cyclic loads. The failure modes, load-carrying capacity, hysteretic behavior, ductility and energy dissipation were obtained and analyzed. In addition, the nonlinear finite element (FE) models of the specimens were established and verified by the test results. Besides, parametric analyses were performed to study the effect of length-to-height ratio, height-to-thickness ratio, material type and arrangement of RC panel. The experimental and numerical results showed that: the CDBs lost their load-carrying capacity because of the large out-of plane deformation and yield of the tension field formed on the steel plate. By increasing the length-to-height ratio of steel plate, the load-carrying capacity, elastic stiffness, ductility and energy dissipation capacity of the specimens were significantly enhanced. The ultimate loading capacity increased with increasing the length-to-height ratio of steel plate and yield strength of steel plate; and such capacity increased with decreasing of height-to-thickness ratio of steel plate and gap. Finally, a unified formula is proposed to calculate their ultimate loading capacity, and fitting formula on such indexes are provided for designation of the CDB.