Optimum Design of Reinforced Concrete Beams

2020 ◽  
pp. 71-91
Keyword(s):  
Reinforced Concrete ◽  
Optimum Design ◽  
Nonlinear Behavior ◽  
Optimization Method ◽  
Reinforced Concrete Beams ◽  
Metaheuristic Algorithms ◽  
Rc Beam ◽  
Rc Structures ◽  
Eurocode 2 ◽  
The Cost

The design of reinforced concrete (RC) beams need special conditions to provide a ductile design. In this design, the maximum amount of tensile reinforcement must be limited to singly reinforced design. After the singly reinforced limit, the cost of doubly reinforced RC beam rapidly increases, and it may not be an optimum design. To consider this nonlinear behavior and other rules used in RC structures according to regulations such as ACI 318: Building code requirements for structural concrete and Eurocode 2: Design of concrete structures, an algorithmic and iteration optimization method is needed. In this chapter, two examples are presented, and optimum results are shared for methodologies employing several metaheuristic algorithms. The importance of using metaheuristic algorithms can be seen in this chapter.

scholarly journals Simplified Estimation Method for Maximum Deflection in Bending-Failure-Type Reinforced Concrete Beams Subjected to Collision Action and Its Application Range

2020 ◽  
Vol 10 (19) ◽  
pp. 6941 ◽  
Author(s):  
Yusuke Kurihashi ◽  
Hiroshi Masuya
Keyword(s):  
Reinforced Concrete ◽  
Estimation Method ◽  
Reinforced Concrete Beams ◽  
Rc Beam ◽  
Maximum Deflection ◽  
Simple Method ◽  
Rc Structures ◽  
Failure Type ◽  
Bending Failure ◽  
The Impact

As natural disasters have become increasingly severe, many structures designed to prevent rockfalls and landslides have been constructed in various areas. The impact resistance capacity of a reinforced concrete (RC) rock shed can be evaluated using its roof deflection. This study establishes a method for estimating the maximum deflection of a bending-failure-type RC beam, subjected to collisions that is based on the energy conservation concept—in which, the transmitted energy from a collision is equivalent to the energy absorbed by the beam. However, the following assumptions have never been confirmed: (1) The energy transmitted to the RC beam, due to the dropped weight, can be estimated by assuming a perfect plastic collision; and (2) the energy absorbed by the RC beam can be estimated by assuming plane conservation. In this study, these assumptions were verified using 134 previous test results of RC beams subject to weight collisions. In addition, we proposed a simple method for calculating the maximum deflection and its application scope. With this method, a performance-based impact-resistant design procedure for various RC structures can be established in the future. Moreover, this method will significantly improve the maintenance and management of existing RC structures subject to collisions.

scholarly journals New design model of reinforced concrete beams in bending considering the ductility factor

2020 ◽  
Vol 13 (1) ◽  
pp. 120-141
Author(s):  
C. G. NOGUEIRA ◽  
I. D. RODRIGUES
Keyword(s):  
Reinforced Concrete ◽  
Concrete Beams ◽  
Input Parameter ◽  
Reinforced Concrete Beams ◽  
Design Model ◽  
Design Codes ◽  
Rc Structures ◽  
Ductility Factor ◽  
Eurocode 2 ◽  
Definition Of

Abstract Ductility is a recommended characteristic by different RC structures design codes around the world, such as ABNT NBR 6118 [2], ACI 318 [1] and EUROCODE 2 [4]. Despite the recommendation of ductility, the codes only define this criterion in a qualitative way, without quantification about how ductile the structure is, and not being able to stablish a ductility level in the design phase. In this context, this paper proposes a new design model of reinforced concrete beams in bending considering the explicit definition of the input parameter named ductility factor, which quantifies the structure’s ability to withstand displacement before it breaks.

Metaheuristic algorithms in optimum design of reinforced concrete beam by investigating strength of concrete

2020 ◽  
Vol 11 (2) ◽  
pp. 26 ◽  
Author(s):  
Serdar Ulusoy ◽  
Aylin Ece Kayabekir ◽  
Gebrail Bekdaş ◽  
Sinan Melih Nigdeli
Keyword(s):  
Reinforced Concrete ◽  
Optimum Design ◽  
Cost Minimization ◽  
Harmony Search ◽  
High Strength ◽  
Bat Algorithm ◽  
Engineering Problem ◽  
Metaheuristic Algorithms ◽  
Rc Structures ◽  
Strength Material

The locations of structural members can be provided according to architectural projects in the design of reinforced concrete (RC) structures. The design of dimensions is the subject of civil engineering, and these designs are done according to the experience of the designer by considering the regulation suggestions, but these dimensions and the required reinforcement plan may not be optimum. For that reason, the dimensions and detailed reinforcement design of RC structures can be found by using optimization methods. To reach optimum results, metaheuristic algorithms can be used. In this study, several metaheuristic algorithms such as harmony search, bat algorithm and teaching learning-based optimization are used in the design of several RC beams for cost minimization. The optimum results are presented for different strength of concrete. The results show that using high strength material for high flexural moment capacity has lower cost than low stretch concrete since doubly reinforced design is not an optimum choice. The results prove that a definite metaheuristic algorithm cannot be proposed for the best optimum design of an engineering problem. According to the investigation of compressive strength of concrete, it can be said that a low strength material are optimum for low flexural moment, while a high strength material may be the optimum one by the increase of the flexural moment as expected.

scholarly journals Statistical and Reliability Study on Shear Strength of Recycled Coarse Aggregate Reinforced Concrete Beams

Materials ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3321
Author(s):  
Hyunjin Ju ◽  
Meirzhan Yerzhanov ◽  
Alina Serik ◽  
Deuckhang Lee ◽  
Jong R. Kim
Keyword(s):  
Reinforced Concrete ◽  
Concrete Beams ◽  
Construction Material ◽  
Safety Margin ◽  
Shear Capacity ◽  
Reinforced Concrete Beams ◽  
Construction And Demolition Waste ◽  
Demolition Waste ◽  
Rc Structures ◽  
Coarse Aggregates

The consumption of structural concrete in the construction industry is rapidly growing, and concrete will remain the main construction material for increasing urbanization all over the world in the near future. Meanwhile, construction and demolition waste from concrete structures is also leading to a significant environmental problem. Therefore, a proper sustainable solution is needed to address this environmental concern. One of the solutions can be using recycled coarse aggregates (RCA) in reinforced concrete (RC) structures. Extensive research has been conducted in this area in recent years. However, the usage of RCA concrete in the industry is still limited due to the absence of structural regulations appropriate to the RCA concrete. This study addresses a safety margin of RCA concrete beams in terms of shear capacity which is comparable to natural coarse aggregates (NCA) concrete beams. To this end, a database for reinforced concrete beams made of recycled coarse aggregates with and without shear reinforcement was established, collecting the shear specimens available from various works in the existing literature. The database was used to statistically identify the strength margin between RCA and NCA concrete beams and to calculate its safety margin based on reliability analysis. Moreover, a comparability study of RCA beams was conducted with its control specimens and with a database for conventional RC beams.

scholarly journals Application of artificial neural networks to predict the deflections of reinforced concrete beams

2016 ◽  
Vol 38 (2) ◽  
pp. 37-46 ◽  
Author(s):  
Mateusz Kaczmarek ◽  
Agnieszka Szymańska
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Network ◽  
Reinforced Concrete ◽  
Concrete Beams ◽  
Reinforced Concrete Beams ◽  
The Neural Network ◽  
Eurocode 2 ◽  
Artificial Neural ◽  
Concrete Elements

Abstract Nonlinear structural mechanics should be taken into account in the practical design of reinforced concrete structures. Cracking is one of the major sources of nonlinearity. Description of deflection of reinforced concrete elements is a computational problem, mainly because of the difficulties in modelling the nonlinear stress-strain relationship of concrete and steel. In design practise, in accordance with technical rules (e.g., Eurocode 2), a simplified approach for reinforced concrete is used, but the results of simplified calculations differ from the results of experimental studies. Artificial neural network is a versatile modelling tool capable of making predictions of values that are difficult to obtain in numerical analysis. This paper describes the creation and operation of a neural network for making predictions of deflections of reinforced concrete beams at different load levels. In order to obtain a database of results, that is necessary for training and testing the neural network, a research on measurement of deflections in reinforced concrete beams was conducted by the authors in the Certified Research Laboratory of the Building Engineering Institute at Wrocław University of Science and Technology. The use of artificial neural networks is an innovation and an alternative to traditional methods of solving the problem of calculating the deflections of reinforced concrete elements. The results show the effectiveness of using artificial neural network for predicting the deflection of reinforced concrete beams, compared with the results of calculations conducted in accordance with Eurocode 2. The neural network model presented in this paper can acquire new data and be used for further analysis, with availability of more research results.

scholarly journals Multiobjective optimal design of reinforced concrete frames using two metaheuristic algorithms

2021 ◽  
Vol 9 (4B) ◽  
Author(s):  
Mehdi Babaei ◽  
◽  
Masoud Mollayi ◽  
Keyword(s):  
Reinforced Concrete ◽  
Optimal Design ◽  
Optimization Problem ◽  
Numerical Models ◽  
Steel Structures ◽  
Metaheuristic Algorithms ◽  
Rc Structures ◽  
Weighted Sum Method ◽  
Rc Frames ◽  
Single Objective

Genetic algorithm (GA) and differential evolution (DE) are metaheuristic algorithms that have shown a favorable performance in the optimization of complex problems. In recent years, only GA has been widely used for single-objective optimal design of reinforced concrete (RC) structures; however, it has been applied for multiobjective optimization of steel structures. In this article, the total structural cost and the roof displacement are considered as objective functions for the optimal design of the RC frames. Using the weighted sum method (WSM) approach, the two-objective optimization problem is converted to a single-objective optimization problem. The size of the beams and columns are considered as design variables, and the design requirements of the ACI-318 are employed as constraints. Five numerical models are studied to test the efficiency of the GA and DE algorithms. Pareto front curves are obtained for the building models using both algorithms. The detailed results show the accuracy and convergence speed of the algorithms.

Performance of Multifiber Beam Element for Seismic Analysis of Reinforced Concrete Structures

2014 ◽  
Vol 14 (06) ◽  
pp. 1450013 ◽  
Author(s):  
Xuan Huy Nguyen
Keyword(s):  
Reinforced Concrete ◽  
Damage Mechanics ◽  
Seismic Analysis ◽  
Axial Strain ◽  
Nonlinear Behavior ◽  
Bending Moment ◽  
Axial Direction ◽  
Beam Element ◽  
Shaking Table ◽  
Rc Structures

This paper presents a simplified modeling strategy for simulating the nonlinear behavior of reinforced concrete (RC) structures under seismic loadings. A new type of Euler–Bernoulli multifiber beam element with axial force and bending moment interaction is introduced. To analyze the behavior of RC structures in the axial direction, the interpolation of the axial strain is enriched using the incompatible modes method. The model uses the constitutive laws based on plasticity for steel and damage mechanics for concrete. The proposed multifiber element is implemented in the finite element Code_Aster to simulate the nonlinear behavior of two different RC structures. One structure is a building tested on a shaking table; the other is a column subjected to cyclic loadings. The comparison between the simulation and experimental results shows that the performance of this approach is quite good. The proposed model can be used to investigate the behavior of a wider variety of configurations which are impossible to study experimentally.

Repair of Severely Damaged Reinforced Concrete Beams with High-Strength Cementitious Grout

2020 ◽  
Vol 2674 (6) ◽  
pp. 372-384
Author(s):  
Antoine N. Gergess ◽  
Mahfoud Shaikh Al Shabab ◽  
Razane Massouh
Keyword(s):  
Reinforced Concrete ◽  
High Performance ◽  
High Performance Concrete ◽  
High Strength ◽  
Cementitious Materials ◽  
Fiber Reinforced Concrete ◽  
Steel Fibers ◽  
Reinforced Concrete Beams ◽  
Rc Beams ◽  
Rc Structures

High-strength cementitious materials such as high-performance concrete are extensively used for retrofit of reinforced concrete (RC) structures. The effectiveness of these materials is increased when mixed with steel fibers. A commonly used technique for strengthening and repair of RC beams consists of applying high-performance fiber-reinforced concrete jackets around the beam perimeter. This paper investigates the jacketing method for repairing severely damaged RC beams. Four 2 m (6 ft 63/4 in.) long rectangular RC beams, 200 × 300 mm (8 ×12 in.) were initially cast and loaded until failure based on three-point bending tests. The four beams were then repaired by thickening the sides of the damaged RC beams using a commercially available high-strength shrinkage grout with and without steel fibers. Strain and deformation were recorded in the damaged and repaired beams to compare structural performance. It is shown that the flexural strength of the repaired beams is increased and the crack pattern under loading is improved, proving that the proposed repair method can restore the resistance capacity of RC beams despite the degree of damage. A method for repair is proposed and an analytical investigation is also performed to understand the structural behavior of the repaired beams based on different thickening configurations.

scholarly journals Heating Temperature Prediction of Concrete Structure Damaged by Fire Using a Bayesian Approach

2020 ◽  
Vol 12 (10) ◽  
pp. 4225
Author(s):  
Hae-Chang Cho ◽  
Sun-Jin Han ◽  
Inwook Heo ◽  
Hyun Kang ◽  
Won-Hee Kang ◽  
...  
Keyword(s):  
Reinforced Concrete ◽  
Elevated Temperatures ◽  
Heating Temperature ◽  
Model Development ◽  
Estimation Model ◽  
Temperature Estimation ◽  
Rc Structures ◽  
Material Development ◽  
Rc Structure ◽  
Eurocode 2

A fire that occurs in a reinforced concrete (RC) structure accompanies a heating temperature, and this negatively affects the concrete material properties, such as the compressive strength, the bond between cement paste and aggregate, and the cracking and spalling of concrete. To appropriately measure the reduced structural performance and durability of fire-damaged RC structures, it is important to accurately estimate the heating temperature of the structure. However, studies in the literature on RC structures damaged by fire have focused mostly on structural member tests at elevated temperatures to ensure the fire resistance or fire protection material development; studies on estimating the heating temperature are very limited except for the very few existing models. Therefore, in this study, a heating temperature estimation model for a reinforced concrete (RC) structure damaged by fire was developed using a statistical Bayesian parameter estimation approach. For the model development, a total of 77 concrete test specimens were utilized; based on them, a statistically highly accurate model has been developed. The usage of the proposed method in the framework of the 500 °C isotherm method in Eurocode 2 has been illustrated through an RC column resistance estimation application.

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