Yielding and Ultimate Deformations of Wide and Deep Reinforced Concrete Beams

Current formulations proposed by Eurocode 8 part 3 for the inelastic deformations of existing reinforced concrete members are assessed separately for wide beams (WB) and conventional deep beams (DB). The current approach, based on a large experimental database of members, predicts larger ultimate chord rotation but lower chord rotation ductility for WB rather than for DB despite the similar curvature ductility, due to lower plastic hinge lengths in WB. However, if the data are disaggregated into DB and WB, predicted chord rotations are consistently conservative for DB and not conservative for WB if compared with experimental values, especially at ultimate deformation. Thus, plastic hinge length may be even greater for DB in comparison to WB. Therefore, some feasible corrections of the formulations for chord rotations are proposed, in order to reduce the bias and thus increase the robustness of the model for cross-section shape variability

Efficiency of Hybrid Algorithms for Estimating the Shear Strength of Deep Reinforced Concrete Beams

Earthquakes occurred in recent years have highlighted the need to examine the strength of reinforced concrete (RC) members. RC beams are one of the elements of reinforced concrete structures. Due to the dramatic increase in the population and the number of medium/high-rise buildings, in recent years, the beams of buildings have been mainly designed and executed in the type of deep beams. In this study, the artificial neural network (ANN) with optimization algorithms, including particle swarm optimization (PSO), Archimedes optimization algorithm (AOA), and sparrow search algorithm (SSA), are used to determine the shear strength of reinforced concrete deep (RCD) beams. 271 samples from experimental tests are employed to develop algorithms. The results of this study, design codes equations, and previous research are compared. Comparison between the results shows that the PSO-ANN algorithm is more accurate than previous methods. Finally, SHApley Additive exPlanations (SHAP) method is utilized to explain the predictions. SHAP reveals that the beam span and the ratio of the beam span to beam depth have the highest impact in predicting shear strength

Neural network modelling of RC deep beam shear strength

YesA 9 x 18 x 1 feed-forward neural network (NN) model trained using a resilient back-propagation algorithm and early stopping technique is constructed to predict the shear strength of deep reinforced concrete beams. The input layer covering geometrical and material properties of deep beams has nine neurons, and the corresponding output is the shear strength. Training, validation and testing of the developed neural network have been achieved using a comprehensive database compiled from 362 simple and 71 continuous deep beam specimens. The shear strength predictions of deep beams obtained from the developed NN are in better agreement with test results than those determined from strut-and-tie models. The mean and standard deviation of the ratio between predicted capacities using the NN and measured shear capacities are 1.028 and 0.154, respectively, for simple deep beams, and 1.0 and 0.122, respectively, for continuous deep beams. In addition, the trends ascertained from parametric study using the developed NN have a consistent agreement with those observed in other experimental and analytical investigations

Experimental Evaluation of Design Procedures for Shear Strength of Deep Reinfoced Concrete Beams

In this paper, results from the monotonic testing of four reinforced concrete deep beams are presented. The behavior of the deep beams is described in terms of cracking pattern, load-versus-deflection response, failure mode, and strains in steel reinforcement and concrete. Despite different failure modes, the failure loads and corresponding ultimate deflections were similar in all four specimens. Yielding of both longitudinal and transverse reinforcement occurred prior to failure. Based on the test results, the shear design procedures contained in the ACI 318-99 Code and Appendix A of the ACI 318-02 Code were evaluated. Both design procedures yielded conservative predictions of the shear strength of the single-span deep beams

Strength and Behavior in Shear of Deep Reinforced Concrete Beams Under Static and Dynamic Loading Vol. 2: Strength and Behavior in Shear

Research Directorate, Air Force Special Weapons Center. Kirtland Air Force Base.Contract AF 29(601)-2372Project 108

Specification of Deep Beams Affect the Shear Strength Capacity

Reinforced Concrete Deep beams researches have attracted attentions of professionals and academics due to the wider use of this type of structures in construction projects; because of characteristics in transferring significant amount of load.  Ultimate strength of deep beams has been a great challenge because of the complexity to Evaluation for this structural member. However, code provisions for capacity of beam equations are conservative.  Essentially influencing parameters are Loading and Supporting Conditions, horizontal and vertical web reinforcement, shear span-to-depth ratio,   load and support bearing plates, distribution of the reinforcement along depth of the deep beam‘s web, tension  reinforcement and compressive strength.  Least influencing parameters are bottom cover, side cover, width of the beam, distribution of vertical stirrups in the web, and aggregate size, presence the web openings. The effect of above factors on the shear capacity and behavior of RC deep beams have been reviewed. Keywords: Deep beams, D-region, Loading condition, Shear strength, Reinforcement distribution, Failure mode

Non Linear Finite Element Method of Analysis of Reinforced Concrete Deep Beam

This paper describes analysis of deep beams subjected to two point loading with three different L/D ratios (1.5, 1.6, 1.71) using Non-linear Finite element method (ANSYS 9.0 software) in order to investigate the stress and strain distribution pattern at mid-section of the beam. In ANSYS 9.0 software, SOLID 65 and LINK 8 element represent concrete and reinforcing steel bars. Non-linear material properties were defined for both elements .Using ANSYS software Flexural Strains and Stresses were determined at mid-section of the beam and shear stresses near the support of the beam. Also the failure crack-patterns were obtained. Variation of flexural stresses and strains, shear stresses were plotted. It was foun

Strut and tie model optimization for reinforced concrete deep beam using genetic algorithm

This paper presents strut and tie model structural optimization of reinforced concrete deep beam using genetic algorithm. Genetic algorithm is used as the optimization platform as it does not require differentiation of the exact mathematical formulation to get the optimum solution. The force analysis is carried out using two-dimensional linear finite element method with truss element. The struts and ties design are based on ACI 318. One RC deep beam example is presented as an example. During optimization, there are two constraints which consisted of strength of the member alone and combination with deformation limit of the nodes. The stress ratio for both struts and ties are set to not exceed unity while the deformation was limited to 2.0 mm. From the optimization analysis, it can be concluded that genetic algorithm can be used to get the most optimum structural configuration which yield the most economical solution for design purposes. On the other hand, it is found out that optimizing only the strength alone can yield a more economical solution compared to the design references. However, if deformation constraint is added in the optimization parameters, larger deep beam depth is required to satisfy the deformation limits

Effect of types of fibres on the shear behaviour of deep beam with opening

This paper discusses experiments on the behaviour of deep beams with and without opening in the styles of stainless-steel fibres under a two-point load test. Triple varieties of stainless steel fibre used (constant fibre fraction (1 percent) by volume of concrete, (straight, hooked and corrugated steel fibre)). In this analysis, the key parameters were the fibre forms and the influence of the opening on the behaviour. The results show that the steel fibres raise the first crack and final loads in both groups (first group without opening the second group with opening). Besides, an increase of (20.6 to 40.5) % in first cracking load for the first group and (36.4 to 56.7) % for the second group and an increase of (59.5 to 110.1) % and (20.2 to 28.8) % in ultimate load for first and second groups respectively

Strut and tie model optimization for reinforced concrete bridge pier head structure using a genetic algorithm

Strut and tie model (STM) is more suitable to design the pierhead structures which resist high shear forces transferred from the girders. These pierhead structures behave like the disturbed regions as in reinforced concrete deep beam. The design of the struts and ties elements requires the initial geometry configuration of the truss model where its boundaries are limited by the shape of the pier head structures. To find the optimum topological shape of the truss model, the genetic algorithm (GA) optimization technique is used in this paper. The objective functions in the GA optimization consisted of minimizing the usage of concrete and steel reinforcement material and ensuring all the stress ratio of the strut and tie elements are less than equal to unity. Both prestressed and non-prestressed pierheads are investigated in this paper. The use of prestressing in the pierhead structures reduces the stresses in the main tension tie significantly and allowing some members of the shear tie and compression struts to have almost zero stresses. For these elements with zero stresses, the elements can be removed and reduces the concrete and rebar materials usage. Furthermore, the genetic algorithm optimization is found to be successful to ensure all the stress ratio in the members to be less than equal to unity