Genetic-programming-based Modeling of RC Beam Torsional Strength

Abdulkadir Cevik,Musa Hakan Arslan,Mehmet Alpaslan Koroglu 대한토목학회 2010 KSCE Journal of Civil Engineering Vol.14 No.3

This study investigates the use of Genetic Programming (GP) to model Reinforced Concrete (RC) beam torsional strength. Experimental data of 76 rectangular RC beams from an existing database were used to develop the GP model. The following input parameters, which affect torsional strength, were selected: beam cross-sectional area, closed stirrup dimensions, stirrup spacing,closed stirrup cross-sectional area of one leg, stirrup and longitudinal reinforcement yield strength, stirrup steel ratio, longitudinal reinforcement steel ratio and concrete compressive strength. Moreover, a short review of well-known building codes in relation to the design of RC beams under pure torsion is presented. The accuracy of the codes in predicting the RC beam torsional strength was also compared with the proposed GP model using the same test data. The study concludes that the proposed GP model predicts RC beam torsional strength more accurately than building codes

Modelling the performance of self-compacting SIFCON of cement slurries using genetic programming technique

Abdulkadir Cevik,Mohammed Sonebi 사단법인 한국계산역학회 2008 Computers and Concrete, An International Journal Vol.5 No.5

The paper explores the potential of applicability of Genetic programming approach (GP), adopted in this investigation, to model the combined effects of five independent variables to predict the mini-slump, the plate cohesion meter, the induced bleeding test, the J-fiber penetration value, and the compressive strength at 7 and 28 days of self-compacting slurry infiltrated fiber concrete (SIFCON). The variables investigated were the proportions of limestone powder (LSP) and sand, the dosage rates of superplasticiser (SP) and viscosity modifying agent (VMA), and water-to-binder ratio (W/B). Twenty eight mixtures were made with 10-50% LSP as replacement of cement, 0.02-0.06% VMA by mass of cement, 0.6-1.2% SP and 50-150% sand (% mass of binder) and 0.42-0.48 W/B. The proposed genetic models of the self-compacting SIFCON offer useful modelling approach regarding the mix optimisation in predicting the fluidity, the cohesion, the bleeding, the penetration, and the compressive strength.

Reliability-based modeling of punching shear capacity of FRP-reinforced two-way slabs

Ahmet Emin Kurtoglu,Abdulkadir Cevik,Hasan M. Albegmprli,Mehmet Eren Gulsan,Mahmut Bilgehan 사단법인 한국계산역학회 2016 Computers and Concrete, An International Journal Vol.17 No.1

This paper deals with the reliability analysis of design formulations derived for predicting the punching shear capacity of FRP-reinforced two-way slabs. Firstly, a new design code formulation was derived by means of gene expression programming. This formulation differs from the existing ones as the slab length (L) was introduced in the equation. Next, the proposed formulation was tested for its generalization capability by a parametric study. Then, the stochastic analyses of derived and existing formulations were performed by Monte Carlo simulation. Finally, the reliability analyses of these equations were carried out based on the results of stochastic analysis and the ultimate state function of ASCE-7 and ACI-318 (2011). The results indicate that the prediction performance of new formulation is significantly higher as compared to available design equations and its reliability index is within acceptable limits.

Modelling fresh properties of self-compacting concrete using neural network technique

Mohammed Sonebi,Steffen Grunewald,Abdulkadir Cevik,Joost Walraven 사단법인 한국계산역학회 2016 Computers and Concrete, An International Journal Vol.18 No.4

The purpose of this paper is to investigate the feasibility of using artificial neural network programming for the prediction of the fresh properties of self-compacting concrete. The input parameters of the neural network were the mix composition influencing the fresh properties of self-compacting concrete namely, the cement content, the dosages of limestone powder and water, fine aggregate, coarse aggregate, and superplasticizer, and other parameter of time of testing (5, 30 and 60 minutes after addition of water). The model is based on a multilayer feed forward neural network. The details of the proposed ANN with its architecture, training and validation are presented in this paper. Six outputs of the ANN models related to the fresh properties were the slump flow, T50, T60, V-funnel flow time, Orimet flow time, and blocking ratio (L-box). The effectiveness of the trained ANN is evaluated by comparing its responses with the experimental data that were used in the training process. The dosage of water was varied from 188 to 208 L/m3, the dosage of SP from 3.8 to 5.8 kg/m3, and the volume of coarse aggregates from 220 to 360 L/m3 (587 to 961 kg/m3). In total twenty mixes were used to measure the fresh properties with different mix compositions. ANN performed well and provided very good correlation coefficients (R2) above 0.957 for slump flow, T50, V-funnel flow time, Orimet flow time, and L-box blocking ratio. The predicting results for T60 was slightly lower (R2=0.823). With the calculated models these properties of new mixes within the practical range of the input variables used in the training can be predicted with an absolute error for slump flow, T50, T60, V-funnel flow time, Orimet flow time, and L-box ratio of 3.3%, 13%, 16%, 14%, 15%, and 22%, respectively. The results show that the ANN model can predict accurately the fresh properties of SCC.

Stochastic finite element based reliability analysis of steel fiber reinforced concrete (SFRC) corbels

Mehmet Eren Gulsan,Abdulkadir Cevik,AhmetEminKurtoglu 사단법인 한국계산역학회 2015 Computers and Concrete, An International Journal Vol.15 No.2

In this study, reliability analyses of steel fiber reinforced concrete (SFRC) corbels based on stochastic finite element were performed for the first time in literature. Prior to stochastic finite element analysis, an experimental database of 84 sfrc corbels was gathered from literature. These sfrc corbels were modeled by a special finite element program. Results of experimental studies and finite element analysis were compared and found to be very close to each other. Furthermore experimental crack patterns of corbel were compared with finite element crack patterns and were observed to be quite similar. After verification of the finite element models, stochastic finite element analyses were implemented by a specialized finite element module. As a result of stochastic finite element analysis, appropriate probability distribution functions (PDF’s) were proposed. Finally, coefficient of variation, bias and strength reduction (resistance) factors were proposed for sfrc corbels as a consequence of stochastic based reliability analysis.

3D FE modeling and parametric analysis of steel fiber reinforced concrete haunched beams

Al Jawahery, Mohammed S.,Cevik, Abdulkadir,Gulsan, Mehmet Eren Techno-Press 2022 Advances in concrete construction Vol.13 No.1

This paper investigates the shear behavior of reinforced concrete haunched beams (RCHBs) without stirrups. The research objective is to study the effectiveness of the ideal steel fiber (SF) ratio, which is used to resist shear strength, besides the influence of main steel reinforcement, compressive strength, and inclination angles of the haunched beam. The modeling and analysis were carried out by Finite Element Method (FE) based on a software package, called Atena-GiD 3D. The program of this study comprises two-part. One of them consists of nine results of experimental SF RCHBs which are used to identify the accuracy of FE models. The other part comprises 81 FE models, which are divided into three groups. Each group differed from another group by the area of main steel reinforcement (A_s) which are 226, 339, and 509 mm². The other parameters which are considered in each group in the same quantities to study the effectiveness of them, were steel fiber volumetric ratios (0.0, 0.5, and 1.0)%, compressive strength (20.0, 40.0, 60.0) MPa, and the inclination angle of haunched beam (0.0°, 10.0°, and 15.0°). Moreover, the parametric analysis was carried out on SF RCHBs to clarify the effectiveness of each parameter on the mechanical behavior of SF RCHBs. The results show that the correlation coefficient (R²) between shear load capacities of FE proposed models and shear load capacities of experimental SF RCHBs is 0.9793, while the effective inclination angle of the haunched beam is 10° which contributes to resisting shear strength, besides the ideal ratio of steel fibers is 1% when the compressive strength of SF RCHBs is more than 20 MPa.

Finite element and design code assessment of reinforced concrete haunched beams

Gulsan, Mehmet Eren,Albegmprli, Hasan M.,Cevik, Abdulkadir Techno-Press 2018 Structural Engineering and Mechanics, An Int'l Jou Vol.66 No.4

This pioneer study focuses on finite element modeling and numerical modeling of three types of Reinforced Concrete Haunched Beams (RCHBs). Firstly, twenty RCHBs, consisting of three types, and four prismatic beams which had been tested experimentally were modeled via a nonlinear finite element method (NFEM) based software named as, ATENA. The modeling results were compared with experimental results including load capacity, deflection, crack pattern and mode of failure. The comparison showed a good agreement between the results and thus the model used can be effectively used for further studies of RCHB with high accuracy. Afterwards, new mechanism modes and design code equations were proposed to improve the shear design equation of ACI-318 and to predict the critical effective depth. These equations are the first comprehensive formulas in the literature involving all types of RCHBs. The statistical analysis showed the superiority of the proposed equation to their predecessors where the correlation coefficient, $R^2$ was found to be 0.89 for the proposed equation. Moreover, the new equation was validated using parametric and reliability analyses. The parametric analysis of both experimental and predicted results shows that the inclination angle and the compressive strength were the most influential parameters on the shear strength. The reliability analysis indicates that the accuracy of the new formulation is significantly higher as compared to available design equations and its reliability index is within acceptable limits.

Comprehensive experimental investigation on mechanical behavior for types of reinforced concrete Haunched beam

Albegmprli, Hasan M.,Gulsan, M. Eren,Cevik, Abdulkadir Techno-Press 2019 Advances in concrete construction Vol.7 No.1

This study presents a comprehensive experimental investigation on mostly encountered types of Reinforced Concrete Haunched Beams (RCHBs) where three modes of RCHBs investigated; the diversity of studied beams makes it a pioneer in this topic. The experimental study consists of twenty RCHBs and four prismatic beams. Effects of important parameters including beam type, the inclination angle, flexure and compressive reinforcement, shear reinforcement on mechanical behavior and failure mode of each mode of RCHBs were examined in detail. Furthermore crack propagation at certain load levels were inspected and visualized for each RCHB mode. The results confirm that RCHBs have different behavior in shear as compared to the prismatic beams. At the same time, different mechanical behavior was observed between the modes of RCHBs. Therefore, RCHBs were classified into three modes according to the inclination shape and mode of failure (Modes A, B and C). However, it was observed that there is no significant difference between RCHBs and prismatic beams regarding flexural behavior. Moreover, a new and unified formula was proposed to predict the critical effective depth of all modes of RCHBs that is very useful to predict the critical section for failure.

Finite element and design code assessment of reinforced concrete haunched beams

Mehmet Eren Gulsan,Hasan M. Albegmprli,Abdulkadir Cevik 국제구조공학회 2018 Structural Engineering and Mechanics, An Int'l Jou Vol.66 No.4

This pioneer study focuses on finite element modeling and numerical modeling of three types of Reinforced Concrete Haunched Beams (RCHBs). Firstly, twenty RCHBs, consisting of three types, and four prismatic beams which had been tested experimentally were modeled via a nonlinear finite element method (NFEM) based software named as, ATENA. The modeling results were compared with experimental results including load capacity, deflection, crack pattern and mode of failure. The comparison showed a good agreement between the results and thus the model used can be effectively used for further studies of RCHB with high accuracy. Afterwards, new mechanism modes and design code equations were proposed to improve the shear design equation of ACI-318 and to predict the critical effective depth. These equations are the first comprehensive formulas in the literature involving all types of RCHBs. The statistical analysis showed the superiority of the proposed equation to their predecessors where the correlation coefficient, R2 was found to be 0.89 for the proposed equation. Moreover, the new equation was validated using parametric and reliability analyses. The parametric analysis of both experimental and predicted results shows that the inclination angle and the compressive strength were the most influential parameters on the shear strength. The reliability analysis indicates that the accuracy of the new formulation is significantly higher as compared to available design equations and its reliability index is within acceptable limits.

Effects of sulphuric acid on mechanical and durability properties of ECC confined by FRP fabrics

Gulsan, Mehmet Eren,Mohammedameen, Alaa,Sahmaran, Mustafa,Nis, Anil,Alzeebaree, Radhwan,Cevik, Abdulkadir Techno-Press 2018 Advances in concrete construction Vol.6 No.2

In this study, the effects of sulphuric acid on the mechanical performance and the durability of Engineered Cementitious Composites (ECC) specimens were investigated. The carbon fiber reinforced polymer (CFRP) and basalt fiber reinforced polymer (BFRP) fabrics were used to evaluate the performances of the confined and unconfined ECC specimens under static and cyclic loading in the acidic environment. In addition, the use of CFRP and BFRP fabrics as a rehabilitation technique was also studied for the specimens exposed to the sulphuric acid environment. The polyvinyl alcohol (PVA) fiber with a fraction of 2% was used in the research. Two different PVA-ECC concretes were produced using low lime fly ash (LCFA) and high lime fly ash (HCFA) with the fly ash-to-OPC ratio of 1.2. Unwrapped PVA-ECC specimens were also produced as a reference concrete and all concrete specimens were continuously immersed in 5% sulphuric acid solution ($H_2SO_4$). The mechanical performance and the durability of specimens were evaluated by means of the visual inspection, weight change, static and cyclic loading, and failure mode. In addition, microscopic changes of the PVA-ECC specimens due to sulphuric acid attack were also assessed using scanning electron microscopy (SEM) to understand the macroscale behavior of the specimens. Results indicated that PVA-ECC specimens produced with low lime fly ash (LCFA) showed superior performance than the specimens produced with high lime fly ash (HCFA) in the acidic environment. In addition, confinement of ECC specimens with BFRP and CFRP fabrics significantly improved compressive strength, ductility, and durability of the specimens. PVA-ECC specimens wrapped with carbon FRP fabric showed better mechanical performance and durability properties than the specimens wrapped with basalt FRP fabric. Both FRP materials can be used as a rehabilitation material in the acidic environment.