• Computers and Concrete
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• v.14 no.3
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• pp.327-345
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• 2014

This paper presents the application of multi-gene genetic programming (MGP) technique for modeling the bond strength of ribbed steel bars in concrete. In this regard, the experimental data of 264 splice beam tests from different technical papers were used for training, validating and testing the model. Seven basic parameters affecting on the bond strength of steel bars were selected as input parameters. These parameters are diameter, relative rib area and yield strength of steel bar, minimum concrete cover to bar diameter ratio, splice length to bar diameter ratio, concrete compressive strength and transverse reinforcement index. The results show that the proposed MGP model can be alternative approach for predicting the bond strength of ribbed steel bars in concrete. Moreover, the performance of the developed model was compared with the building codes' empirical equations for a complete comparison. The study concludes that the proposed MGP model predicts the bond strength of ribbed steel bars better than the existing building codes' equations. Using the proposed MGP model and building codes' equations, a parametric study was also conducted to investigate the trend of the input variables on the bond strength of ribbed steel bars in concrete.

• Computers and Concrete
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• v.16 no.3
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• pp.357-380
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• 2015

In this study, a simple indeterminate strut-tie model which reflects complicated characteristics of the ultimate structural behavior of continuous reinforced concrete deep beams was proposed. In addition, the load distribution ratio, defined as the fraction of applied load transferred by a vertical tie of truss load transfer mechanism, was proposed to help structural designers perform the analysis and design of continuous reinforced concrete deep beams by using the strut-tie model approaches of current design codes. In the determination of the load distribution ratio, a concept of balanced shear reinforcement ratio requiring a simultaneous failure of inclined concrete strut and vertical steel tie was introduced to ensure the ductile shear failure of reinforced concrete deep beams, and the primary design variables including the shear span-to-effective depth ratio, flexural reinforcement ratio, and compressive strength of concrete were reflected upon. To verify the appropriateness of the present study, the ultimate strength of 58 continuous reinforced concrete deep beams tested to shear failure was evaluated by the ACI 318M-11's strut-tie model approach associated with the presented indeterminate strut-tie model and load distribution ratio. The ultimate strength of the continuous deep beams was also estimated by the experimental shear equations, conventional design codes that were based on experimental and theoretical shear strength models, and current strut-tie model design codes. The validity of the proposed strut-tie model and load distribution ratio was examined through the comparison of the strength analysis results classified according to the primary design variables. The present study associated with the indeterminate strut-tie model and load distribution ratio evaluated the ultimate strength of the continuous deep beams fairly well compared with those by other approaches. In addition, the present approach reflected the effects of the primary design variables on the ultimate strength of the continuous deep beams consistently and reasonably. The present study may provide an opportunity to help structural designers conduct the rational and practical strut-tie model design of continuous deep beams.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.4 s.193
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• pp.93-101
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• 2007

Aluminum alloy which is one of the light materials has been tried to apply to light weight vehicle body. In order to do that, welding technology is very important. In case of the aluminum laser welding, the strength of welded part is reduced due to porosity, underfill, and magnesium loss. To overcome these problems, laser welding of aluminum with filler wire was suggested. In this study, experiment about laser welding of AA5182 aluminum alloy with AA5356 filler wire was performed according to process parameters such as laser power, welding speed and wire feed rate. The tensile strength was measured to find the weldability of laser welding with filler wire. The models to estimate tensile strength were suggested using three regression models and one neural network model. For regression models, one was the multiple linear regression model, another was the second order polynomial regression model, and the other was the multiple nonlinear regression model. Neural network model with 2 hidden layers which had 5 and 3 nodes respectively was investigated to find the most suitable model for the system. Estimation performance was evaluated for each model using the average error rate. Among the three regression models, the second order polynomial regression model had the best estimation performance. For all models, neural network model has the best estimation performance.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.03a
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• pp.139-146
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• 2002

The characteristics and prediction model for the shear strength of unsaturated residual soils was studied. In order to investigate the influence of the net normal stress on the shear strength, unsaturated triaxial tests and SWCC tests were carried out varying the net normal stress, and the experimental data for unsaturated shear strength tests were compared with predicted shear strength envelopes using existing prediction models. It was shown that the soil - water characteristic curve and the shear strength of the unsaturated soil varied with the change of the net normal stress. Therefore, to achieve a truly descriptive shear strength envelope for unsaturated soils, tile effect of the normal stress on the contribution of matric suction to the shear strength has to be taken into consideration. In this paper, a modified prediction model for the unsaturated shear strength was proposed.

• 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.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.2053-2061
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• 1994

The static and fatigue tensile tests have been conduted to predict the fatigue life of 8-harness satin woven and plain woven carbon/epoxy composite plates containing a circular hole. A fatigue residual strength degradation model, based on the assumption that the residual strength for unnotched specimen decreases monotonically, has been applied to predict statistically the fatigue life of materials used in this study. To determine the parameters(c, b and K) of the residual strength degradation model, the minimization technique and the maximum likelihood method are used. Agreement of the converted ultimate strength by using the minimization technique with the static ultimate strength is reasonably good. Therefore, the minimization technique is more adjustable in the determination of the parameter and the prediction of the fatigue life than the maximum likelihood method.

• Computers and Concrete
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• v.5 no.1
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• pp.21-36
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• 2008

Steel fiber reinforced concrete is increasingly used day by day in various structural applications. An extensive experimentation was carried out with w/cm ratio ranging from 0.25 to 0.40, and fiber content ranging from zero to1.5 percent by volume with an aspect ratio of 80 and silica fume replacement at 5%, 10% and 15%. The influence of steel fiber content in terms of fiber reinforcing index on the compressive strength of high-performance fiber reinforced concrete (HPFRC) with strength ranging from 45 85 MPa is presented. Based on the test results, equations are proposed using statistical methods to predict 28-day strength of HPFRC effecting the fiber addition in terms of fiber reinforcing index. A strength model proposed by modifying the mix design procedure, can utilize the optimum water content and efficiency factor of pozzolan. To examine the validity of the proposed strength model, the experimental results were compared with the values predicted by the model and the absolute variation obtained was within 5 percent.

• Structural Engineering and Mechanics
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• v.78 no.2
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• pp.199-207
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• 2021

In the present paper, an analytical model is proposed to determine the flexural and shear strength of normal and high-strength reinforced concrete beams with longitudinal bars, in the presence of transverse stirrups. The model is based on evaluation of the resistance contribution due to beam and arch actions including interaction with stirrups. For the resistance contribution of the main bars in tension the residual bond adherence of steel bars, including the effect of stirrups and the crack spacing of R.C. beams, is considered. The compressive strength of the compressed arch is also verified by taking into account the biaxial state of stresses. The model was verified on the basis of experimental data available in the literature and it is able to include the following variables in the resistance provision: - geometrical percentage of steel bars; - depth-to-shear span ratio; - resistance of materials; - crack spacing; - tensile stress in main bars; - residual bond resistance including the presence of stirrups;- size effects. Finally, some of the more recent analytical expressions able to predict shear and flexural resistance of concrete beams are mentioned and a comparison is made with experimental data.

• Advances in concrete construction
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• v.10 no.3
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• pp.185-193
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• 2020

An analytical model is developed in this paper to predict the shear capacity of reinforced concrete (RC) columns with corroded transverse reinforcements. The shear strength model for corroded RC columns is proposed based on modifying the existing strut-and-tie model, which considers the deformational compatibility between truss and arch mechanisms. The contributions to the shear strength from both truss and arch mechanisms are incorporated in the proposed model. The effects of corrosion level of transverse reinforcements are considered in the proposed model through the minimum residual cross-sectional area of transverse reinforcements and the reduction of concrete compressive strength for the cover area. The shear strengths calculated from the developed model are compared with the experimental results from Vu's study (2017), which consisted of RC columns with corroded transverse reinforcements showing shear failure under the cyclic loading. The comparison results indicate satisfactory correlations. Parametric studies are conducted based on the developed shear strength model to explore the effects of column axial loading, aspect ratios, transverse reinforcements and the corrosion levels in transverse reinforcements to the shear strength of RC columns with corroded transverse reinforcements.

• Journal of the Earthquake Engineering Society of Korea
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• v.27 no.6
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• pp.275-281
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• 2023

The demand for high-strength steel is rising due to its economic efficiency. Low-cycle fatigue (LCF) tests have been conducted to investigate the nonlinear behaviors of high-strength steel. Accurate material models must be used to obtain reliable results on seismic performance evaluation using numerical analyses. This study uses the combined hardening model to simulate the LCF behavior of high-strength steel. However, it is challenging and complex to determine material model parameters for specific high-strength steel because a highly nonlinear equation is used in the model, and several parameters need to be resolved. This study used the particle swarm algorithm (PSO) to determine the model parameters based on the LCF test data of HSA 650 steel. It is shown that the model with parameter values selected from the PSO accurately simulates the measured LCF curves.