• Advances in concrete construction
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• v.5 no.4
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• pp.313-330
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• 2017

Geopolymer is a sustainable concrete, replaces traditional cement concrete using alternative sustainable construction materials as binders and alkaline solution as alkaline activator. This paper presents the strength characteristics of geopolymer concrete (GPC) developed with fly ash and GGBS as binders, combined Sodium silicate ($Na_2SiO_3$) and Sodium Hydroxide (NaOH) solution as alkaline activators. The parameters considered in this research work are proportions of fly ash and GGBS (70-30 and 50-50), curing conditions (Outdoor curing and oven curing at $600^{\circ}C$ for 24 hours), two grades of concrete (GPC20 and GPC50). The mechanical properties such as compressive strength, split tensile strength and flexural strength along with durability characteristics were determined. For studying the durability characteristics of geopolymer concrete 5% $H_2SO_4$ solutions was used and the specimens were immersed up to an exposure period of 56 days. The main parameters considered in this study were Acid Mass Loss Factor (AMLF), Acid Strength Loss Factor (ASLF) and products of degradation. The results conclude that GPC with sufficient strength can be developed even under Outdoor curing using fly ash and GGBS combination i.e., without the need for any heat curing.

• Steel and Composite Structures
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• v.11 no.4
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• pp.273-290
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• 2011

In current ductility-based earthquake-resistant design, the estimation of design forces continues to be carried out with the application of response modification factors on elastic design spectra. It is well-known that the response modification factor (R) takes into account the force reduction, strength, redundancy, and damping of structural systems. The key components of the response modification factor (R) are force reduction ($R_{\mu}$) and strength ($R_S$) factors. However, the response modification and strength factors for structural systems presented in design codes were based on professional judgment and experiences. A numerical study has been accomplished to evaluate force reduction, strength, and response modification factors for special steel moment resisting frames. A total of 72 prototype steel frames were designed based on the recommendations given in the AISC Seismic Provisions and UBC Codes. Number of stories, soil profiles, seismic zone factors, framing systems, and failure mechanisms were considered as the design parameters that influence the response. The effects of the design parameters on force reduction ($R_{\mu}$), strength ($R_S$), and response modification (R) factors were studied. Based on the analysis results, these factors for special steel moment resisting frames are evaluated.

• Computers and Concrete
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• v.27 no.3
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• pp.225-239
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• 2021

Carbon fiber reinforced polymer (CFRP) has extensive use in strengthening reinforced concrete structures due to its high strength and elastic modulus, low weight, fast and easy application, and excellent durability performance. Many studies have been carried out to determine the performance of the CFRP confined concrete cylinder. Although studies about the prediction of confined compressive strength using ANN are in the literature, the insufficiency of the studies to predict the strain of confined concrete cylinder using ANN, which is the most appropriate analysis method for nonlinear and complex problems, draws attention. Therefore, to predict both strengths and also strain values, two different ANNs were created using an extensive experimental database. The strength and strain networks were evaluated with the statistical parameters of correlation coefficients (R2), root mean square error (RMSE), and mean absolute error (MAE). The estimated values were found to be close to the experimental results. Mathematical equations to predict the strength and strain values were derived using networks prepared for convenience in engineering applications. The sensitivity analysis of mathematical models was performed by considering the inputs with the highest importance factors. Considering the limit values obtained from the sensitivity analysis of the parameters, the performances of the proposed models were evaluated by using the test data determined from the experimental database. Model performances were evaluated comparatively with other analytical models most commonly used in the literature, and it was found that the closest results to experimental data were obtained from the proposed strength and strain models.

• Computers and Concrete
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• v.34 no.4
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• pp.427-446
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• 2024

The I-shaped steel reinforced recycled aggregate concrete (SRRC) composite structure has the advantages of high bearing capacity and environmental protection, and the interfacial bond strength is an important theory. To this end, the I-shaped SRRC bond strength and its calculation based on artificial neural network (ANN) will be studied. Firstly, 39 push out tests of I-shaped SRRC were conducted, the load-slip curve has obvious regularity, which is divided into 4 segments by 3 regular points. Three bond strengths were defined based on these three rule points, and the approximate ranges of their values and the laws of influence of each factor on them were found. Secondly, the Elman ANN model used for the prediction of bond strength was established, and the parameters of Elman ANN predicting I-shaped SRRC bond strength were studied, and the effects of detailed parameters on the prediction results were revealed. Finally, the bond strength of SRRC was predicted using Elman and BP (back propagation) neural network models, both of which showed good prediction results. This study is a theoretical basis for the design and fine simulation of I-shaped SRRC composite structures.

• Tunnel and Underground Space
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• v.26 no.2
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• pp.100-109
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• 2016

This study suggests three spatial distribution functions of strength parameters, which can be adopted in the derivation of failure conditions for transversely isotropic rocks. All three proposed functions, which are the oblate spheroidal function, the exponential function, and the function based on the directional projection of the strength parameter tensor, consist of two model parameters. With assumption that the cohesion and friction angle can be described by the proposed distribution functions, the transversely isotropic Mohr-Coulomb criterion is formulated and used as a failure condition in the simulation of the conventional triaxial tests. The simulation results confirm that the failure criteria incorporating the proposed distribution functions could reproduce the general trend in the variations of the axial stress at failure and the directions of failure planes with varying inclination of the weankness planes and confining pressure. Among three distribution functions, the function based on the directional projection of the strength parameter tensor yields the highest axial strength, while the axial strength estimated by the oblate spheroidal distribution function is the lowest.

• The Journal of Engineering Geology
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• v.13 no.3
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• pp.335-344
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• 2003

This study is focused to the physical and shear strength properties of the weathered limestone soils distributed in Changsung and Hwasun area, Chonnam province. Disturbed soil was used as soil samples. To grasp the physical and shear strength properties of weathered limestone soil, specific gravity test, atterberg limit, grain size distribution and direct shear test were conducted in the laboratory. The physical and shear strength properties of the weathered limestone soil in the study areas are as follows. The range of specific gravity (Gs) is 2.78 to 2.80, liquid limits (LL) 37 to 38 (%), plasticity index (PI) 13.7 to 15.4, and soil classification CL. The range of strength parameters by direct shear test (vd, $1.5t/\textrm{m}^3$) is 3.07 to 4.4 ($t/\textrm{m}^2$) of cohesion and 34.8 to $42.4^{\circ}$ of internal friction angle in unsaturated soils. As a result of comparing with the weathered granite soils (Yang, 1997: Mun, 1998: Park, 1998), it is considered that physical properties of the weathered limestone soils in this study are different from the weathered granite soils. On the other hand, internal friction angle of shear parameters is found to be similar.

• Composite Materials and Engineering
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• v.3 no.3
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• pp.201-220
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• 2021

In this study, potential of three machine learning techniques i.e., M5P, Support vector machines and Gaussian processes were evaluated to find the best algorithm for the prediction of flexural strength of concrete mix with steel fibre. The study comprises the comparison of results obtained from above-said techniques for given dataset. The dataset consists of 124 observations from past research studies and this dataset is randomly divided into two subsets namely training and testing datasets with (70-30)% proportion by weight. Cement, fine aggregates, coarse aggregates, water, super plasticizer/ high-range water reducer, steel fibre, fibre length and curing days were taken as input parameters whereas flexural strength of the concrete mix was taken as the output parameter. Performance of the techniques was checked by statistic evaluation parameters. Results show that the Gaussian process technique works better than other techniques with its minimum error bandwidth. Statistical analysis shows that the Gaussian process predicts better results with higher coefficient of correlation value (0.9138) and minimum mean absolute error (1.2954) and Root mean square error value (1.9672). Sensitivity analysis proves that steel fibre is the significant parameter among other parameters to predict the flexural strength of concrete mix. According to the shape of the fibre, the mixed type performs better for this data than the hooked shape of the steel fibre, which has a higher CC of 0.9649, which shows that the shape of fibers do effect the flexural strength of the concrete. However, the intricacy of the mixed fibres needs further investigations. For future mixes, the most favorable range for the increase in flexural strength of concrete mix found to be (1-3)%.

• Structural Engineering and Mechanics
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• v.83 no.4
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• pp.515-535
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• 2022

The strength models for fiber-reinforced polymer (FRP)-confined normal strength concrete (NC) cylinders available in the literature have been suggested based on small databases using limited variables of such structural members portraying less accuracy. The artificial neural network (ANN) is an advanced technique for precisely predicting the response of composite structures by considering a large number of parameters. The main objective of the present investigation is to develop an ANN model for the axial strength of FRP-confined NC cylinders using various parameters to give the highest accuracy of the predictions. To secure this aim, a large experimental database of 313 FRP-confined NC cylinders has been constructed from previous research investigations. An evaluation of 33 different empirical strength models has been performed using various statistical parameters (root mean squared error RMSE, mean absolute error MAE, and coefficient of determination R²) over the developed database. Then, a new ANN model using the Group Method of Data Handling (GMDH) has been proposed based on the experimental database that portrayed the highest performance as compared with the previous models with R²=0.92, RMSE=0.27, and MAE=0.33. Therefore, the suggested ANN model can accurately capture the axial strength of FRP-confined NC cylinders that can be used for the further analysis and design of such members in the construction industry.

• Advances in nano research
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• v.15 no.6
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• pp.495-511
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• 2023

In this research, the impact of micro-silica, nano-silica, and polypropylene fibers on the fracture energy of self-compacting concrete was thoroughly examined. Enhancing the fracture energy is very important to increase the crack propagation resistance. The study focused on evaluating the self-compacting properties of the concrete through various tests, including J-ring, V-funnel, slump flow, and T50 tests. Additionally, the mechanical properties of the concrete, such as compressive and tensile strengths, modulus of elasticity, and fracture parameters were investigated on hardened specimens after 28 days. The results demonstrated that the incorporation of micro-silica and nano-silica not only decreased the rheological aspects of self-compacting concrete but also significantly enhanced its mechanical properties, particularly the compressive strength. On the other hand, the inclusion of polypropylene fibers had a positive impact on fracture parameters, tensile strength, and flexural strength of the specimens. Utilizing the response surface method, the relationship between micro-silica, nano-silica, and fibers was established. The optimal combination for achieving the highest compressive strength was found to be 5% micro-silica, 0.75% nano-silica, and 0.1% fibers. Furthermore, for obtaining the best mixture with superior tensile strength, flexural strength, modulus of elasticity, and fracture energy, the ideal proportion was determined as 5% micro-silica, 0.75% nano-silica, and 0.15% fibers. Compared to the control mixture, the aforementioned parameters showed significant improvements of 26.3%, 30.3%, 34.3%, and 34.3%, respectively. In order to accurately model the tensile cracking of concrete, the authors used softening curves derived from an inverse algorithm proposed by them. This method allowed for a precise and detailed analysis of the concrete under tensile stress. This study explores the effects of micro-silica, nano-silica, and polypropylene fibers on self-compacting concrete and shows their influences on the fracture energy and various mechanical properties of the concrete. The results offer valuable insights for optimizing the concrete mix to achieve desired strength and performance characteristics.

• Magazine of the Korean Society of Agricultural Engineers
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• v.31 no.3
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• pp.57-69
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• 1989

The study was carried out for the strength parameter of coarse grained Soil and slope stability analysis of earth dam. The test samples were taken fifteen kinds of soil from cohesive soil to coarse gravel. The degree of compaction of test samples for shear test and permeability test was chosen 95 percentage of maximum dry density. The results of this study are as follows ; 1.The maximum dry density(Yd) of coarse grained soil increase in proportion to coarse particles(P) with the relation of Y d= 1.609+0.0043P. 2.The coefficients of permeability(k) decrease by the increase of fine particles(n) with the relation of k=0.0426e-0 185n. 3.The cohesions of soil decrease by the increase of coarse particles, but internal friction angles are more increased in same condition. 4.The internal friction angles(${\Phi}$) decrease in inverse proportion to void ratio(e) with the relation of ${\Phi}$ = 73.068 - 69.268e. 5.The strength parameters( Ct ${\Phi}$t) by triaxial compression test are clearly smaller than that (Cd, ${\Phi}$d) by direct shear test in fine grained soil, but the differences between both parameters are a little in coarse grained soil.The relations of both parameters are as follows; Ct = O.544Cd + 0.04 ${\Phi}$t= 1.282${\Phi}$d-2306 6.In cohesive soil, the strength parameters( Cl ${\Phi}$l) by large size shear test apparatus are similar to the strength parameters(Cs , ${\Phi}$s) by small size shear test appratus, but Cs and ${\Phi}$s values are larger than Cl and ${\Phi}$l values from 10 percentage to 20 percentage in coarse grained soil. 7.The fine grained soil is inappropriate to high dam more than 20 meters and it must be taken coarse grained soil with high internal friction angle for high dam.