• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.6
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• pp.175-182
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• 2006

In the design of composite structures, shear connectors such as headed stud, channel, perforated plate, etc, are commonly used to transfer longitudinal shear forces across the steel-concrete interface. Many researches have been conducted to improve the characteristics of different types of shear connector. This paper presents the results of 11 push-out tests performed on the new perforated rib connectors with shearing bars embedded in concrete slab under static loads. The results obtained from these tests are as following : 1) The bearing plate welded on both sides of perforated rib plate improves the stiffness and strength. 2) The capacity of perforated connectors is influenced primarily by the transverse reinforcements and shearing bars.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.1
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• pp.123-130
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• 2006

The duties of the restorative materials are to bear up against stress and to protect reinforcement corrosion. So the restorative materials are estimated by various kinds of strength, permeability and etc, But, in case of existing performance evaluation of restorative materials, because various deterioration factors are separately acted, the system of performance evaluation is different from that of combined deterioration of real structure and it is difficult to evaluate the exact performance of restorative materials. In this study, to evaluate Performance of restorative materials, we compare their korea standard properties in terms of compressive and bending strength and permeability of water and air with real durability for carbonation, salt damage and actual reinforcement corrosion like ratio of corrosion area. weight reduction and corrosion velocity of steel bar under environment of combined deterioration. The results showed that strength and permeability of restorative materials are similar but their resistance to carbonation, salt damage and actual reinforcement corrosion are very different.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.1
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• pp.81-90
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• 2008

This study deals with a method to identify structural damage using the combined finite element method (FEM) and the advanced damage search technique. The novelty of this study is the application of plates with arbitrary damage shapes and their response due to the anomalies in a structure subjected to impact loading. The technique described in this paper may allow us not only to detect the stiffness distribution of the damaged areas but also to find locations and the extent of damage. To demonstrate the feasibility of the method, the algorithm is applied to a steel thin plate structures with an arbitrary damage shape. The results demonstrate the excellencies of the method from the standpoints of computation efficiency as well as its ability to investigate the arbitrary stiffness reductions.

• Journal of the Korea institute for structural maintenance and inspection
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• v.13 no.6 s.58
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• pp.126-134
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• 2009

Generally, reinforced concrete structures exposed to the outside temperature are affected by freezing and thawing process during winter and early spring. These freeze-thawing process can lead to the reduction in durability of concrete as cracking or surface spalling. This paper is to study the flexural behavior of RC beams exposed to freeze-thawing environments. To compare the difference in flexural behavior of RC Beams, limited tests were conducted under different types of Longitudinal steel ratio and freeze-thawing cycles. For this purpose, fourteen small-scale RC beams ($100mm{\times} 100mm {\times}600mm$) were strengthened in monotonic and cyclic loadings, subjected to up to 150, 300 cycles freeze-thawing from $-18{\sim}4^{\circ}C$. It is thought that experimental results will be used as basic data to evaluate flexural behavior of RC beams exposed to freeze-thawing.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.4
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• pp.195-202
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• 2008

Underestimation of the capacity can have serious economic consequences, as deficient bridges must be posted, repaired or replaced. Accurate prediction of bridge behavior may allow for more bridges to remain in service with or without minor repairs. The presented research is focused on the reliability evaluation of the actual load carrying capacity of existing bridges based on the field testing. Reliability analysis is performed on 17 previously tested bridges. Bridges are first evaluated based on the code specified values and design resistance. However, after the field testing program, it is possible to apply the experimental results into the bridge reliability evaluation procedures. The girder distribution factors obtained from the tests are also applied in the reliability calculation. The results indicate that the reliability indices of selected bridges can be significantly increased due to the reduction of uncertainties without sacrificing the safety of structures, by including the result of field measurement data into calculation.

• Steel and Composite Structures
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• v.52 no.2
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• pp.121-134
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• 2024

To investigate the compressive behavior of partially encased recycled aggregate concrete (PERAC) stub columns after exposed to elevated temperatures, 22 specimens were tested. The maximum temperature suffered, the replacement ratio of recycled coarse aggregate (RCA), the endurance time and the spacing between links were considered as the main parameters. It was found that the failure mode of post-heated PERAC columns generally matched that of traditional partially encased composite (PEC) columns, but the flange of specimens appeared premature buckling after undergoing the temperature of 400℃ and above. Additionally, the ultimate strength and ductility of the specimens deteriorated with the elevated temperatures and extended heating time. When 400℃< T ≤ 600℃, the strength reduction range is the largest, about 11% ~ 17%. The higher the replacement ratio of RCA, the lower the ultimate strength of specimens. At the temperature of 600℃, the ultimate strength of specimens with the RCA replacement ratio of 50% and 100% is 0.94 and 0.91 times than that of specimens without RCA, respectively. But the specimen with 50% replacement ratio of RCA showed the best ductility performance. And the bearing capacity and ductility of PERAC stub columns were changed for the better due to the application of links. When the RCA replacement ratio is 100%, the ultimate strength of specimens with the link spacing of 100 mm and 50 mm increased 14% and 25% than that of the specimen without links, respectively. Based on the results above, a formula for calculating the ultimate strength of PERAC stub columns after exposure to high temperatures was proposed.

• Steel and Composite Structures
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• v.52 no.2
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• pp.135-143
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• 2024

Once the foundation displacement of the transmission tower occurs, additional stress will be generated on the tower members, which will affect the seismic response of transmission tower-line systems (TTLSs). Furthermore, existing research has shown that the reciprocating slippage of joints needs to be considered in the seismic analysis. The hysteretic behavior of joints is obtained by model tests or numerical simulations, which leads to the low modeling efficiency of TTLSs. Therefore, this paper first utilized numerical simulation and model tests to construct a BP neural network for predicting the skeleton curve of joints, and then a numerical model for a TTLS considering the bolt slippage was established. Then, the seismic response of the TTLS under foundation displacement was studied, and the member stress changes and the failed member distribution of the tower were analyzed. The influence of foundation displacement on the seismic performance were discussed. The results showed that the trained BP neural network could accurately predict the hysteresis performance of joints. The slippage could offset part of the additional stress caused by foundation settlement and reduce the stress of some members when the TTLS with foundation settlement was under earthquakes. The failure members were mainly distributed at the diagonal members of the tower leg adjacent to the foundation settlement and that of the tower body. To accurately analyze the seismic performance of TTLSs, the influence of foundation displacement and the joint effect should be considered, and the BP neural network can be used to improve modeling efficiency.

• Steel and Composite Structures
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• v.52 no.2
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• pp.145-163
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• 2024

This paper presents six novel hybrid machine learning (ML) models that combine support vector machines (SVM), Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), extreme gradient boosting (XGB), and categorical gradient boosting (CGB) with the Harris Hawks Optimization (HHO) algorithm. These models, namely HHO-SVM, HHO-DT, HHO-RF, HHO-GB, HHO-XGB, and HHO-CGB, are designed to predict the ultimate strength of both rectangular and circular reinforced concrete (RC) columns. The prediction models are established using a comprehensive database consisting of 325 experimental data for rectangular columns and 172 experimental data for circular columns. The ML model hyperparameters are optimized through a combination of cross-validation technique and the HHO. The performance of the hybrid ML models is evaluated and compared using various metrics, ultimately identifying the HHO-CGB model as the top-performing model for predicting the ultimate shear strength of both rectangular and circular RC columns. The mean R-value and mean a20-index are relatively high, reaching 0.991 and 0.959, respectively, while the mean absolute error and root mean square error are low (10.302 kN and 27.954 kN, respectively). Another comparison is conducted with four existing formulas to further validate the efficiency of the proposed HHO-CGB model. The Shapely Additive Explanations method is applied to analyze the contribution of each variable to the output within the HHO-CGB model, providing insights into the local and global influence of variables. The analysis reveals that the depth of the column, length of the column, and axial loading exert the most significant influence on the ultimate shear strength of RC columns. A user-friendly graphical interface tool is then developed based on the HHO-CGB to facilitate practical and cost-effective usage.

• Steel and Composite Structures
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• v.52 no.3
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• pp.293-312
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• 2024

Researchers are actively investigating the potential for utilizing alternative materials in construction to tackle the environmental and economic challenges linked to traditional concrete-based materials. Nevertheless, conventional laboratory methods for testing the mechanical properties of concrete are both costly and time-consuming. The limitations of traditional models in predicting the tensile strength of concrete composited with geopolymer have created a demand for more advanced models. Fortunately, the increasing availability of data has facilitated the use of machine learning methods, which offer powerful and cost-effective models. This paper aims to explore the potential of several machine learning methods in predicting the tensile strength of geopolymer concrete under different curing conditions. The study utilizes a dataset of 221 tensile strength test results for geopolymer concrete with varying mix ratios and curing conditions. The effectiveness of the machine learning models is evaluated using additional unseen datasets. Based on the values of loss functions and evaluation metrics, the results indicate that most models have the potential to estimate the tensile strength of geopolymer concrete satisfactorily. However, the Takagi Sugeno fuzzy model (TSF) and gene expression programming (GEP) models demonstrate the highest robustness. Both the laboratory tests and machine learning outcomes indicate that geopolymer concrete composed of 50% fly ash and 40% ground granulated blast slag, mixed with 10 mol of NaOH, and cured in an oven at 190°F for 28 days has superior tensile strength.

• Steel and Composite Structures
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• v.52 no.3
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• pp.273-291
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• 2024

This paper presents a three-dimensional displacement-based formulation to investigate the free vibration of functionally graded nanoplates resting on a Winkler-Pasternak foundation based on the nonlocal elasticity theory. The material properties of the FG nanoplate are considered to vary continuously through the thickness of the nanoplate according to the power-law distribution model. A general three-dimensional displacement field is considered for the plate, which takes into account the out-of-plane strains of the plate as well as the in-plane strains. Unlike the shear deformation theories, in the present formulation, no predetermined form for the distribution of displacements and transverse strains is considered. The equations of motion for functionally graded nanoplate are derived based on Hamilton's principle. The solution is obtained for simply-supported nanoplate, and the predicted results for natural frequencies are compared with the predictions of shear deformation theories which are available in the literature. The predictions of the present theory are discussed in detail to investigate the effects of power-law index, length-to-thickness ratio, mode numbers and the elastic foundation on the dynamic behavior of the functionally graded nanoplate. The present study presents a three-dimensional solution that is able to determine more accurate results in predicting of the natural frequencies of flexural and thickness modes of nanoplates. The effects of parameters that play a key role in the analysis and mechanical design of functionally graded nanoplates are investigated.