• 제목/요약/키워드: CFST members

검색결과 28건 처리시간 0.018초

Vibration analysis of CFST tied-arch bridge due to moving vehicles

  • Yang, Jian-Rong;Li, Jian-Zhong;Chen, Yong-Hong
    • Interaction and multiscale mechanics
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    • 제3권4호
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    • pp.389-403
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    • 2010
  • Based on the Model Coupled Method (MCM), a case study has been carried out on a Concrete-Filled Steel Tubular (CFST) tied arch bridge to investigate the vibration problem. The mathematical model assumed a finite element representation of the bridge together with beam, shell, and link elements, and the vehicle simulation employed a three dimensional linear vehicle model with seven independent degrees-of-freedom. A well-known power spectral density of road pavement profiles defined the road surface roughness for Perfect, Good and Poor roads respectively. In virtue of a home-code program, the dynamic interaction between the bridge and vehicle model was simulated, and the dynamic amplification factors were computed for displacement and internal force. The impact effects of the vehicle on different bridge members and the influencing factors were studied. Meanwhile the acceleration responses of some of the components were analyzed in the frequency domain. From the results some valuable conclusions have been drawn.

Predicting the axial compressive capacity of circular concrete filled steel tube columns using an artificial neural network

  • Nguyen, Mai-Suong T.;Thai, Duc-Kien;Kim, Seung-Eock
    • Steel and Composite Structures
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    • 제35권3호
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    • pp.415-437
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    • 2020
  • Circular concrete filled steel tube (CFST) columns have an advantage over all other sections when they are used in compression members. This paper proposes a new approach for deriving a new empirical equation to predict the axial compressive capacity of circular CFST columns using the Artificial Neural Network (ANN). The developed ANN model uses 5 input parameters that include the diameter of circular steel tube, the length of the column, the thickness of steel tube, the steel yield strength and the compressive strength of concrete. The only output parameter is the axial compressive capacity. Training and testing the developed ANN model was carried out using 219 available sets of data collected from the experimental results in the literature. An empirical equation is then proposed as an important result of this study, which is practically used to predict the axial compressive capacity of a circular CFST column. To evaluate the performance of the developed ANN model and the proposed equation, the predicted results are compared with those of the empirical equations stated in the current design codes and other models. It is shown that the proposed equation can predict the axial compressive capacity of circular CFST columns more accurately than other methods. This is confirmed by the high accuracy of a large number of existing test results. Finally, the parametric study result is analyzed for the proposed ANN equation to consider the effect of the input parameters on axial compressive strength.

Study on the progressive collapse resistance of CP-FBSP connections in L-CFST frame structure

  • Xiong, Qingqing;Wu, Wenbo;Zhang, Wang;Chen, Zhihua;Liu, Hongbo;Su, Tiancheng
    • Steel and Composite Structures
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    • 제44권3호
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    • pp.437-450
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    • 2022
  • When the vertical load-bearing members in high-rise structures fail locally, the beam-column joints play an important role in the redistribution of the internal forces. In this paper, a static laboratory test of three full-scale flush flange beam-reinforced connections with side and cover plates (CP-FBSP connection) with double half-span steel beams and single L-shaped columns composed of concrete-filled steel tubes (L-CFST columns) was conducted. The influence of the side plate width and cover plate thickness on the progressive collapse resistance of the substructure was thoroughly analyzed. The failure mode, vertical force-displacement curves, strain variation, reaction force of the pin support and development of internal force in the section with the assumed plastic hinge were discussed. Then, through the verified finite element model, the corresponding analyses of the thickness and length of the side plates, the connecting length between the steel beam flange and cover plate, and the vertical-force eccentricity were carried out. The results show that the failure of all the specimens occurred through the cracking of the beam flange or the cover plate, and the beam chord rotations measured by the test were all greater than 0.085 rad. Increasing the length, thickness and width of the side plates slightly reduced the progressive collapse resistance of the substructures. The vertical-force eccentricity along the beam length reduced the progressive collapse resistance of the substructure. An increase in the connecting length between the beam flange and cover plate can significantly improve the progressive collapse resistance of substructures.

Monitoring degradation in concrete filled steel tubular sections using guided waves

  • Beena, Kumari;Shruti, Sharma;Sandeep, Sharma;Naveen, Kwatra
    • Smart Structures and Systems
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    • 제19권4호
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    • pp.371-382
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    • 2017
  • Concrete filled steel tubes are extensively applied in engineering structures due to their resistance to high tensile and compressive load and convenience in construction. But one major flaw, their vulnerability to environmental attack, can severely reduce the strength and life of these structures. Degradation due to corrosion of steel confining the concrete is one of the major durability problems faced by civil engineers to maintain these structures. The problem accelerates as inner surface of steel tube is in contact with concrete which serves as electrolyte. If it remains unnoticed, it further accelerates and can be catastrophic. This paper discusses a non-destructive degradation monitoring technique for early detection corrosion in steel tubes in CFST members. Due to corrosion, damage in the form of debonding and pitting occurs in steel sections. Guided ultrasonic waves have been used as a feasible and attractive solution for the detection and monitoring of corrosion damages in CFST sections. Guided waves have been utilized to monitor the effect of notch and debond defects in concrete filled steel tubes simulating pitting and delamination of steel tubes from surrounding concrete caused by corrosion. Pulse transmission has been used to monitor the healthy and simulated damaged specimens. A methodology is developed and successfully applied for the monitoring of concrete filled steel tubular sections undergoing accelerated chloride corrosion. The ultrasonic signals efficiently narrate the state of steel tube undergoing corrosion.

Shear behavior of concrete-encased square concrete-filled steel tube members: Experiments and strength prediction

  • Yang, Yong;Chen, Xin;Xue, Yicong;Yu, Yunlong;Zhang, Chaorui
    • Steel and Composite Structures
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    • 제38권4호
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    • pp.431-445
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    • 2021
  • This paper presents experiments and theoretical analysis on shear behavior of eight concrete-encased square concrete-filled steel tube (CECFST) specimens and three traditional reinforced concrete (RC) specimens. A total of 11 specimens with the test parameters including the shear span-to-depth ratio, steel tube size and studs arrangement were tested to explore the shear performance of CECFST specimens. The failure mode, shear capacity and displacement ductility were thoroughly evaluated. The test results indicated that all the test specimens failed in shear, and the CECFST specimens enhanced by the interior CFST core exhibited higher shear capacity and better ductility performance than that of the RC specimens. When the other parameters were the same, the larger steel tube size, the smaller shear span-to-depth ratio and the existence of studs could lead to the more satisfactory shear behavior. Then, based on the compatible truss-arch model, a set of formulas were developed to analytically predict the shear strength of the CECFST members by considering the compatibility of deformation between the truss part, arch part and the steel tube. Compared with the calculated results based on several current design specifications, the proposed formulas could get more accurate prediction.

Shape effect on axially loaded CFDST columns

  • R, Manigandan;Kumar, Manoj
    • Steel and Composite Structures
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    • 제43권6호
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    • pp.759-772
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    • 2022
  • Concrete-filled double skinned steel tubular (CFDST) columns have been used to construct modern structures such as tall buildings and bridges as well as infrastructures as they provide better, lesser weight, and greater stiffness in structural performance than conventional reinforced concrete or steel members. Different shapes of CFDST columns may be needed to satisfy the architectural and aesthetic criteria. In the study, three-dimensional FE simulations of circular and elliptical CFDST columns under axial compression were developed and verified through the experimental test data from the perspectives of full load-displacement histories, ultimate axial strengths, and failure modes. The verified FE models were used to investigate and compare the structural performance of CFDST columns with circular and elliptical cross-section shapes by evaluating the overall load-deformation curves, interaction stress-deformation responses, and composite actions of the column. At last, the accuracy of available design models in predicting the ultimate axial strengths of CFST columns were investigated. Research results showed that circular and elliptical CFDST column behaviors were generally similar. The overall structural performance of circular CFDST columns was relatively improved compared to the elliptical CFDST column.

Steel and FRP double-tube confined RAC columns under compression: Comparative study and stress-strain model

  • Xiong, Ming-Xiang;Chen, Guangming;Long, Yue-Ling;Cui, Hairui;Liu, Yaoming
    • Steel and Composite Structures
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    • 제43권2호
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    • pp.257-270
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    • 2022
  • Recycled aggregate concrete (RAC) is rarely used in load-carrying structural members. To widen its structural application, the compressive behavior of a promising type of composite column, steel-fiber reinforced polymer (FRP) double-tube confined RAC column, has been experimentally and analytically investigated in this study. The objectives are the different performance of such columns from their counterparts using natural aggregate concrete (NAC) and the different mechanisms of the double-tube and single-tube confined concrete. The single-tube confined concrete refers to that in concrete-filled steel tubular (CFST) columns and concrete-filled FRP tubular (CFFT) columns. The test results showed that the use of recycled coarse aggregates (RCA) affected the axial load-strain response in terms of deformation capacity but such effect could be eliminated with the increasing confinement. The composite effect can be triggered by the double confinement of the steel and carbon FRP (CFRP) tubes but not by the steel and polyethylene terephthalate (PET) FRP tubes. The proposed analysis-oriented stress-strain model is capable to capture the load-deformation history of such steel-FRP double-tube confined concrete columns under axial compression.

A robust approach in prediction of RCFST columns using machine learning algorithm

  • Van-Thanh Pham;Seung-Eock Kim
    • Steel and Composite Structures
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    • 제46권2호
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    • pp.153-173
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    • 2023
  • Rectangular concrete-filled steel tubular (RCFST) column, a type of concrete-filled steel tubular (CFST), is widely used in compression members of structures because of its advantages. This paper proposes a robust machine learning-based framework for predicting the ultimate compressive strength of RCFST columns under both concentric and eccentric loading. The gradient boosting neural network (GBNN), an efficient and up-to-date ML algorithm, is utilized for developing a predictive model in the proposed framework. A total of 890 experimental data of RCFST columns, which is categorized into two datasets of concentric and eccentric compression, is carefully collected to serve as training and testing purposes. The accuracy of the proposed model is demonstrated by comparing its performance with seven state-of-the-art machine learning methods including decision tree (DT), random forest (RF), support vector machines (SVM), deep learning (DL), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and categorical gradient boosting (CatBoost). Four available design codes, including the European (EC4), American concrete institute (ACI), American institute of steel construction (AISC), and Australian/New Zealand (AS/NZS) are refereed in another comparison. The results demonstrate that the proposed GBNN method is a robust and powerful approach to obtain the ultimate strength of RCFST columns.