Figure 9 - uploaded by Ali Nadjai
Content may be subject to copyright.
Source publication
This paper presents the results of an experimental and validated theoretical study to investigate the performance of steel columns with hollow and concrete-filled elliptical sections subjected to hydrocarbon fire. The test programme involved 18 columns with 200 × 100 × 8-mm, 300 × 150 × 8-mm and 400 × 200 × 8-mm elliptical sections representing sle...
Context in source publication
Similar publications
A novel connection adopting lap-spliced large-diameter bars and ultra-high performance concrete (UHPC) grout was developed to accelerate the assemble progress of precast bridge columns. The precast bridge column adopting the connections was testified to be on a par with the monolithic concrete counterpart in terms of seismic performance in previous...
State-of-the-art slim floor systems are the newest addition to the composite construction industry and several types are currently being used for building and construction purposes. Asymmetric slim floor beams are a type of slim floor systems which consist of a rolled section with a larger bottom flange. The larger bottom flange induces asymmetry a...
Citations
... Extensive research on the bridges performance in fire was initiated in the early 2000s, with particular emphasis on studying the fire behavior of different types of steel sections employed in bridge construction [30]. Studies have investigated the fire performance of hollow circular [6,35,36], elliptical [37,38], and rectangular [35] cross sections, aiming to understand their behavior under fire conditions. While corrugated steel sections have been identified as potentially showing superior fire resistance due to their unique geometry and increased surface area [33], there remains a lack of comprehensive studies on the fire performance of corrugated steel sections, especially in the context of hydrocarbon fires and their application as thin-walled structures in bridge piers. ...
... For the current study, the CRG column was exposed to a simulated hydrocarbon fire to replicate real-world fire scenarios on bridge structures. The relationship between time and temperature was determined using equation (1) [37,67]. In this equation, the variable "t" represents time in minutes, "T" represents the air temperature in degrees Celsius, and "T o " represents the room temperature assumed to be 20 • C. Fig. 4 illustrates the temperature progression in diverse CRG columns. ...
... Chena et al. (2018) measured the performance of CFT columns by considering the effect of critical parameters including steel wall thickness, different concrete strength, and placement at different temperature levels. Ali et al. (2016) investigated hollow and concretefilled elliptical steel columns subjected to severe fire using experimental and numerical methods. This study revealed that the concrete-filled sections demonstrated improved fire resistance when compared with the hollow sections under low loading ratios. ...
The use of mineral fireproofing coating (spray-applied fire-resistive material, SFRM) is one of the most important approaches employed to strengthen structures, especially steel structures exposed to fire. Columns are a major building component, so the use of fireproofing coatings for columns may be necessary. The required thickness of the fireproof coating for some kinds of columns was extracted from experimental results. The use of numerical methods is an attractive alternative to costly experimental studies. In this research, concrete-filled tube (CFT) columns were considered as one of the most widely used types of columns in terms of fire vulnerability. Thus, the appropriate thickness of a type of mineral-based fire-retardant coating for CFT columns was determined using the finite element model. The numerical results were validated in several steps, and showed that this technique can be used as a rapid and reliable approach for computing the thickness of SFRM for CFT columns.
... In addition, the behavior of CFST elliptical stub columns under axial loading conditions was examined by many other researchers [26][27][28][29][30]. The fire behaviors of axially loaded CFST elliptical columns were examined by Ali et al. [31]; whereas that of eccentrically loaded ones were investigated by Espinos et al. [32]. Also, the structural characteristics of the CFST elliptical slender and stub columns subjected to an eccentric load have been studied by Yang et al. [3], Sheen et al. [4], McCann et al. [5], and Ren et al. [28]. ...
The present study mainly aims to propose design models for the prediction of the peak strength of the concrete-filled steel tubular (CFST) elliptical columns subjected to eccentric compressive loading. At that point, the study has gain importance since the design of specifically such elliptical columns is not covered by current design codes. For example, the current provisions of Eurocode 4 provide a simplified method for the design of composite columns having circular or rectangular/square cross-sections. To this aim, first of all, the applicability and assessment of Eurocode 4 to the CFST elliptical columns under eccentric loading conditions were performed. Following, a data repository covering the experimental results of eccentrically loaded CFST elliptical columns (having different geometry, material property, load eccentricity in y and z axes, and longitudinal reinforcement ratio) was constituted. This data repository was used in the evaluation of the design guidance in Eurocode 4. Besides, the same experimental results were employed to develop two new numerical models based on gene expression programming (GEP) and artificial neural network (ANN) approaches. Finally, a sensitive statistical analysis was made to compare the prediction performances of Eurocode 4, GEP, and ANN models against experimental results. It was observed that Eurocode 4 design provisions had sufficiently accurate prediction performance, however, the developed GEP and ANN design models yielded consistent and robust prediction performance than the current design provisions by providing a much smaller mean absolute percent error of 7.5 and 1.4, respectively.
... Concrete-filled steel tubular (CFST) structural members exhibit very interesting properties, as they combine the advantages of the two constituent materials. In such composite structures, the tensile strength of the steel tube and the compressive strength of the concrete core combine to enhance many properties and structural performances of the members, such as strength [1,2], ductility [3,4], loadbearing capacity [5,6], fire resistance [7,8], earthquake resistance [9,10], energy absorption capacity [11,12], and so on. To date, rectangular CFST members have been employed in many constructions such as buildings, bridges, and underground stations because of their strong moment resistance [13] and simple beam-column joints [10,14]. ...
The ultimate compressive load of concrete-filled steel tubular (CFST) structural members is recognized as one of the most important engineering parameters for the design of such composite structures. Therefore, this paper deals with the prediction of ultimate load of rectangular CFST structural members using the adaptive neurofuzzy inference system (ANFIS) surrogate model. To this end, compression test data on CFST members were extracted from the available literature, including: (i) the mechanical properties of the constituent materials (i.e., steel’s yield strength and concrete’s compressive strength) and (ii) the geometric parameters (i.e., column length, width and height of cross section, and steel tube thickness). The ultimate load is the output response of the problem. The ANFIS model was trained using a hybrid of the least-squares and backpropagation gradient descent method. Quality assessment criteria such as coefficient of determination (R²), root mean square error (RMSE), and slope of linear regression were used for error measurements. A 11-fold cross-validation technique was employed to evaluate the performance of the model. Results showed that for the training process, the average performance was as follows: R², RMSE, and slope were 0.9861, 89.83 kN, and 0.9861, respectively. For the validating process, the average performance was as follows: R², RMSE, and slope were 0.9637, 140.242 kN, and 0.9806, respectively. Therefore, the ANFIS model may be considered valid because it performs well in predicting ultimate load using the validated data. Moreover, partial dependence (PD) analysis was employed to interpret the “black-box” ANFIS model. It is observed that PD enabled us to locally track the influence of each input variable on the output response. Besides reliable prediction of ultimate load, ANFIS can also provide maps of ultimate load. Finally, the ANFIS model developed in this study was compared with other works in the literature, showing that the ANFIS model could improve the accuracy of ultimate load prediction, in comparison to previously published results.
1. Introduction
Concrete-filled steel tubular (CFST) structural members exhibit very interesting properties, as they combine the advantages of the two constituent materials. In such composite structures, the tensile strength of the steel tube and the compressive strength of the concrete core combine to enhance many properties and structural performances of the members, such as strength [1, 2], ductility [3, 4], load-bearing capacity [5, 6], fire resistance [7, 8], earthquake resistance [9, 10], energy absorption capacity [11, 12], and so on. To date, rectangular CFST members have been employed in many constructions such as buildings, bridges, and underground stations because of their strong moment resistance [13] and simple beam-column joints [10, 14]. Moreover, with a given sectional size, rectangular CFST members exhibit greater stiffness than circular or elliptical members [15–17]. Although the design process for rectangular CFST columns is set forth in many current codes such as Eurocode 4 [18], AISC [19], and ACI [20], up until now, the axial behavior of rectangular CFST members has received crucial attention from researchers/engineers. The main reason is that current codes do not necessarily have the capacity to take account of different material strengths or ranges of geometrical dimension [21–24]. As indicated in Xiong et al. [22], Eurocode 4 is only applicable to CFST members with steel yield strength in the range of 235 MPa to 460 MPa, whereas concrete cylinder compressive strength varies from 20 MPa to 50 MPa. In the case of AISC, the yield strength of steel may vary up to 525 MPa, whereas the cylinder compressive strength of concrete may be up to 70 MPa. As axial compression of composite columns is a complex problem, there are a range of questions which still need to be investigated. Indeed, many variables are involved in this problem, including geometrical parameters and mechanical properties of the constituent materials [25]. As CFST members are composite structures, the relationship between variables and macroscopic properties must be established in order to accurately investigate their mechanical performance and failure. Therefore, there are many ongoing theoretical, numerical, and experimental studies to obtain a better understanding of the axial behavior of rectangular CFST members.
Experimental investigations are normally the best approach to study the behavior of CFST members. However, experimental design is often carried out subject to a small range of parameters, leading to a limited number of specimens [13]. In addition, extensive experimental studies have hitherto been costly and time-consuming [25, 26]. In terms of numerical modeling, An and Han [27] put forward a finite element (FE) model for investigating CFST members under both compression and bending. The model developed has been used for a parametric study of the parameters influencing the strength of the composite structures. In another study, Zhou and Han [28] also employed the FE method to model the fire behavior of CFST members. Nguyen et al. [29] developed a FE model taking account of the interface properties between steel and concrete in CFST columns. The FE technique has also been used in many other works to numerically model the axial behavior of CFST columns [30–33]. There are also several empirical formulae in the available literature such as Ding et al. [1], Wang et al. [23], Tran et al., [21] and Han et al. [34] for predicting the ultimate load of rectangular CFST members. However, these equations have been derived on the basis of simple assumptions and observations. Consequently, it is not guaranteed that these models will be applicable. The aforesaid studies have provided significant contributions to progress in modeling and prediction of axial behavior of CFST members. However, there is a need for a more efficient and robust manner to better characterize the mechanical performance of such composite structures, including the influence of variables on their macroscopic properties.
Artificial intelligence- (AI-) based models have received significant attention from researchers all around the world, especially in civil engineering-related problems [35–46]. For single-material structures, various studies have set out to predict (i) the buckling capacity of steel members [47–50] and (ii) the compressive strength of concrete [51–55]. For composite structures, Sarir et al. [36] proposed a tree-based and whale optimization model for predicting the load-bearing capacity of circular CFST members. In addition, Ahmadi et al. [56, 57] applied an artificial neural network to predict the axial capacity of short CFST columns. Güneyisi et al. [58, 59] derived a gene expression programming model to predict the load-bearing capacity of circular CFST members. The performance of such a model has been shown to be better higher than the formulae found in the preexisting literature. Al-Khaleefi et al. [60] introduced a neural network model for studying the fire resistance of CFST members, taking account of different structural, material factors, and loading conditions. Moon et al. [61] have successfully developed a fuzzy logic model for predicting the strength of circular CFST stub columns. The study investigated the effect of concrete confinement on the axial capacity of the columns. Despite the importance of rectangular CFST columns, most AI-based studies so far have concentrated on members with a circular cross section [36, 58, 61]. Most recently, a few studies have been published involving square cross sections. Ren et al. [35] employed support vector machine and particle swarm optimization to investigate the axial capacity of square CFST members. Tran et al. [21] developed a neural network-based model to predict the load-bearing capacity of square CFST columns. Therefore, more investigations are required to assess the potential applications of AI-based models for studying axial behavior of rectangular CFST columns, especially in the highly topical context of high-rise construction.
This work is devoted to the prediction and influence of variables on the ultimate load of rectangular CFST columns, using the adaptive neurofuzzy inference system (ANFIS) model. It should be noted that ANFIS has not yet been used, in the literature, for studying rectangular CFST members and highlighting the influence of variables on the macroscopic properties. The reason for selecting the interpretable ANFIS technique is described in Section 2.2. Section 2.1 introduces the database used to train and validate the developed ANFIS model. In Section 2.2, details of considered variables and reasons for selection are presented. Section 3 presents the phase of training and 11-fold cross-validation of the ANFIS model, together with regression analysis. Finally, partial dependence (PD) analysis was applied in order to interpret the “black-box” ANFIS model, which elucidated the influence of each variable on the output response.
2. Materials and Methods
2.1. Database
As set forth in the literature, the experimental process followed the steps below [35, 62–64]:(1)Design of specimens.(2)Manufacture of steel tube (cold-formed or welded).(3)Manufacture of concrete.(4)Assembly of composite structural members.(5)Loading and measurement (see Figure 1 for schematic description of the test).
... The available experimental investigations on concrete-filled elliptical columns at elevated temperatures are even more limited: six tests of cross-sectional dimensions 220×110×12 mm carried out by the authors [18] and 18 tests carried out by Ali et al. [19] on hollow and concrete-Romero ML, Espinós A, Lapuebla-Ferri A, Albero V, Hospitaler A. Recent developments and fire design provisions for CFST columns and slim-floor beams. Journal of Constructional Steel Research 2020; 172(9):106159,1-21. ...
This paper summarizes the latest technical and scientific progresses on steel-concrete composite structures exposed to fire, presenting the recent research carried out on this subject and the progress of the design codes. In particular, this review focuses on concrete-filled steel tubular columns and slim-floor beams, topics where the authors have carried out extensive research during the last years. The more recent experimental and numerical studies performed by the authors as well as those available in the literature are presented, along with applications where these composite elements have been used in practice. The use of advanced materials, such as high strength steel and concrete, stainless steel, lightweight concrete or geopolymer concrete is considered for the enhancement of the fire behaviour of concrete-filled steel tubular columns and slim-floor beams. Finally, the currently available design methods for the calculation of isolated members at elevated temperatures are reviewed and the recent progress of the code provisions for the fire design of these composite elements is presented.
... Also, one of the very few research studies that investigated the fire behaviour of moment-resisting HSS beam-to-column connections using both experimental and FE simulation is the research carried out by Salem et al. (2012). However, most of the research carried out on HSS steel members subjected to fire was to investigate the structural behaviour of concrete-filled HSS columns, such as the work done by Kodur (1999), Han et al., (2003), Wong and Wang, (2010), Lu and Zhao (2010), Ali et al., (2015). ...
Purpose: In fire condition, the limiting temperature of a restrained steel beam depends on a few parameters, e.g. temperature distributions along and across the beam, beam’s load ratio and span length. The purpose of this study is to investigate the structural fire behaviour of axially restrained steel beams under different beam’s load ratios, taking into consideration the effect of the beam’s end connections configuration.
Design/methodology/approach: A three-dimensional finite element (FE) computer model has been developed to simulate the structural fire behaviour of axially restrained steel beams and their end connections. After successfully validating the developed model against the outcomes of the available large-size fire resistance experiments, the FE model has been used in a parametric study to investigate the beam’s load ratio effect on the behaviour of the axially restrained steel beams and their end connections.
Findings: The parametric study showed that increasing the beam loading level significantly increased the beam deflections at elevated temperatures; where, increasing the beam’s load ratio from 0.5 to 0.9 reduced the beam fire resistance by about 100 s. In contrast, decreasing the beam’s load ratio from 0.5 to 0.3 allowed the beam to easily achieve a 30-min fire resistance rating with no fire protection applied.
Originality/value: Experimental parametric studies are difficult to control in a laboratory setting and are also expensive and time consuming. Therefore, the reasonable accuracy of the validated FE model in reproducing the experimental fire behaviour of steel beams and their end connections makes it a very useful tool for both numerical and analytical studies.
... However, these researches on elliptical sections focused on behaviour under room temperatures. A limited number of researches under high temperatures were carried out by Scullion et al. [6] and [7] on hollow elliptical sections and some other researches were carried out on concrete filled elliptical columns by Ali et al. [8] and by Espinos et al. [9] [10] who used the Finite Element Method to study the behaviour of concrete filled elliptical sections in fire. It is obvious from the available literature that there is a very limited research carried out on hollow elliptical sections under fire situations in general. ...
... The test programme has been designed to investigate factors that can influence the fire performance of elliptical columns including slenderness, load ratio and axial restraint. The columns were subjected to the hydrocarbon fire curve shown in Ali et al. [8] which is taken from EC1 [11], with the ultimate strength of the columns calculated using EC3 [12] and [13]. The paper also includes a parametric finite element study where the validated model was used to study the effect of factors including loads, restraint, and slenderness. ...
... The loading imposed on columns was increased gradually in equal time steps to allow the column to settle and to get stable readings. Once the load level was reached the burner was ignited subjecting the columns to a hydrocarbon fire Ali et al. [8]. The columns were with pin ended supports at the The testing rig is shown in Figure 1 where LVDT's displacement sensors were used to measure the axial displacement at the top of the column at the front and back and also at the bottom of the test rig and the average values were calculated. ...
... Dai and Lam [7], McCann et al. [8], Mahgub et al. [9] and Qiu et al. [10] studied the axially and eccentrically loaded slender elliptical CFST columns. Ali et al. studied the behaviour of elliptical CFST columns exposed to hydrocarbon fire [11,12]. ...
Experimental and numerical studies were conducted to investigate the behaviours of the concrete-filled cold-formed elliptical hollow section beam-columns. A total of 11 specimens were tested to evaluate the failure modes, load-deformation histories and strains development in the steel tube. Complementary finite element (FE) models were developed and validated against experimental results. Validated FE methodology was then used to study the influence of key parameters, including aspect ratio, slenderness ratio, load eccentricity ratio, yield strength of steel, compressive strength of concrete and steel tube to concrete area ratio, on the load carrying capacity. As a result, the design method for elliptical concrete-filled steel tubular (CFST) columns in Chinese code - GB50936-2014 and the design method for circular CFST columns in EC4 were assessed to confirm their applicability for cold-formed elliptical CFST columns with aspect ratio ranging from 1.0 to 2.5.
In this study, the critical capacity of concrete-filled steel tubes (CFST) under axial compression is investigated through a machine learning model (BCM-NN) that is a combination of Balancing Composite Motion Optimization (BCM) and Artificial Neural Network (NN). To develop the model, a database of experimental results is gathered from literature works. Such database includes variables related to the CFST geometry parameters and its mechanical behavior. Quality assessments namely coefficient of determination (R2) and Root Mean Square Error (RMSE) are used to evaluate the performance of the proposed model. The value range of each model parameter has also been studied in this work. The obtained results show that the hybrid BCM-NN model produced great performance in predicting the critical load of CFST compared to conventional neural network algorithms.KeywordsArtificial Neural NetworkUltimate loadBalancing composite motion optimizationCFST columnPrediction
