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In the present paper, the effect of multiple longitudinal web stiffeners (up to four) located at their optimum location on the ultimate strength of steel plate girders subjected to predominant shear loading, and combined bending and shear loading is investigated by using nonlinear inelastic analysis. Three dimensional (3D) finite element (FE) models of the steel plate girder are developed and analyzed by using ABAQUS commercial software. The accuracy of the FE models is validated by comparing their results with analogous experimental data. An extensive parametric analysis has been carried out to estimate the influence of specific geometric parameters on the ultimate strength. It has been shown that the shear resistance obtained from AASHTO LRFD equation is conservative since the influence of the longitudinal stiffeners was not considered in computing the shear resistance of the web plate girders under predominant shear loading and combined bending and shear. In addition, it has been demonstrated that the variation of the ultimate strength of the girder is almost monotonic against the various dimensionless geometric parameters, enabling thus the design of girder beams based on interpolation of tabulated data. Finally the results indicate that by adding not more than four stiffeners at the web of a steel plate girder subject either to predominant shear or combined shear and bending loads, an increase in its ultimate strength between 8% and 105% can be achieved.

This paper presents an investigation of the optimum locations of multiple longitudinal web stiffeners (up to six) for steel plates under pure bending by using the gradient-based interior point optimization algorithm. Performing eigenvalue buckling analyses, buckling coefficients are calculated accounting for the lowest eigenvalues. The optimization algorithm is then employed to maximize the buckling coefficients until the optimum stiffener locations of the plates are attained. Based on this research, the optimum locations of multiple longitudinal stiffeners are suggested for plates under pure bending. Moreover, equations to determine minimum flexural rigidities of multiple longitudinal stiffeners for steel plates are also proposed. The results obtained from this study are compared with the AASHTO requirement and previous works. It is proved that the minimum flexural rigidities of stiffeners recommended by AASHTO and the previous work are conservative.

In the present study, concrete-filled double skin steel tubes (CFDSTs) with a joint, which are lighter and more economical than concrete-filled steel tubes (CFSTs), were developed. The CFDSTs are made of two steel tubes of different diameters with concrete filling the space between them. The length, the outer and inner diameters of a CFDST are 10 m, 914.4 mm, and 514.4 mm, respectively. Two types of shear connectors consisting of M16 and steel plate studs were used. A new type of connection in CFDSTs was developed to transfer the imposed load effectively. Four different specimens were made to test all possible combinations of the two different shear connectors (M16 studs, steel plate studs) and joints. The bending performance of the CFDSTs was investigated through 4-point loading experiments and finite element analysis (FEA). Finally, a comparison of design predictions and experiment results was made for these tubes.

In this paper, the optimum positions of multiple (two) longitudinal stiffeners for steel plates subjected to pure bending, and combined bending and shear forces, are investigated by using the gradient-based interior point optimization algorithm. An eigenvalue analysis is performed by means of the finite element method, and an optimization algorithm is employed to maximize the buckling coefficients until attaining the optimum position of the stiffeners under various loading conditions. In order to ensure the accuracy of the method, the results obtained from this research are compared with analogous results found in the literature. Based on this study, the optimal location of a single and two longitudinal stiffeners are recommended for plates under pure bending. In addition, the interaction curves between the optimum stiffener location and bending-shear ratio for plates subjected to combined bending and shear forces are proposed for practical design.

The objective of this study is to develop a new formulation for predicting the permanent local denting damage of steel ring and/or stringer-stiffened cylinders under dynamic lateral mass impact. The considered scenarios could represent the collisions of offshore cylindrical structures with bow or stern of service vessels or floating objects. Before deriving the formulations, the numerical methods were developed using ABAQUS/Explicit to determine the deformation of these stiffened cylinder structures subjected to dynamic lateral mass impact. Next, rigorous parametric studies were performed on the actual design full-scaled stiffened cylinder examples using the developed numerical method. Based on the rigorous numerical results, new simple design formulations to predict the maximum permanent local dent depth of a stiffened cylinder are derived through a regression study as the function of a non-dimensional energy parameter. The accuracy and reliability of the derived formulations are confirmed by comparison with the available test results, nonlinear FEA and existing analytical, and empirical equations in the literature. A good agreement with existing test data for ship-offshore structure collisions was achieved.

Connection affects the whole behavior of a steel frame and its fracture will lead to the collapse of a structure. Corrosion, widely appeared in engineering, will change the mechanical behavior of members or connections, which seriously influences the safety of in-service steel structures. As such, safety assessment of in-service corroded connections has been concerned a lot in recent years. In this study, the structural behavior of corroded high-strength bolt under shear force is investigated using experimental method. The Copper-Accelerated Acetic Acid-Salt Spray Testing is employed to obtain the high-strength bolt connections with different corrosion degree. The shear testing of corroded high-strength bolt connections is then performed to study the variation law of the anti-sliding load and the ultimate bearing capacity of corroded high-strength bolt connections. The anti-sliding load and the anti-sliding coefficient of corroded high-strength bolt connections shows a trend of first increase and then decrease as the mass loss ratio of steel plates increases. A model for estimating the anti-sliding coefficient of corroded high-strength bolt connections is suggested. GB50017-2017 is not good for predicting the anti-sliding load of corroded high-strength bolt connections as the maximum error estimated from GB50017-2017 approaches 35.94%. The effect of corrosion on the structural behavior of high-strength bolt connections is considered and a more accurate model is proposed for estimating the anti-sliding load of corroded high-strength bolt connections. GB50017-2017 is not accurate for predicting the ultimate bearing capacity of corroded high-strength bolt connections as the maximum error estimated from GB50017-2017 reaches 55.43%. This is mainly attributed to the ignorance of the residual friction force of steel plates. A more accurate model considering the effect of corrosion is developed for predicting the ultimate bearing capacity of corroded high-strength bolt connections. The conclusion based on the experiment of Q235 and Q345 high-strength bolt connections with Grade 10.9 twist-off tension-control bolts can provide a reference for the safety assessment of in-service corroded connections.

In the incremental launching method employed for steel bridge construction, the girder is subjected to patch loading which occurs at the piers’ position. This loading significantly affects the girder resistance in the construction stage. Therefore, prediction of the girder resistance under this loading is important. This paper proposes a new approach for predicting the patch load resistance of stiffened plate girders using an extreme gradient boosting algorithm (XGBoost). A total of 170 experimental data on stiffened plate girders under patch loading collected from the literature serves as the training and testing data to build the predictive model. To demonstrate the efficiency of the proposed model, its predictions were compared with those obtained from other Machine Learning (ML) methods such as support vector machines (SVM), decision tree (DT), random forest (RF), adaptive boost (Adaboost), and deep learning (DL). The accuracy of the proposed model was validated against the existing equations taken from the design standards (EN-1993-1-5 and BS 5400) as well as existing formulae in the literature. The comparative results reveal that the proposed model provides better and more accurate predictions than the existing formulae.

Intermediate diaphragms are used in box girders not only to prevent premature distortion under eccentric loading conditions but also to improve the distribution of live loads. This paper reports an investigation into the effect of intermediate diaphragms on the load - carrying capacity of a Steel – Concrete Composite Box (SCCB) girder bridge with open steel box section. In the current study, a three - dimensional finite element (FE) model of the SCCB girder is developed and analyzed using ABAQUS software. The nonlinear inelastic analysis is invoked in order to accurately capture the actual behavior of the girder. The numerical model is verified with experimental results to ensure the accuracy of the FE modeling method. A parametric analysis is implemented to study the effect of intermediate diaphragms on the load – carrying capacity of an SCCB girder with a 30–60 m span length. Based on parametric studies, the number of intermediate diaphragms (N) is recommended for practical design of the girder, which satisfies the requirement stated in the provisions of the AASHTO LRFD standard.

A finite element model for predicting the moment-rotation curves of stainless steel web cleat connections is developed, and validated by test data. The effects of several parameters (i.e., number of bolts, gage distance of angles, thickness of angles, and types of stainless steel) on the moment-rotation curves of stainless steel web cleat connections are investigated using the validated finite element models. The stiffness and ultimate moment of stainless steel web cleat connections increase as the angle thickness or number of bolts increases, and they decreases as the gage distance of angles increases. S22053 stainless steel web cleat connections exhibit a higher stiffness and moment resistance than S30408 and S31608 stainless steel web cleat connections. Chen and Kishi's model can accurately predict the moment-rotation curves of stainless steel web cleat connections, but the initial stiffness and ultimate moment capacity calculated from Kishi and Chen are not ideal. An empirical formula for calculating the initial stiffness of web cleat connections is proposed. Compared with the test data for the initial stiffness, the average error of the proposed formula is only 14.67%, making it more accurate than existing models. The finite element analysis results indicate that current yield line mechanisms for the angle may not reflect the behaviour of the angle. A new yield line mechanism for the angle is proposed on the basis of stress distribution in the angle at the ultimate strength state. An analytical model for estimating the ultimate moment capacity of web cleat connections is derived. The proposed formula produces a more accurate prediction than the existing formulas, as the average error of the ultimate moment capacity between the estimated values and test data is only 6.00%. Good agreement between the proposed model and the moment-rotation curves of the test data is observed. Design recommendations for the structural behaviour of stainless steel web cleat connections are provided.

The biggest challenge of an advanced analysis is that it is time-consuming compared to an elastic analysis. This leads to the limitation of application of advanced analysis in complicated design problems such as optimization design and reliability analysis of structures where a very large number of structural analyses are required. To solve this problem, a deep learning (DL) based procedure for safety evaluation of steel frames is introduced in this study. An advanced analysis is used to capture the nonlinear inelastic behaviors of structures. Two DL models are proposed for estimation of the structural load-carrying capacity and evaluation of the strength safety of the structure by predicting the structural ultimate load factor greater or smaller than 1.0. A two-story space steel frame is studied.

This paper aims at introducing a new method to determine the buckling coefficient kb of the stiffened plate girders under pure bending using deep learning, one of the most powerful algorithms in machine learning. Firstly, output data kb is generated from eigenvalue buckling analyses based on input data (various geometric dimensions of the girder). This procedure is implemented by using the Abaqus2Matlab toolbox, which allows the transfer of data between Matlab and Abaqus and vice versa. After that, 2,200 training data are used to build the model for predicting kb using deep learning. Finally, 200 test data are used to evaluate the accuracy of the model. The results obtained from this model are also compared with analogous results of previous works with a good agreement.

The response of concrete-filled double-skin steel tube (CFDST) members with shear connectors due to bending load is examined using the finite element (FE) method. A three dimensional FE model of the CFDST member with shear connectors (M16 and plate studs) was developed and analyzed using ABAQUS software. In order to demonstrate the accuracy of the FE model, a comparison between the results obtained from FE analysis and experiment was made. The model is further used to perform parametric studies to investigate the influence of geometric and material properties on the behavior of the CFDST member with M16 studs subjected to bending. Additionally, a comparison between the ultimate loads obtained from FE analyses and design predictions was made to evaluate the efficiency of the design predictions of the proposed FE model.

This paper aims to derive new simple and consistently reliable residual strength equations for predicting the residual ultimate strength of steel dented stiffened cylinders under combined axial compression and radial pressure including hydrostatic pressure. For this, two types of the stiffened cylinders, namely, stringer- and/or ring-stiffened cylinders, which are generally main components of offshore marine structures used in semi-submersibles, submarines, tension legs of platforms (TLPs), and other various types of floating offshore structures, are investigated. Firstly, the various collision damage scenarios which illustrated the collision accidents of offshore stiffened cylinders with supply vessels or floating subjects, were analysed. Then, a finite element modelling of the stiffened cylinders was developed using a commercial software package ABAQUS/Explicit after being validated against available test results. Next, rigorous parametric studies on full-scaled design examples of stiffened cylinders were carried out by changing the design variables. Based on the rigorous case of the study results, new simple design equations, which are used to predict the ultimate residual strength of the damaged stiffened cylinders under combined loads are proposed through a regression study. Finally, the accuracy and reliability of the proposed equations have been compared with available test data and a nonlinear finite element analysis (NFEA). These equations can be useful for the initial design stage of stiffened cylinders under the risk conditions of offshore structures in the case of collision incidents.

Among recent artificial intelligence techniques, machine learning (ML) has gained significant attention during the past decade as an emerging topic in civil and structural engineering. This paper presents an efficient and powerful machine learning-based framework for strength predicting of concrete filled steel tubular (CFST) columns under concentric loading. The proposed framework was based on the gradient tree boosting (GTB) algorithm which is one of the most powerful ML techniques for developing predictive models. A comprehensive database of over 1,000 tests on circular CFST columns was also collected from the open literature to serve as training and testing purposes of the developed framework. The efficiency of the proposed framework was demonstrated by comparing its performance with that obtained from other ML methods such as random forest (RF), support vector machines (SVM), decision tree (DT) and deep learning (DL). The accuracy of the developed predictive model was also verified with the current design equations from modern codes of practice as well as existing ML-based predictive models.

This paper aims at investigating the optimum positions and the required flexural rigidity (γrq) of a single and two longitudinal web stiffeners of unsymmetric plate girders subjected to pure bending by using gradient-based optimization algorithms. The optimization procedure is performed into two steps: The first step is to maximize the bend-buckling coefficient kb generated from eigenvalue buckling analyses, and then the second step aims to minimize the flexural rigidity of the stiffeners (γ). This procedure is implemented using the Abaqus2Matlab toolbox which allows for the transfer of data between Matlab and Abaqus and vice versa. Based on this research, the optimum locations of the stiffeners are recommended for the unsymmetric plate girders under pure bending. Additionally, equations are suggested to determine γrq of the longitudinal web stiffeners of the unsymmetric plate girders. These proposed equations are more realistic in the practical designs than those recommended by AASHTO LRFD specifications and several works in the literature in which γrq of the longitudinal web stiffeners is determined based on the simply supported plates but not the unsymmetric plate girders under bending.

In this study, new equations are developed for predicting the initial stiffness and ultimate moment of flush end-plate connections (FECs). FECs exhibit partially restrained behavior, which affects the distribution of forces and the displacement of a steel frame. Thus, the influences of the nonlinearity of connections on second-order moments are incorporated into structural analysis. FECs bolted to column flanges and welded to beams are investigated. The experimental data of FECs are collected, including initial stiffness and ultimate moment. Finite element analyses are used for analyzing the mechanical behavior of FECs and identifying the fracture mechanism of FECs. The finite element model of FECs is developed using ABAQUS software, and it is verified through comparison with the experimental results of previous studies. The mechanical behavior of FECs is investigated. An improved semi-empirical equation for the initial stiffness is suggested, and it provides good accuracy. A new type of fracture mechanism for FECs is suggested. An equation for estimating the ultimate moment is derived from the suggested fracture mechanism, and it shows good agreement with experimental data.

In this article, an efficient methodology is developed to optimize nonlinear steel frames under several load combinations. For that purpose, inelastic advanced analyses of steel frames are performed using plastic hinge beam–column elements to reduce computational efforts. An improved differential evolution (DE) algorithm is utilized as a global optimizer to refine the solution accuracy and enhance the convergence speed. Compared to the conventional DE algorithm, this newly developed method provides four major improvements such as: (1) a new mutation strategy based on the p-best method; (2) the multi-comparison technique (MCT) to decrease the number of unnecessary objective function evaluations; (3) a promising individual method (PIM) to choose trial individuals; and (4) a trial matrix containing all evaluated individuals to avoid objective function evaluations of duplicate individuals. Furthermore, panel zones are taken account of optimum design for the first time. Doubler plates are designed to prevent panel-zone shear deformations. Three mid- to large-size steel frames considering several load combinations required by AISC-LRFD are considered. Five new and efficient meta-heuristic algorithms are employed for comparison.