Reliability evaluation of 2D semi-rigid steel frames accounting for corrosion effects

Nowadays, steel frames are widely used in civil and industrial engineering structures. The design process for steel frames with semi-rigid beam-column connections is an interesting topic for designers and researchers. However, the current design codes purely deal with the structural reliability at the pristine and the degradation of steel due to corrosion is not specified. This study proposes a procedure for evaluating the reliability of two-dimensional semi-rigid steel frames considering corrosion effects. A series of Monte Carlo simulations are performed to evaluate the reliability of the corroded steel structures. The random variables including corrosion phenomenon, semi-rigid connection, and applied load, are considered in the proposed method. The safety deterioration of the steel structures due to the corrosion phenomenon until 50 years is obtained. Additionally, the effects of input parameters, which are safety factors and coefficients of variation, on the reliability of structures are examined in the present study. Finally, a verification of this study and previous results is performed, highlighting the capability of the proposed method.

Reliability evaluation of 2D semi-rigid steel frames accounting for corrosion effects

Nowadays, steel frames are widely used in civil and industrial engineering structures. The design process for steel frames with semi-rigid beam-column connections is an interesting topic for designers and researchers. However, the current design codes purely deal with the structural reliability at the pristine and the degradation of steel due to corrosion is not specified. This study proposes a procedure for evaluating the reliability of two-dimensional semi-rigid steel frames considering corrosion effects. A series of Monte Carlo simulations are performed to evaluate the reliability of the corroded steel structures. The random variables including corrosion phenomenon, semi-rigid connection, and applied load, are considered in the proposed method. The safety deterioration of the steel structures due to the corrosion phenomenon until 50 years is obtained. Additionally, the effects of input parameters, which are safety factors and coefficients of variation, on the reliability of structures are examined in the present study. Finally, a verification of this study and previous results is performed, highlighting the capability of the proposed method.

Evaluation of loading capacity of corroded reinforced concrete beams using experiment and finite element method

The purpose of this paper is to evaluate the performance of corroded reinforced concrete (RC) beams using experiments and a proposed finite element (FE) model, which is able to consider the reduction of the reinforcement diameter and adhesion force. The developed FE model comprised of three main components including concrete elements, reinforcing bar elements, and adhesion elements, in which the plane cross-section hypothesis was adopted. Thus, the necessary number of elements in the model of corroded RC beam was greatly reduced, while the accuracy of the model was still ensured. An experimental test was employed to verify the developed FE model. The results show that the proposed FE model in this study is capable of modeling RC beams under corrosion effects. Additionally, the rebar diameter and adhesion force have a significant influence on the load-carrying capacity of corroded RC beams. Moreover, a series of experimental tests of corrosive RC beams including 1-month, 2-month, and 3-month corrosion levels was conducted for various exposed times to investigate the influences of the corrosion time on the strength of RC beams. It reveals that the effect of the corrosion time on the strength of RC beams show to be pronounced

Fuzzy Structural Analysis Using Improved Jaya-based Optimization Approach

A new approach to performing the α-level optimization in the fuzzy analysis of structural systems is developed in this study. The method uses a simple global optimizer, the Jaya algorithm, together with an innovative dimension reduction technique. The dimension reduction technique aims to transform the original large α-level optimization problem into a low-dimension one by making use of the monotonic behavior of the system output with respect to the input variables. Then, the Jaya algorithm is applied to solve the reduced max/min α-level optimization problems to determine the bounds of the fuzzy output. Two numerical examples, including a 2D truss and a 3D truss, with a relatively large number of fuzzy input variables are analyzed and the fuzzy displacements under static loads are predicted. It is demonstrated that the proposed approach can save a significant computational amount and also estimate the fuzzy displacement with high accuracy

Efficient prediction of axial load-bearing capacity of concrete columns reinforced with FRP bars using GBRT model

The behavior of concrete columns reinforced with fiber reinforced polymer (FRP) bars is different from conventional reinforced concrete columns due to the mechanical properties of FRP bars. This study develops a novel machine learning (ML) model, namely gradient boosting regression tree (GBRT), for efficiently predicting the axial load-bearing capacity (ALC) of concrete columns reinforced with FRP bars. A data base containing 283 experimental results is collected to develop the ML model. Seven code-based and empirical-based equations are also included in comparison with the developed ML models. Moreover, we also propose a multiple linear regression (MLR)-based formula for calculating the ALC of the FRP-concrete column. The performance results of GBRT model are compared with those of published formulas and the proposed MLR-based formula. Statistical properties including , , and  are calculated to evaluate the accuracy of those predictive models. The comparisons demonstrate that GBRT outperforms other models with very high  values and small . Moreover, the influence of input parameters on the predicted ALC isevaluated. Finally, an efficient graphical user interface tool is developed to simplify the practical design process of FRP-concrete columns

Efficient prediction of axial load-bearing capacity of concrete columns reinforced with FRP bars using GBRT model

The behavior of concrete columns reinforced with fiber reinforced polymer (FRP) bars is different from conventional reinforced concrete columns due to the mechanical properties of FRP bars. This study develops a novel machine learning (ML) model, namely gradient boosting regression tree (GBRT), for efficiently predicting the axial load-bearing capacity (ALC) of concrete columns reinforced with FRP bars. A data base containing 283 experimental results is collected to develop the ML model. Seven code-based and empirical-based equations are also included in comparison with the developed ML models. Moreover, we also propose a multiple linear regression (MLR)-based formula for calculating the ALC of the FRP-concrete column. The performance results of GBRT model are compared with those of published formulas and the proposed MLR-based formula. Statistical properties including , , and  are calculated to evaluate the accuracy of those predictive models. The comparisons demonstrate that GBRT outperforms other models with very high  values and small . Moreover, the influence of input parameters on the predicted ALC isevaluated. Finally, an efficient graphical user interface tool is developed to simplify the practical design process of FRP-concrete columns

Influence of ground motion duration on seismic fragility of base isolated NPP structures

This study investigates the influence of earthquake duration on seismic fragility of base isolated nuclear power plant (NPP) structures. Two groups of ground motions are employed in performing time history analyses, in which short duration (SD) and long duration (LD) characteristics are considered. The advanced power reactor 1400 (APR1400) NPP structures are used for developing finite element model, which is constructed using lumped-mass stick elements. A series of 486 lead rubber bearings (LRBs) are installed under the base mat of the NPP structures to reduce the seismic damage. Seismic responses of the base isolated NPP are quantified in terms of lateral displacements and hysteretic energy distributions of LRBs. Seismic fragility curves for damage states, which are defined based on the deformation of LRB, are developed. The results reveal that the average lateral displacements of LRBs under SD and LD motions are very similar. For PGA larger than 0.4g, the mean deformation of LRB for LD motions is higher than that for SD motions. The probability of damage of base isolated NPP structures under LD motions is reduced approximately 15% compared to that asubjected to SD earthquakes. This finding emphasizes that it is crucial to use both SD and LD ground motions in seismic evaluations of base isolated NPP structure

Influence of ground motion duration on seismic fragility of base isolated NPP structures

This study investigates the influence of earthquake duration on seismic fragility of base isolated nuclear power plant (NPP) structures. Two groups of ground motions are employed in performing time history analyses, in which short duration (SD) and long duration (LD) characteristics are considered. The advanced power reactor 1400 (APR1400) NPP structures are used for developing finite element model, which is constructed using lumped-mass stick elements. A series of 486 lead rubber bearings (LRBs) are installed under the base mat of the NPP structures to reduce the seismic damage. Seismic responses of the base isolated NPP are quantified in terms of lateral displacements and hysteretic energy distributions of LRBs. Seismic fragility curves for damage states, which are defined based on the deformation of LRB, are developed. The results reveal that the average lateral displacements of LRBs under SD and LD motions are very similar. For PGA larger than 0.4g, the mean deformation of LRB for LD motions is higher than that for SD motions. The probability of damage of base isolated NPP structures under LD motions is reduced approximately 15% compared to that asubjected to SD earthquakes. This finding emphasizes that it is crucial to use both SD and LD ground motions in seismic evaluations of base isolated NPP structure

A New High Performance Decoder for LDPC Codes

The article introduces a new decoder for LDPC codes based on the general check matrix and soft syndrome. Simulation result shows that the new decoder can improve the performance of LDPC codes. Compared with some other improvements, the new decoding algorithm is simpler, and it can detect errors and be applied to great length LDPC codes