Yafei Ma

Bridge Remaining Strength Prediction Integrated with Bayesian Network and In Situ Load Testing

This paper proposes a new framework for predicting remaining bridge strength that integrates a Bayesian network and in situ load testing. It discusses the uncertainty of important factors on corrosion damage and develops a stiffness degradation model for corroded beams based on experimental investigations. Following this, the authors develop a Bayesian network that includes corrosion damage, stiffness degradation, load-deflection response, and other factors to predict structural strength degradation. A numerical example using an existing RC bridge demonstrates the general procedures. The comparison between the theoretical and the experimental deflections from load testing shows that the proposed methodology can efficiently improve prediction accuracy and reduce prediction uncertainty.

Probabilistic Analysis of Corrosion of Reinforcement in RC Bridges Considering Fuzziness and Randomness

AbstractA general methodology for probabilistic corrosion analysis of reinforcing bar in RC bridges is proposed in this paper. Uncertainties due to limited number of experimental data, incomplete inspection information, as well as the intrinsic randomness of random variables affect the prognostics of corrosion damage. The proposed study includes both fuzziness and randomness to consider different types of uncertainties. First, the chloride-induced corrosion initiation and propagation model are developed for reinforcement in RC bridge. The relationship between the area corrosion rate and the yield strength degradation is proposed on the basis of experimental investigation from accelerated corrosion testing. Following this, the randomness and fuzziness are included using fuzzy random variables to consider the uncertainties of the degradation under corrosive environments. The probabilistic modeling of the mean and the SD of reinforcement yield strength is discussed in detail. Finally, the proposed methodolog...

Static and Fatigue Behavior Investigation of Artificial Notched Steel Reinforcement

Pitting corrosion is one of the most common forms of localized corrosion. Corrosion pit results in a stress concentration and fatigue cracks usually initiate and propagate from these corrosion pits. Aging structures may fracture when the fatigue crack reaches a critical size. This paper experimentally simulates the effects of pitting morphologies on the static and fatigue behavior of steel bars. Four artificial notch shapes are considered: radial ellipse, axial ellipse, triangle and length-variable triangle. Each shape notch includes six sizes to simulate a variety of pitting corrosion morphologies. The stress-strain curves of steel bars with different notch shape and depth are obtained based on static tensile testing, and the stress concentration coefficients for various conditions are determined. It was determined that the triangular notch has the highest stress concentration coefficient, followed by length-variable triangle, radial ellipse and axial ellipse shaped notches. Subsequently, the effects of notch depth and notch aspect ratios on the fatigue life under three stress levels are investigated by fatigue testing, and the equations for stress range-fatigue life-notch depth are obtained. Several conclusions are drawn based on the proposed study. The established relationships provide an experimental reference for evaluating the fatigue life of concrete bridges.

Effects of stress ratio and banded microstructure on fatigue crack growth behavior of HRB400 steel bar

AbstractThis paper investigates the effects of stress ratio and microstructure on the fatigue crack growth (FCG) behavior of HRB400 steel bars widely used in concrete bridges. A constant stress–con...

Uncertainty Quantification and Structural Reliability Estimation Considering Inspection Data Scarcity

AbstractReliability estimation of aging RC structures under environmental attack involves various sources of uncertainties. In realistic operational conditions, uncertainties due to limited number of experimental data and incomplete inspection information affect the reliability assessment of the existing RC structures. A fuzzy probabilistic methodology is proposed in this paper to consider the inspection data scarcity for the RC structures uncertainty quantification and reliability estimation. The membership function is used to describe the fuzzy characteristic of small numbers of detection results. Following this, the fuzzy variables are transformed to the equivalent random variables and the classic reliability index can be obtained. The proposed methodology is compared with the conventional probabilistic approach using the goodness-of-fit method. The effect of data scarcity is discussed in detail. Next, the developed methodology is demonstrated with a RC bridge. Parametric studies of the concrete streng...

Shear capacity of reinforced concrete beam with diagonal reinforcement based on modified compression field theory

AbstractFor the compression—shear failure of a reinforced concrete bridge beam with diagonal reinforcement, the calculation of ultimate shear capacity is proposed based on the modified compression field theory (MCFT). Shear force is shared by the shear compression zone of concrete, stirrups, and diagonal reinforcements intersecting with diagonal cracks. The shear capacities of concrete in the tensile and compression areas are calculated. The new balance equation between the average stress and the internal force of cracked concrete is established, and the effects of diagonal reinforcement on the stress of diagonal cracks are considered. This procedure considers the constitutive relation conditions of materials and the deformation compatibility of concrete. The theoretical shear capacity predicted by MCFT is validated by the test results of two reinforced concrete beams, providing a reference for calculating the capacity of reinforced concrete beam.