Junxiang Li

For traditional surrogate model-based methods, the distribution parameters of random variables will change with the enrichment of the data, ultimately leading to the reconstruction of surrogate model and reassessment of reliability, which often results in a wastage of computational resources. In response, an extended Kriging model-based method is proposed in this paper for efficient reliability analysis under parameters change. Different from the standard Kriging model, in addition to random variables, variable distribution parameters are also included in the proposed method to constitute the extended input variables. In this way, the updated Kriging model with prior parameter information can be directly treated as the initial surrogate model for the posterior problem. Consequently, there is no need to reconstruct the surrogate model if the distribution parameters change, and only one Kriging model is required for this method. The efficiency, robustness and accuracy of the proposed method are demonstrated through three examples. This study contributes to dynamic assessment techniques for structural reliability analysis.

The main focus of this work is the successful deposition of hard and wear-resistant TiAlCN coating on the surface of GCr15 bearing steel by means of magnetron sputtering technology. The phase composition of the chromium nitride transition layer was monitored by precisely controlling the nitrogen (N₂) flow rate to strengthen the bonding between the TiAlCN coating and the GCr15 bearing steel surface. It was found that coating performance reached the optimal state at a N₂ flow rate of 40 sccm, yielding a hardness of 23.3 GPa, a friction coefficient of only 0.27, and a wear rate of 0.19 × 10⁻⁸ mm³/N·m.

It remains a significant challenge to quantitatively describe the corrosion of reinforced concrete (RC) structures under chloride penetration. Moreover, when considering uncertainties throughout the life cycle of corroded RC structures for assessing their safety, reliability, and optimal design, the complexity of the problem intensifies. To address these issues, this paper studies the time-dependent reliability analysis and optimal design of corroded RC beams. At first, the time-dependent reliability of beams is investigated by considering both the serviceability limit state (SLS), which corresponds to the corrosion initiation of the reinforced steel, and the ultimate limit state (ULS), associated with the bending failure of the beam. This analysis takes into account the time-dependent chloride diffusion coefficient and incorporates a stochastic process. The reliability is evaluated using the Monte Carlo Simulation (MCS) method and the cumulative distribution function (CDF) method. Subsequently, a time-dependent reliability-based design optimization (TRBDO) problem is formulated, and the PSO-MCS, a methodology incorporating a particle swarm optimization (PSO) algorithm and MCS is adopted to solve it. After optimization, the initial cost of the specific RC beam is reduced from 1351.879€ to 1247.075€, while the time-dependent reliability within [0, 100] years is improved from 0.6057 to 0.6508. The effectiveness of the CDF, MCS and PSO-MCS methods are demonstrated through reliability analysis and design examples of corroded RC beams.

It remains an important challenge to quantitatively describe the corrosion of reinforced concrete (RC) structures under chloride penetration. When considering the uncertainties encountered throughout the life cycle of RC structures exposed to a corrosive environment and evaluating their safety and reliability, the complexity of the problem intensifies. To address these issues, this paper focuses on the time-dependent reliability analysis of corroded RC beams, utilizing the phase-type (PH) fitting method. Initially, a model for the time-dependent reliability of corroded RC beams is established, incorporating the time-dependent chloride diffusion coefficient. Subsequently, a novel PH fitting method is proposed. The effectiveness of this new method is demonstrated through numerical examples. Furthermore, the time-dependent reliability analysis of corroded RC beams is compared using both the PH fitting method and the Monte Carlo simulation. The results reveal that the proposed method can accurately and efficiently deal with time-dependent reliability problems.