Seismic Reliability Assessment of Inelastic SDOF Systems Subjected to Near-Fault Ground Motions Considering Pulse Occurrence

The ground motions in the orientation corresponding to the strongest pulse energy impose more serious demand on structures than that of ordinary ground motions.Moreover,not all near-fault ground motion records present distinct pulses in the velocity time histories.In this paper,the parameterized stochastic model of near-fault ground motion with the strongest energy and pulse occurrence probability is suggested,and the Monte Carlo simulation(MSC)and subset simulation are utilized to calculate the first excursion probability of inelastic single-degree-of-freedom(SDOF)systems subjected to these types of near-fault ground motion models,respectively.Firstly,the influences of variation of stochastic pulse model parameters on structural dynamic reliability with different fundamental periods are explored.It is demonstrated that the variation of pulse period,peak ground velocity and pulse waveform number have significant effects on structural reliability and should not be ignored in reliability analysis.Then,subset simulation is verified to be unbiased and more efficient for computing small reliable probabilities of structures compared to MCS.Finally,the reliable probabilities of the SDOF systems with different fundamental periods subjected to impulsive,non-pulse ground motions and the ground motions with pulse occurrence probability are performed,separately.It is indicated that the ground motion model with the pulse occurrence probability can give a rational estimate on structural reliability.The impulsive and ordinary ground motion models may overestimate and underestimate the reliability of structures with fundamental period much less than the mean pulse period of earthquake ground motions.

Minimal cut-based recursive decomposition algorithm for seismic reliability evaluation of lifeline networks

In this paper, a new probabilistic analytical approach, the minimal cut-based recursive decomposition algorithm （MCRDA）, is presented to evaluate the seismic reliability of large-scale lifeline systems. Based on the minimal cut searching algorithm, the approach calculates the disjoint minimal cuts one by one using the basic procedure of the recursive decomposition method. At the same time, the process obtains the disjoint minimal paths of the system. In order to improve the computation efficiency, probabilistic inequality is used to calculate a solution that satisfies the prescribed error bound. A series of case studies show that MCRDA converges rapidly when the edges of the systems have low reliabilities. Therefore, the approach can be used to evaluate large-scale lifeline systems subjected to strong seismic wave excitation.

Seismic reliability analysis of large electric power systems

Based on the De.Morgan laws and Boolean simplification, a recursive decomposition method is introduced in this paper to identify the main exclusive safe paths and failed paths of a network. The reliability or the reliability bound of a network can be conveniently expressed as the summation of the joint probabilities of these paths. Under the multivariate normal distribution assumption, a conditioned reliability index method is developed to evaluate joint probabilities of various exclusive safe paths and failed paths, and, finally, the seismic reliability or the reliability bound of an electric power system. Examples given in the paper show that the method is very simple and provides accurate results in the seismic reliability analysis.

Seismic reliability analysis of urban water distribution network

An approach to analyze the seismic reliability of water distribution networks by combining a hydraulic analysis with a first-order reliability method （FORM）, is proposed in this paper. The hydraulic analysis method for normal conditions is modified to accommodate the special conditions necessary to perform a seismic hydraulic analysis. In order to calculate the leakage area and leaking flow of the pipelines in the hydraulic analysis method, a new leakage model established from the seismic response analysis of buried pipelines is presented. To validate the proposed approach, a network with 17 nodes and 24 pipelines is investigated in detail. The approach is also applied to an actual project consisting of 463 nodes and 767 pipelines. The results show that the proposed approach achieves satisfactory results in analyzing the seismic reliability of large-scale water distribution networks.

Seismic elastic-plastic time history analysis and reliability study of quayside container crane

Quayside container crane is a kind of huge dimension steel structure,which is the major equipment used for handling container at modern ports.With the aim to validate the safety and reliability of the crane under seismic loads,besides conventional analysis,elastic-plastic time history analysis under rare seismic intensity is carried out.An ideal finite element（FEM） elastic-plastic mechanical model of the quayside container crane is presented by using ANSYS codes.Furthermore,according to elastic-plastic time history analysis theory,deformation,stress and damage pattern of the structure under rare seismic intensity are investigated.Based on the above analysis,the established reliability model according to the reliability theory,together with seismic reliability analysis based on Monte-Carlo simulation is applied to practical analysis.The results show that the overall structure of the quayside container crane is generally unstable under rare seismic intensity,and the structure needs to be reinforced.

Reliability and sensitivity analysis of wedge stability in the abutments of an arch dam using artificial neural network

In this study,the seismic stability of arch dam abutments is investigated within the framework of the probabilistic method.A large concrete arch dam is considered with six wedges for each abutment.The seismic safety of the dam abutments is studied with quasi-static analysis for different hazard levels.The Londe limit equilibrium method is utilized to calculate the stability of the wedges in the abutments.Since the finite element method is time-consuming,the neural network is used as an alternative for calculating the wedge safety factor.For training the neural network,1000 random samples are generated and the dam response is calculated.The direction of applied acceleration is changed within 5-degree intervals to reveal the critical direction corresponding to the minimum safety factor.The Latin hypercube sampling(LHS)is employed for sample generation,and the safety level is determined with reliability analysis.Three sample numbers of 1000,2000 and 4000 are used to examine the average and standard deviation of the results.The global sensitivity analysis is used to identify the effects of random variables on the abutment stability.It is shown that friction,cohesion and uplift pressure have the most significant effects on the wedge stability variance.