Sentence examples for dimensional reliability from inspiring English sources

Results for the benchmark problems show that both S3 and ADM are efficient for treating high dimensional reliability problems.

The results show that asymptotic sampling is capable of providing good approximations of low failure probability events for very high dimensional reliability problems in structural dynamics.

The numerical examples show that the proposed approach, applicable to both component and system reliability problems, has superior performance for high dimensional reliability analysis problems with low failure probabilities.

The dimensional reliability scores are also heartening, especially considering the overall instrument internal consistency (α = 0.903).

The MLS approach demonstrated efficient performance in low to medium-dimensional reliability problems.

In this paper we adopt a geometric perspective to highlight the challenges associated with solving high-dimensional reliability problems.

To tackle challenges in low-probability, high-dimensional reliability analysis, this paper proposes hyper-spherical extrapolation method to estimate the failure probabilities efficiently and accurately.

This paper draws attention to a fundamental problem that occurs in applying importance sampling to 'high-dimensional' reliability problems, i.e., those with a large number of uncertain parameters.

In this paper we propose a novel advanced stochastic simulation algorithm for solving high-dimensional reliability problems, called Horseracing Simulation (HRS).

The development of an efficient MCMC strategy for sampling from complex distributions is a difficult task that needs to be solved for calculating the small failure probabilities encountered in the high-dimensional reliability analysis of engineering systems.

This paper focuses on enhancements to Subset Simulation (SS), proposed by Au and Beck, which provides an efficient algorithm based on MCMC (Markov chain Monte Carlo) simulation for computing small failure probabilities for general high-dimensional reliability problems.