In this contribution, a novel procedure denoted as 'Local Domain Monte Carlo Simulation' (LD-MCS) is studied for its potential use in structural reliability analysis.
Sensors of modern monitoring systems used in structural engineering provide data used for reliability assessment and maintenance planning.
For such structures, it is important to determine the environmental loads to apply in structural reliability calculations and structural design.
This paper combines the Monte Carloethod, used in many structural reliability algorithms, with a simplified but conservative progressive collapse structural model.
Furthermore, various scenarios of global warming that can be used to assess the effect of climate change in structural reliability are proposed.
In structural reliability analysis, sensitivity analysis can be used to measure how the input variable influences the failure of structure.
This paper presents a survey on the development and use of Artificial Neural Network (ANN) models in structural reliability analysis.
