Reliability analysis

## What is the 'safety margin' in structural reliability analysis?

The difference between the capacity and the demand is the safety margin.

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Reliability analysis

The difference between the capacity and the demand is the safety margin.

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Reliability analysis

When the limit state function can be expressed as the difference between capacity and demand, the problem is sometimes referred to as basic reliability problem.

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Reliability analysis

Use our web app to quantify the uncertainty about the probability of failure based on a conducted Monte Carlo simulation.

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Reliability analysis

The underlying distribution can be highly skewed, even if the total number of samples in the Monte Carlo simultion is very large. This is why the Normal approximation often performs poorly in practice.

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Reliability analysis

The distribution quantifying the uncertainty about the probability of failure can be highly skewed, even for a large number of samples. The coefficient of variation is easier to interprete for symmetric distributions.

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Reliability analysis

Even if Monte Carlo simulation returns not a single sample in the failure domain, we can still quantify the uncertainty about whether a specified target reliability level is maintained.

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Reliability analysis

We explain a Bayesian post-processing step for MCS. It is ideally suited to quantify the uncertainty and to evaluate credible intervals for the probability of failure.

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Reliability analysis

For a given probability of failure, the variance and coefficient of variation of the Monte Carlo estimate can be evaluated analytically. From this, the total number of samples required to maintain a target coefficient of variation can be deduced.

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Reliability analysis

Monte Carlo simulation is a very robust structural reliability method because its performance depends solely on the total number of samples and the underlying probability of failure.

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Reliability analysis

Monte Carlo simulation divides the number of samples with system failure by the total number of random samples generated to estimate the probability of failure in a reliability analysis.

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