First Order Reliability Method (FORM)The First Order Reliability Method (FORM) is a Most Probable Point (MPP) search method that uses an optimization strategy to find the closest point (MPP) on each constraint to the current design, called the Mean Value Point (MVP). FORM uses a first-order analysis. For more information, see First Order Reliability Method (FORM). Importance SamplingThe Importance Sampling technique is a type of reliability method where a distribution other than the original distribution is used to compute the probability of failure more efficiently. Importance Sampling, similar to the First Order Reliability Method (FORM), computes the Most Probable Point (MPP)—the point on the constraint that is closest to the mean value point in the standard normal space. A new distribution with the MPP as the mean is used to generate random designs near the failure surface. The probability of failure is then calculated by summing the scaled contribution of the failed points; scaling is done to transform the points from the new distribution to the original distribution. For more information, see Importance Sampling Method. Mean Value MethodThe Mean Value Method is the default selection and is usually the most efficient method. The mean value method is based on a first- or second-order Taylor’s expansion to estimate response mean and standard deviation. For more information, see Mean Value Methods. Second Order Reliability Method (SORM)The Second Order Reliability Method (SORM) is a Most Probable Point (MPP) search method that uses an optimization strategy to find the closest point (MPP) on each constraint to the current design, called the Mean Value Point (MVP). SORM uses a first-order analysis and the principle curvatures of the failure function (second-order analysis) to determine the probability of failure at the MPP. For more information, see Second Order Reliability Method (SORM). |