Uncertainty Quantification of the Ishigami Function
Application ID: 103131
This example demonstrates how to perform uncertainty quantification analysis of the Ishigami function. This random function of three variables is a well-known benchmark used to test global sensitivity analysis and uncertainty quantification algorithms. The mean, standard deviation, maximum, and mininum values as well as Sobol indices of the Ishigami function can be calculated analytically for the input distributions used here. A separate version of this model is provided which performs a direct Monte Carlo simulation using no add-on products.
This model example illustrates applications of this type that would nominally be built using the following products:
however, additional products may be required to completely define and model it. Furthermore, this example may also be defined and modeled using components from the following product combinations:
The combination of COMSOL® products required to model your application depends on several factors and may include boundary conditions, material properties, physics interfaces, and part libraries. Particular functionality may be common to several products. To determine the right combination of products for your modeling needs, review the Specification Chart and make use of a free evaluation license. The COMSOL Sales and Support teams are available for answering any questions you may have regarding this.