Abstract: A device includes one or more processors configured to generate simulation data by providing first sets of first values of first input parameters to a simulation of a physical system. The processors are configured to develop at least one surrogate model based on the simulation data, and to select second input parameters from the first input parameters based on the at least one surrogate model. A count of the second input parameters is less than a count of the first input parameters. The processors are configured to generate second simulation data by providing second sets of second values of the second input parameters to the simulation. The processors are configured to develop at least a second surrogate model based on the second simulation data.

Abstract: A computing system, method and computer program product dynamically manage Monte Carlo simulations. In a method, convergence criteria conditions are identified and a set of outcomes is generated following the repeated performance of one or more functions upon randomly sampled input parameter distributions. The method also determines whether the convergence criteria condition is satisfied based upon a plurality of samples. In an instance in which the convergence criteria condition is not satisfied, the method supplements the set of outcomes by repeatedly performing the one or more functions upon randomly sampled input parameter distributions. In an instance in which the convergence criteria condition is satisfied, the method determines whether the set of outcomes has been supplemented prior to satisfying the convergence criteria condition and, if the set of outcomes has not been supplemented, the size of the set of outcomes to be generated during a subsequent Monte Carlo simulation is reduced.

Abstract: A computing system, method and computer program product dynamically manage Monte Carlo simulations. In a method, convergence criteria conditions are identified and a set of outcomes is generated following the repeated performance of one or more functions upon randomly sampled input parameter distributions. The method also determines whether the convergence criteria condition is satisfied based upon a plurality of samples. In an instance in which the convergence criteria condition is not satisfied, the method supplements the set of outcomes by repeatedly performing the one or more functions upon randomly sampled input parameter distributions. In an instance in which the convergence criteria condition is satisfied, the method determines whether the set of outcomes has been supplemented prior to satisfying the convergence criteria condition and, if the set of outcomes has not been supplemented, the size of the set of outcomes to be generated during a subsequent Monte Carlo simulation is reduced.