
This model addresses the need to randomly order a given number of indexed items

This example illustrates an efficient way (using cloned containers) to model multiple objects of the same type without having to manually reimplement identical model logic.

This model shows an implementation of the classic game Mastermind

This model illustrates how to fit a trend line to data using the GaussNewton method.

Uses SubModels to preprocess (and plot) historic time series data

This model provides an example of calculating statistics for a data time series.

This model provides examples of two different methods which can be used to generate statistics for time histories.

This model plots paired data for equivalent time intervals on the same scatterplot.

This model creates a histogram from time series values and uses it to create a PMF of the data.

In this example, a SubModel is used to calculate average monthly rainfall amounts from a Time Series element containing rainfall rate data

This model compares the bisection and secant methods for finding roots of 2nd order polynomials (i.e. of the form C1*x^2 + C2*x + C3).

This model illustrate how conditional containers can be used to simulate projects.

This model simulates the process of obtaining FDA approval for a new drug.

This model simulates a Markov process that randomly switches between a wet state and a dry state to simulate rainfall given some key historic statistics.

Watershed runoff is calculated for three catchments using the same function but different inputs

This model presents a pond discharge versus pond capacity optimization problem.

Using the GoldSim optimization module, a rainfall generator is calibrated using historical data

Simulation of a diving bell released at a specified depth and moving towards the surface where it emerges above the water

This reliability model illustrates a typical closed circuit grinding mill circuit, used in many mine processing plants.

Monte Carlo Simulation of the Dam Breach algorithm to calculate risk of failure

This model uses a submodel to estimate a possible shortfall for the coming year in order to set a supply curtailment if needed.