This tutorial will introduce the GPS-X interface, and teach users how to construct a simple plant model, enter input parameters and run a simple simulation.

This tutorial will instruct users on how run dynamic simulations with the layout that was created in Tutorial 1, and how to set up interactive input controllers and output graphs.

This tutorial will show users how to use the layout editing tools such as Copy and Paste to make additions to a layout. Users will also explore the Scenario function, and learn how to set up specialized data sets for comparing the performance of the clarifiers in the event of uneven flow distribution.

This tutorial will instruct users on how to create custom tables and graphs of simulation results, and also explore the various plant-wide data visualization tools available in GPS-X. Users will also learn how to export simulation results into Word or Excel reports.

In this tutorial, users will investigate the influent models and the use of Influent Advisor as a tool to help characterize influent data.

This tutorial demonstrates how to read data into GPS-X to drive dynamic simulations, and how to plot data alongside simulation results for calibration purposes. You will also see how to use the GPS-X statistical analysis package to assess the goodness-of-fit of the model results.

This tutorial will show you how to set up a dissolved oxygen controller that automatically changes the aeration flow rate to meet the dissolved oxygen set point. You will see how to set up an MLSS controller to automatically adjust the biosolids wastage rate to meet the specified MLSS set point.

In this tutorial, you will learn how to define custom variables for your GPS-X model, such as totals and moving averages of typical process parameters. The GPS-X define function can also be used to create plant-specific definitions of key calculations such as F/M Ratio and solids retention time (SRT). This tutorial shows how to define and plot those values on output graphs, to understand how process operational changes effect SRT and plant effluent quality.

In this tutorial, you will learn how to use the GPS-X Analyzer function to investigate the relationship between various variables in a GPS-X model. The analyzer function runs multiple simulation while changing the one input parameter, and plots the results versus that independent variable. Learn how to use the analyzer tools to do steady-state and dynamic analyses of important process parameters.

In this tutorial, you will learn how to use the GPS-X Optimizer tool to determine the best set of parameters to fit a model prediction to measured results. This tutorial uses an example of a simple benchscale batch test where the GPS-X Optimizer tool determines two kinetic parameters (growth rate and half-saturation coefficient) by searching for the best set of parameter values to fit dynamic concentration data.

In this tutorial, you will learn how to add your own custom calculations, parameters and display variables to a GPS-X layout. In this example, users will add a custom randomized noise signal to an existing GPS-X variable, and create a new variable to plot in the GPS-X output graphs.

In this tutorial, users will learn how to use the GPS-X Dynamic Parameter Estimator (DPE) tool to determine a time series of optimized parameter values that fit the model best to the given data. The tutorial shows how to set up the DPE tool, and run the optimizer under different conditions.