Download Product Sheet GPS-X has everything you need to model, simulate and analyze advanced wastewater plant designs with confidence. You can rely on our suite of proven wastewater models and the industry™s largest collection of unit processes. You can monitor and interact with your model inputs in real-time during simulation and seamlessly manage and compare different scenarios all in one place. And if you need support, our industry-leading team of experts is always ready to help…..
Innovative Tools:
GPS-XTM contains a suite of sophisticated tools allowing you to create advanced plant layouts, run interactive simulations, and perform in-depth analysis on model results.
Process Controllers:
GPS-X includes a set of robust process controllers to create treatment plant layouts with complex process control schemes.
Various Types of Controllers
1. PID Controller
2. ON/OFF Controller
3. Timer Controller
4. Flow Timer Controller
5. Scheduler Controller
In addition to stand-alone controllers, many unit processes have built-in PID controllers for easy setup (e.g. DO controller in aeration tank, RAS and WAS controller in secondary clarifier etc.).
A collection of standalone PID, PID feedforward, ON/OFF, Timer and Scheduler controllers allow you to build complex control systems like cascade ammonia based DO control, flow sequencing control in plant etc.
Analyzer:
The Analyzer module allows you to automatically perform steady-state or dynamic sensitivity analyses on model parameters, which will save you a significant amount of time and effort.
Monte Carlo Analysis:
Monte Carlo analysis in GPS-XTM allows users to generate probabilistic distribution of model outputs based on inputs with predefined
probabilistic distribution. Both steady-state or dynamic Monte Carlo simulations can be performed in GPS-XTM. This analysis can be used to assess the effect of uncertainty in model parameter and or model input on the model outputs.
A robust Monte Carlo Analysis Tool allows users to evaluate plant performance when not all of the model inputs are well-known. Users can now run simulations using a typical distribution of values, rather than being forced to choose a single value, and observe a range of model outputs.
For example, users can predict a range of effluent ammonia concentrations given the typical range of nitrifier growth rates, even though the true actual growth rate isn’t known.
The Monte Carlo Analysis Tool is a valuable addition to the GPS-XTM toolkit, and provides users with a way to bring the uncertainty of real life into their models.