Solving optimization tasks#
The solution of optimization tasks using the REPEAT VISION platform allows:
Designing units with maximum EF;
Perform optimal design of process systems;
Effectively adapt the computational models to the diagnostic results of the operated products.
Setting an optimization problem comprises a mandatory stage of developing and debugging a physical and mathematical model of a unit, product or system on the REPEAT VISION platform, as well as preparing this model to solve the optimization problem.
Optimization tasks on the REPEAT platform are solved using a notebook available in the application, as well as using the repeat package, designed for Python programs to interact with the REPEAT VISION platform.
Note
To successfully complete the practical guides for solving optimization problems, you must have basic skills in using the Optimization of the REPEAT VISION platform.
If you are not familiar with the process of creating models on the REPEAT VISION platform, then read the basic tutorials in the simulation area of interest to you.
To successfully master the practical guides provided in this section, it is recommended to have basic skills in automating models on the REPEAT VISION platform.
In this how-to guide, you will learn how to find the orifice plate area to provide the required flow rate in a piping system.
This how-to guide examines the problem of maximizing the flow rate in a gas gathering system at a well cluster containing two gas wells.
Here you will learn how to use optimization to tune the coefficients of an aircraft’s pitch attitude control system.