chapter1.tex

\chapter{Introduction}

Optimization problems are everywhere, especially in engineering. Achieving the highest performance and increasing as much as possible the efficiency while reducing the costs are some of the objectives that every design tries to achieve. Finding the optimum is not always easy. In complex cases, the physics and the models used cannot be analyzed as a plain mathematical function from which extra information may be extracted to get the optimum solution. 

In those cases, machine learning is one of the tools that are in constant rise for problems from all disciplines. One of any of its different subdisciplines is almost always suitable to achieve a particular solution for one specific problem. 

As an aerospace engineering, the use of computer fluid dynamics is essential for the analysis of aerodynamics and heat transfer problems. In order to optimize different engineering systems, the use of computer fluid dynamics to obtain accurate solutions appears to be one of the best tools. Combining this with some optimization techniques taken from machine learning will create a robust toolbox to perform optimization problems and apply them to engineering.