  Partial differential equations can be used to model many problems in several
fields of application including, e.g., fluid mechanics, heat and mass transfer,
and electromagnetism. Accurate discretization methods (e.g., finite element or
finite volume methods, the so-called full order models) are widely used to
numerically solve these problems. However, when many physical and/or
geometrical parameters are involved, the computational cost required by full
order models becomes prohibitively expensive and this is not acceptable for
real-time computations that are becoming more and more popular for rapid
prototyping. Therefore, there is the need to introduce reduced order methods
(also referred to as reduced basis methods) able to provide, as the input
parameters change, fast and reliable solutions at a reduced computational cost.
