Multi-phase flows exist in many natural and technological systems.
Owing to the many challenges that are being faced by many applied scientists,
practising engineers, undergraduate and graduate students or
researchers engaging in the subject of multi-phase flows, the advancement
of digital computers has apparently re-focused the reliance on computational
predictions to better understand and predict the multi-phase
phenomenon. With increasing prevalence, the feasibility of application of
computational models is certainly gaining significant traction. Modelling
multi-phase flows, in general, encompasses a wide spectrum of different
length scales, a broad range of engineering disciplines, and a multitude of
different computational approaches. In spite of the comprehensive treatment
in the subject of multi-phase flows, a single text that provides a systematic
exposition of a physical model utilizing the computational fluid
dynamics concepts, techniques and models remains elusive. Therefore,
the authors truly understand the difficulties faced by multi-phase
modellers to gain sufficient knowledge in employing the necessary computational
techniques and models in their investigative studies. For the
uninitiated multi-phase modeller who is learning about the basic concepts
of computational fluid dynamics for the first time, the nitty-gritty
elements within this particular mathematically sophisticated discipline
can be rather difficult to master. For practical multi-phase flows, appropriate
models in aptly handling the complexity associated with the state
of the different phases are, in general, required. Each of these models
requires some prior basic knowledge of which the multi-phase modeller
may not have sufficiently acquired during his/her course of study.
Therefore, the authors fully acknowledge the predicament of multi-phase
modellers in attempting to obtain sensible results for a range of flow
problems by simply concentrating on the application rather than understanding
the basic theory behind the formulation and limits of applicability
of these models.