Context

The Lattice Boltzmann Method (LBM), derived from the gas kinetic theory, has emerged as an alternative to the resolution of Navier-Stokes equations using computational fluid dynamics. LBM is an unsteady method and has several strengths: (1) easy mesh generation on complex geometry and (2) allows massively parallel computing. This training aims at providing basic knowledge on how LBM works.

Scientific content

This online training course presents the fundamental concepts of the Lattice Boltzmann Method (LBM) for single-phase flows. It is divided in 3 consecutive weeks:

• week 1: introduction to LBM: why and what for?
• week 2: the Bolztmann equation and the kinetic theory
• week 3: solving the Boltzmann equation: the Lattice Bolztmann Method

An interactive live conference will close the session and will deal with an application case where you will try to predict the stability of a system. This conference will be held during week 4.

Learning outcomes

At the end of this training, you will be able to:

• evaluate the relevance of using LBM for a given case: benefits and limitations compared to the traditional resolution of the Navier-Stokes equations,
• choose the appropriate lattice depending on physical phenomena of interest,
• explain the numerical efficiency of LBM from the point of view of HPC: multiprocessing and wall-clock time.

Organization

This is a fully online training session. It is divided into 5 consecutive weeks, based on learning activities delivered each week.

• Week 1 to week 3 require around 2 hours of work per week. Learning activities are released on Monday of each week and you have 7 days to complete each week's activities. The 2 hours of work can be distributed over the week, depending on your schedule.
• A 1 hour live interactive session will hold during week 4. This live session will deal with an applicative case. This live session will also be recorded.
• Last week is dedicated to revising and a final exam, leading to a certificate of learning.

Our pedagogical principles

All our learning sessions are built upon evidence-based principles from cognitive psychology and learning research:

• concepts first: the course is focused on conceptual understanding of the meaning of equations and how they apply in practical cases (Van Heuvelen, 1991).
• active learning: the course is organized around activities especially designed to make participants interact between each other, involving a deep processing of the scientific content previously shown in short videos (Salmon, 2013).
• long-term retention and transfer: because you need to apply what you will learn during this session in the future and in various contexts, our courses are designed using the 10 laboratory-tested principles drawn from cognitive psychology (Halpern and Hakel, 2003).

Be prepared to be engaged and to interact with a community sharing a common goal: learning the scientific content of this course.

Requirements