Covers Latin Hypercube Sampling and Quasi Monte Carlo methods for stochastic simulation, explaining the goal of stratification and generating independent permutations.
Covers the fundamentals of numerical flow simulation, emphasizing the importance of understanding the methodology and practicing simulation techniques to run full simulations autonomously.
Emphasizes the impact of boundary conditions on solution convergence in numerical flow simulation and discusses the choice between pressure-based and density-based solvers.