The book collects relevant contributions presented at a conference, organized in honour of Carlo Cercignani, that took place at Politecnico di Milano on May 24–28, 2021. Different research areas characterizing the scientific work of Carlo Cercignani have been considered with a particular focus on: mathematical and numerical methods for kinetic equations; kinetic modelling of gas mixtures and polyatomic gases; applications of the Boltzmann equation to electron transport, social phenomena and epidemic spread; turbulence modelling; the Einstein Classical Program; Dynamical Systems Theory.

Many applications require reliable numerical simulations of realistic set-ups e.g. plasma physics. This book gives a short introduction into kinetic models of gas mixtures describing the time evolution of rarefied gases and plasmas. Recently developed models are presented which extend existing literature by including more physical phenomena. We develop a numerical scheme for these more elaborated equations. The scheme is proven to maintain the physical properties of the models at the discrete level. We show several numerical test cases inspired by physical experiments.

This book constitutes the thoroughly refereed post-conference proceedings of the 7th International Conference on Parallel Processing and Applied Mathematics, PPAM 2007, held in Gdansk, Poland, in September 2007. The 63 revised full papers of the main conference presented together with 85 revised workshop papers were carefully reviewed and selected from over 250 initial submissions. The papers are organized in topical sections on parallel/distributed architectures and mobile computing, numerical algorithms and parallel numerics, parallel and distributed non-numerical algorithms, environments and tools for as well as applications of parallel/distributed/grid computing, evolutionary computing, meta-heuristics and neural networks. The volume proceeds with the outcome of 11 workshops and minisymposia dealing with novel data formats and algorithms for dense linear algebra computations, combinatorial tools for parallel sparse matrix computations, grid applications and middleware, large scale computations on grids, models, algorithms and methodologies for grid-enabled computing environments, scheduling for parallel computing, language-based parallel programming models, performance evaluation of parallel applications on large-scale systems, parallel computational biology, high performance computing for engineering applications, and the minisymposium on interval analysis.

This text is an introduction to methods of grid generation technology in scientific computing. Special attention is given to methods developed by the author for the treatment of singularly-perturbed equations, e.g. in modeling high Reynolds number flows. Functionals of conformality, orthogonality, energy and alignment are discussed.

The aim of this book is twofold: to provide an introduction for newcomers to state of the art computer simulation techniques in space plasma physics and an overview of current developments. Computer simulation has reached a stage where it can be a highly useful tool for guiding theory and for making predictions of space plasma phenomena, ranging from microscopic to global scales. The various articles are arranged, as much as possible, according to the - derlying simulation technique, starting with the technique that makes the least number of assumptions: a fully kinetic approach which solves the coupled set of Maxwell’s equations for the electromagnetic ?eld and the equations of motion for a very large number of charged particles (electrons and ions) in this ?eld. Clearly, this is also the computationally most demanding model. Therefore, even with present day high performance computers, it is the most restrictive in terms of the space and time domain and the range of particle parameters that can be covered by the simulation experiments. It still makes sense, therefore, to also use models, which due to their simp- fying assumptions, seem less realistic, although the e?ect of these assumptions on the outcome of the simulation experiments needs to be carefully assessed.