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Moving Particle Semi-implicit Method: A Meshfree Particle Method for Fluid Dynamics begins by familiarizing the reader with basic theory that supports their journey through sections on advanced MPH methods. The unique insights that this method provides include fluid-structure interaction, non-Newtonian flow, and cavitation, making it relevant to a wide range of applications in the mechanical, structural, and nuclear industries, and in bioengineering. Co-authored by the originator of the MPS method, this book is the most authoritative guide available. It will be of great value to students, academics and researchers in industry. - Presents the differences between MPH and SPH, helping readers choose between methods for different purposes - Provides pieces of computer code that readers can use in their own simulations - Includes the full, extended algorithms - Explores the use of MPS in a range of industries and applications, including practical advice

The Material Point Method: A Continuum-Based Particle Method for Extreme Loading Cases systematically introduces the theory, code design, and application of the material point method, covering subjects such as the spatial and temporal discretization of MPM, frequently-used strength models and equations of state of materials, contact algorithms in MPM, adaptive MPM, the hybrid/coupled material point finite element method, object-oriented programming of MPM, and the application of MPM in impact, explosion, and metal forming. Recent progresses are also stated in this monograph, including improvement of efficiency, memory storage, coupling/combination with the finite element method, the contact algorithm, and their application to problems. - Provides a user's guide and several numerical examples of the MPM3D-F90 code that can be downloaded from a website - Presents models that describe different types of material behaviors, with a focus on extreme events. - Includes applications of MPM and its extensions in extreme events, such as transient crack propagation, impact/penetration, blast, fluid-structure interaction, and biomechanical responses to extreme loading

This is the first-ever book on smoothed particle hydrodynamics (SPH) and its variations, covering the theoretical background, numerical techniques, code implementation issues, and many novel and interesting applications.It contains many appealing and practical examples, including free surface flows, high explosive detonation and explosion, underwater explosion and water mitigation of explosive shocks, high velocity impact and penetration, and multiple scale simulations coupled with the molecular dynamics method. An SPH source code is provided, making this a friendly book for readers and SPH users.

This book addresses selected aspects of steel-deformation modelling, both at very high temperatures and under the conditions in which the liquid and the solid phases coexist. Steel-deformation modelling with its simultaneous solidification is particularly difficult due to its specificity and complexity. With regard to industrial applications and the development of new, integrated continuous casting and rolling processes, the issues related to modelling are becoming increasingly important. Since the numerous industrial tests that are necessary when traditional methods are used to design the process of continuous casting immediately followed by rolling are expensive, new modelling concepts have been sought. Comprehensive tests were applied to solve problems related to the deformation of steel with a semi-solid core. Physical tests using specialist laboratory instruments (Gleeble 3800thermo-mechanical simulator, NANOTOM 180 N computer tomography, Zwick Z250 testing equipment, 3D blue-light scanning systems), and advanced mathematical modelling (finite element method (FEM), SPH smoothed particle method, cellular automata method CA) were used. This book presents in detail a modelling concept for steel deformation in the semi-solid state based on an approach integrating physical and computer simulations with a full or partial information exchange between these areas.

A simplified approach to Malliavin calculus adapted to Poisson random measures is developed and applied in this book. Called the “lent particle method” it is based on perturbation of the position of particles. Poisson random measures describe phenomena involving random jumps (for instance in mathematical finance) or the random distribution of particles (as in statistical physics). Thanks to the theory of Dirichlet forms, the authors develop a mathematical tool for a quite general class of random Poisson measures and significantly simplify computations of Malliavin matrices of Poisson functionals. The method gives rise to a new explicit calculus that they illustrate on various examples: it consists in adding a particle and then removing it after computing the gradient. Using this method, one can establish absolute continuity of Poisson functionals such as Lévy areas, solutions of SDEs driven by Poisson measure and, by iteration, obtain regularity of laws. The authors also give applications to error calculus theory. This book will be of interest to researchers and graduate students in the fields of stochastic analysis and finance, and in the domain of statistical physics. Professors preparing courses on these topics will also find it useful. The prerequisite is a knowledge of probability theory.

the solution or its gradient. These new discretization techniques are promising approaches to overcome the severe problem of mesh-generation. Furthermore, the easy coupling of meshfree discretizations of continuous phenomena to dis­ crete particle models and the straightforward Lagrangian treatment of PDEs via these techniques make them very interesting from a practical as well as a theoretical point of view. Generally speaking, there are two different types of meshfree approaches; first, the classical particle methods [104, 105, 107, 108] and second, meshfree discretizations based on data fitting techniques [13, 39]. Traditional parti­ cle methods stem from physics applications like Boltzmann equations [3, 50] and are also of great interest in the mathematical modeling community since many applications nowadays require the use of molecular and atomistic mod­ els (for instance in semi-conductor design). Note however that these methods are Lagrangian methods; i. e., they are based On a time-dependent formulation or conservation law and can be applied only within this context. In a particle method we use a discrete set of points to discretize the domain of interest and the solution at a certain time. The PDE is then transformed into equa­ tions of motion for the discrete particles such that the particles can be moved via these equations. After time discretization of the equations of motion we obtain a certain particle distribution for every time step.

Stochastic numerical methods play an important role in large scale computations in the applied sciences. The first goal of this book is to give a mathematical description of classical direct simulation Monte Carlo (DSMC) procedures for rarefied gases, using the theory of Markov processes as a unifying framework. The second goal is a systematic treatment of an extension of DSMC, called stochastic weighted particle method. This method includes several new features, which are introduced for the purpose of variance reduction (rare event simulation). Rigorous convergence results as well as detailed numerical studies are presented.