Numerical Simulation An Art Of Prediction 1

Numerical simulation is a technique of major importance in various technical and scientific fields. Used to understand diverse physical phenomena or to design everyday objects, it plays a major role in innovation in the industrial sector. Whilst engineering curricula now include training courses dedicated to it, numerical simulation is still not well-known in some economic sectors, and even less so among the general public. Simulation involves the mathematical modeling of the real world, coupled with the computing power offered by modern technology. Designed to perform virtual experiments, digital simulation can be considered as an "art of prediction". Embellished with a rich iconography and based on the testimony of researchers and engineers, this book shines a light on this little-known art. It is the first of two volumes and focuses on the principles, methods and industrial practice of numerical modeling.

Numerical simulation is a technique of major importance in various technical and scientific fields. Whilst engineering curricula now include training courses dedicated to it, numerical simulation is still not well-known in some economic sectors, and even less so among the general public. Simulation involves the mathematical modeling of the real world, coupled with the computing power offered by modern technology. Designed to perform virtual experiments, digital simulation can be considered as an "art of prediction". Embellished with a rich iconography and based on the testimony of researchers and engineers, this book shines a light on this little-known art. It is the second of two volumes and gives examples of the uses of numerical simulation in various scientific and technical fields: agriculture, industry, Earth and universe sciences, meteorology and climate studies, energy, biomechanics and human and social sciences.

Triangulations, and more precisely meshes, are at the heart of many problems relating to a wide variety of scientific disciplines, and in particular numerical simulations of all kinds of physical phenomena. In Volume 1, the theoretical foundations relating to triangulations, finite element shape functions and their interpretations as geometric patches were explored. This has made it possible to build tools that make the geometric modeling of any object possible. These elements are used in Volume 2 to treat meshing problems in their different implementations. Meshing, Geometric Modeling and Numerical Simulation 3 offers technical additions to the methods seen in the first two volumes and a significant portion of this book is dedicated to mesh visualization problems and solutions, especially those with a high degree of complexity.

In order to describe soil–structure interaction in various situations (nonlinear, static, dynamic, hydro-mechanical couplings), this book gives an overview of the main modeling methods developed in geotechnical engineering. The chapters are centered around: the finite element method (FEM), the finite difference method (FDM), and the discrete element method (DEM). Deterministic Numerical Modeling of Soil–Structure Interaction allows the reader to explore the classical and well-known FEM and FDM, using interface and contact elements available for coupled hydro-mechanical problems. Furthermore, this book provides insight on the DEM, adapted for interaction laws at the grain level. Within a classical finite element framework, the concept of macro-element is introduced, which generalizes constitutive laws of SSI and is particularly straightforward in dynamic situations. Finally, this book presents the SSI, in the case of a group of structures, such as buildings in a town, using the notion of metamaterials and a geophysics approach.

Simulation technology, and computational fluid dynamics (CFD) in particular, is essential in the search for solutions to the modern challenges faced by humanity. Revolutions in CFD over the last decade include the use of unstructured meshes, permitting the modeling of any 3D geometry. New frontiers point to mesh adaptation, allowing not only seamless meshing (for the engineer) but also simulation certification for safer products and risk prediction. Mesh Adaptation for Computational Dynamics 1 is the first of two volumes and introduces basic methods such as feature-based and multiscale adaptation for steady models. Also covered is the continuous Riemannian metrics formulation which models the optimally adapted mesh problem into a pure partial differential statement. A number of mesh adaptative methods are defined based on a particular feature of the simulation solution. This book will be useful to anybody interested in mesh adaptation pertaining to CFD, especially researchers, teachers and students.

The new book series “The Science and Art of Simulation” (SAS) addresses computer simulations as a scientific activity and engineering artistry (in the sense of a technē). The first volume is devoted to three topics: 1. The Art of Exploring Computer Simulations Philosophy began devoting attention to computer simulations at a relatively early stage. Since then, the unquestioned point of view has been that computer simulation is a new scientific method; the philosophy of simulation is therefore part of the philosophy of science. The first section of this volume discusses this implicit, unchallenged assumption by addressing, from different perspectives, the question of how to explore (and how not to explore) research on computer simulations. Scientists discuss what is still lacking or considered problematic, while philosophers draft new directions for research, and both examine the art of exploring computer simulations. 2. The Art of Understanding Computer Simulations The results of computer simulations are integrated into both political and social decisions. It is implicitly assumed that the more detailed, and consequently more realistic, a computer simulation is, the more useful it will be in decision-making. However, this idea is by no means justified. Different types of computer simulations have to be differentiated, which in turn requires the specific skill of understanding computer simulation results. The articles in this section examine the capabilities and limits of simulation results in political and social contexts, exploring the art of understanding computer simulation results. 3. The Art of Knowing through Computer Simulations? The advent of computer simulation in today’s scientific practices challenges the order of science. What kind of knowledge is gained through computer simulations is the key question in this section. Computer simulations are often compared to experiments or to arguments, and the transformation of our traditional scientific notions might be more challenging than expected – these Ideas are put forward in the third section to conceptualize the art of knowing through computer simulations.

The finite element method, which emerged in the 1950s to deal with structural mechanics problems, has since undergone continuous development. Using partial differential equation models, it is now present in such fields of application as mechanics, physics, chemistry, economics, finance and biology. It is also used in most scientific computing software, and many engineers become adept at using it in their modeling and numerical simulation activities. This book presents all the essential elements of the finite element method in a progressive and didactic way: the theoretical foundations, practical considerations of implementation, algorithms, as well as numerical illustrations created in MATLAB. Original exercises with detailed answers are provided at the end of each chapter.

Isogeometric analysis (IGA) consists of using the same higher-order and smooth spline functions for the representation of geometry in Computer Aided Design as for the approximation of solution fields in Finite Element Analysis. Now, almost twenty years after its creation, substantial works are being reported in IGA, making it very competitive in scientific computing. This book proposes to use IGA jointly with standard finite element methods (FEM), presenting IGA as a projection of FEM on a more regular reduced basis. By shedding new light on how IGA relates to FEM, we can see how IGA can be implemented on top of an FE code in order to improve the solution of problems that require more regularity. This is illustrated by using IGA with FEM in a non-invasive fashion to perform efficient and robust multiscale global/local simulations in solid mechanics. Furthermore, we show that IGA can regularize the inverse problem of FE digital image correlation in experimental mechanics.