Computational Modeling Of Intelligent Soft Matter

Computational Modelling of Intelligent Soft Matter: Shape Memory Polymers and Hydrogels covers the multiphysics response of various smart polymer materials, such as temperature-sensitive shape memory polymers and temperature/ chemosensitive hydrogels. Several thermo–chemo-mechanical constitutive models for these smart polymers are outlined, and their real-world applications are highlighted. The numerical counterpart of each introduced constitutive model is also presented, empowering readers to solve practical problems requiring thermomechanical responses of these materials as well as design and analyze real-world structures made of them. Introduces constitutive models based on continuum thermodynamics for intelligent soft materials Presents calibration methods for identifying material model parameters as well as finite element implementation of the featured models Allows readers to solve practical problems requiring thermomechanical responses from these materials as well as the design and analysis of real-world structures made of them

Soft matter science is nowadays an acronym for an increasingly important class of materials, which ranges from polymers, liquid crystals, colloids up to complex macromolecular assemblies, covering sizes from the nanoscale up the microscale. Computer simulations have proven as an indispensable, if not the most powerful, tool to understand properties of these materials and link theoretical models to experiments. In this first volume of a small series recognized leaders of the field review advanced topics and provide critical insight into the state-of-the-art methods and scientific questions of this lively domain of soft condensed matter research.

The scope of this book is to identify and emphasize the successful link between computational materials modeling as a simulation and design tool and its synergistic application to experimental research and alloy development. The book provides a more balanced perspective of the role that computational modeling can play in every day research and development efforts. Each chapter describes one or more particular computational tool and how they are best used.

“Soft matter” is nowadays used to describe an increasingly important class of - terials that encompasses polymers, liquid crystals, molecular assemblies building hierarchical structures, organic-inorganic hybrids, and the whole area of colloidal science. Common to all is that ?uctuations, and thus the thermal energy k T and B entropy, play an important role. “Soft” then means that these materials are in a state of matter that is neither a simple liquid nor a hard solid of the type studied in hard condensed matter, hence sometimes many types of soft matter are also named “c- plex ?uids. ” Soft matter, either of synthetic or biological origin, has been a subject of physical and chemical research since the early ?nding of Staudinger that long chain mo- cules exist. From then on, synthetic chemistry as well as physical characterization underwent an enormous development. One of the outcomes is the abundant pr- ence of polymeric materials in our everyday life. Nowadays, methods developed for synthetic polymers are being more and more applied to biological soft matter. The link between modern biophysics and soft matter physics is quite close in many respects. This also means that the focus of research has moved from simple - mopolymers to more complex structures, such as branched objects, heteropolymers (random copolymers, proteins), polyelectrolytes, amphiphiles and so on.

This book presents recent advances in the theory and implementation of intelligent and other computational techniques in the insurance industry. The paradigms covered encompass artificial neural networks and fuzzy systems, including clustering versions, optimization and resampling methods, algebraic and Bayesian models, decision trees and regression splines. Thus, the focus is not just on intelligent techniques, although these constitute a major component; the book also deals with other current computational paradigms that are likely to impact on the industry. The application areas include asset allocation, asset and liability management, cash-flow analysis, claim costs, classification, fraud detection, insolvency, investments, loss distributions, marketing, pricing and premiums, rate-making, retention, survival analysis, and underwriting.

In this book, internationally recognized experts in philosophy of science, computer science, and modeling and simulation are contributing to the discussion on how ontology, epistemology, and teleology will contribute to enable the next generation of intelligent modeling and simulation applications. It is well understood that a simulation can provide the technical means to display the behavior of a system over time, including following observed trends to predict future possible states, but how reliable and trustworthy are such predictions? The questions about what we can know (ontology), how we gain new knowledge (epistemology), and what we do with this knowledge (teleology) are therefore illuminated from these very different perspectives, as each experts uses a different facet to look at these challenges. The result of bringing these perspectives into one book is a challenging compendium that gives room for a spectrum of challenges: from general philosophy questions, such as can we use modeling and simulation and other computational means at all to discover new knowledge, down to computational methods to improve semantic interoperability between systems or methods addressing how to apply the recent insights of service oriented approaches to support distributed artificial intelligence. As such, this book has been compiled as an entry point to new domains for students, scholars, and practitioners and to raise the curiosity in them to learn more to fully address the topics of ontology, epistemology, and teleology from philosophical, computational, and conceptual viewpoints.

This IMA Volume in Mathematics and its Applications MODELING OF SOFT MATTER contains papers presented at a very successful workshop with the same ti tle. The event, which was held on September 27-October 1, 2004, was an integral part of the 2004-2005 IMA Thematic Year on "Mathematics of Ma terials and Macromolecules: Multiple Scales, Disorder, and Singularities. " We would like to thank Maria-Carme T. Calderer (School of Mathematics, University of Minnesota) and Eugene M. Terentjev (Cavendish Laboratory, University of Cambridge) for their superb role as workshop organizers and editors of the proceedings. We take this opportunity to thank the National Science Foundation for its support of the IMA. Series Editors Douglas N. Arnold, Director of the IMA Arnd Scheel, Deputy Director of the IMA PREFACE The physics of soft matter in particular, focusing on such materials as complex fluids, liquid crystals, elastomers, soft ferroelectrics, foams, gels and particulate systems is an area of intense interest and contemporary study. Soft matter plays a role in a wide variety of important processes and application, as well as in living systems. For example, gel swelling is an essential part of many biological processes such as motility mecha nisms in bacteria and the transport and absorption of drugs. Ferroelectrics, liquid crystals, and elastomers are being used to design ever faster switch ing devices. Experiments of the last decade have provided a great deal of detailed information on structures and properties of soft matter.

This series presents critical reviews of the present and future trends in polymer and biopolymer science including chemistry, physical chemistry, physics and materials science. It is addressed to all scientists at universities and in industry who wish to keep abreast of advances in the topics covered. Impact Factor Ranking: Always number one in Polymer Science. More information as well as the electronic version of the whole content available at: www.springerlink.com

Soft computing is a consortium of computing methodologies that provide a foundation for the conception, design, and deployment of intelligent systems and aims to formalize the human ability to make rational decisions in an environment of uncertainty and imprecision. This book is based on a NATO Advanced Study Institute held in 1996 on soft computing and its applications. The distinguished contributors consider the principal constituents of soft computing, namely fuzzy logic, neurocomputing, genetic computing, and probabilistic reasoning, the relations between them, and their fusion in industrial applications. Two areas emphasized in the book are how to achieve a synergistic combination of the main constituents of soft computing and how the combination can be used to achieve a high Machine Intelligence Quotient.

This introduction and textbook familiarizes engineers with the use of mathematical and computational modeling and simulation in a way that develops their understanding of the solution characteristics of a broad class of real-world problems. The relevant basic and advanced methodologies are explained in detail, with special emphasis on ill-defined problems. Some fifteen simulation systems are presented on the language and the logical level. Moreover, the reader also can accumulate an experiential overview by studying the wide variety of case studies spanning much of science and engineering. The latter are briefly described within the book but their full versions as well as some simulation software demos are available on the Web. The book can be used for courses on various levels as well as for self-study. Advanced sections are identified and can be skipped in a first reading or in undergraduate courses.