Multiphysics Modelling: Materials, Components, and Systems by Murat Peksen
This book focuses on situations where coupled phenomena involving a combination of thermal, fluid, and solid mechanics occur. Important fundamentals of the various physics that are required in multiphysics modeling are introduced and supported with practical problems. More advanced topics such as creep deformation, fatigue, and fracture, multiphase flow or melting in porous media are tackled. 3D interactions in system architectures and energy systems such as batteries, reformer or fuel cells, and modelling of high-performance materials are exemplified. Important multiphysics modelling issues are highlighted. In addition to theory, solutions to problems, such as in linear and non-linear situations are addressed, as well as specific solutions for multiphysics modelling of fluid-solid, solid-solid and fluid-fluid interactions are given.
Adaptive Identification and Control of Uncertain Systems with Nonsmooth Dynamics by Jing Na, Qiang Chen and Xuemei Ren
This volume in the series Emerging Methodologies and Applications in Modelling reports some of the latest research on modelling, identification and adaptive control for systems with non-smooth dynamics (e.g., backlash, dead zone, friction, saturation, etc). The authors present recent research results for the modelling and control designs of uncertain systems with non-smooth dynamics, such as friction, dead-zone, saturation, and hysteresis, etc., with particular applications in servo systems. The book is organised into 19 chapters, distributed in five parts, concerning the four types of non-smooth characteristics—namely friction, dead-zone, saturation, and hysteresis, respectively. Practical experiments are also included to validate and exemplify the proposed approaches.
Drag Reduction of Complex Mixtures by Keizo Watanabe
This book discusses the concept of drag reduction phenomena in complex mixtures in internal and external flows that are shown experimentally by dividing flow patterns into three categories. The book is intended to support further experiments or analysis in drag reduction. As accurately modeling flow behavior with drag reduction is always complex, and since drag reducing additives or solid particles are mixed in fluids, this book covers these complex phenomena in a concise, but comprehensive manner.
Adaptive Learning Methods for Nonlinear System Modeling by Danilo Comminiello and José Príncipe
This book presents some of the recent advances in adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modelling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity introduced by the unknown system.
