The book presents twelve state of the art contributions in the field of numerical modeling of materials subjected to large strain, high strain rates, large pressure and high stress triaxialities, organized into two sections. The first part is focused on high strain rate-high pressures such as those occurring in impact dynamics and shock compression related phenomena, dealing with material response identification, advanced modeling incorporating microstructure and damage, stress waves propagation in solids and structures response under impact. The latter part is focused on large strain-low strain rates applications such as those occurring in technological material processing, dealing with microstructure and texture evolution, material response at elevated temperatures, structural behavior under large strain and multi axial state of stress.

This book provides a fresh approach to reliability theory, an area that has gained increasing relevance in fields from statistics and engineering to demography and insurance. Its innovative use of quantile functions gives an analysis of lifetime data that is generally simpler, more robust, and more accurate than the traditional methods, and opens the door for further research in a wide variety of fields involving statistical analysis. In addition, the book can be used to good effect in the classroom as a text for advanced undergraduate and graduate courses in Reliability and Statistics.

A groundbreaking text and professional resource on natural attenuation technology
Natural attenuation is rapidly becoming a widely used approach to manage groundwater and soil contamination by hazardous substances in petroleum-product releases and leachate from hazardous waste sites and landfills. This book provides, under one cover, the current methodologies needed by groundwater scientists and engineers in their efforts to evaluate subsurface contamination problems, to estimate risk to human health and ecosystems through mathematical models, and to design and formulate appropriate remediation strategies.
Incorporating the authors' extensive backgrounds as educators, researchers, and consultants in environmental biotechnology and hydrogeology, the text emphasizes new concepts and recent advances in the science, including:
* Quantification of the role of microbes in natural attenuation
* Biodegradation and chemical transformation principles
* Immobilization and phase change
* Biotransformation mechanisms
* Groundwater flow and contaminant transport
* Analytical models for contaminant transport and reaction processes
* Numerical modeling of contaminant transport, transformation, and degradation
Detailed descriptions of fundamental processes, characterization approaches, and analytical and numerical methods tied to relevant real-world applications make Bioremediation and Natural Attenuation: Process Fundamentals and Mathematical Models both a timely course text in hydrogeology and environmental engineering and a valuable reference for anyone in the groundwater or risk assessment professions.

This book presents lecture notes from the XVI 'Jacques-Louis Lions' Spanish-French School on Numerical Simulation in Physics and Engineering, held in Pamplona (Navarra, Spain) in September 2014. The subjects covered include: numerical analysis of isogeometric methods, convolution quadrature for wave simulations, mathematical methods in image processing and computer vision, modeling and optimization techniques in food processes, bio-processes and bio-systems, and GPU computing for numerical simulation. The book is highly recommended to graduate students in Engineering or Science who want to focus on numerical simulation, either as a research topic or in the field of industrial applications. It can also benefit senior researchers and technicians working in industry who are interested in the use of state-of-the-art numerical techniques in the fields addressed here. Moreover, the book can be used as a textbook for master courses in Mathematics, Physics, or Engineering.

Dimensional metrology is an essential part of modern manufacturing technologies, but the basic theories and measurement methods are no longer sufficient for today's digitized systems. The information exchange between the software components of a dimensional metrology system not only costs a great deal of money, but also causes the entire system to lose data integrity.

"Information Modeling for Interoperable Dimensional Metrology" analyzes interoperability issues in dimensional metrology systems and describes information modeling techniques. It discusses new approaches and data models for solving interoperability problems, as well as introducing process activities, existing and emerging data models, and the key technologies of dimensional metrology systems.

Written for researchers in industry and academia, as well as advanced undergraduate and postgraduate students, this book gives both an overview and an in-depth understanding of complete dimensional metrology systems. By covering in detail the theory and main content, techniques, and methods used in dimensional metrology systems, "Information Modeling for Interoperable Dimensional Metrology" enables readers to solve real-world dimensional measurement problems in modern dimensional metrology practices. "

This book presents recent research on Advanced Computing in Industrial Mathematics, which is one of the most prominent interdisciplinary areas and combines mathematics, computer science, scientific computations, engineering, physics, chemistry, medicine, etc. Further, the book presents the tools of Industrial Mathematics, which are based on mathematical models, and the corresponding computer codes, which are used to perform virtual experiments to obtain new data or to better understand the existing experimental results. The book gathers the peer-reviewed papers presented during the 10th Annual Meeting of the Bulgarian Section of SIAM (BGSIAM) from December 21 to 22, 2015 in Sofia, Bulgaria.

Computer simulation and mathematical modelling are the most important approaches in the quantitative analysis of the diffusive processes fundamental to many physical, chemical, biological, and geological systems.

This comprehensive text/reference addresses the key issues in the "Modelling and Simulation of Diffusive Processes" from a broad range of different application areas. Applying an holistic approach, the book presents illuminating viewpoints drawn from an international selection of experts across a wide spectrum of disciplines, from computer science, mathematics and engineering, to natural resource management, environmental sciences, applied geo-sciences, agricultural sciences, and theoretical medicine.

Topics and features: presents a detailed introduction to diffusive processes and modelling; discusses diffusion and molecular transport in living cells, and suspended sediment in open channels; examines the mathematical modelling of peristaltic transport of nanofluids, and isotachophoretic separation of ionic samples in microfluidics; reviews thermal characterization of non-homogeneous media, and scale-dependent porous dispersion resulting from velocity fluctuations; describes the modelling of nitrogen fate and transport at the sediment-water interface, and groundwater flow in unconfined aquifers; investigates two-dimensional solute transport from a varying pulse type point source, and futile cycles in metabolic flux modelling; studies contaminant concentration prediction along unsteady groundwater flow, and modelling synovial fluid flow in human joints; explores the modelling of soil organic carbon, and crop growth simulation.

This interdisciplinary volume will be invaluable to researchers, lecturers and graduate students from such diverse fields as computer science, mathematics, hydrology, agriculture and biology.

This book gathers contributions presented at the 9th Workshop on Cyclostationary Systems and Their Applications, held in Grodek nad Dunajcem, Poland in February 2016. It includes both theory-oriented and practice-oriented chapters. The former focus on heavy-tailed time series and processes, PAR models, rational spectra for PARMA processes, covariance invariant analysis, change point problems, and subsampling for time series, as well as the fraction-of-time approach, GARMA models and weak dependence. In turn, the latter report on case studies of various mechanical systems, and on stochastic and statistical methods, especially in the context of damage detection. The book provides students, researchers and professionals with a timely guide to cyclostationary systems, nonstationary processes and relevant engineering applications.

This volume contains the invited papers presented at the 9th International C- ference "Dynamical Systems - Theory and Applications" held in ?od ' z, ' Poland, December 17-20, 2007 dealing with nonlinear dynamical systems. The conf- encegatheredanumerousgroupofscientistsandengineers,whodealwithwidely understoodproblemsofdynamicsmetalsoinengineeringanddailylife. Organizationof the conferencewould nothavebeen possiblewithouta great effortofthestaffoftheDepartmentofAutomaticsandBiomechanicsoftheTech- calUniversityof?od ' z. ' Thepatronageovertheconferencehasbeentakenbythef- lowingscienti?cinstitutions:MechanicsandMachineDynamicsCommitteesofthe PolishAcademyofSciences,PolishSocietyofTheoreticalandAppliedMech- ics,PolishAssociationforComputationalMechanics,andTechnicalCommitteeof NonlinearOscillationsofIFToMM. The ?nancial support has been given by the Department of Education at the ?'odz' City Hall, Ministry of National Education and the Polish Association for ComputationalMechanics. We welcomednearly100personsfrom13countriesallovertheworld.They decidedto share the results of their researchandmanyyears of experiencein a disciplineofdynamicalsystemsbysubmittingmanyinterestingpapers. TheScienti?cCommitteeincludesthefollowingmembers:IgorV.Andrianov- Aachen;JanAwrejcewicz -?od ' z; ' Jose M. Balthazar- Rio Claro;Denis Bla- more- Newark; Iliya Blekhman - Sankt Petersburg;Roman Bogacz - Warsaw; TadeuszBurczyns ' ki-Gliwice;DickvanCampen-Eindhoven;Czes?awCempel- Poznan';LotharGaul- Stuttgart;Jozef ' Giergiel-Cracow;Katica Hedrih-Nis; ? Janusz Kowal - Cracow; Vadim A. Krysko - Saratov; W?odzimierz Kurnik - Warsaw; Claude-Henri Lamarque - Lyon; Nuno M. Maia - Lisbon; Leonid I.

"Fixed-Point Algorithms for Inverse Problems in Science and Engineering" presents some of the most recent work from top-notch researchers studying projection and other first-order fixed-point algorithms in several areas of mathematics and the applied sciences. The material presented provides a survey of the state-of-the-art theory and practice in fixed-point algorithms, identifying emerging problems driven by applications, and discussing new approaches for solving these problems.

This book incorporates diverse perspectives from broad-ranging areas of research including, variational analysis, numerical linear algebra, biotechnology, materials science, computational solid-state physics, and chemistry.

Topics presented include:

Theory of Fixed-point algorithms: convex analysis, convex optimization, subdifferential calculus, nonsmooth analysis, proximal point methods, projection methods, resolvent and related fixed-point theoretic methods, and monotone operator theory.

Numerical analysis of fixed-point algorithms: choice of step lengths, of weights, of blocks for block-iterative and parallel methods, and of relaxation parameters; regularization of ill-posed problems; numerical comparison of various methods.

Areas of Applications: engineering (image and signal reconstruction and decompression problems), computer tomography and radiation treatment planning (convex feasibility problems), astronomy (adaptive optics), crystallography (molecular structure reconstruction), computational chemistry (molecular structure simulation) and other areas.

Because of the variety of applications presented, this book can easily serve as a basis for new and innovated research and collaboration.

The main objective of Credit Risk: Modeling, Valuation and Hedging is to present a comprehensive survey of the past developments in the area of credit risk research, as well as to put forth the most recent advancements in this field. An important aspect of this text is that it attempts to bridge the gap between the mathematical theory of credit risk and the financial practice, which serves as the motivation for the mathematical modeling studied in the book. Mathematical developments are presented in a thorough manner and cover the structural (value-of-the-firm) and the reduced (intensity-based) approaches to credit risk modeling, applied both to single and to multiple defaults. In particular, the book offers a detailed study of various arbitrage-free models of defaultable term structures with several rating grades.

This book contributes to an understanding of how bifurcation theory adapts to the analysis of economic geography. It is easily accessible not only to mathematicians and economists, but also to upper-level undergraduate and graduate students who are interested in nonlinear mathematics. The self-organization of hexagonal agglomeration patterns of industrial regions was first predicted by the central place theory in economic geography based on investigations of southern Germany. The emergence of hexagonal agglomeration in economic geography models was envisaged by Krugman. In this book, after a brief introduction of central place theory and new economic geography, the missing link between them is discovered by elucidating the mechanism of the evolution of bifurcating hexagonal patterns. Pattern formation by such bifurcation is a well-studied topic in nonlinear mathematics, and group-theoretic bifurcation analysis is a well-developed theoretical tool. A finite hexagonal lattice is used to express uniformly distributed places, and the symmetry of this lattice is expressed by a finite group. Several mathematical methodologies indispensable for tackling the present problem are gathered in a self-contained manner. The existence of hexagonal distributions is verified by group-theoretic bifurcation analysis, first by applying the so-called equivariant branching lemma and next by solving the bifurcation equation. This book offers a complete guide for the application of group-theoretic bifurcation analysis to economic agglomeration on the hexagonal lattice.

Progress in today's high-technology industries is strongly associated with the development of new mathematical tools. A typical illustration of this partnership is the mathematical modelling and numerical simulation of electric circuits and semiconductor devices. At the second Oberwolfach conference devoted to this important and timely field, scientists from around the world, mainly applied mathematicians and electrical engineers from industry and universities, presented their new results. Their contributions, forming the body of this work, cover electric circuit simulation, device simulation and process simulation. Discussions on experiences with standard software packages and improvements of such packages are included. In the semiconductor area special lectures were given on new modelling approaches, numerical techniques and existence and uniqueness results. In this connection, mention is made, for example, of mixed finite element methods, an extension of the Baliga-Patankar technique for a three dimensional simulation, and the connection between semiconductor equations and the Boltzmann equations.

This thesis has two parts, each based on an application of the renormalization-group (RG). The first part is an analysis of the d-dimensional Coulomb gas. The goal was to determine if the Wilson RG could provide input into particle-in-cell simulations in plasma physics, which are the main family of simulation methods used in this field. The role of the RG was to identify the effect of coarse-graining on the coupling constants as a function of the cut-offs. The RG calculation reproduced established results, but in a more concise form, and showed the effect of the cut-offs on the Debye screening length.
The main part of the thesis is the application of the dynamic RG to turbulence in magnetohydrodynamics. After transformation to Elsasser variables, which is a symmetrisation of the original equations, the solution is presented as a functional integral, which includes stirring forces, their conjugates and functional Jacobian. The coarse-graining of the functional integral is represented as a diagrammatic expansion, followed by rescaling, and casting the results into differential equations for the analysis of RG trajectories. Detailed comparisons are made with the Navier-Stokes limit and with previous calculations for MHD.

This is a thoroughly revised and enlarged second edition that presents the main results of descriptive complexity theory, that is, the connections between axiomatizability of classes of finite structures and their complexity with respect to time and space bounds. The logics that are important in this context include fixed-point logics, transitive closure logics, and also certain infinitary languages; their model theory is studied in full detail. The book is written in such a way that the respective parts on model theory and descriptive complexity theory may be read independently.

Practical Goal Programming is intended to allow academics and practitioners to be able to build effective goal programming models, to detail the current state of the art, and to lay the foundation for its future development and continued application to new and varied fields. Suitable as both a text and reference, its nine chapters first provide a brief history, fundamental definitions, and underlying philosophies, and then detail the goal programming variants and define them algebraically. Chapter 3 details the step-by-step formulation of the basic goal programming model, and Chapter 4 explores more advanced modeling issues and highlights some recently proposed extensions.

Chapter 5 then details the solution methodologies of goal programming, concentrating on computerized solution by the Excel Solver and LINGO packages for each of the three main variants, and includes a discussion of the viability of the use of specialized goal programming packages. Chapter 6 discusses the linkages between Pareto Efficiency and goal programming. Chapters 3 to 6 are supported by a set of ten exercises, and an Excel spreadsheet giving the basic solution of each example is available at an accompanying website.

Chapter 7 details the current state of the art in terms of the integration of goal programming with other techniques, and the text concludes with two case studies which were chosen to demonstrate the application of goal programming in practice and to illustrate the principles developed in Chapters 1 to 7. Chapter 8 details an application in healthcare, and Chapter 9 describes applications in portfolio selection.

The Model-Free Prediction Principle expounded upon in this monograph is based on the simple notion of transforming a complex dataset to one that is easier to work with, e.g., i.i.d. or Gaussian. As such, it restores the emphasis on observable quantities, i.e., current and future data, as opposed to unobservable model parameters and estimates thereof, and yields optimal predictors in diverse settings such as regression and time series. Furthermore, the Model-Free Bootstrap takes us beyond point prediction in order to construct frequentist prediction intervals without resort to unrealistic assumptions such as normality. Prediction has been traditionally approached via a model-based paradigm, i.e., (a) fit a model to the data at hand, and (b) use the fitted model to extrapolate/predict future data. Due to both mathematical and computational constraints, 20th century statistical practice focused mostly on parametric models. Fortunately, with the advent of widely accessible powerful computing in the late 1970s, computer-intensive methods such as the bootstrap and cross-validation freed practitioners from the limitations of parametric models, and paved the way towards the `big data' era of the 21st century. Nonetheless, there is a further step one may take, i.e., going beyond even nonparametric models; this is where the Model-Free Prediction Principle is useful. Interestingly, being able to predict a response variable Y associated with a regressor variable X taking on any possible value seems to inadvertently also achieve the main goal of modeling, i.e., trying to describe how Y depends on X. Hence, as prediction can be treated as a by-product of model-fitting, key estimation problems can be addressed as a by-product of being able to perform prediction. In other words, a practitioner can use Model-Free Prediction ideas in order to additionally obtain point estimates and confidence intervals for relevant parameters leading to an alternative, transformation-based approach to statistical inference.

This book contains a selection of the best theoretical and applied papers from the inaugural International Choice Modelling Conference. The conference was organised by the Institute for Transport Studies at the University of Leeds and held in Harrogate, North Yorkshire on 30 March to 1 April 2009. The conference brought together leading researchers and practitioners from across the many different areas in which choice modelling is a key technique for understanding behaviour and evaluating policy. The diversity of the field was reflected in presentations by both academics and practitioners, coming from six continents and a variety of fields including transport and economics. Key contributions include papers from Professor Daniel McFadden, from the University of California, Berkeley - Nobel Prize laureate in Economics and chief architect of random utility modelling. The conference also included keynote presentations by five other leading choice modellers, namely Professor Moshe Ben-Akiva, Professor Chandra Bhat, Professor Michel Bierlaire, Professor David Hensher, and Professor Riccardo Scarpa.

This thesis describes a new connection between algebraic geometry, topology, number theory and quantum field theory. It offers a pedagogical introduction to algebraic topology, allowing readers to rapidly develop basic skills, and it also presents original ideas to inspire new research in the quest for dualities. Its ambitious goal is to construct a method based on the universal coefficient theorem for identifying new dualities connecting different domains of quantum field theory. This thesis opens a new area of research in the domain of non-perturbative physics-one in which the use of different coefficient structures in (co)homology may lead to previously unknown connections between different regimes of quantum field theories. The origin of dualities is an issue in fundamental physics that continues to puzzle the research community with unexpected results like the AdS/CFT duality or the ER-EPR conjecture. This thesis analyzes these observations from a novel and original point of view, mainly based on a fundamental connection between number theory and topology. Beyond its scientific qualities, it also offers a pedagogical introduction to advanced mathematics and its connection with physics. This makes it a valuable resource for students in mathematical physics and researchers wanting to gain insights into (co)homology theories with coefficients or the way in which Grothendieck's work may be connected with physics.

The topology optimization method solves the basic engineering problem of distributing a limited amount of material in a design space. The first edition of this book has become the standard text on optimal design, which is concerned with the optimization of structural topology, shape and material. This edition has been substantially revised and updated to reflect progress made in modelling and computational procedures. It also encompasses a comprehensive and unified description of the state of the art of the so-called material distribution method, based on the use of mathematical programming and finite elements. Applications treated include not only structures but also MEMS and materials.

This collection of selected papers presented at the 11th International Conference on Scientific Computing in Electrical Engineering (SCEE), held in St. Wolfgang, Austria, in 2016, showcases the state of the art in SCEE. The aim of the SCEE 2016 conference was to bring together scientists from academia and industry, mathematicians, electrical engineers, computer scientists, and physicists, and to promote intensive discussions on industrially relevant mathematical problems, with an emphasis on the modeling and numerical simulation of electronic circuits and devices, electromagnetic fields, and coupled problems. The focus in methodology was on model order reduction and uncertainty quantification. This extensive reference work is divided into six parts: Computational Electromagnetics, Circuit and Device Modeling and Simulation, Coupled Problems and Multi-Scale Approaches in Space and Time, Mathematical and Computational Methods Including Uncertainty Quantification, Model Order Reduction, and Industrial Applications. Each part starts with a general introduction, followed by the respective contributions. This book will appeal to mathematicians and electrical engineers. Further, it introduces algorithm and program developers to recent advances in the other fields, while industry experts will be introduced to new programming tools and mathematical methods.

Over the past decade there has been an increasing demand for suitable material in the area of mathematical modelling as applied to science, engineering, business and management. Recent developments in computer technology and related software have provided the necessary tools of increasing power and sophistication which have significant implications for the use and role of mathematical modelling in the above disciplines. In the past, traditional methods have relied heavily on expensive experimentation and the building of scaled models, but now a more flexible and cost effective approach is available through greater use of mathematical modelling and computer simulation. In particular, developments in computer algebra, symbolic manipulation packages and user friendly software packages for large scale problems, all have important implications in both the teaching of mathematical modelling and, more importantly, its use in the solution of real world problems. Many textbooks have been published which cover the art and techniques of modelling as well as specific mathematical modelling techniques in specialist areas within science and business. In most of these books the mathematical material tends to be rather tailor made to fit in with a one or two semester course for teaching students at the undergraduate or postgraduate level, usually the former. This textbook is quite different in that it is intended to build on and enhance students' modelling skills using a combination of case studies and projects.

This textbook has been developed from the lecture notes for a one-semester course on stochastic modelling. It reviews the basics of probability theory and then covers the following topics: Markov chains, Markov decision processes, jump Markov processes, elements of queueing theory, basic renewal theory, elements of time series and simulation. Rigorous proofs are often replaced with sketches of arguments -- with indications as to why a particular result holds, and also how it is connected with other results -- and illustrated by examples. Wherever possible, the book includes references to more specialised texts containing both proofs and more advanced material related to the topics covered.

During its 2004 meeting in Warsaw the General Assembly of the International Union of Theoretical and Applied Mechanics (IUTAM) decided to support a proposal of the Georgian National Committee to hold in Tbilisi (Georgia), on April 23-27, 2007, the IUTAM Symposium on the Relation of Shell, Plate, Beam, and 3D Models, dedicated to the Centenary of Ilia Vekua. The sci- ti?c organization was entrusted to an international committee consisting of Philipppe G. Ciarlet (Hong Kong), the late Anatoly Gerasimovich Gorshkov (Russia),JornHansen(Canada),GeorgeV.Jaiani(Georgia,Chairman),Re- hold Kienzler (Germany), Herbert A. Mang (Austria), Paolo Podio-Guidugli (Italy), and Gangan Prathap (India). The main topics to be included in the scienti?c programme were c- sen to be: hierarchical, re?ned mathematical and technical models of shells, plates, and beams; relation of 2D and 1D models to 3D linear, non-linear and physical models; junction problems. The main aim of the symposium was to thoroughly discuss the relations of shell, plate, and beam models to the 3D physicalmodels.Inparticular,peculiaritiesofcuspedshells,plates,andbeams were to be emphasized and special attention paid to junction, multibody and ? uid-elastic shell (plate, beam) interaction problems, and their applications. The expected contributions of the invited participants were anticipated to be theoretical, practical, and numerical in character.

With the use of ecological models, managers and decision makers can make sure that the ecological systems affected by their decisions are accurately represented. Unfortunately, the most relevant ecological science and modeling techniques are often not used because managers are not familiar with them or find them inappropriate for their circumstances. The authors of this volume hope to close the gap between the state of the art in ecological modeling and the state of the practice in the use of models as decision-making tools. It will serve as a readable introduction to modeling for people involved in resource management and will also review specific applications of interest to more experienced modelers. The first chapters detail several successful uses of ecological models in resource management. There are then five pairs of chapters addressing important issues in ecological modeling, including barriers to the use of modeling in decision making, evolving approaches in the field, effective use of data, the toolkit approach to management, and the various scientific and technological investments required for productive modeling. Ecologists and other scientists will learn how best to focus their research for practical, real-world applications, and resource managers and other practitioners will learn the most appropriate methods of understanding dynamic processes and making projections about the implications of their decisions.