This book provides an in-depth analysis of investment problems pertaining to electric energy infrastructure, including both generation and transmission facilities. The analysis encompasses decision-making tools for expansion planning, reinforcement, and the selection and timing of investment options. In this regard, the book provides an up-to-date description of analytical tools to address challenging investment questions such as: How can we expand and/or reinforce our aging electricity transmission infrastructure? How can we expand the transmission network of a given region to integrate significant amounts of renewable generation? How can we expand generation facilities to achieve a low-carbon electricity production system? How can we expand the generation system while ensuring appropriate levels of flexibility to accommodate both demand-related and production-related uncertainties? How can we choose among alternative production facilities? What is the right time to invest in a given production or transmission facility? Written in a tutorial style and modular format, the book includes a wealth of illustrative examples to facilitate comprehension. It is intended for advanced undergraduate and graduate students in the fields of electric energy systems, operations research, management science, and economics. Practitioners in the electric energy sector will also benefit from the concepts and techniques presented here.

This book is intended for students of computational systems biology with only a limited background in mathematics. Typical books on systems biology merely mention algorithmic approaches, but without offering a deeper understanding. On the other hand, mathematical books are typically unreadable for computational biologists. The authors of the present book have worked hard to fill this gap. The result is not a book on systems biology, but on computational methods in systems biology. This book originated from courses taught by the authors at Freie Universitat Berlin. The guiding idea of the courses was to convey those mathematical insights that are indispensable for systems biology, teaching the necessary mathematical prerequisites by means of many illustrative examples and without any theorems. The three chapters cover the mathematical modelling of biochemical and physiological processes, numerical simulation of the dynamics of biological networks and identification of model parameters by means of comparisons with real data. Throughout the text, the strengths and weaknesses of numerical algorithms with respect to various systems biological issues are discussed. Web addresses for downloading the corresponding software are also included.

Managing today's lands is becoming an increasingly difficult task. Complex ecological interactions across multiple spatiotemporal scales create diverse landscape responses to management actions that are often novel, counter-intuitive and unexpected. To make matters worse, exotic invasions, human land use, and global climate change complicate this complexity and make past observational ecological studies limited in application to the future. Natural resource professionals can no longer rely on empirical data to analyze alternative actions in a world that is rapidly changing with few historical analogs. New tools are needed to synthesize the high complexity in ecosystem dynamics into useful applications for land management. Some of the best new tools available for this task are ecological and landscape simulation models. However, many land management professionals and scientists have little expertise in simulation modeling, and the costs of training these people will probably be exorbitantly high because most ecosystem and landscape models are exceptionally complicated and difficult to understand and use for local applications. This book was written to provide natural resource professionals with the rudimentary knowledge needed to properly use ecological models and then to interpret their results. It is based on the lessons learned from a career spent modeling ecological systems. It is intended as a reference for novice modelers to learn how to correctly employ ecosystem landscape models in natural resource management applications and to understand subsequent modeling results.

Modeling and computing is becoming an essential part of the analysis and design of an engineered system. This is also true of "geotechnical systems", such as soil foundations, earth dams and other soil-structure systems. The general goal of modeling and computing is to predict and understand the behaviour of the system subjected to a variety of possible conditions/scenarios (with respect to both external stimuli and system parameters), which provides the basis for a rational design of the system. The essence of this is to predict the response of the system to a set of external forces. The modelling and computing essentially involve the following three phases: (a) Idealization of the actual physical problem, (b) Formulation of a mathematical model represented by a set of equations governing the response of the system, and (c) Solution of the governing equations (often requiring numerical methods) and graphical representation of the numerical results. This book will introduce these phases. MATLAB (R) codes and MAPLE (R) worksheets are available for those who have bought the book. Please contact the author at [email protected] or [email protected]. Kindly provide the invoice number and date of purchase.

Modeling, in the past 60 years, has been constantly evolving and has revolutionized the industrial sector. Its continuous development will still have profound impact in the upcoming future. For big or small companies, modeling is a tool which brings technical improvement and profitability. What is modeling? What are the benefits and limits? What are the best practices, technical and non-technical, to apply? The objective of this book is to bring answers to these questions in a synthetic and transversal manner, so that engineers, managers and directors can see future challenges not as a threat, but as an opportunity. Features: Transversal and synthetic view on modeling, written in a clear and pragmatic way Technical best practices to build/ develop a model Non-technical best practices to efficiently deploy modeling in companies All best practices discussed in the book have been truly already implemented in past situations Theory is illustrated in a case study from the beginning to the end of the book

From mulching to greenhouses, the air space between the cover and the soil surface is the key to the classification of climates under cover. The same mechanism governs environments produced by the various covers. This book describes and analyses all the different environments from mulching to greenhouses. The relationship between plants and environment is another important topic in the book. Stress is placed on the link between quantitative phenomena and qualitative analyses. Most phenomena involved are nonlinear and non-steady-state. An approach called System Dynamics is used, and simulation models developed in the simulation language CSMP are fully used. The subjects covered are of relevance to graduate students, to scientists and researchers in agriculture and biological sciences and, of course, to agricultural organizations in both the developing and developed countries.

Stochastic hydrogeology, which emerged as a research area in the late 1970s, involves the study of subsurface, geological variability on flow and transport processes and the interpretation of observations using existing theories. Lacking, however, has been a rational framework for modeling the impact of the processes that take place in heterogeneous media and for incorporating it in predictions and decision-making. This book provides this important framework. It covers the fundamental and practical aspects of stochastic hydrogeology, coupling theoretical aspects with examples, case studies, and guidelines for applications.

Focuses on the assumptions underlying the algorithms rather than their statistical properties Presents cutting-edge analysis of factor models and finite mixture models. Uses a hands-on approach to examine the assumptions made by the models and when the models fail to estimate accurately Utilizes interesting real-world data sets that can be used to analyze important microeconomic problems Introduces R programming concepts throughout the book. Includes appendices that discuss many of the concepts introduced in the book, as well as measures of uncertainty in microeconometrics.

This book teaches you all necessary (problem-independent) tools and techniques needed to implement and perform sophisticated scientific numerical simulations. Thus, it is suited for undergraduate and graduate students who want to become experts in computer simulations in Physics, Chemistry, Biology, Engineering, Computer Science and other fields.

This book teaches you all necessary (problem-independent) tools and techniques needed to implement and perform sophisticated scientific numerical simulations. Thus, it is suited for undergraduate and graduate students who want to become experts in computer simulations in Physics, Chemistry, Biology, Engineering, Computer Science and other fields.

The new edition of 3D Game Textures: Create Professional Game Art Using Photoshop features the most up-to-date techniques that allow you to create your own unique textures, shaders, and materials. Revised to take new technology into account, it is an ideal hands-on resource for creating online worlds, simulations, web-based applications, and architectural visualization projects. Continuing the practical, no-nonsense approach of its predecessors, the fourth edition shows you how to advance your digital art skills with textures and shaders by exploring their interactions in single objects or entire scenes. It contains expanded coverage of shader nodes, and the companion website-www.lukeahearn.com/textures-has been updated to include video tutorials as well as updated sample textures, shaders, materials, actions, brushes, and all of the art from the book.

The second edition of Building Energy Simulation includes studies of various components and systems of buildings and their effect on energy consumption, with the help of DesignBuilderTM, a front-end for the EnergyPlus simulation engine, supported by examples and exercises. The book employs a "learning by doing" methodology. It explains simulation-input parameters and how-to-do analysis of the simulation output, in the process explaining building physics and energy simulation. Divided into three sections, it covers the fundamentals of energy simulation followed by advanced topics in energy simulation and simulation for compliance with building codes and detailed case studies for comprehensive building energy simulation. Features: Focuses on learning building energy simulation while being interactive through examples and exercises. Explains the building physics and the science behind the energy performance of buildings. Encourages an integrated design approach by explaining the interactions between various building systems and their effect on energy performance of building. Discusses a how-to model for building energy code compliance including three projects to practice whole building simulation. Provides hands-on training of building energy simulation tools: DesignBuilder (TM) and EnergyPlus. Includes practical projects problems, appendices and CAD files in the e-resources section. Building Energy Simulation is intended for students and researchers in building energy courses, energy simulation professionals, and architects.

Principles of Synthetic Aperture Radar Imaging: A System Simulation Approach demonstrates the use of image simulation for SAR. It covers the various applications of SAR (including feature extraction, target classification, and change detection), provides a complete understanding of SAR principles, and illustrates the complete chain of a SAR operation. The book places special emphasis on a ground-based SAR, but also explains space and air-borne systems. It contains chapters on signal speckle, radar-signal models, sensor-trajectory models, SAR-image focusing, platform-motion compensation, and microwave-scattering from random media. While discussing SAR image focusing and motion compensation, it presents processing algorithms and applications that feature extraction, target classification, and change detection. It also provides samples of simulation on various scenarios, and includes simulation flowcharts and results that are detailed throughout the book. Introducing SAR imaging from a systems point of view, the author: Considers the recent development of MIMO SAR technology Includes selected GPU implementation Provides a numerical analysis of system parameters (including platforms, sensor, and image focusing, and their influence) Explores wave-target interactions, signal transmission and reception, image formation, motion compensation Covers all platform motion compensation and error analysis, and their impact on final image radiometric and geometric quality Describes a ground-based SFMCW system Principles of Synthetic Aperture Radar Imaging: A System Simulation Approach is dedicated to the use, study, and development of SAR systems. The book focuses on image formation or focusing, treats platform motion and image focusing, and is suitable for students, radar engineers, and micr

Geospatial information modeling and mapping has become an important tool for the investigation and management of natural resources at the landscape scale. Spatial Statistics: GeoSpatial Information Modeling and Thematic Mapping reviews the types and applications of geospatial information data, such as remote sensing, geographic information systems (GIS), and GPS as well as their integration into landscape-scale geospatial statistical models and maps. The book explores how to extract information from remotely sensed imagery, GIS, and GPS, and how to combine this with field data-vegetation, soil, and environmental-to produce a spatial model that can be reconstructed and displayed using GIS software. Readers learn the requirements and limitations of each geospatial modeling and mapping tool. Case studies with real-life examples illustrate important applications of the models. Topics covered in this book include: An overview of the geospatial information sciences and technology and spatial statistics Sampling methods and applications, including probability sampling and nonrandom sampling, and issues to consider in sampling and plot design Fine and coarse scale variability Spatial sampling schemes and spatial pattern Linear and spatial correlation statistics, including Moran's I, Geary's C, cross-correlation statistics, and inverse distance weighting Geospatial statistics analysis using stepwise regression, ordinary least squares (OLS), variogram, kriging, spatial auto-regression, binary classification trees, cokriging, and geospatial models for presence and absence data How to use R statistical software to work on statistical analyses and case studies, and to develop a geospatial statistical model

Concrete-filled stainless steel tubular (CFSST) columns are increasingly used in modern composite construction due to their high strength, high ductility, high corrosion resistance, high durability and aesthetics and ease of maintenance. Thin-walled CFSST columns are characterized by the different strain-hardening behavior of stainless steel in tension and in compression, local buckling of stainless steel tubes and concrete confinement. Design codes and numerical models often overestimate or underestimate the ultimate strengths of CFSST columns. This book presents accurate and efficient computational models for the nonlinear inelastic analysis and design of CFSST short and slender columns under axial load and biaxial bending. The effects of different strain-hardening characteristics of stainless steel in tension and in compression, progressive local and post-local buckling of stainless steel tubes and concrete confinement are taken into account in the computational models. The numerical models simulate the axial load-strain behavior, moment-curvature curves, axial load-deflection responses and axial load-moment strength interaction diagrams of CFSST columns. The book describes the mathematical formulations, computational procedures and model verifications for circular and rectangular CFSST short and slender columns. The behavior of CFSST columns under various loading conditions is demonstrated by numerous numerical examples. This book is written for practising structural and civil engineers, academic researchers and graduate students in civil engineering who are interested in the latest computational techniques and design methods for CFSST columns.

Multi-scale and multi-physics modeling is useful and important for all areas in engineering and sciences. Particle Methods for Multi-Scale and Multi-Physics systematically addresses some major particle methods for modeling multi-scale and multi-physical problems in engineering and sciences. It contains different particle methods from atomistic scales to continuum scales, with emphasis on molecular dynamics (MD), dissipative particle dynamics (DPD) and smoothed particle hydrodynamics (SPH).This book covers the theoretical background, numerical techniques and many interesting applications of the particle methods discussed in this text, especially in: micro-fluidics and bio-fluidics (e.g., micro drop dynamics, movement and suspension of macro-molecules, cell deformation and migration); environmental and geophysical flows (e.g., saturated and unsaturated flows in porous media and fractures); and free surface flows with possible interacting solid objects (e.g., wave impact, liquid sloshing, water entry and exit, oil spill and boom movement). The presented methodologies, techniques and example applications will benefit students, researchers and professionals in computational engineering and sciences.

When I attended college we studied vacuum tubes in our junior year. At that time an average radio had ?ve vacuum tubes and better ones even seven. Then transistors appeared in 1960s. A good radio was judged to be one with more thententransistors. Latergoodradioshad15-20transistors and after that everyone stopped counting transistors. Today modern processors runing personal computers have over 10milliontransistorsandmoremillionswillbeaddedevery year. The difference between 20 and 20M is in complexity, methodology and business models. Designs with 20 tr- sistors are easily generated by design engineers without any tools, whilst designs with 20M transistors can not be done by humans in reasonable time without the help of Prof. Dr. Gajski demonstrates the Y-chart automation. This difference in complexity introduced a paradigm shift which required sophisticated methods and tools, and introduced design automation into design practice. By the decomposition of the design process into many tasks and abstraction levels the methodology of designing chips or systems has also evolved. Similarly, the business model has changed from vertical integration, in which one company did all the tasks from product speci?cation to manufacturing, to globally distributed, client server production in which most of the design and manufacturing tasks are outsourced.

This hard-hitting research report presents a rigorous critique of the most widely used trade models based on computable general equilibrium (or CGE) models. The authors present concise analytical arguments explaining the fundamental weaknesses of typical CGE models. They show that these models tend to make unrealistic assumptions about the macro-economy and do not allow an accurate estimation of the welfare gains that trade liberalisation is supposed to induce. The report appeals for honest simulation strategies showing a variety of possible outcomes, which would enable policy-makers to assess the different scenarios for themselves.

This book is open access under a CC BY 4.0 license. This book summarizes work being pursued in the context of the CIPRNet (Critical Infrastructure Preparedness and Resilience Research Network) research project, co-funded by the European Union under the Seventh Framework Programme (FP7). The project is intended to provide concrete and on-going support to the Critical Infrastructure Protection (CIP) research communities, enhancing their preparedness for CI-related emergencies, while also providing expertise and technologies for other stakeholders to promote their understanding and mitigation of the consequences of CI disruptions, leading to enhanced resilience. The book collects the tutorial material developed by the authors for several courses on the modelling, simulation and analysis of CIs, representing extensive and integrated CIP expertise. It will help CI stakeholders, CI operators and civil protection authorities understand the complex system of CIs, and help them adapt to these changes and threats in order to be as prepared as possible for mitigating emergencies and crises affecting or arising from CIs.

Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language. The book uses the Python programming language interpreter and several packages from the huge Python Library that improve the performance of numerical computing, such as the Numpy and Scipy modules. The Python source code and data files are available on the author's website. The book's five sections present: An overview of problem solving and simple Python programs, introducing the basic models and techniques for designing and implementing problem solutions, independent of software and hardware tools Programming principles with the Python programming language, covering basic programming concepts, data definitions, programming structures with flowcharts and pseudo-code, solving problems, and algorithms Python lists, arrays, basic data structures, object orientation, linked lists, recursion, and running programs under Linux Implementation of computational models with Python using Numpy, with examples and case studies The modeling of linear optimization problems, from problem formulation to implementation of computational models This book introduces the principles of computational modeling as well as the approaches of multi- and interdisciplinary computing to beginners in the field. It provides the foundation for more advanced studies in scientific computing, including parallel computing using MPI, grid computing, and other methods and techniques used in high-performance computing.

Data and its technologies now play a large and growing role in humanities research and teaching. This book addresses the needs of humanities scholars who seek deeper expertise in the area of data modeling and representation. The authors, all experts in digital humanities, offer a clear explanation of key technical principles, a grounded discussion of case studies, and an exploration of important theoretical concerns. The book opens with an orientation, giving the reader a history of data modeling in the humanities and a grounding in the technical concepts necessary to understand and engage with the second part of the book. The second part of the book is a wide-ranging exploration of topics central for a deeper understanding of data modeling in digital humanities. Chapters cover data modeling standards and the role they play in shaping digital humanities practice, traditional forms of modeling in the humanities and how they have been transformed by digital approaches, ontologies which seek to anchor meaning in digital humanities resources, and how data models inhabit the other analytical tools used in digital humanities research. It concludes with a glossary chapter that explains specific terms and concepts for data modeling in the digital humanities context. This book is a unique and invaluable resource for teaching and practising data modeling in a digital humanities context.

This textbook offers theoretical and practical knowledge of the finite element method. The book equips readers with the skills required to analyze engineering problems using ANSYS (R), a commercially available FEA program. Revised and updated, this new edition presents the most current ANSYS (R) commands and ANSYS (R) screen shots, as well as modeling steps for each example problem. This self-contained, introductory text minimizes the need for additional reference material by covering both the fundamental topics in finite element methods and advanced topics concerning modeling and analysis. It focuses on the use of ANSYS (R) through both the Graphics User Interface (GUI) and the ANSYS (R) Parametric Design Language (APDL). Extensive examples from a range of engineering disciplines are presented in a straightforward, step-by-step fashion. Key topics include: * An introduction to FEM * Fundamentals and analysis capabilities of ANSYS (R) * Fundamentals of discretization and approximation functions * Modeling techniques and mesh generation in ANSYS (R) * Weighted residuals and minimum potential energy * Development of macro files * Linear structural analysis * Heat transfer and moisture diffusion * Nonlinear structural problems * Advanced subjects such as submodeling, substructuring, interaction with external files, and modification of ANSYS (R)-GUI Electronic supplementary material for using ANSYS (R) can be found at http://link.springer.com/book/10.1007/978-1-4899-7550-8. This convenient online feature, which includes color figures, screen shots and input files for sample problems, allows for regeneration on the reader's own computer. Students, researchers, and practitioners alike will find this an essential guide to predicting and simulating the physical behavior of complex engineering systems."

This book, originally published in 1970, concerns the new technique of computer simulation in psychology at the time. Computer programs described include models of learning, problem-solving, pattern recognition, the use of language, and personality. More general topics are discussed including the evaluation of such models, the relation of the field to cybernetics, and the problem posed by consciousness. Today it can be read and enjoyed in its historical context.

This volume features original contributions and invited review articles on mathematical statistics, statistical simulation and experimental design. The selected peer-reviewed contributions originate from the 8th International Workshop on Simulation held in Vienna in 2015. The book is intended for mathematical statisticians, Ph.D. students and statisticians working in medicine, engineering, pharmacy, psychology, agriculture and other related fields. The International Workshops on Simulation are devoted to statistical techniques in stochastic simulation, data collection, design of scientific experiments and studies representing broad areas of interest. The first 6 workshops took place in St. Petersburg, Russia, in 1994 - 2009 and the 7th workshop was held in Rimini, Italy, in 2013.

The SISDEP 93 conference proceedings present outstanding research and development results in the area of numerical process and device simulation. The miniaturization of today's semiconductor devices, the usage of new materials and advanced process steps in the development of new semiconductor technologies suggests the design of new computer programs. This trend towards more complex structures and increasingly sophisticated processes demands advanced simulators, such as fully three-dimensional tools for almost arbitrarily complicated geometries. With the increasing need for better models and improved understanding of physical effects, these proceedings support the simulation community and the process- and device engineers who need reliable numerical simulation tools for characterization, prediction, and development. This book covers the following topics: process simulation and equipment modeling, device modeling and simulation of complex structures, device simulation and parameter extraction for circuit models, integration of process, device and circuit simulation, practical applications of simulation, algorithms and software.