The Delft Method For System Dynamics
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The Delft Method for System Dynamics
Author: Willem Auping
language: en
Publisher: TU Delft OPEN Publishing
Release Date: 2024-11-19
The Delft Method for System Dynamics (SD) is a proven method for learning basic SD. The method focuses on learning by doing: first you try to work through an exercise, and if you do not understand something, then you can look up the theory. The book contains exercises on topics such as causal loop diagrams, delays, and when SD is an appropriate methodology. It also contains modelling exercises that show students how to build low to medium complexity models, and how to use these models for policy analysis. The theory chapters cover all phases of the modelling cycle: problem articulation, conceptualisation, formulation, evaluation (including validation and scenario analysis), and policy analysis. This book is intended for students and teachers in large or small System Dynamics courses, and for motivated students that want to learn SD at their own pace.
Road and Off-Road Vehicle System Dynamics Handbook
Featuring contributions from leading experts, the Road and Off-Road Vehicle System Dynamics Handbook provides comprehensive, authoritative coverage of all the major issues involved in road vehicle dynamic behavior. While the focus is on automobiles, this book also highlights motorcycles, heavy commercial vehicles, and off-road vehicles. The authors of the individual chapters, both from automotive industry and universities, address basic issues, but also include references to significant papers for further reading. Thus the handbook is devoted both to the beginner, wishing to acquire basic knowledge on a specific topic, and to the experienced engineer or scientist, wishing to have up-to-date information on a particular subject. It can also be used as a textbook for master courses at universities. The handbook begins with a short history of road and off-road vehicle dynamics followed by detailed, state-of-the-art chapters on modeling, analysis and optimization in vehicle system dynamics, vehicle concepts and aerodynamics, pneumatic tires and contact wheel-road/off-road, modeling vehicle subsystems, vehicle dynamics and active safety, man-vehicle interaction, intelligent vehicle systems, and road accident reconstruction and passive safety. Provides extensive coverage of modeling, simulation, and analysis techniques Surveys all vehicle subsystems from a vehicle dynamics point of view Focuses on pneumatic tires and contact wheel-road/off-road Discusses intelligent vehicle systems technologies and active safety Considers safety factors and accident reconstruction procedures Includes chapters written by leading experts from all over the world This text provides an applicable source of information for all people interested in a deeper understanding of road vehicle dynamics and related problems.
Analytical Methods for Dynamic Modelers
A user-friendly introduction to some of the most useful analytical tools for model building, estimation, and analysis, presenting key methods and examples. Simulation modeling is increasingly integrated into research and policy analysis of complex sociotechnical systems in a variety of domains. Model-based analysis and policy design inform a range of applications in fields from economics to engineering to health care. This book offers a hands-on introduction to key analytical methods for dynamic modeling. Bringing together tools and methodologies from fields as diverse as computational statistics, econometrics, and operations research in a single text, the book can be used for graduate-level courses and as a reference for dynamic modelers who want to expand their methodological toolbox. The focus is on quantitative techniques for use by dynamic modelers during model construction and analysis, and the material presented is accessible to readers with a background in college-level calculus and statistics. Each chapter describes a key method, presenting an introduction that emphasizes the basic intuition behind each method, tutorial style examples, references to key literature, and exercises. The chapter authors are all experts in the tools and methods they present. The book covers estimation of model parameters using quantitative data; understanding the links between model structure and its behavior; and decision support and optimization. An online appendix offers computer code for applications, models, and solutions to exercises. Contributors Wenyi An, Edward G. Anderson Jr., Yaman Barlas, Nishesh Chalise, Robert Eberlein, Hamed Ghoddusi, Winfried Grassmann, Peter S. Hovmand, Mohammad S. Jalali, Nitin Joglekar, David Keith, Juxin Liu, Erling Moxnes, Rogelio Oliva, Nathaniel D. Osgood, Hazhir Rahmandad, Raymond Spiteri, John Sterman, Jeroen Struben, Burcu Tan, Karen Yee, Gönenç Yücel