Автор: Gindis, Elliot J. Название: Up And Running With Autocad 2021 ISBN: 0128231173 ISBN-13(EAN): 9780128231173 Издательство: Elsevier Science Рейтинг: Цена: 11957.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Up and Running with AutoCAD 2021: 2D and 3D Drawing, Design and Modeling presents a combination of step-by-step instruction, examples and insightful explanations. The book emphasizes core concepts and practical application of AutoCAD in engineering, architecture and design. Equally useful in instructor-led classroom training, self-study, or as a professional reference, the book is written with the user in mind by a long-time AutoCAD professional and instructor.
Описание: Reduction of Simulation Time.- Recent Developments of TAU Adaptation Capability.- Adaptive Wall Function for the Prediction of Turbulent Flows.- Acceleration of CFD Processes for Transport Aircraft.- Efficient Combat Aircraft Simulations with the TAU RANS Code.- Improvement of Simulation Quality.- Universal Wall Functions for Aerodynamic Flows: Turbulence Model Consistent Design, Potential and Limitations.- Computational Modelling of Transonic Aerodynamic Flows Using Near-Wall, Reynolds Stress Transport Models.- Transition Prediction for Three-Dimensional Configurations.- Application of Transition Prediction.- Numerical Simulation Quality Assessment for Transport Aircraft.- Fluid Structure Coupling.- Computational Methods for Aero-Structural Analysis and Optimisation of Aircrafts Based on Reduced-Order Structural Models.- Development and Application of TAU-ANSYS Coupling Procedure.- Fluid-Structure Coupling: Simplified Structural Model on Complex Configurations.- Improvement of Shape Optimization Strategies.- Development of an Automated Artificial Neural Network for Numerical Optimization.- modeFRONTIER(c), a Framework for the Optimization of Military Aircraft Configurations.- One-Shot Methods for Aerodynamic Shape Optimization.- Automatic Differentiation of FLOWer and MUGRIDO.- Adjoint Methods for Coupled CFD-CSM Optimization.- Aerodynamic and Multidisciplinary Optimization of 3D-Configurations.- Aerodynamic Optimization for Cruise and High-Lift Configurations.- Aerodynamic Optimization of an UCAV Configuration.- Flexible Wing Optimisation Based on Shapes and Structures.- Multidisciplinary Optimization of an UAV Combining CFD and CSM.
Автор: Peddie, Jon Название: Body of Knowledge for Modeling and Simulation ISBN: 3031110846 ISBN-13(EAN): 9783031110849 Издательство: Springer Рейтинг: Цена: 11878.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Commissioned by the Society for Modeling and Simulation International (SCS), this needed, useful new ‘Body of Knowledge’ (BoK) collects and organizes the common understanding of a wide collection of professionals and professional associations. Modeling and simulation (M&S) is a ubiquitous discipline that lays the computational foundation for real and virtual experimentation, clearly stating boundaries—and interactions—of systems, data, and representations. The field is well known, too, for its training support via simulations and simulators. Indeed, with computers increasingly influencing the activities of today’s world, M&S is the third pillar of scientific understanding, taking its place along with theory building and empirical observation. This valuable new handbook provides intellectual support for all disciplines in analysis, design and optimization. It contributes increasingly to the growing number of computational disciplines, addressing the broad variety of contributing as well as supported disciplines and application domains. Further, each of its sections provide numerous references for further information. Highly comprehensive, the BoK represents many viewpoints and facets, captured under such topics as: * Mathematical and Systems Theory Foundations * Simulation Formalisms and Paradigms * Synergies with Systems Engineering and Artificial Intelligence * Multidisciplinary Challenges * Ethics and Philosophy * Historical Perspectives Examining theoretical as well as practical challenges, this unique volume addresses the many facets of M&S for scholars, students, and practitioners. As such, it affords readers from all science, engineering, and arts disciplines a comprehensive and concise representation of concepts, terms, and activities needed to explain the M&S discipline. Tuncer ?ren is Professor Emeritus at the University of Ottawa. Bernard Zeigler is Professor Emeritus at the University of Arizona. Andreas Tolk is Chief Scientist at The MITRE Corporation. All three editors are long-time members and Fellows of the Society for Modeling and Simulation International. Under the leadership of three SCS Fellows, Dr. ?ren, University of Ottawa, Dr. Zeigler, The University of Arizona, and Dr. Tolk, The MITRE Corporation, more than 50 international scholars from 15 countries provided insights and experience to compile this initial M&S Body of Knowledge.
Applications William Rouse and Philomena Zimmerman
Conceptual Modeling Conrad Bock, Fatma Dandashi, Sanford Friedenthal, Nathalie Harrison, Steven Jenkins, Leon McGinnis, Janos Sztipanovits, Adelinde Uhrmacher, Eric Weisel, Lin Zhang
Computational Challenges in Modeling and Simulation Christopher Carothers, Alois Ferscha, Richard Fujimoto, David Jefferson, Margaret Loper, Madhav Marathe, Simon J.E. Taylor, Hamid Vakilzadian
Uncertainty in M&S Wei Chen, George Kesidis, Tina Morrison, J. Tinsley Oden, Jitesh H. Panchal, Christiaan Paredis, Michael Pennock, Sez Atamturktur, Gabriel Terejanu, Michael Yukish
Model Reuse, Composition and Adaptation Osman Balci, George L. Ball, Katherine L. Morse, Ernie Page, Mikel D. Petty, Andreas Tolk, Sandra N. Veautour
Автор: Bingen Yang, Inna Abramova Название: Dynamic Systems: Modeling, Simulation, and Analysis ISBN: 1107179793 ISBN-13(EAN): 9781107179790 Издательство: Cambridge Academ Рейтинг: Цена: 15682.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presenting a comprehensive and efficient approach to the modelling, simulation, and analysis of dynamic systems, this undergraduate textbook addresses mechanical, electrical, thermal and fluid systems, feedback control systems, and their combinations. Ideal for a single-semester course in mechanical, aerospace and civil engineering.
This illuminating text/reference presents a review of the key aspects of the modeling and simulation (M&S) life cycle, and examines the challenges of M&S in different application areas. The authoritative work offers valuable perspectives on the future of research in M&S, and its role in engineering complex systems.
Topics and features: reviews the challenges of M&S for urban infrastructure, healthcare delivery, automated vehicle manufacturing, deep space missions, and acquisitions enterprise; outlines research issues relating to conceptual modeling, covering the development of explicit and unambiguous models, communication and decision-making, and architecture and services; considers key computational challenges in the execution of simulation models, in order to best exploit emerging computing platforms and technologies; examines efforts to understand and manage uncertainty inherent in M&S processes, and how these can be unified under a consistent theoretical and philosophical foundation; discusses the reuse of models and simulations to accelerate the simulation model development process.
This thought-provoking volume offers important insights for all researchers involved in modeling and simulation across the full spectrum of disciplines and applications, defining a common research agenda to support the entire M&S research community.
The capability modeling and simulation (M&S) supplies for managing systems complexity and investigating systems behaviors has made it a central activity in the development of new and existing systems. However, a handbook that provides established M&S practices has not been available. Until now. Modeling and Simulation-Based Systems Engineering Handbook details the M&S practices for supporting systems engineering in diverse domains. It discusses how you can identify systems engineering needs and adapt these practices to suit specific application domains, thus avoiding redefining practices from scratch.
Although M&S practices are used and embedded within individual disciplines, they are often developed in isolation. However, they address recurring problems common to all disciplines. The editors of this book tackled the challenge by recruiting key representatives from several communities, harmonizing the different perspectives derived from individual backgrounds, and lining them up with the book's vision. The result is a collection of M&S systems engineering examples that offer an initial means for cross-domain capitalization of the knowledge, methodologies, and technologies developed in several communities. These examples provide the pros and cons of the methods and techniques available, lessons learned, and pitfalls to avoid.
As our society moves further in the information era, knowledge and M&S capabilities become key enablers for the engineering of complex systems and systems of systems. Therefore, knowledge and M&S methodologies and technologies become valuable output in an engineering activity, and their cross-domain capitalization is key to further advance the future practices in systems engineering. This book collates information across disciplines to provide you with the tools to more efficiently design and manage complex systems that achieve their goals.
Автор: Ronny Frevert; Joachim Haase; Roland Jancke; Uwe K Название: Modeling and Simulation for RF System Design ISBN: 1461498325 ISBN-13(EAN): 9781461498322 Издательство: Springer Рейтинг: Цена: 20896.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Preface. Acknowledgments. 1 Introduction. 2 Design Flow Overview. 2.1 Design Levels. 2.2 Top-down System Design. 2.3 Bottom-up Verification. 3 Simulation Tools in System Design. 3.1 Use of Simulation Tools within the Design Flow. 3.2 Specific Simulation Algorithms of RF Simulators. 3.3 Criteria of the Simulator Selection. 3.4 Internet Resources for Simulation Tools. 4 System Level Modeling. 4.1 System Level Simulation. 4.2 Simulation Technology of System Level Simulators. 4.3 Complex Baseband Simulation. 4.4 Model Libraries for System Simulation. 4.5 Creation of Own Primitive and Hierarchical Models. 5 VHDL-AMS for Block Level Simulation. 5.1 Introduction. 5.2 VHDL-AMS Standardization. 5.3 A Simple Block Level Example - Analog PLL. 5.4 Summary 6 Introduction to VHDL-AMS. 6.1 Aim of this Introduction. 6.2 Repetition of Basics of VHDL 1076-1993. 6.3 Conservative Systems Description. 6.4 Description of Nonconservative Systems. 6.5 Mixed-Signal Simulation. 6.6 Analysis Domains. 6.7 Summary. 7 Selected RF Blocks in VHDL-AMS. 7.1 Library Overview. 7.2 Signal Sources. 7.3 Basic RF Building Blocks. 7.4 Measurement and Observation Units. 7.5 Block Level Example of a Linear PLL. 8 Macromodeling in VHDL-AMS. 8.1 Introduction. 8.2 General Methodology. 8.3 Input and Output Stages. 8.3.1 Input stages. 8.3.2 Output stages. 8.4 OpAmp Macromodel. 9 Complex Example: WLAN Receiver. 9.1 Introduction. 9.2 Example Specification. 9.3 Example Modeling. 9.4 Example Calibration. 9.5 Example Verification. 10 Modeling of Analog Blocks in Verilog-A. 10.1 Introduction. 10.2 Writing Custom Behavioral Models. 10.3 Overview of the Cadence Model Library rfLib. 10.4 Modeling and Simulation of a WLAN Receiver. 11 Characterization forBottom-Up Verification. 11.1 Concept of Characterization. 11.2 RF Characteristics and Parameters. 11.3 Application of Characterization. 11.4 Example Characterization of an LNA. 11.5 Characterization Environment. 11.6 Characterization Using the OCEAN Script Language. 12 Advanced Methods for Overall System Specification and Validation. 12.1 Gap between System Level and Block Level Simulation. 12.2 File Coupling of Simulators. 12.3 Direct Cosimulation of System Level and Analog Simulators. 12.4 Generated Black Box Models. References. Index.
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