Simulation and Modeling Methodologies, Technologies and Applications (eBook, PDF)

International Online Conference (SIMULTECH 2021)
Redaktion: Wagner, Gerd; de Rango, Floriano; Oren, Tuncer; Werner, Frank

• Format: PDF

Produktbeschreibung

The present book includes a set of selected papers from the 11th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2021) that was held as an online event, from July 7 to 9, 2021. The conference brought together researchers and practitioners interested in methodologies and applications of modeling and simulation. New and innovative solutions are reported in this book. A selection was made after the conference, based also on the conference chairs assessment, reviewers' assessment, quality of presentation and audience interest, so that this book includes the extended and revised versions of the very best papers of the conference.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 225
• Erscheinungstermin: 10. Februar 2023
• Englisch
• ISBN-13: 9783031231490
• Artikelnr.: 67434459

Inhaltsangabe

Development and Extended Validation of a Lumped Parameter Prediction Model for Analysing Injury Parameters in a Vehicle Crash.- Integrating GPU-accelerated Tetrahedral Mesh Editing and Simulation.- Performance Study of Vertical Submersible Pump in Terms of Induced Loads and Vibrations.- Comparison of Modelling Approaches and Solvers on Harmonic Studies for Renewable Energy Integration.- Stretching Simulation of Viscoelastic Fluid with Spring Connection.- SysML and Petri Nets based Methodology for Analysis and Performance Evaluation in WSNs.- Growing Bioinspired Synthetic Landscape Ecologies and the Adequacy of Object Oriented Programming.- On Advanced Modeling of Compressors and Weighted Mix Iteration for Simulation of Gas Transport Networks.- Quasi-static Optimal Control Strategy of Lattice Boom Crane based on Large-scale Flexible Non-linear Dynamics.- Simulation Conditionally to a Subvariety and Application to Bayesian Optimization: A Dichotomous Approach.- A Python-based Mixed Discrete-Continuous Simulation Framework for Digital Twins.