Angielski
Model Validation and Uncertainty Quantification in Biomechanics: From Soft Biological Tissue to Blood Flow provides a comprehensive overview of the latest technology in biomechanical modeling and analysis. Divided into four comprehensive parts, this book offers a thorough exploration of key concepts and cutting-edge advancements in the field. Part I presents the foundational principles of modeling primary biomechanical systems, including the intricate workings of the cardiovascular system. This section also provides invaluable insights into essential topics such as sensitivity analysis, uncertainty quantification, machine learning, and surrogate modeling. In Part 2, the book transitions into an in-depth examination of the current state-of-the-art in model validation techniques across a diverse array of biomechanical disciplines. This section presents the latest advancements and best practices for ensuring the accuracy and reliability of computational models. Part 3 introduces current and innovative approaches for quantifying uncertainties inherent in biomechanical modeling. Chapters range from established methodologies to emerging techniques, providing a comprehensive overview of the various strategies employed in addressing uncertainty in biomechanical studies. Finally, in Part 4, the book concludes with a focus on cutting-edge methods, specifically spotlighting the utilization of machine learning and surrogate modeling for both model validation and uncertainty quantification. Through real-world applications and case studies, providing an in-depth understanding of how these advanced techniques are reshaping the landscape of biomechanics research.
