Computational methods in engineering & the sciences - série de 5 livres (111 résultats)

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Paperback. Etat : new. Paperback. This volume presents the emerging applications of immersed boundary (IB) methods in computational mechanics and complex CFD calculations. It discusses formulations of different IB implementations and also demonstrates applications of these methods in a wide range of problems. It will be of special value to researchers and engineers as well as graduate students working on immersed boundary methods, specifically on recent developments and applications. The book can also be used as a supplementary textbook in advanced courses in computational fluid dynamics. This volume presents the emerging applications of immersed boundary (IB) methods in computational mechanics and complex CFD calculations. It will be of special value to researchers and engineers as well as graduate students working on immersed boundary methods, specifically on recent developments and applications. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Paperback. Etat : Brand New. 454 pages. 9.25x6.10x0.80 inches. In Stock.

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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume presents the emerging applications of immersed boundary (IB) methods in computational mechanics and complex CFD calculations. It discusses formulations of different IB implementations and also demonstrates applications of these methods in a wide range of problems. It will be of special value to researchers and engineers as well as graduate students working on immersed boundary methods, specifically on recent developments and applications. The book can also be used as a supplementary textbook in advanced courses in computational fluid dynamics.…

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Hardcover. Etat : Brand New. 454 pages. 9.25x6.10x1.06 inches. In Stock.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The volume showcases how basic formulation and solution methods can be used for an improved understanding of stability-affected structures. It also highlights the numerical treatment of the resulting equations, demonstrating and quantifying many aspects of structural stability not available to engineers by the traditional methods. The elaborated theoretical background is also used to show how methods included in commercial software can give misleading conclusions. The book will be of interest to researchers and professionals working in computational modelling of structures. The book includes exercises and projects, appended to each chapter, which further extends its usability as a text book in classroom teaching and for professional courses. …

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Taschenbuch. Etat : Neu. Structural Stability and Its Computational Modelling | Anders Eriksson (u. a.) | Taschenbuch | Computational Methods in Engineering & the Sciences | xii | Englisch | 2025 | Springer | EAN 9783031360749 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

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Hardcover. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

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Taschenbuch. Etat : Neu. Machine Learning and Deep Learning in Computational Toxicology | Huixiao Hong | Taschenbuch | Computational Methods in Engineering & the Sciences | xix | Englisch | 2024 | Springer | EAN 9783031207327 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

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Etat : New. 1st ed. 2024 edition NO-PA16APR2015-KAP.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a collection of machine learning and deep learning algorithms, methods, architectures, and software tools that have been developed and widely applied in predictive toxicology. It compiles a set of recent applications using state-of-the-art machine learning and deep learning techniques in analysis of a variety of toxicological endpoint data. The contents illustrate those machine learning and deep learning algorithms, methods, and software tools and summarise the applications of machine learning and deep learning in predictive toxicology with informative text, figures, and tables that are contributed by the first tier of experts. One of the major features is the case studies of applications of machine learning and deep learning in toxicological research that serve as examples for readers to learn how to apply machine learning and deep learning techniques in predictive toxicology. This book is expected to provide a reference for practical applications of machine learning anddeep learning in toxicological research. It is a useful guide for toxicologists, chemists, drug discovery and development researchers, regulatory scientists, government reviewers, and graduate students. The main benefit for the readers is understanding the widely used machine learning and deep learning techniques and gaining practical procedures for applying machine learning and deep learning in predictive toxicology.…

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a collection of machine learning and deep learning algorithms, methods, architectures, and software tools that have been developed and widely applied in predictive toxicology. It compiles a set of recent applications using state-of-the-art machine learning and deep learning techniques in analysis of a variety of toxicological endpoint data. The contents illustrate those machine learning and deep learning algorithms, methods, and software tools and summarise the applications of machine learning and deep learning in predictive toxicology with informative text, figures, and tables that are contributed by the first tier of experts. One of the major features is the case studies of applications of machine learning and deep learning in toxicological research that serve as examples for readers to learn how to apply machine learning and deep learning techniques in predictive toxicology. This book is expected to provide a reference for practical applications of machine learning anddeep learning in toxicological research. It is a useful guide for toxicologists, chemists, drug discovery and development researchers, regulatory scientists, government reviewers, and graduate students. The main benefit for the readers is understanding the widely used machine learning and deep learning techniques and gaining practical procedures for applying machine learning and deep learning in predictive toxicology.…