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Springer New Trends In Computational Engineering
Springer New Trends In Computational Engineering

Springer New Trends In Computational Engineering

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New Trends in Computational Engineering5th International Conference on Computational Engineering, ICCE 2024, Darmstadt, Germany, September 30October 2\nAuthor(s): Michael Schfer, Marek Behr, Hans-Joachim Bungartz, Sebastian Schps, Miriam Schulte, Manuel Torrilhon, Oliver Weeger\nFormat: Hardback\nPublisher: Springer Nature Switzerland AG, Switzerland\nImprint: Springer Nature Switzerland AG\nISBN-13: 9783032162526, 978-3032162526\nSynopsis\nThe book is the proceedings of the 5th InternationalConference on Computational Engineering (ICCE 2024), Darmstadt, Germany, 30th September to 2nd October, [url] Engineering is a modern andultidisciplinary science for computer based modeling, simulation, analysis andoptimization of complex engineering applications and natural phenomena. Thebook contains an overview of selected approaches from numerics and optimizationof Partial Differential Equations as well as uncertainty quantification andmachine learning techniques, typically in multiphysics en.

Springer New Trends In Computational Engineering

New Trends in Computational Engineering5th International Conference on Computational Engineering, ICCE 2024, Darmstadt, Germany, September 30October 2\nAuthor(s): Michael Schfer, Marek Behr, Hans-Joachim Bungartz, Sebastian Schps, Miriam Schulte, Manuel Torrilhon, Oliver Weeger\nFormat: Hardback\nPublisher: Springer Nature Switzerland AG, Switzerland\nImprint: Springer Nature Switzerland AG\nISBN-13: 9783032162526, 978-3032162526\nSynopsis\nThe book is the proceedings of the 5th InternationalConference on Computational Engineering (ICCE 2024), Darmstadt, Germany, 30th September to 2nd October, [url] Engineering is a modern andultidisciplinary science for computer based modeling, simulation, analysis andoptimization of complex engineering applications and natural phenomena. Thebook contains an overview of selected approaches from numerics and optimizationof Partial Differential Equations as well as uncertainty quantification andmachine learning techniques, typically in multiphysics en.

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