Data-Driven Fluid Mechanics. Combining First Principles and Machine Learning, Hardback/***
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Big data and machine learning are driving profound technological progress across nearly every industry, and are rapidly shaping fluid mechanics research. This is a self-contained and pedagogical treatment of the data-driven tools that are leading research in model-order reduction, system identification, flow control, and turbulence closures. Publisher: Cambridge University Press Illustration(s): Worked examples or Exercises Number of pages: 468 Publication date: 2023 Dimensions: 176 x 252 x 27 Cover type: Hardback Editor(s): Steven L. (University of Washington) Brunton
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