A Physics-Informed, Deep Double Reservoir Network for Forecasting Boundary Layer Velocity

IF 3 1区 数学 Q1 STATISTICS & PROBABILITY Journal of the American Statistical Association Pub Date : 2024-11-04 DOI:10.1080/01621459.2024.2422131
Matthew Bonas, David H. Richter, Stefano Castruccio
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Abstract

When a fluid flows over a solid surface, it creates a thin boundary layer where the flow velocity is influenced by the surface through viscosity, and can transition from laminar to turbulent at suf...
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用于预测边界层速度的物理信息深层双水库网络
当流体流过固体表面时,会形成一个薄薄的边界层,在这个边界层中,流速会受到表面粘度的影响,并在适当的时候从层流过渡到湍流。
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来源期刊
CiteScore
7.50
自引率
8.10%
发文量
168
审稿时长
12 months
期刊介绍: Established in 1888 and published quarterly in March, June, September, and December, the Journal of the American Statistical Association ( JASA ) has long been considered the premier journal of statistical science. Articles focus on statistical applications, theory, and methods in economic, social, physical, engineering, and health sciences. Important books contributing to statistical advancement are reviewed in JASA . JASA is indexed in Current Index to Statistics and MathSci Online and reviewed in Mathematical Reviews. JASA is abstracted by Access Company and is indexed and abstracted in the SRM Database of Social Research Methodology.
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