Articles producció científica> Enginyeria Química

Bayesian Machine Scientist to Compare Data Collapses for the Nikuradse Dataset

  • Datos identificativos

    Identificador: imarina:6389816
    Autores:
    Reichardt, IgnasiPallares, JordiSales-Pardo, MartaGuimera, Roger
    Resumen:
    © 2020 American Physical Society. Ever since Nikuradse's experiments on turbulent friction in 1933, there have been theoretical attempts to describe his measurements by collapsing the data into single-variable functions. However, this approach, which is common in other areas of physics and in other fields, is limited by the lack of rigorous quantitative methods to compare alternative data collapses. Here, we address this limitation by using an unsupervised method to find analytic functions that optimally describe each of the data collapses for the Nikuradse dataset. By descaling these analytic functions, we show that a low dispersion of the scaled data does not guarantee that a data collapse is a good description of the original data. In fact, we find that, out of all the proposed data collapses, the original one proposed by Prandtl and Nikuradse over 80 years ago provides the best description of the data so far, and that it also agrees well with recent experimental data, provided that some model parameters are allowed to vary across experiments.
  • Otros:

    Autor según el artículo: Reichardt, Ignasi; Pallares, Jordi; Sales-Pardo, Marta; Guimera, Roger
    Departamento: Enginyeria Química Enginyeria Mecànica
    Autor/es de la URV: Guimera Manrique, Roger / Pallarés Curto, Jorge María / Pallarès Marzal, Josep / Sales Pardo, Marta
    Palabras clave: Growth
    Resumen: © 2020 American Physical Society. Ever since Nikuradse's experiments on turbulent friction in 1933, there have been theoretical attempts to describe his measurements by collapsing the data into single-variable functions. However, this approach, which is common in other areas of physics and in other fields, is limited by the lack of rigorous quantitative methods to compare alternative data collapses. Here, we address this limitation by using an unsupervised method to find analytic functions that optimally describe each of the data collapses for the Nikuradse dataset. By descaling these analytic functions, we show that a low dispersion of the scaled data does not guarantee that a data collapse is a good description of the original data. In fact, we find that, out of all the proposed data collapses, the original one proposed by Prandtl and Nikuradse over 80 years ago provides the best description of the data so far, and that it also agrees well with recent experimental data, provided that some model parameters are allowed to vary across experiments.
    Áreas temáticas: Química Physics, multidisciplinary Physics and astronomy (miscellaneous) Physics and astronomy (all) Physics Medicina ii Materiais Matemática / probabilidade e estatística Interdisciplinar Geociências General physics and astronomy General medicine Filosofía Farmacia Ensino Engenharias iv Engenharias iii Engenharias ii Economia Ciências biológicas ii Ciências agrárias i Ciência da computação Biotecnología Astronomia / física
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 0031-9007
    Direcció de correo del autor: roger.guimera@urv.cat josep.pallares@urv.cat jordi.pallares@urv.cat marta.sales@urv.cat
    Identificador del autor: 0000-0002-3597-4310 0000-0001-7221-5383 0000-0003-0305-2714 0000-0002-8140-6525
    Fecha de alta del registro: 2024-10-19
    Volumen de revista: 124
    Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
    Enlace a la fuente original: https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.124.084503
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Physical Review Letters. 124 (8): 084503-
    Referencia de l'ítem segons les normes APA: Reichardt, Ignasi; Pallares, Jordi; Sales-Pardo, Marta; Guimera, Roger (2020). Bayesian Machine Scientist to Compare Data Collapses for the Nikuradse Dataset. Physical Review Letters, 124(8), 084503-. DOI: 10.1103/PhysRevLett.124.084503
    DOI del artículo: 10.1103/PhysRevLett.124.084503
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2020
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Physics,Physics and Astronomy (Miscellaneous),Physics, Multidisciplinary
    Growth
    Química
    Physics, multidisciplinary
    Physics and astronomy (miscellaneous)
    Physics and astronomy (all)
    Physics
    Medicina ii
    Materiais
    Matemática / probabilidade e estatística
    Interdisciplinar
    Geociências
    General physics and astronomy
    General medicine
    Filosofía
    Farmacia
    Ensino
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Economia
    Ciências biológicas ii
    Ciências agrárias i
    Ciência da computação
    Biotecnología
    Astronomia / física
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