Autor segons l'article: Reichardt I; Pallarès J; Sales-Pardo M; Guimerà R
Departament: Enginyeria Química Enginyeria Mecànica
Autor/s de la URV: Guimera Manrique, Roger / Pallarés Curto, Jorge María / Sales Pardo, Marta
Paraules clau: Growth
Resum: © 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.
Àrees temàtiques: 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
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 0031-9007
Adreça de correu electrònic de l'autor: roger.guimera@urv.cat marta.sales@urv.cat jordi.pallares@urv.cat
Identificador de l'autor: 0000-0002-3597-4310 0000-0002-8140-6525 0000-0003-0305-2714
Data d'alta del registre: 2023-02-26
Volum de revista: 124
Versió de l'article dipositat: info:eu-repo/semantics/acceptedVersion
Enllaç font original: https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.124.084503
URL Document de llicència: http://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Physical Review Letters. 124 (8): 084503-
Referència de l'ítem segons les normes APA: Reichardt I; Pallarès J; Sales-Pardo M; Guimerà R (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 de l'article: 10.1103/PhysRevLett.124.084503
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2020
Tipus de publicació: Journal Publications
Repositori URV