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Journal of Porous Media
Fator do impacto: 1.752 FI de cinco anos: 1.487 SJR: 0.43 SNIP: 0.762 CiteScore™: 2.3

ISSN Imprimir: 1091-028X
ISSN On-line: 1934-0508

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Journal of Porous Media

DOI: 10.1615/JPorMedia.v19.i9.20
pages 771-782

IMPACT OF POST-PROCESSING METHODS ON ACCURACY OF DARCIAN AND FORCHHEIMER PERMEABILITIES DETERMINATION

Eddy EL Tabach
PRISME Laboratory, University of Orleans, 63 Avenue de Lattre de Tassigny, 18000 Bourges, France
Nicolas Gascoin
PRISME Laboratory, INSA-Centre Val de Loire, 88 boulevard Lahitolle, 18000 Bourges, France
Marc Bouchez
MBDA-France, 18 rue Le Brix, 18000 Bourges, France
Guillaume Fau
PRISME Laboratory, INSA-Centre Val de Loire, 88 boulevard Lahitolle, 18000 Bourges, France

RESUMO

Getting the Darcian and Forchheimer permeabilities is required by a number of applications to characterize porous materials. In the meantime, ensuring the reliability of these numerical values is essential. While a number of studies aim at developing appropriate test benches, the quantitative importance of post-processing methods is often underestimated. Yet, they play a major role in terms of accuracy and reliability, in addition to the test benches and test methods themselves. The present work uses experimental data obtained in the framework of transpiration cooling of high-speed cooled structures. It presents a comparison between six methodologies which are found in the literature to post-process the experimental raw data. Their accuracy is found to be influenced by several parameters (Darcian and Forchheimer permeabilities orders of magnitude, operating range, and flow nature). This work intends to quantify these methods and to suggest which method to choose to minimize the uncertainty. Above 10−17 m2, the Darcian description should be replaced by the Brinkman one and the ISO 4022 method is generally the best processing method (best correlation factor) over the entire range of test. The Multiple Linear regression method shows a clear advantage over the Simple Linear Regression one without rebutting computation cost.


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