Towards Sustainable Inland Transport in the Brazilian Amazon: Estimating the Effective Power of Regional Boats

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Authors: Jassiel V. H. Fontes, Irving D. Hernández, Edgar Mendoza, Rodolfo Silva
Cited by: 1
References: 44

Abstract

A significant number of regional boats are used in the Brazilian Amazon to perform a range of social activities. However, the estimation of their propulsion parameters still requires exploring technically supported methods if the efficiency and sustainability of inland navigation is to be optimized. This study explores various approaches for estimating the total resistance and effective propulsive power required by regional boats. The research examines the real case of a rabeta, a regional boat commonly used in the Brazilian Amazon, by analyzing the applicability at full scale of two approaches: the conventional Mercier–Savitsky pre-planing method and a multiphase computational fluid dynamics (CFD) approach. Using experimental data, such as boat speed and the patterns of boat-generated waves, computational analysis and the comparison of results, respectively, were carried out. It was found that for the case considered, the CFD results underpredicted the conventional approach in less than 10% for the minimum and maximum drafts considered, suggesting that both approaches are useful for estimating the effective power of artisanal boats. However, the use of CFD has the potential to visualize a greater number of parameters, such as the generated waves during vessel motion, which can facilitate the optimization of the hydrodynamics of boats, thus contributing to the sustainability of inland navigation in the region. The procedure employed in this study can be further extended to estimate the propulsive parameters of other regional vessels in the Amazon and similar areas.

Fields of Study & Subjects

Ship Hydrodynamics and Maneuverability Maritime Transport Emissions and Efficiency Wave and Wind Energy Systems

Publication details

Journal / source
Modelling—International Open Access Journal of Modelling in Engineering Science
Publisher
MDPI AG
Volume
7
Issue
3
Pages
84–84
Publication date
28 April 2026
Language
EN