Regression Analysis of Principal Ship Attributes for Purse Seiners in the Concept Design Stage - De La Torre, Dennys; Cervan, Dheybi (Ingeniería, 2026)
Context: In the ship concept design stage, naval architects must estimate the principal attributes of a vessel before the final definition of hull proportions and detailed arrangements. These estimates are essential for assessing feasibility, performance, and operational capability. However, reliable vessel-specific predictive tools are often unavailable for certain vessel categories. Method: A database of 130 American-type semi-industrial purse with RSW systems was employed to develop practical regression-based power-law models for estimating key ship attributes directly from principal hull dimensions. Results: The results show that the main volumetric and power attributes exhibit strong and consistent scaling relationships with the principal dimensions, yielding moderate to high determination coefficients, while the fuel and water capacities report a weak geometric dependence. The proposed regression equations demonstrate improved predictive performance when compared to existing formulations reported in the literature for semi-industrial purse seiners. Conclusions: This work provides a set of vessel-specific, empirically grounded regression tools tailored to American-type semi-industrial purse seiners, which can be directly applied during the ship concept design stage to support rapid and informed decision-making. This study complements previous analyses focused on hull geometric ratios by addressing a distinct and application-oriented design problem that deals with attribute estimation rather than geometric proportion selection.