Resistance and Trim Modeling of Naples Hard Chine Systematic Series

Abstract

An Artificial Neural Network (ANN) method with multiple outputs is used to develop the mathematical models for the Naples Systematic Series (NSS) of resistance (actually (RT/Δ)100000), dynamic trim (τ), wetted area (S/V2/3) and length of wetted area (LWL/LP), as functions of length beam ratio (LP/BPX), slenderness ratio (LP/V1/3), longitudinal centre of gravity (LCG/LP) and volumetric Froude number (FnV). Multiple ANN output feature enables simultaneous use of all the available (RT/Δ)100000 and τ data, producing both, an output for R/Δ and for τ. Similar results are obtained for the S/V2/3 and LWL/LP datasets. Note that the multiple output models share a common ANN structure, with only slight differences in equations for R/Δ & τ, and S/V2/3 & LWL/LP.