RESISTANCE PREDICTION USING ARTIFICIAL NEURAL NETWORKS FOR PRELIMINARY TRI-SWACH DESIGN

Due to the novel hull form design, at present no standard series or full-scale data is publicly available to predict Tri- SWACH resistance during the preliminary ship design process. This work investigates the viability of using an Artificial Neural Network (ANN) to quickly predict total resistance for preliminary Tri-SWACH design. An ANN was trained using total resistance experimental data obtained from model tests, which varied side hull arrangements. The results highlight strong correlation for model resistance prediction. A Tri-SWACH case study was then developed which had side hull geometric properties different to any previously used to train the ANN. The results, validated against CFD predictions, mimicked the resistance pattern generated by other model experimental data, providing confidence in the ANN’s ability to function as a resistance prediction tool. This work demonstrates the viability of ANN to assess Tri-SWACH resistance as part of a preliminary design process. These results suggest that ANNs can be effective tools for assessing performance given relevant training data.

Nurbs modeling for design waterline based on the variation of sectional area curve

Hull form design from parent ships transforms the ship's parameters based on the variation of theoretical sectional area curve of the Lackenby method. The correction and modification of the theoretical sectional area curve is essentially the change of ship displacement, hull form coefficients, and the longitudinal center of buoyancy from the parent ships. In the preliminary design stage, the hull form design approach from parent ships minimizes the risks compared to the new design while still retaining hydrostatic and hydrodynamics' advantages. However, the Lackenby method of ship hull form variation uses a linear or quadratic function to shift the sectional area curves, regardless of the ship's hull form faring, especially the curvature's discontinuity the bow, stern, and midship. Therefore, the computer graphic algorithm based on the B-spline function is studied and applied; simultaneously, the mathematical model for the designed waterline is built in the form of a continuous curve instead of the B-spline segments. In this study, the mathematical model for the coastal container ship's design water line is constructed, ensuring continuity and fairing throughout the continuous B-spline curve. The geometry continuity evaluation results are expressed through the parameter curve's curvature and resistance component calculations' performance by computational analysis.

Hybridization of Multi-Objective Deterministic Particle Swarm with Derivative-Free Local Searches

The paper presents a multi-objective derivative-free and deterministic global/local hybrid algorithm for the efficient and effective solution of simulation-based design optimization (SBDO) problems. The objective is to show how the hybridization of two multi-objective derivative-free global and local algorithms achieves better performance than the separate use of the two algorithms in solving specific SBDO problems for hull-form design. The proposed method belongs to the class of memetic algorithms, where the global exploration capability of multi-objective deterministic particle swarm optimization is enriched by exploiting the local search accuracy of a derivative-free multi-objective line-search method. To the authors best knowledge, studies are still limited on memetic, multi-objective, deterministic, derivative-free, and evolutionary algorithms for an effective and efficient solution of SBDO for hull-form design. The proposed formulation manages global and local searches based on the hypervolume metric. The hybridization scheme uses two parameters to control the local search activation and the number of function calls used by the local algorithm. The most promising values of these parameters were identified using forty analytical tests representative of the SBDO problem of interest. The resulting hybrid algorithm was finally applied to two SBDO problems for hull-form design. For both analytical tests and SBDO problems, the hybrid method achieves better performance than its global and local counterparts.

Design of River Tour Boat’s Hull For Taman Nasional Tanjung Puting, Central Borneo

Tanjung Puting National Park is a natural wildlife park with a positively increasing trend in the number of visitors. The transportation which is utilized in Sekonyer river is ‘klotok’ boat, a traditional tour boat modified from a fishing boat. The design of a fiberglass-based tour boat is needed to accommodate the limitation of Kalimantan’s logs, which become the main structural components of klotok and to comply with the technical characteristic of the river. The purpose of this study is to obtain the optimum main dimensions of the fiberglass-based tour boat and its hull form design. The method performed to obtain the main dimension of the boat is non-linear optimization with the help of solver in Microsoft Excel software. The process of boat’s hull design is done by line distortion approach where the shape of a reference boat’s hull is conformed to a particular size and hydrodynamical coefficients, which are obtained from the optimization process. The result of optimization process is the main dimension of the boat (Lpp = 12.23 m, B = 2.70 m, H = 1.14 m, T = 0.80 m and Cb = 0.55). By conducting a series of calculations, the obtained value of the total boat’s resistance worths 2,427 N. Therefore, the number of boat’s power needed is less than the power of existing boats. The boat’s hull also complies with technical requirements and regulations, which are freeboard and intact stability.