Multiple Feature Extraction Long Short-Term Memory Using Skip Connections for Ship Electricity Forecasting DOI Creative Commons

Ji-Yoon Kim,

Jin-Seok Oh

Journal of Marine Science and Engineering, Journal Year: 2023, Volume and Issue: 11(9), P. 1690 - 1690

Published: Aug. 27, 2023

The power load data of electric-powered ships vary with the ships’ operational status and external environmental factors such as sea conditions. Therefore, a model is required to accurately predict ship’s load, which depends on changes in marine environment, weather situation. This study used an actual ship ship. research forecasting fluctuations has been quite limited, existing models have inherent limitations predicting these accurately. In this paper, A multiple feature extraction (MFE)-long short-term memory (LSTM) skip connections introduced address deep learning models. novel approach enables analysis intricate variations ships, thereby facilitating prediction complex fluctuations. performance was compared that previous convolutional neural network-LSTM network squeeze excitation (SE) feed-forward (DFF) model. metrics for comparison were mean absolute error, root squared percentage R-squared, wherein best, average, worst performances evaluated both proposed exhibited superior predictive models, evidenced by metrics: error (MAE) 55.52, (RMSE) 125.62, (MAPE) 3.56, R-squared (R2) 0.86. expected be during operations.

Language: Английский

Review of current regulations, available technologies, and future trends in the green shipping industry DOI Creative Commons
Mina Tadros, L. Ventura, C. Guedes Soares

et al.

Ocean Engineering, Journal Year: 2023, Volume and Issue: 280, P. 114670 - 114670

Published: May 11, 2023

This paper presents a comprehensive review of the current regulations and various technologies as well decision support methods for each technology maritime industry considers to ensure fleet's sustainability. It covers period between 2010 2022, emphasizing last four years. shows impact on reduction ship resistance energy required board, affecting amount fuel consumption avoiding transportation harmful species around world achieve smooth transition towards green shipping by improving efficiency achieving goals 2050 plan. The five main topics: hull design, propulsion systems, new clean fuels treatment power systems operation; topic has different included. study's findings contribute mapping scientific knowledge in field, identifying relevant areas, visualising links topics, recognising research gaps opportunities. helps present holistic approaches future supporting cooperation stakeholders provide more realistic solutions toward

Language: Английский

Citations

90
Review of the Decision Support Methods Used in Optimizing Ship Hulls towards Improving Energy Efficiency DOI Creative Commons
Mina Tadros, L. Ventura, C. Guedes Soares

et al.

Journal of Marine Science and Engineering, Journal Year: 2023, Volume and Issue: 11(4), P. 835 - 835

Published: April 15, 2023

This paper presents a review of the different methods and techniques used to optimize ship hulls over last six years (2017–2022). shows percentages reduction in resistance, thus fuel consumption, improve ships’ energy efficiency, towards achieving goal maritime decarbonization. Operational research machine learning are common decision support find optimal solution. covers four areas hulls, including hull form, structure, cleaning lubrication. In each area research, several computer programs used, depending on study’s complexity objective. It has been found that no specific method is considered optimum, while combination can achieve more accurate results. Most work focused concept stage design, operational conditions recently taken place, an improvement efficiency. The finding this study contributes mapping scientific knowledge technology identifying relevant topic areas, recognizing gaps opportunities. also helps present holistic approaches future supporting realistic solutions sustainability.

Language: Английский

Citations

18
A Scoping Review on Simulation-Based Design Optimization in Marine Engineering: Trends, Best Practices, and Gaps DOI Creative Commons
Andrea Serani, Thomas P. Scholcz, Valentina Vanzi

et al.

Archives of Computational Methods in Engineering, Journal Year: 2024, Volume and Issue: 31(8), P. 4709 - 4737

Published: May 15, 2024

Abstract This scoping review assesses the current use of simulation-based design optimization (SBDO) in marine engineering, focusing on identifying research trends, methodologies, and application areas. Analyzing 277 studies from Scopus Web Science, finds that SBDO is predominantly applied to optimizing vessel hulls, including both surface underwater types, extends key components like bows, sterns, propellers, fins. It also covers structures renewable energy systems. A notable trend preference for deterministic single-objective methods, indicating potential growth areas multi-objective stochastic approaches. The points out necessity integrating more comprehensive multidisciplinary methods address complex challenges environments. Despite extensive there remains a need enhancing methodologies’ efficiency robustness. offers critical overview SBDO’s role engineering highlights opportunities future advance field.

Language: Английский

Citations

8
Computational fluid dynamics-based ship energy-saving technologies: A comprehensive review DOI
Kai Wang, Z. Li, Rui Zhang

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2024, Volume and Issue: 207, P. 114896 - 114896

Published: Sept. 18, 2024

Language: Английский

Citations

5
Research progress on intelligent optimization techniques for energy-efficient design of ship hull forms DOI

Shuwei Zhu,

Ning Sun,

Siying Lv

et al.

Journal of Membrane Computing, Journal Year: 2024, Volume and Issue: 6(4), P. 318 - 334

Published: Aug. 28, 2024

Language: Английский

Citations

4
Research and implementation of an online platform for efficient and accurate ship hull design DOI

Yi-zheng Yang,

Yaqing Shu,

Guangnian Li

et al.

Advances in Engineering Software, Journal Year: 2025, Volume and Issue: 202, P. 103870 - 103870

Published: Feb. 1, 2025

Language: Английский

Citations

0
Resistance and propulsion performance of a twin skeg ship with different rudder angle DOI Creative Commons
Weimin Chen,

LI Yong-yue,

Lei Xing

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: June 3, 2025

Language: Английский

Citations

0
Multi-objective hull form optimization utilizing sequential sampling optimization method DOI

Ya-bo Wei,

Xi Chen,

Jianhua Wang

et al.

Ocean Engineering, Journal Year: 2024, Volume and Issue: 310, P. 118667 - 118667

Published: July 9, 2024

Language: Английский

Citations

1
Hull Form Optimization Study Based on Multiple Parametric Modification Curves and Free Surface Reynolds-Averaged Navier–Stokes (RANS) Solver DOI Creative Commons
Sungwoo Park, Seunghyeon Kim,

Yang-Ik Kim

et al.

Applied Sciences, Journal Year: 2022, Volume and Issue: 12(5), P. 2428 - 2428

Published: Feb. 25, 2022

In this study, the hull form optimization process to minimize resistance of KCS (KRISO containership) at Fn=0.26 is described. The bow was modified by varying such design parameters as sectional area curve (SAC), section shape, bulb breadth, and height using multiple parametric modification curves devised authors. performances forms were analysed viscous flow Reynolds-Averaged Navier–Stokes (RANS) solver WAVIS ver.2.2. With a view saving computational time during iterative analyses in process, sinkage trim set fixed values which had been obtained for original with free condition. validity constant sinkage/trim then verified conducting analysis optimal Optimization cost function total coefficient model CTM performed sequential quadratic programming (SQP), one gradient-based local methods. Utilization parallel computing led simultaneous calculation gradient, thereby speeding up whole process. At speed 24 knots, yielded reduction 1.8%, extrapolated 3.1% effective power PE full scale.

Language: Английский

Citations

6
Simulation-Driven Design Optimization of a Destroyer-Type Vessel via Multi-Fidelity Supervised Active Learning DOI Creative Commons
Emanuele Spinosa, Riccardo Pellegrini, Antonio Posa

et al.

Journal of Marine Science and Engineering, Journal Year: 2023, Volume and Issue: 11(12), P. 2232 - 2232

Published: Nov. 25, 2023

The paper presents the use of a supervised active learning approach for solution simulation-driven design optimization (SDDO) problem, pertaining to resistance reduction destroyer-type vessel in calm water. is formulated as single-objective, single-point problem with both geometrical and operational constraints. latter also considers seakeeping performance at multiple conditions. A surrogate model used, based on stochastic radial basis functions lower confidence bounding, approach. Furthermore, multi-fidelity formulation, leveraging unsteady Reynolds-averaged Navier–Stokes equations potential flow solvers, used order reduce computational cost SDDO procedure. Exploring five-dimensional space free-form deformation under limited resources, optimal configuration achieves about 3% escape speed 6.4% average over range.

Language: Английский

Citations

3