Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
194 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Research progress on intelligent optimization techniques for energy-efficient design of ship hull forms (2403.05832v1)

Published 9 Mar 2024 in cs.CE

Abstract: The design optimization of ship hull form based on hydrodynamics theory and simulation-based design (SBD) technologies generally considers ship performance and energy efficiency performance as the design objective, which plays an important role in smart design and manufacturing of green ship. An optimal design of sustainable energy system requires multidisciplinary tools to build ships with the least resistance and energy consumption. Through a systematic approach, this paper presents the research progress of energy-efficient design of ship hull forms based on intelligent optimization techniques. We discuss different methods involved in the optimization procedure, especially the latest developments of intelligent optimization algorithms and surrogate models. Moreover, current development trends and technical challenges of multidisciplinary design optimization and surrogate-assisted evolutionary algorithms for ship design are further analyzed. We explore the gaps and potential future directions, so as to paving the way towards the design of the next generation of more energy-efficient ship hull form.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (129)
  1. Decision support methods for sustainable ship energy systems: A state-of-the-art review, Energy 239 (2022) 122288.
  2. C. A. Frangopoulos, Developments, trends, and challenges in optimization of ship energy systems, Applied Sciences 10 (2020) 4639.
  3. A novel method for optimal performance of ships by simultaneous optimisation of hull-propulsion-bipv systems, Energy Conversion and Management 197 (2019) 111879.
  4. Review of the decision support methods used in optimizing ship hulls towards improving energy efficiency, Journal of Marine Science and Engineering 11 (2023) 835.
  5. Y. Chi, F. Huang, An overview of simulation-based hydrodynamic design of ship hull forms, Journal of Hydrodynamics, Ser. B 28 (2016) 947–960.
  6. Stochastic optimization methods for ship resistance and operational efficiency via cfd, Structural and Multidisciplinary Optimization 57 (2018) 735–758.
  7. Hull form optimisation in waves based on cfd technique, Ships and Offshore Structures 13 (2018) 149–164.
  8. Automatic design optimization of swath applying cfd and rsm model, Ocean Engineering 172 (2019) 146–154.
  9. Cfd-based multi-objective optimisation of s60 catamaran considering demihull shape and separation, Applied Ocean Research 97 (2020) 102071.
  10. A. Nazemian, P. Ghadimi, Multi-objective optimization of ship hull modification based on resistance and wake field improvement: combination of adjoint solver and cad-cfd-based approach, Journal of the Brazilian Society of Mechanical Sciences and Engineering 44 (2022) 1–27.
  11. Comparison between empirical and cfd based methods for ship resistance and power prediction, Trends in Maritime Technology and Engineering (2022) 347–357.
  12. Derivative-free optimization methods, Acta Numerica 28 (2019) 287–404.
  13. Ship hydrodynamic optimization by local hybridization of deterministic derivative-free global algorithms, Applied Ocean Research 59 (2016) 115–128.
  14. Heuristic scheduling of batch production processes based on petri nets and iterated greedy algorithms, IEEE Transactions on Automation Science and Engineering 19 (2022a) 251–261.
  15. Iterated greedy algorithms for flow-shop scheduling problems: A tutorial, IEEE Transactions on Automation Science and Engineering 19 (2022b) 1941–1959.
  16. Ship design for real sea states under uncertainty, Ocean Engineering 266 (2022) 113127.
  17. Conceptual design of a long-range autonomous underwater vehicle based on multidisciplinary optimization framework, Ocean Engineering 248 (2022) 110684.
  18. Optimized support vector regression algorithm-based modeling of ship dynamics, Applied ocean research 90 (2019) 101842.
  19. Ship hull automated optimization of minimum resistance via cfd and rsm technique, Journal of Ship Mechanics 16 (2012) 36–43.
  20. Hull-form optimization using parametric modification functions and particle swarm optimization, Journal of Marine Science and Technology 21 (2016) 129–144.
  21. Minimum resistance ship hull uncertainty optimization design based on simulation-based design method, Journal of Shanghai Jiaotong University (Science) 22 (2017) 657–663.
  22. Surrogate modeling: tricks that endured the test of time and some recent developments, Structural and Multidisciplinary Optimization (2021) 1–28.
  23. An investigation into fishing boat optimisation using a hybrid algorithm, Ocean Engineering 167 (2018) 204–220.
  24. Design optimization for self-propulsion of a bulk carrier hull using a discrete adjoint method, Computers & Fluids 192 (2019) 104259.
  25. Computational fluid dynamics-based hull form optimization using approximation method, Engineering Applications of Computational Fluid Mechanics 12 (2018) 74–88.
  26. Hull form optimization of trimaran using self-blending method, Applied Ocean Research 80 (2018) 240–247.
  27. Parametric design and optimization of swath for reduced resistance based on evolutionary algorithm, Journal of Marine Science and Technology 26 (2021) 54–70.
  28. Hull optimization of an underwater vehicle based on dynamic surrogate model, Ocean Engineering 230 (2021) 109050.
  29. Improved sequential sampling for meta-modeling promotes design optimization of swath, Ocean Engineering 198 (2020) 106958.
  30. F. Huang, Y. Chi, Hull form optimization of a cargo ship for reduced drag, Journal of Hydrodynamics, Ser. B 28 (2016) 173–183.
  31. Hydrodynamic shape optimization by high fidelity cfd solver and gaussian process based response surface method, Applied Ocean Research 90 (2019) 101841.
  32. Multi-objective bayesian hull form optimisation for high-speed craft, Ocean Engineering 266 (2022) 112688.
  33. Multi-fidelity model and reduced-order method for comprehensive hydrodynamic performance optimization and prediction of jbc ship, Ocean Engineering 267 (2023) 113321.
  34. An effective mesh deformation approach for hull shape design by optimization, Journal of Marine Science and Engineering 9 (2021) 1107.
  35. A reduced order data-driven method for resistance prediction and shape optimization of hull vane, Ocean Engineering 235 (2021) 109406.
  36. Neumann-michell theory-based multi-objective optimization of hull form for a naval surface combatant, Applied Ocean Research 63 (2017) 129–141.
  37. Hull form optimization based on calm-water wave drag with or without generating bulbous bow, Applied Ocean Research 116 (2021) 102861.
  38. Resistance and wake distortion optimization of jbc considering ship-propeller interaction, Ocean Engineering 244 (2022) 110376.
  39. Constrained multi-objective optimization for uav-enabled mobile edge computing: Offloading optimization and path planning, IEEE Wireless Communications Letters 11 (2022) 861–865.
  40. An improved radial basis function for marine vehicle hull form representation and optimization, Ocean Engineering 260 (2022) 112000.
  41. An integrated optimization design of a fishing ship hullform at different speeds, Journal of Hydrodynamics 30 (2018) 1174–1181.
  42. Multiple speed integrated optimization design for a swath using sbd technique, Journal of Marine Science and Technology 25 (2020) 185–195.
  43. Application of mesh deformation and adaptive method in hullform design optimization, Journal of Marine Science and Technology (2022) 1–10.
  44. A. Hamed, Multi-objective optimization method of trimaran hull form for resistance reduction and propeller intake flow improvement, Ocean Engineering 244 (2022) 110352.
  45. Many-objective optimization for a deep-sea aquaculture vessel based on an improved rbf neural network surrogate model, Journal of Marine Science and Technology 26 (2021) 582–605.
  46. Hull form optimization for reduced calm-water resistance and improved vertical motion performance in irregular head waves, Ocean Engineering 233 (2021) 109208.
  47. Hull surface modification for ship resistance performance optimization based on delaunay triangulation, Ocean Engineering 153 (2018) 333–344.
  48. Y. Ichinose, Method involving shape-morphing of multiple hull forms aimed at organizing and visualizing the propulsive performance of optimal ship designs, Ocean Engineering 263 (2022) 112355.
  49. Design-space assessment and dimensionality reduction: An off-line method for shape reparameterization in simulation-based optimization, Ocean Engineering 197 (2020) 106852.
  50. Dynamic space reduction optimization framework and its application in hull form optimization, Applied Ocean Research 114 (2021) 102812.
  51. Shape-supervised dimension reduction: Extracting geometry and physics associated features with geometric moments, Computer-Aided Design 150 (2022) 103327.
  52. Linear reduced order method for design-space dimensionality reduction and flow-field learning in hull form optimization, Ocean Engineering 237 (2021) 109680.
  53. Optimization method for hierarchical space reduction method and its application in hull form optimization, Ocean Engineering 262 (2022) 112108.
  54. Design-space dimensionality reduction in shape optimization by karhunen–loève expansion, Computer Methods in Applied Mechanics and Engineering 283 (2015) 1525–1544.
  55. Hull-form stochastic optimization via computational-cost reduction methods, Engineering with computers 38 (2022) 2245–2269.
  56. High-fidelity global optimization of shape design by dimensionality reduction, metamodels and deterministic particle swarm, Engineering Optimization 47 (2015) 473–494.
  57. Uncertainty quantification of delft catamaran resistance, sinkage and trim for variable froude number and geometry using metamodels, quadrature and karhunen–loève expansion, Journal of Marine Science and Technology 19 (2014) 143–169.
  58. Research on the karhunen–loève transform method and its application to hull form optimization, Journal of Marine Science and Engineering 11 (2023) 230.
  59. Study of a hull form optimization system based on a gaussian process regression algorithm and an adaptive sampling strategy, part i: Single-objective optimization, Ocean Engineering 279 (2023a) 114502.
  60. Study of a hull form optimization system based on a gaussian process regression algorithm and an adaptive sampling strategy, part ii: Multi-objective optimization, Ocean Engineering 286 (2023b) 115501.
  61. Z. Zhou, S. Zhu, Kernel-based multiobjective clustering algorithm with automatic attribute weighting, Soft Computing 22 (2018) 3685–3709.
  62. A new many-objective evolutionary algorithm based on generalized pareto dominance, IEEE Transactions on Cybernetics 52 (2022) 7776–7790.
  63. S. Zhu, L. Xu, Many-objective fuzzy centroids clustering algorithm for categorical data, Expert Systems with Applications 96 (2018) 230–248.
  64. Evolutionary multi-objective automatic clustering enhanced with quality metrics and ensemble strategy, Knowledge-Based Systems 188 (2020) 105018:1–21.
  65. Hierarchical topology-based cluster representation for scalable evolutionary multiobjective clustering, IEEE Transactions on Cybernetics 52 (2022) 9846–9860.
  66. A fast and elitist multiobjective genetic algorithm: Nsga-ii, IEEE transactions on evolutionary computation 6 (2002) 182–197.
  67. Q. Zhang, H. Li, Moea/d: A multiobjective evolutionary algorithm based on decomposition, IEEE Transactions on evolutionary computation 11 (2007) 712–731.
  68. Handling multiple objectives with particle swarm optimization, IEEE Transactions on evolutionary computation 8 (2004) 256–279.
  69. K. Deb, H. Jain, An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part i: solving problems with box constraints, IEEE transactions on evolutionary computation 18 (2013) 577–601.
  70. Multi-fidelity co-kriging surrogate model for ship hull form optimization, Ocean Engineering 243 (2022) 110239.
  71. Optimal design of an autonomous underwater helicopter’s shape based on combinatorial optimization strategy, Ocean Engineering 266 (2022) 113015.
  72. A new approach to system design optimization of underwater gliders, IEEE/ASME Transactions on Mechatronics 27 (2022) 3494–3505.
  73. A new improved artificial bee colony algorithm for ship hull form optimization, Engineering Optimization 48 (2016) 672–686.
  74. Aerodynamic optimization of a luxury cruise ship based on a many-objective optimization system, Ocean Engineering 236 (2021) 109438.
  75. S. Zhang, Research on the deep learning technology in the hull form optimization problem, Journal of Marine Science and Engineering 10 (2022) 1735.
  76. Uncertain multidisciplinary design optimization on next generation subsea production system by using surrogate model and interval method, China Ocean Engineering 35 (2021) 609–621.
  77. M. Diez, D. Peri, Robust optimization for ship conceptual design, Ocean engineering 37 (2010) 966–977.
  78. Hull form reliability-based robust design optimization combining polynomial chaos expansion and maximum entropy method, Applied Ocean Research 90 (2019) 101860.
  79. Parameter selection in synchronous and asynchronous deterministic particle swarm optimization for ship hydrodynamics problems, Applied Soft Computing 49 (2016) 313–334.
  80. Multi-objective optimisation of ship resistance performance based on cfd, Journal of Marine Science and Technology 24 (2019) 152–165.
  81. Parametric design and optimisation of high-speed ro-ro passenger ships, Ocean Engineering 189 (2019) 106346.
  82. Interval optimization design of a submersible surface ship form considering the uncertainty of surrogate model, Ocean Engineering 263 (2022) 112262.
  83. A. Miao, D. Wan, Hull form optimization based on an nm+ cfd integrated method for kcs, International Journal of Computational Methods 17 (2020) 2050008.
  84. Hull form optimization design of swath with combination evaluations of resistance and seakeeping performance, Ocean Engineering 264 (2022) 112513.
  85. Cfd-based multi-objective optimization of a waterjet-propelled trimaran, Ocean Engineering 195 (2020) 106755.
  86. Y.-W. Jung, Y. Kim, Hull form optimization in the conceptual design stage considering operational efficiency in waves, Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment 233 (2019) 745–759.
  87. Multidisciplinary optimization of an offshore aquaculture vessel hull form based on the support vector regression surrogate model, Ocean Engineering 166 (2018) 145–158.
  88. Multi-objective optimization of semi-submersible platforms based on a support vector machine with grid search optimized mixed kernels surrogate model, Ocean Engineering 260 (2022) 112077.
  89. Multiple objective multidisciplinary design optimization of heavier-than-water underwater vehicle using cfd and approximation model, Journal of Marine Science and Technology 22 (2017) 135–148.
  90. Hull form design optimization of twin-skeg fishing vessel for minimum resistance based on surrogate model, Advances in Engineering Software 123 (2018) 38–50.
  91. M. Mittendorf, A. D. Papanikolaou, Hydrodynamic hull form optimization of fast catamarans using surrogate models, Ship Technology Research 68 (2021) 14–26.
  92. Multi-objective optimization of the hull form for the semi-submersible medical platform, Ocean Engineering 230 (2021) 109038.
  93. Design optimization of an unmanned underwater vehicle using low-and high-fidelity models, IEEE Transactions on Systems, Man, and Cybernetics: Systems 47 (2015) 2794–2808.
  94. Formulation and parameter selection of multi-objective deterministic particle swarm for simulation-based optimization, Applied Soft Computing 58 (2017) 714–731.
  95. H. Zakerdoost, H. Ghassemi, A multi-level optimization technique based on fuel consumption and energy index in early-stage ship design, Structural and Multidisciplinary Optimization 59 (2019) 1417–1438.
  96. Multi-objective structural profile optimization of ships based on improved artificial bee colony algorithm and structural component library, Ocean Engineering 283 (2023) 115124.
  97. Multi-objective multidisciplinary design optimization of a robotic fish system, Journal of marine science and engineering 9 (2021) 478.
  98. A. Nazemian, P. Ghadimi, Cfd-based optimization of a displacement trimaran hull for improving its calm water and wavy condition resistance, Applied Ocean Research 113 (2021) 102729.
  99. Computational fluid dynamics-based multiobjective optimization of a surface combatant using a global optimization method, Journal of marine science and technology 13 (2008) 95–116.
  100. Single-and multiobjective design optimization of a fast multihull ship: numerical and experimental results, Journal of marine science and technology 16 (2011) 412–433.
  101. Sample selection method for ship resistance performance optimization based on approximated model, Journal of Ship Research 60 (2016) 1–13.
  102. A marine propeller design method based on two-fidelity data levels, Applied Ocean Research 123 (2022) 103156.
  103. Development and validation of a dynamic metamodel based on stochastic radial basis functions and uncertainty quantification, Structural and Multidisciplinary Optimization 51 (2015) 347–368.
  104. Application of an improved maximum entropy sampling method in hull form optimization, Ocean Engineering 270 (2023) 112702.
  105. An optimal pointwise weighted ensemble of surrogates based on minimization of local mean square error, Structural and Multidisciplinary Optimization 62 (2020) 529–542.
  106. Multi-objective hull form optimization of a swath configuration using surrogate models, Ocean Engineering 256 (2022) 111209.
  107. Design of wake equalizing ducts using ranse-based sbdo, Applied Ocean Research 97 (2020) 102087.
  108. Design optimization of ship hulls via cfd techniques, Journal of ship research 45 (2001) 140–149.
  109. A variable-accuracy metamodel-based architecture for global mdo under uncertainty, Structural and Multidisciplinary Optimization 54 (2016) 573–593.
  110. Multi-objective hydrodynamic optimization of the dtmb 5415 for resistance and seakeeping, in: SNAME International Conference on Fast Sea Transportation, SNAME, 2015, p. D021S005R012.
  111. Bow and stern shape integrated optimization for a full ship by a simulation-based design technique, Journal of Ship Research 58 (2014) 83–96.
  112. A multi-fidelity active learning method for global design optimization problems with noisy evaluations, Engineering with Computers (2022) 1–24.
  113. Comparing multi-index stochastic collocation and multi-fidelity stochastic radial basis functions for forward uncertainty quantification of ship resistance, Engineering with Computers 39 (2023) 2209–2237.
  114. Multi-fidelity hydrodynamic analysis of an autonomous surface vehicle at surveying speed in deep water subject to variable payload, Ocean Engineering 271 (2023) 113529.
  115. Ensemble of surrogates, Structural and Multidisciplinary Optimization 33 (2007) 199–216.
  116. Kriging-based shape optimization framework for blended-wing-body underwater glider with nurbs-based parametrization, Ocean Engineering 219 (2021) 108212.
  117. Y. H. Hou, Hull form uncertainty optimization design for minimum eeoi with influence of different speed perturbation types, Ocean Engineering 140 (2017) 66–72.
  118. Research on the hull form optimization using the surrogate models, Engineering Applications of Computational Fluid Mechanics 15 (2021) 747–761.
  119. J. R. Martins, A. B. Lambe, Multidisciplinary design optimization: a survey of architectures, AIAA journal 51 (2013) 2049–2075.
  120. Ship design optimization with mixed uncertainty based on evidence theory, Ocean Engineering 279 (2023) 114554.
  121. Multidisciplinary robust optimization for ship design, in: 28th symposium on naval hydrodynamic, Pasadena, Caloifornia, USA, 2010.
  122. Heterogeneous ensemble-based infill criterion for evolutionary multiobjective optimization of expensive problems, IEEE transactions on cybernetics 49 (2018) 1012–1025.
  123. Surrogate-assisted autoencoder-embedded evolutionary optimization algorithm to solve high-dimensional expensive problems, IEEE Transactions on Evolutionary Computation 26 (2022) 676–689.
  124. Data-driven evolutionary optimization: An overview and case studies, IEEE Transactions on Evolutionary Computation 23 (2018) 442–458.
  125. When gaussian process meets big data: A review of scalable gps, IEEE transactions on neural networks and learning systems 31 (2020) 4405–4423.
  126. A bi-population cooperative optimization algorithm assisted by an autoencoder for medium-scale expensive problems, IEEE/CAA Journal of Automatica Sinica 9 (2022) 1952–1966.
  127. H. Wang, Y. Jin, A random forest-assisted evolutionary algorithm for data-driven constrained multiobjective combinatorial optimization of trauma systems, IEEE transactions on cybernetics 50 (2018) 536–549.
  128. Data-driven surrogate assisted evolutionary optimization of hybrid powertrain for improved fuel economy and performance, Energy 183 (2019) 235–248.
  129. A novel deep-learning based surrogate modeling of stochastic electric vehicle traffic user equilibrium in low-carbon electricity–transportation nexus, Applied Energy 315 (2022) 118961.
Citations (2)

Summary

We haven't generated a summary for this paper yet.