Neumann-Michell theory-based multi-objective optimization of hull form for a naval surface combatant

Wu, Jianwei; Liu, Xiaoyi; Zhao, Min; Wan, Decheng

doi:10.1016/j.apor.2017.01.007

Cited by 31 publications

(3 citation statements)

References 18 publications

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“…In this part, the proposed IM-DEAM is used to optimise the hull form of the David Taylor Model Basin 5415 (DTMB 5415) vessel [31], and the hull surface modification method is the RBF method that is developed by our research group [32]. The CFD simulation experiment is executed by SHIPFLOW.…”

Section: Application To Hull Form Optimisationmentioning

confidence: 99%

Information Matrix-Based Adaptive Sampling in Hull Form Optimisation

Ouyang

Chang

Feng

et al. 2021

JMSE

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Hull form optimisation involves challenges such as large design spaces, numerous design variables, and high nonlinearity. Therefore, optimisation that only use global approximate models alone cannot yield desirable results. An information matrix-based method is proposed for dynamically embedded local approximate models (IM-DEAM) in this paper, which uses the Gaussian-function information matrix to extract one or more subspaces for additional sampling and a Latin hypercube design (LHD) for adaptive sampling. In addition, to prevent overfitting by global approximate models in some spaces because of the uneven distribution of the samples, local approximate models are embedded in the subspaces identified for additional sampling to enable accurate description of subspaces. The effectiveness and robustness of the method are validated and analysed by applying the proposed method to optimise mathematical functions and the hull form of the DTMB 5415. The results demonstrate that the proposed method is effective for improving the accuracies and can produce reliable optimisation results.

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Section: Application To Hull Form Optimisationmentioning

confidence: 99%

Information Matrix-Based Adaptive Sampling in Hull Form Optimisation

Ouyang

Chang

Feng

et al. 2021

JMSE

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“…As a powerful methodology to solve the complicated design problems of coupled engineering systems, multidisciplinary design optimization (MDO) has received extensive attention from industry and academia (Zhu et al, 2021a, b;Wang et al, 2018a, b;Zadeh et al, 2019;Meng et al, 2018Meng et al, , 2021aHe et al, 2020;Zhang et al, 2016;D ıaz et al, 2017;Xiao et al, 2015;Martins and Lambe, 2013). Following its success in aeronautics and astronautics engineering, the application field of MDO has been widely extended to other engineering fields, such as vehicles and ships (Wang et al, 2014;Jaeger et al, 2013;Balesdent et al, 2012;Miao et al, 2020a, b;Wu et al, 2017;Wang et al, 2017;Meng et al, 2021b;Yin et al, 2020;Shi et al, 2021;Li et al, 2021a, b). In MDO, design variables and parameters are often treated as deterministic input information.…”

Section: Introductionmentioning

confidence: 99%

Multidisciplinary design optimization of engineering systems under uncertainty: a review

Meng

Yang

et al. 2022

IJSI

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PurposeAs an advanced calculation methodology, reliability-based multidisciplinary design optimization (RBMDO) has been widely acknowledged for the design problems of modern complex engineering systems, not only because of the accurate evaluation of the impact of uncertain factors but also the relatively good balance between economy and safety of performance. However, with the increasing complexity of engineering technology, the proposed RBMDO method gradually cannot effectively solve the higher nonlinear coupled multidisciplinary uncertainty design optimization problems, which limits the engineering application of RBMDO. Many valuable works have been done in the RBMDO field in recent decades to tackle the above challenges. This study is to review these studies systematically, highlight the research opportunities and challenges, and attempt to guide future research efforts.Design/methodology/approachThis study presents a comprehensive review of the RBMDO theory, mainly including the reliability analysis methods of different uncertainties and the decoupling strategies of RBMDO.FindingsFirst, the multidisciplinary design optimization (MDO) preliminaries are given. The basic MDO concepts and the corresponding mathematical formulas are illustrated. Then, the procedures of three RBMDO methods with different reliability analysis strategies are introduced in detail. These RBMDO methods were proposed for the design optimization problems under different uncertainty types. Furtherly, an optimization problem for a certain operating condition of a turbine runner blade is introduced to illustrate the engineering application of the above method. Finally, three aspects of future challenges for RBMDO, namely, time-varying uncertainty analysis; high-precision surrogate models, and verification, validation and accreditation (VVA) for the model, are discussed followed by the conclusion.Originality/valueThe scope of this study is to introduce the RBMDO theory systematically. Three commonly used RBMDO-SORA methods are reviewed comprehensively, including the methods' general procedures and mathematical models.

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“…In recent years, with the rapid development of computer and computational fluid dynamics (CFD), simulation-based design (SBD) hull form optimization has been widely used to develop energy-saving ships. Wu et al [1], Miao et al [2], Liu et al [3], and Nazemian et al [4] established an integrated CAD/CFD optimization platform to complete the hull form design through simulation-based optimization and obtained ship forms with excellent hydrodynamic performance. The integrated, multidisciplinary hull form optimization platform includes a hull form design module, hydrodynamic performance evaluation module, and optimization module.…”

Section: Introductionmentioning

confidence: 99%

NURBS-Based Parametric Design for Ship Hull Form

Zhou

Feng

Liu

et al. 2022

JMSE

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Recently, the NURBS technique has been widely used in the 3D design software for ships. However, in most research, the NURBS technique is only applied to the mathematical representation of hull curves and surfaces, and the parametric deformation of hull surfaces based on geometric feature parameters is less understood. The aims of this paper are to establish the parametric design process of hull surfaces through the classification of geometric feature parameters and the design of feature curves, apply the NURBS technique to the parametric geometric modeling of hull curves and surfaces, and finally achieve the parametric deformation of hull surfaces driven by geometric feature parameters and develop the parametric deformation software. Taking the Series 60 ship as an example, we first analyze the hull geometric features and parameters, then design the longitudinal feature curves and cross-section curves based on the NURBS technique and establish the correlation between them, and finally generate the smooth hull surface by the skinning technique to achieve the parametric geometric deformation of the Series 60 ship. The research in this paper shows that the smoothness of the surfaces generated by the NURBS-based parametric design method is good. Additionally, the extracted feature parameters have a clear geometric meaning and can automatically generate hull forms to meet the design requirements quickly and effectively, which has some practical engineering value.

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Neumann-Michell theory-based multi-objective optimization of hull form for a naval surface combatant

Cited by 31 publications

References 18 publications

Information Matrix-Based Adaptive Sampling in Hull Form Optimisation

Information Matrix-Based Adaptive Sampling in Hull Form Optimisation

Multidisciplinary design optimization of engineering systems under uncertainty: a review

NURBS-Based Parametric Design for Ship Hull Form

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