共查询到19条相似文献,搜索用时 187 毫秒
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对KCS的船首和船尾型线优化开展研究。船体采用径向基函数描述,艏部型线以减小总阻力为目标,艉部型线则侧重于降低尾流不均匀度,以期提高推进效率。在优化过程中,利用基于拉丁超立方采样点构建Kriging近似模型替代直接计算流体力学(CFD)模拟。分别采用多岛遗传算法和非支配排序遗传算法-Ⅱ开展单目标和多目标优化,避免优化的早熟。结果表明,在服务航速下,优化船型的总阻力降低了1.36%,优化船型的伴流目标函数降低了10.2%。在此基础上,进一步针对优化过程中产生的3个优化船型以及原始船型,选用KP505桨进行自航模拟,结果显示虽然阻力有些许增大,但伴流不均匀度明显降低的优化船型的推进效率更优,相对于原始船型,其推进效率最高提升了1.08%。 相似文献
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将船体几何建模重构技术与CFD技术及最优化理论相融合形成的SBD(Simulation Based Design)船型设计方法,使得船型设计从传统经验设计向以数值评估数理寻优为特征的知识化设计新模式转变,为船型设计创新打开了新的局面。本文针对该设计模式中船体几何重构和高精度CFD数值计算网格自适应关键技术进行研究,给出了船体几何整体/局部重构方法及其流程,同时详细阐述了船体表面网格自动变形与体网格自适应方法及其实现过程,突破了高精度CFD方法在船型自动优化流程中应用的瓶颈,为开展SBD船型设计打下了坚实的基础。 相似文献
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基于CFD的KCS船舶艏部型线优化研究 总被引:2,自引:1,他引:1
《江苏船舶》2016,(6):1-6
为实现基于CFD船体型线优化设计,开发了船体型线优化平台,并以KCS船为初始船型,对其艏部型线进行了优化。首先,重点介绍了径向基函数插值的基本原理及其在船体曲面变形中的应用;其次,将该方法与CFD软件及优化算法结合,开发了基于CFD的船体型线优化平台;最后,将该平台应用于KCS船的艏部型线优化设计,获得给定约束条件下阻力性能最优的船体外形。研究结果表明:基于径向基函数船体曲面修改方法是可行的,建立的船型优化平台具有一定的工程应用价值。 相似文献
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基于CFD和响应面方法的最小阻力船型自动优化 总被引:1,自引:0,他引:1
计算流体动力学CFD方法凭借其较高的计算精度和获取更多流场信息的能力逐渐成为新船型设计重要手段.文章利用iSight多学科优化平台建立了一套船型优化系统,集成了CFD技术、船型变换及自动生成技术和响应面代理模型技术和组合优化算法.编制了船型参数变换和生成系统实现了船型变换和CFD计算程序Shipflow输入数据的自动连接;通过对主要船型参数的控制,实现整个船型优化流程的自动化.采用了进化遗传算法(GA)与二次序列规划法(SQP)相结合的二阶组合优化方法实现了从全局探索再到局部空间寻优的整个流程.同时,将响应面近似模型(RSM)引入到优化进程中,解决了计算精度与优化效率间的矛盾,使得高精度的CFD分析工具融入到船舶优化设计进程中成为可能.最后利用该系统对一条设计船的阻力性能进行了优化. 相似文献
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CFD数值模拟技术可以为船舶水下噪声水平和噪声传播提供高精度的预报,同时还可以洞察船体绕流场的变化。本文利用VOF方法与SSTκ-ω两方程湍流模型用于求解船舶非定常粘性流场,并结合FW-H方程进行噪声传播。基于Lighthill声类比理论,对不同球鼻首船型的噪声进行数值计算,对船体流噪声的空间指向性、近远场分布特性进行分析。计算结果表明,CFD技术可以用于模拟分析船舶的绕流场和流致发声问题,能够为低噪声船体线型设计提供参考。 相似文献
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以KCS船型为研究对象,用FRIENDSHIP软件创建CFD数值计算所需的几何模型;将船舶阻力分为兴波阻力和粘性阻力两部分计算,兴波阻力通过基于势流理论方法求解Euler方程得到,粘性阻力根据对RANS方程的求解来获取;将计算结果与实验数据进行对比分析.结果表明该参数化模型适用于CFD数值模拟. 相似文献
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采用遗传算法进行球鼻艏优化的流体动力计算(英文) 总被引:1,自引:0,他引:1
Computational fluid dynamics(CFD) plays a major role in predicting the flow behavior of a ship.With the development of fast computers and robust CFD software,CFD has become an important tool for designers and engineers in the ship industry.In this paper,the hull form of a ship was optimized for total resistance using CFD as a calculation tool and a genetic algorithm as an optimization tool.CFD based optimization consists of major steps involving automatic generation of geometry based on design parameters,automatic generation of mesh,automatic analysis of fluid flow to calculate the required objective/cost function,and finally an optimization tool to evaluate the cost for optimization.In this paper,integration of a genetic algorithm program,written in MATLAB,was carried out with the geometry and meshing software GAMBIT and CFD analysis software FLUENT.Different geometries of additive bulbous bow were incorporated in the original hull based on design parameters.These design variables were optimized to achieve a minimum cost function of "total resistance".Integration of a genetic algorithm with CFD tools proves to be effective for hull form optimization. 相似文献
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Yusuke Tahara Daniele Peri Emilio Fortunato Campana Frederick Stern 《Journal of Marine Science and Technology》2008,13(2):95-116
The main objective of this article is to describe the development of two advanced multiobjective optimization methods based
on derivative-free techniques and complex computational fluid dynamics (CFD) analysis. Alternatives for the geometry and mesh
manipulation techniques are also described. Emphasis is on advanced strategies for the use of computer resource-intensive
CFD solvers in the optimization process: indeed, two up-to-date free surface-fitting Reynolds-averaged Navier-Stokes equation
solvers are used as analysis tools for the evaluation of the objective function and functional constraints. The two optimization
methods are realized and demonstrated on a real design problem: the optimization of the entire hull form of a surface combatant,
the David Taylor Model Basin—Model 5415. Realistic functional and geometrical constraints for preventing unfeasible results
and to get a final meaningful design are enforced and discussed. Finally, a recently proposed verification and validation
methodology is applied to assess uncertainties and errors in simulation-based optimization, based on the differences between
the numerically predicted improvement of the objective function and the actual improvement measured in a dedicated experimental
campaign. The optimized model demonstrates improved characteristics beyond the numerical and experimental uncertainty, confirming
the validity of the simulation-based design frameworks. 相似文献
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