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A one-dimensional polynomial chaos method in CFD–Based uncertainty quantification for ship hydrodynamic performance 被引量:5

A one-dimensional polynomial chaos method in CFD–Based uncertainty quantification for ship hydrodynamic performance
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摘要 A one-dimensional non-intrusive Polynomial Chaos (PC) method is applied in Uncertainty Quantification (UQ) studies for CFD-based ship performances simulations. The uncertainty properties of Expected Value (EV) and Standard Deviation (SD) are evaluated by solving the PC coefficients from a linear system of algebraic equations. The one-dimensional PC with the Legendre polynomials is applied to: (1) stochastic input domain and (2) Cumulative Distribution Function (CDF) image domain, allowing for more flexibility. The PC method is validated with the Monte-Carlo benchmark results in several high-fidelity, CFD-based, ship UQ problems, evaluating the geometrical, operational and environmental uncertainties for the Delft Catamaran 372. Convergence is studied versus PC order P for both EV and SD, showing that high order PC is not necessary for present applications. Comparison is carried out for PC with/without the least square minimization when solving the PC coefficients. The least square minimization, using larger number of CFD samples, is recommended for current test cases. The study shows the potentials of PC method in Robust Design Optimization (RDO) and Reliability-Based Design Optimization (RBDO) of ship hydrodynamic performances. A one-dimensional non-intrusive Polynomial Chaos (PC) method is applied in Uncertainty Quantification (UQ) studies for CFD-based ship performances simulations. The uncertainty properties of Expected Value (EV) and Standard Deviation (SD) are evaluated by solving the PC coefficients from a linear system of algebraic equations. The one-dimensional PC with the Legendre polynomials is applied to: (1) stochastic input domain and (2) Cumulative Distribution Function (CDF) image domain, allowing for more flexibility. The PC method is validated with the Monte-Carlo benchmark results in several high-fidelity, CFD-based, ship UQ problems, evaluating the geometrical, operational and environmental uncertainties for the Delft Catamaran 372. Convergence is studied versus PC order P for both EV and SD, showing that high order PC is not necessary for present applications. Comparison is carried out for PC with/without the least square minimization when solving the PC coefficients. The least square minimization, using larger number of CFD samples, is recommended for current test cases. The study shows the potentials of PC method in Robust Design Optimization (RDO) and Reliability-Based Design Optimization (RBDO) of ship hydrodynamic performances.
出处 《Journal of Hydrodynamics》 SCIE EI CSCD 2013年第5期655-662,共8页 水动力学研究与进展B辑(英文版)
基金 Project supported by the National Natural Science Foundation of China(Grant No.50979060)
关键词 Uncertainty Quantification (UQ) Polynomial Chaos (PC) method Legendre polynomials ship design Uncertainty Quantification (UQ), Polynomial Chaos (PC) method, Legendre polynomials, ship design
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参考文献14

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同被引文献69

  • 1WANG XiaoDong1,2 & KANG Shun1 1 Key Laboratory of Condition Monitoring and Control for Power Plant Equipment, Ministry of Education, School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China,2 Department of Mechanical Engineering, Vrije Universiteit Brussel, Brussels 1050, Belgium.Application of polynomial chaos on numerical simulation of stochastic cavity flow[J].Science China(Technological Sciences),2010,53(10):2853-2861. 被引量:9
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  • 6HUANG J., CARRICA P. M. and STERN F. Semi-cou- pled air/water immersed boundary approach for curvili- near dynamic overset grids with application to ship hy- drodynamics[J]. International Journal for Numerical Methods in Fluids, 2008, 58(6): 591-624.
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  • 9WANG Z., YANG J. and STERN F. A new volume-of- fluid method with a constructed distance function on general structured grids[J]. Journal of Computaional Physics, 2012, 231(9): 3703-3722.
  • 10WANG Z., YANG J. and STERN F. A simple and con- servative operator-splitting semi-Lagrangian volume- of-fluid advection scheme[J]. Journal of Computatio- nal Physics, 2012, 231(15): 4981-4992.

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