http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Bin Yang,Kai-Uwe Bletzinger,Qilin Zhang,Zhihao Zhou 대한토목학회 2013 KSCE Journal of Civil Engineering Vol.17 No.6
As a comparatively new developed stochastic method - Particle Swarm Optimization (PSO), it is widely applied to various kinds of optimization problems especially of nonlinear, non-differentiable or non-concave types. In this paper, a Parallel Modified Guaranteed Converged Particle Swarm algorithm (PMGCPSO) is proposed, which is inspired by the Guaranteed Converged Particle Swarm algorithm (GCPSO) proposed by von den Bergh. Details in the algorithm implementation and properties are presented and, an analytical benchmark test and structural sizing and topological test cases are used to evaluate the performance of the proposed PSO variant, PMGCPSO exhibited competitive performance due to improved global searching ability and its corresponding parallel model indicates nice parallel efficiency.
Mayu Sakuma,Nick Pepper,Suneth Warnakulasuriya,Francesco Montomoli,Roland Wüchner,Kai-Uwe Bletzinger 한국풍공학회 2022 Wind and Structures, An International Journal (WAS Vol.34 No.1
In this work a multi-fidelity non-intrusive polynomial chaos (MF-NIPC) has been applied to a structural wind engineering problem in architectural design for the first time. In architectural design it is important to design structures that are safe in a range of wind directions and speeds. For this reason, the computational models used to design buildings and bridges must account for the uncertainties associated with the interaction between the structure and wind. In order to use the numerical simulations for the design, the numerical models must be validated by experi-mental data, and uncertainties contained in the experiments should also be taken into account. Uncertainty Quantifi-cation has been increasingly used for CFD simulations to consider such uncertainties. Typically, CFD simulations are computationally expensive, motivating the increased interest in multi-fidelity methods due to their ability to lev-erage limited data sets of high-fidelity data with evaluations of more computationally inexpensive models. Previous-ly, the multi-fidelity framework has been applied to CFD simulations for the purposes of optimization, rather than for the statistical assessment of candidate design. In this paper MF-NIPC method is applied to flow around a rectan-gular 5:1 cylinder, which has been thoroughly investigated for architectural design. The purpose of UQ is validation of numerical simulation results with experimental data, therefore the radius of curvature of the rectangular cylinder corners and the angle of attack are considered to be random variables, which are known to contain uncertainties when wind tunnel tests are carried out. Computational Fluid Dynamics (CFD) simulations are solved by a solver that employs the Finite Element Method (FEM) for two turbulence modeling approaches of the incompressible Navier-Stokes equations: Unsteady Reynolds Averaged Navier Stokes (URANS) and the Large Eddy simulation (LES). The results of the uncertainty analysis with CFD are compared to experimental data in terms of time-averaged pressure coefficients and bulk parameters. In addition, the accuracy and efficiency of the multi-fidelity framework is demonstrated through a comparison with the results of the highfidelity model.