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Xiaosong Du
Iowa State University
24Publications
3H-index
25Citations
Publications 26
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#1Leifur Leifsson (Iowa State University)H-Index: 8
#2Xiaosong Du (Iowa State University)H-Index: 3
Last.Slawomir Koziel (RU: Reykjavík University)H-Index: 44
view all 3 authors...
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#1Xiaosong Du (Iowa State University)H-Index: 3
#2Leifur Leifsson (Iowa State University)H-Index: 15
Last.Leifur Leifsson (Iowa State University)H-Index: 8
view all 2 authors...
Abstract In this work, utility theory is introduced to optimum aerodynamic shape design under uncertainty (also called robust aerodynamic design). Specifically, utility theory is used to formulate the objective function of the optimization problem. The advantage of the proposed approach over the commonly used weighted sum method is that it does not require the use of weighting factors or the addition of constraints on the statistical moments. The polynomial chaos expansion metamodel with the lea...
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#1Xiaosong Du (Iowa State University)H-Index: 3
#2Leifur Leifsson (Iowa State University)H-Index: 8
Last.Leifur Leifsson (Iowa State University)H-Index: 15
view all 2 authors...
Abstract This work introduces multifidelity metamodeling for reliability analysis of nondestructive testing (NDT) systems. Specifically, the Cokriging metamodel is utilized to accelerate the uncertainty propagation within model-assisted probability of detection (MAPOD) analysis of ultrasonic testing (UT) systems. The Cokriging multifidelity metamodel fuses a limited amount of data obtained from high-fidelity (HF) physics-based UT models, which are accurate but time-consuming to evaluate, with a ...
2 CitationsSource
#1Xiaosong Du (Iowa State University)H-Index: 3
#2Leifur Leifsson (Iowa State University)H-Index: 15
Last.Ronald A. Roberts (Iowa State University)H-Index: 10
view all 6 authors...
1 CitationsSource
Model-assisted probability of detection (MAPOD) is an important approach used as part of assessing the reliability of nondestructive testing systems. The purpose of this paper is to apply the polynomial chaos-based Kriging (PCK) metamodeling method to MAPOD for the first time to enable efficient uncertainty propagation, which is currently a major bottleneck when using accurate physics-based models.,In this paper, the state-of-the-art Kriging, polynomial chaos expansions (PCE) and PCK are applied...
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#1Xiaosong Du (Iowa State University)H-Index: 3
#2Leifur Leifsson (Iowa State University)H-Index: 15
Last.Slawomir Koziel (RU: Reykjavík University)H-Index: 44
view all 3 authors...
Yield estimation of antenna systems is important to check their robustness with respect to the uncertain sources. Since the Monte Carlo sampling-based real physics simulation model evaluations are computationally intensive, this work proposes the polynomial chaos-Kriging (PC-Kriging) metamodeling technique for fast yield estimation. PC-Kriging integrates the polynomial chaos expansion (PCE) as the trend function of Kriging metamodel since the PCE is good at capturing the function tendency and Kr...
Source
#1Xiaosong Du (Iowa State University)H-Index: 3
#2Leifur Leifsson (Iowa State University)H-Index: 15
Last.Slawomir Koziel (RU: Reykjavík University)H-Index: 44
view all 3 authors...
The PC-Kriging metamodeling method is proposed for yield estimation of multi-band patch antennas. PC-Kriging is a combination of polynomial chaos expansion (PCE) and Kriging metamodeling, where PCE is used as a trend function for the Kriging interpolation metamodel. The method is demonstrated on the Ishigami analytical function and a dual-band patch antenna. The PC-Kriging is shown to reach the prescribed accuracy limit with significantly fewer training points than both PCE and Kriging. This tra...
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#1Jin YanH-Index: 2
#2Xiaosong DuH-Index: 3
Last.An ChenH-Index: 12
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#1Xiaosong Du (Iowa State University)H-Index: 3
#2Jie Ren (Iowa State University)H-Index: 3
Last.Leifur Leifsson (Iowa State University)H-Index: 15
view all 3 authors...
Abstract Aerodynamic inverse design is proposed using multifidelity models and the manifold mapping (MM) technique. Aerodynamic inverse design aims at achieving a target performance characteristic, such as a pressure coefficient distribution of an airfoil or local lift distribution of a wing. Due to the high computational cost of accurate aerodynamic models and the large number of design variables, the overall cost of inverse design can be prohibitive. The MM-based optimization algorithm leverag...
3 CitationsSource
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