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Multifidelity Modeling By Polynomial Chaos-Based Cokriging To Enable Efficient Model-Based Reliability Analysis Of Ndt Systems, Xiaosong Du, Leifur Leifsson
Multifidelity Modeling By Polynomial Chaos-Based Cokriging To Enable Efficient Model-Based Reliability Analysis Of Ndt Systems, Xiaosong Du, Leifur Leifsson
Mechanical and Aerospace Engineering Faculty Research & Creative Works
This work proposes a novel multifidelity metamodeling approach, the polynomial chaos-based Cokriging (PC-Cokriging). The proposed approach is used for fast uncertainty propagation in a reliability analysis of nondestructive testing systems using model-assisted probability of detection (MAPOD). In particular, PC-Cokriging is a multivariate version of polynomial chaos-based Kriging (PC-Kriging), which aims at combining the advantages of the regression-based polynomial chaos expansions and the interpolation-based Kriging metamodeling methods. Following a similar process as Cokriging, the PC-Cokriging advances PC-Kriging by enabling the incorporation of multifidelity physics information. The proposed PC-Cokriging is demonstrated on two analytical functions and three ultrasonic testing MAPOD cases. The …
Fast Uncertainty Propagation Of Ultrasonic Testing Simulations For Mapod And Sensitivity Analysis, Xiaosong Du, Leifur Leifsson, Praveen Gurrala, Jiming Song, Slawomir Koziel
Fast Uncertainty Propagation Of Ultrasonic Testing Simulations For Mapod And Sensitivity Analysis, Xiaosong Du, Leifur Leifsson, Praveen Gurrala, Jiming Song, Slawomir Koziel
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Model-assisted probability of detection (MAPOD) and sensitivity analysis (SA) are widelyused for measuring the reliability of nondestructive testing (NDT) systems., such as ultrasonictesting (UT), and understanding the effects of uncertainty parameters. In this work, a stochastic expansion-based metamodel is used in lieu of the physics-based NDT simulation model for efficient uncertainty propagation while keeping satisfactory accuracy. The proposed stochasticmetamodeling approach is demonstrated for MAPOD and SA on a benchmark case for UT simulations on a fused quartz block with a spherically-void defect. The proposed approach is compared with direct Monte Carlo sampling (MCS), and MCS with Kriging metamodels. The results …