Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Engineering
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 …
Multifidelity Modeling Of Ultrasonic Testing Simulations With Cokriging, Leifur Leifsson, Xiaosong Du, Slawomir Koziel
Multifidelity Modeling Of Ultrasonic Testing Simulations With Cokriging, Leifur Leifsson, Xiaosong Du, Slawomir Koziel
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Multifidelity methods are introduced to the nondestructive evaluation (NDE) of measurement systems. In particular, Cokriging interpolation metamodels of physics-based ultrasonic testing (UT) simulation responses are utilized to accelerate the uncertainty propagation in model-assisted NDE. The proposed approach is applied to a benchmark test case of UT simulations and compared with the current state-of-the-art techniques. The results show that Cokriging captures the physics of the problem well and is able to reduce the computational burden by over one order of magnitude compared to the state of the art. To the best of the author's knowledge, this the first time multifidelity methods …