Abstract
Ultrasonic testing (UT) is used to detect internal flaws in materials and to characterize material properties. In many applications, computational simulations are an important part of the inspection-design and analysis processes. Having fast surrogate models for UT simulations is key for enabling efficient inverse analysis and model-assisted probability of detection (MAPOD). In many cases, it is impractical to perform the aforementioned tasks in a timely manner using current simulation models directly. Fast surrogate models can make these processes computationally tractable. This paper presents investigations of using surrogate modeling techniques to create fast approximate models of UT simulator responses. In particular, we propose to integrate data-driven methods (here, kriging interpolation with variable-fidelity models to construct an accurate and fast surrogate model. These techniques are investigated using test cases involving UT simulations of solid components immersed in a water bath during the inspection process. We will apply the full ultrasonic solver and the surrogate model to the detection and characterization of the flaw. The methods will be compared in terms of quality of the responses.
Recommended Citation
X. Du et al., "Surrogate Modeling of Ultrasonic Simulations using Data-Driven Methods," AIP Conference Proceedings, vol. 1806, article no. 150002, American Institute of Physics, Feb 2017.
The definitive version is available at https://doi.org/10.1063/1.4974726
Department(s)
Mechanical and Aerospace Engineering
International Standard Book Number (ISBN)
978-073541474-7
International Standard Serial Number (ISSN)
1551-7616; 0094-243X
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2023 American Institute of Physics, All rights reserved.
Publication Date
16 Feb 2017
