Abstract
We are concerned with high-fidelity subsurface imaging of the soil, which commonly arises in geotechnical site characterization and geophysical explorations. Specifically, we attempt to image the spatial distribution of the Lamé parameters in semi-infinite, three-dimensional, arbitrarily heterogeneous formations, using surficial measurements of the soil's response to probing elastic waves. We use the complete waveform response of the medium to drive the inverse problem, by using a partial-differential-equation (PDE)-constrained optimization approach, directly in the time-domain, to minimize the misfit between the observed response of the medium at select measurement locations, and a computed response corresponding to a trial distribution of the Lamé parameters. We discuss strategies that lend algorithmic robustness to our proposed inversion scheme. To limit the computational domain to the size of interest, we employ perfectly-matched-layers (PMLs).In order to resolve the forward problem, we use a recently developed hybrid finite element approach, where a displacement-stress formulation for the PML is coupled to a standard displacement-only formulation for the interior domain, thus leading to a computationally cost-efficient scheme. Time-integration is accomplished by using an explicit Runge-Kutta scheme, which is well-suited for large-scale problems on parallel computers.We verify the accuracy of the material gradients obtained via our proposed scheme, and report numerical results demonstrating successful reconstruction of the two Lamé parameters for both smooth and sharp profiles.
Original language | English (US) |
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Pages (from-to) | 39-72 |
Number of pages | 34 |
Journal | Computer Methods in Applied Mechanics and Engineering |
Volume | 296 |
DOIs | |
State | Published - Aug 15 2015 |
Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2022-06-07Acknowledgements: The first author wishes to thank Dr. Georg Stadler of Courant Institute of Mathematical Sciences for fruitful discussions and helpful comments. We would also like to thank the two anonymous reviewers whose comments improved the quality of this paper. Partial support for the authors’ research has been provided by the National Science Foundation under grant awards CMMI-0619078 and CMMI-1030728 , and through an Academic Alliance Excellence grant between the King Abdullah University of Science and Technology in Saudi Arabia (KAUST) and the University of Texas at Austin. This support is gratefully acknowledged.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
ASJC Scopus subject areas
- General Physics and Astronomy
- Mechanics of Materials
- Mechanical Engineering
- Computational Mechanics
- Computer Science Applications