Gast ::
| Hauptseite > Publikationsdatenbank > Non-destructive testing and interior transmission eigenvalues > print |
| Hauptseite > Publikationsdatenbank > Non-destructive testing and interior transmission eigenvalues > print |
| 001 | 830540 | ||
| 005 | 20210129230534.0 | ||
| 037 | _ | _ | |a FZJ-2017-04072 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |a Kleefeld, Andreas |0 P:(DE-Juel1)169421 |b 0 |e Corresponding author |u fzj |
| 111 | 2 | _ | |a Applied Inverse Problems 2017 |g AIP2017 |c Hangzhou |d 2017-05-29 - 2017-06-02 |w China |
| 245 | _ | _ | |a Non-destructive testing and interior transmission eigenvalues |
| 260 | _ | _ | |c 2017 |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a Other |2 DataCite |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a LECTURE_SPEECH |2 ORCID |
| 336 | 7 | _ | |a Conference Presentation |b conf |m conf |0 PUB:(DE-HGF)6 |s 1497254935_22221 |2 PUB:(DE-HGF) |x After Call |
| 520 | _ | _ | |a The objective in non-destructive testing is to obtain a visualization of a given three-dimensional object's interior in order to reveal location, size, and geometry of inhomogeneities. Interior transmission eigenvalues can be used for this task. However, the efficient numerical calculation of the interior transmission eigenvalues is a challenging problem due to the fact that the corresponding interior transmission problem is non-linear, non-elliptic, and non-self-adjoint. In this talk, it is explained what interior transmission eigenvalues are, how they can be computed to high accuracy using boundary integral equations, andhow they can be used to visualize the interior of a given object.Finally, some open problems both from the theoretical and practical point of view are exemplified. |
| 536 | _ | _ | |a 511 - Computational Science and Mathematical Methods (POF3-511) |0 G:(DE-HGF)POF3-511 |c POF3-511 |f POF III |x 0 |
| 909 | C | O | |o oai:juser.fz-juelich.de:830540 |p VDB |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)169421 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |1 G:(DE-HGF)POF3-510 |0 G:(DE-HGF)POF3-511 |2 G:(DE-HGF)POF3-500 |v Computational Science and Mathematical Methods |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |l Supercomputing & Big Data |
| 914 | 1 | _ | |y 2017 |
| 920 | _ | _ | |l no |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
| 980 | _ | _ | |a conf |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
| 980 | _ | _ | |a UNRESTRICTED |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|