@article{AlaladeReichertKoehnetal.,
  author    = {Alalade, Muyiwa and Reichert, Ina and K{\"o}hn, Daniel and Wuttke, Frank and Lahmer, Tom},
  title     = {A Cyclic Multi-Stage Implementation of the Full-Waveform Inversion for the Identification of Anomalies in Dams},
  series = {Infrastructures},
  volume    = {2022},
  journal   = {Infrastructures},
  number    = {Volume 7, issue 12, article 161},
  editor    = {Qu, Chunxu and Gao, Chunxu and Zhang, Rui and Jia, Ziguang and Li, Jiaxiang},
  publisher = {MDPI},
  address   = {Basel},
  doi       = {10.3390/infrastructures7120161},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20221201-48396},
  pages     = {19},
  abstract  = {For the safe and efficient operation of dams, frequent monitoring and maintenance are required. These are usually expensive, time consuming, and cumbersome. To alleviate these issues, we propose applying a wave-based scheme for the location and quantification of damages in dams. To obtain high-resolution "interpretable" images of the damaged regions, we drew inspiration from non-linear full-multigrid methods for inverse problems and applied a new cyclic multi-stage full-waveform inversion (FWI) scheme. Our approach is less susceptible to the stability issues faced by the standard FWI scheme when dealing with ill-posed problems. In this paper, we first selected an optimal acquisition setup and then applied synthetic data to demonstrate the capability of our approach in identifying a series of anomalies in dams by a mixture of reflection and transmission tomography. The results had sufficient robustness, showing the prospects of application in the field of non-destructive testing of dams.},
  subject      = {Damm},
  language  = {en}
}
@article{ReichertOlneyLahmer,
  author    = {Reichert, Ina and Olney, Peter and Lahmer, Tom},
  title     = {Combined approach for optimal sensor placement and experimental verification in the context of tower-like structures},
  series = {Journal of Civil Structural Health Monitoring},
  volume    = {2021},
  journal   = {Journal of Civil Structural Health Monitoring},
  number    = {volume 11},
  publisher = {Heidelberg},
  address   = {Springer},
  doi       = {10.1007/s13349-020-00448-7},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210804-44701},
  pages     = {223 -- 234},
  abstract  = {When it comes to monitoring of huge structures, main issues are limited time, high costs and how to deal with the big amount of data. In order to reduce and manage them, respectively, methods from the field of optimal design of experiments are useful and supportive. Having optimal experimental designs at hand before conducting any measurements is leading to a highly informative measurement concept, where the sensor positions are optimized according to minimal errors in the structures' models. For the reduction of computational time a combined approach using Fisher Information Matrix and mean-squared error in a two-step procedure is proposed under the consideration of different error types. The error descriptions contain random/aleatoric and systematic/epistemic portions. Applying this combined approach on a finite element model using artificial acceleration time measurement data with artificially added errors leads to the optimized sensor positions. These findings are compared to results from laboratory experiments on the modeled structure, which is a tower-like structure represented by a hollow pipe as the cantilever beam. Conclusively, the combined approach is leading to a sound experimental design that leads to a good estimate of the structure's behavior and model parameters without the need of preliminary measurements for model updating.},
  subject      = {Strukturmechanik},
  language  = {en}
}