This study proposes a method for inversely estimating the spatial distribution characteristic of a material’s elastic modulus using the measured value of the observation data and the distance between the measurement points. The structural factors in the structural system possess temporal and spatial randomness. One of the representative structural factors, the material’s elastic modulus, possesses temporal and spatial randomness in the stiffness of the plate structure. The structural factors with randomness are typically modeled as having a certain probability distribution (probability density function) and a probability characteristic (mean and standard deviation). However, this method does not consider spatial randomness. Even if considered, the existing method presents limitations because it does not know the randomness of the actual material. To overcome the limitations, we propose a method to numerically define the spatial randomness of the material’s elastic modulus and confirm factors such as response variability and response variance.
|Number of pages||17|
|Publication status||Published - 2020 Jun|
Bibliographical noteFunding Information:
Funding: This project was received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant agreement no. 841592. Pawel Sikora is supported by the Foundation for Polish Science.
Acknowledgments: The authors would like to acknowledge that this work was supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) and the grant was funded by the Ministry of Land, Infrastructure and Transport (Grant 13IFIP-C113546-01 and Grant 20NANO-B156177-01).
This project was received funding from the European Union?s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant agreement no. 841592. Pawel Sikora is supported by the Foundation for Polish Science.
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
All Science Journal Classification (ASJC) codes
- Chemical Engineering(all)
- Materials Science(all)
- Condensed Matter Physics
- Inorganic Chemistry