The porosity of cement paste affects its mechanical and thermal properties. Even when two specimens have the same degree of porosity each other, the void distribution considerably affects the behavior of material. To evaluate the material properties of cement pastes statistically, a sensitivity analysis using a First-Order Second-Moment (FOSM) method can be used. This is a probabilistic method to determine the probability distribution of output variables with random input variables. The porosity(φ) and continuity of void (L p area, Ω) are selected as input variables, and the thermal conductivity and stiffness of cement paste are selected as output variables. When a virtual specimen is generated from micro-level computerized tomographic (μ-CT) images of a real cement paste specimen, the specimens that have objective microstructures can be obtained using a reconstruction process. In this study, statistical distributions of input variables are from 64 virtual specimens and output variables are estimated from reconstructed specimens using finite element analysis. Based on sensitivity analysis, sensitivity measures of material properties on both characterizations are evaluated. From this results, the probability distributions of the responses can be estimated and the relation between input and output variables can be evaluated.
|Title of host publication||Computational Modelling of Concrete Structures - Proceedings of the conference on Computational Modelling of Concrete and Concrete Structures, EURO-C 2018|
|Editors||Bernhard Pichler, Jan G. Rots, Günther Meschke|
|Number of pages||8|
|Publication status||Published - 2018|
|Event||Conference on Computational Modelling of Concrete and Concrete Structures, EURO-C 2018 - Bad Hofgastein, Austria|
Duration: 2018 Feb 26 → 2018 Mar 1
|Name||Computational Modelling of Concrete Structures - Proceedings of the conference on Computational Modelling of Concrete&amp;amp;amp;amp;amp;amp;amp;nbsp;and Concrete Structures, EURO-C 2018|
|Conference||Conference on Computational Modelling of Concrete and Concrete Structures, EURO-C 2018|
|Period||18/2/26 → 18/3/1|
Bibliographical noteFunding Information:
This research was supported by a Korea Research Foundation Grant funded by the Korean Government (NRF–2015K1A3A1A59073929 and NRF–2016R1D1A1B03931635).
© 2018 Taylor & Francis Group, London.
All Science Journal Classification (ASJC) codes
- Modelling and Simulation
- Civil and Structural Engineering