[P2-56] Estimation for probabilistic distribution of material response according to microstructural characteristics
There is a strong correlation between the material microstructure and its response [1]. It is expected that the statistical distribution of material response has a relation with that of the microstructure characteristics, so that the effect of the microstructure to the response can be investigated. In this study, the sensitivity of the material responses due to microstructural characteristics is investigated using a first-order second moment (FOSM) method [2]. The FOSM method is a probabilistic method, which determines the mean and deviation of a function of responses with random input variables. For applying the FOSM method, specimens with certain microstructure characteristics might have to be reconstructed. For this reason, the reconstruction process [3] to generate the target specimens are needed. The area of lineal-path function and porosity of cement paste specimens are selected as random input variables, and the stiffness and strength evaluated by phase field fracture model are selected as output variables. The result of sensitivity analysis from the FOSM method is compared to the simulation results using whole specimens. From this result, the sensitivity of material response to microstructure is estimated using two reconstructed specimens, and the FOSM method is confirmed to reduce the time and cost for evaluating the probabilistic distribution of properties.
[1] Mindess, S., Young, J. F., and Darwin, D. Concrete. 2nd ed. Prentice Hall U.S.A. (2003) 57-80.
[2] Lee, T.-H. Probabilistic Seismic Evaluation of Reinforced Concrete Structural Components and Systems. University of California, Berkeley (2005).
[3] Chung, S.-Y., Han, T.-S., Kim, S.-Y., and Lee, T.-H. Investigation of the permeability of porous concrete reconstructed using probabilistic description methods. Construction and Building Materials (2014) 66:760-770.
[1] Mindess, S., Young, J. F., and Darwin, D. Concrete. 2nd ed. Prentice Hall U.S.A. (2003) 57-80.
[2] Lee, T.-H. Probabilistic Seismic Evaluation of Reinforced Concrete Structural Components and Systems. University of California, Berkeley (2005).
[3] Chung, S.-Y., Han, T.-S., Kim, S.-Y., and Lee, T.-H. Investigation of the permeability of porous concrete reconstructed using probabilistic description methods. Construction and Building Materials (2014) 66:760-770.