Life Prediction of Hydraulic Concrete Based on Grey Residual Markov Model
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초록
Hydraulic concrete buildings in the northwest of China are often subject to the combined effects of lowtemperaturefrost damage, during drying and wetting cycles, and salt erosion, so the study of concretedeterioration prediction is of major importance. The prediction model of the relative dynamic elastic modulus(RDEM) of four different kinds of modified concrete under the special environment in the northwest of Chinawas established using Grey residual Markov theory. Based on the available test data, modified values of thedynamic elastic modulus were obtained based on the Grey GM(1,1) model and the residual GM(1,1) model,combined with the Markov sign correction, and the dynamic elastic modulus of concrete was predicted. Thecomputational analysis showed that the maximum relative error of the corrected dynamic elastic modulus wassignificantly reduced, from 1.599% to 0.270% for the BS2 group. The analysis error showed that the modelwas more adjusted to the concrete mixed with fly ash and mineral powder, and its calculation error wassignificantly lower than that of the rest of the groups. The analysis of the data for each group proved that themodel could predict the loss of dynamic elastic modulus of the deterioration of the concrete effectively, as wellas the number of cycles when the concrete reached the damaged state.
Abstract
Hydraulic concrete buildings in the northwest of China are often subject to the combined effects of lowtemperaturefrost damage, during drying and wetting cycles, and salt erosion, so the study of concretedeterioration prediction is of major importance. The prediction model of the relative dynamic elastic modulus(RDEM) of four different kinds of modified concrete under the special environment in the northwest of Chinawas established using Grey residual Markov theory. Based on the available test data, modified values of thedynamic elastic modulus were obtained based on the Grey GM(1,1) model and the residual GM(1,1) model,combined with the Markov sign correction, and the dynamic elastic modulus of concrete was predicted. Thecomputational analysis showed that the maximum relative error of the corrected dynamic elastic modulus wassignificantly reduced, from 1.599% to 0.270% for the BS2 group. The analysis error showed that the modelwas more adjusted to the concrete mixed with fly ash and mineral powder, and its calculation error wassignificantly lower than that of the rest of the groups. The analysis of the data for each group proved that themodel could predict the loss of dynamic elastic modulus of the deterioration of the concrete effectively, as wellas the number of cycles when the concrete reached the damaged state.
참고문헌 (9)
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