Drying shrinkage of thermal insulation mortar with glazed hollow beads was measured by a vertical length comparator, and the influences of fly ash with different contents(0, 18%, 36%, and 54% were used) on the long-...Drying shrinkage of thermal insulation mortar with glazed hollow beads was measured by a vertical length comparator, and the influences of fly ash with different contents(0, 18%, 36%, and 54% were used) on the long-term drying shrinkage were discussed. The mass loss was measured by the weighting method and the pore structure was characterized using three different methods, including the light microscopy, the mercury intrusion porosimetry(MIP), and the nitrogen adsorption/desorption(NAD) experiments, and the correlations among them were researched. The results show that drying shrinkage process of thermal insulation mortar includes three steps with increasing curing time: the acceleration period(before 7 d), the deceleration period(7-365 d), and the metastable period(after 365 d). Drying shrinkage in the first stage(7 d before) increases quickly owing to the fast water loss, and its development in the last two stages is attributed to the increment of the pore volume of mortar with the radius below 50 nm, especially the increment of the pore volume fraction of the pore radius within the size range between 7.3 nm and 12.3 nm. There is no change in the drying shrinkage development trend of mortar with fly ash addition, and three steps in the service life, but fly ash addition in the mortar restrains its value. There is a linear relationship between the drying shrinkage and fly ash content, which means that drying shrinkage reduces with fly ash addition.展开更多
This study explored the potential of using probabilistic neural networks (PNN) to predict shrinkage of thermal insulation mortar.Probabilistic results were obtained from the PNN model with the aid of Parzen non-parame...This study explored the potential of using probabilistic neural networks (PNN) to predict shrinkage of thermal insulation mortar.Probabilistic results were obtained from the PNN model with the aid of Parzen non-parametric estimator of the probability density functions (PDF).Five variables,water-cementitious materials ratio,content of cement,fly ash,aggregate and plasticizer,were employed for input variables,while a category of 56-d shrinkage of mortar was used for the output variable.A total of 192 groups of experimental data from 64 mixtures designed using JMP7.0 software were collected,of which 120 groups of data were used for training the model and the other 72 groups of data for testing.The simulation results showed that the PNN model with an optimal smoothing parameter determined by the curves of the mean square error (MSE) and the number of unrecognized probability densities (UPDs) exhibited a promising capability of predicting shrinkage of mortar.展开更多
基金Funded by the National Key Technology R&D Program of China during the 12th Five-year Plan(No.2012BAJ20B02)
文摘Drying shrinkage of thermal insulation mortar with glazed hollow beads was measured by a vertical length comparator, and the influences of fly ash with different contents(0, 18%, 36%, and 54% were used) on the long-term drying shrinkage were discussed. The mass loss was measured by the weighting method and the pore structure was characterized using three different methods, including the light microscopy, the mercury intrusion porosimetry(MIP), and the nitrogen adsorption/desorption(NAD) experiments, and the correlations among them were researched. The results show that drying shrinkage process of thermal insulation mortar includes three steps with increasing curing time: the acceleration period(before 7 d), the deceleration period(7-365 d), and the metastable period(after 365 d). Drying shrinkage in the first stage(7 d before) increases quickly owing to the fast water loss, and its development in the last two stages is attributed to the increment of the pore volume of mortar with the radius below 50 nm, especially the increment of the pore volume fraction of the pore radius within the size range between 7.3 nm and 12.3 nm. There is no change in the drying shrinkage development trend of mortar with fly ash addition, and three steps in the service life, but fly ash addition in the mortar restrains its value. There is a linear relationship between the drying shrinkage and fly ash content, which means that drying shrinkage reduces with fly ash addition.
基金Project (No. 2006BAJ05B03) supported by the National Key Tech-nologies Supporting Program of China during the 11th Five-Year Plan Period
文摘This study explored the potential of using probabilistic neural networks (PNN) to predict shrinkage of thermal insulation mortar.Probabilistic results were obtained from the PNN model with the aid of Parzen non-parametric estimator of the probability density functions (PDF).Five variables,water-cementitious materials ratio,content of cement,fly ash,aggregate and plasticizer,were employed for input variables,while a category of 56-d shrinkage of mortar was used for the output variable.A total of 192 groups of experimental data from 64 mixtures designed using JMP7.0 software were collected,of which 120 groups of data were used for training the model and the other 72 groups of data for testing.The simulation results showed that the PNN model with an optimal smoothing parameter determined by the curves of the mean square error (MSE) and the number of unrecognized probability densities (UPDs) exhibited a promising capability of predicting shrinkage of mortar.