The unconfined compressive strength(UCS)of alkali-activated slag(AAS)-based cemented paste backfill(CPB)is influenced by multiple design parameters.However,the experimental methods are limited to understanding the rel...The unconfined compressive strength(UCS)of alkali-activated slag(AAS)-based cemented paste backfill(CPB)is influenced by multiple design parameters.However,the experimental methods are limited to understanding the relationships between a single design parameter and the UCS,independently of each other.Although machine learning(ML)methods have proven efficient in understanding relationships between multiple parameters and the UCS of ordinary Portland cement(OPC)-based CPB,there is a lack of ML research on AAS-based CPB.In this study,two ensemble ML methods,comprising gradient boosting regression(GBR)and random forest(RF),were built on a dataset collected from literature alongside two other single ML methods,support vector regression(SVR)and artificial neural network(ANN).The results revealed that the ensemble learning methods outperformed the single learning methods in predicting the UCS of AAS-based CPB.Relative importance analysis based on the bestperforming model(GBR)indicated that curing time and water-to-binder ratio were the most critical input parameters in the model.Finally,the GBR model with the highest accuracy was proposed for the UCS predictions of AAS-based CPB.展开更多
The effect of magnesia bumt at 800-950℃ on the properties, especially the shrinkage, of alkali-activated slag cement (AASC.) was experimentally studied. Experimental results show that, although adding 4%-8% lightly...The effect of magnesia bumt at 800-950℃ on the properties, especially the shrinkage, of alkali-activated slag cement (AASC.) was experimentally studied. Experimental results show that, although adding 4%-8% lightly-burnt magnesia may shorten the setting time and slightly reduce the compressive strength of AASC, it c, an remarkably reduce the shrinkage of AASC. The results also show that the setting time of AASC with a certain amount of magnesia increases with the buming temperature, and that the flexural and compressive strengths of AASC decrease with the increase of the additive amount of magnesia. Generally, the adverse effect of magnesia decreases with the increase of the burning temperature:, and the shrinkage-reducing effect of magnesia increases with the additive amount of magnesia. X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses show that some magnesia particles in the hardened AASC paste at a 28-d age remained unhydrated, and that the compactness decreased a little as magnesia was added. We can also conclude that magnesia bumt at 850-950℃ can be used to reduce the shrinkage of AASC only when its additive amount does not exceed 8%; otherwise, the setting time may be too short, and the flexural and compressive strengths may severely decrease.展开更多
The dielectric performance of alkali activated slag (AAS) cement paste was investigated in the frequency range of 1 to 1000 MHz. The experimental results showed the unstable dielectric properties of harden paste wer...The dielectric performance of alkali activated slag (AAS) cement paste was investigated in the frequency range of 1 to 1000 MHz. The experimental results showed the unstable dielectric properties of harden paste were mostly influenced by the fraction of free water in paste or absorbed water from ambient, but not including hydration water and microstructure. The free water was completely eliminated by heat treatment at 105 ℃ about 4 hours, and then its dielectric loss was depressed; but with the exposure time in air increasing, the free water adsorption in ambient air made the dielectric property of harden cement paste to be bad. The temperature and relative humidity of environment was the key factors of free water adsorption; hence, if the influence of free water on dielectric constant was measured or eliminated, the cement-based materials may be applied in humidity sensitive materials or dielectric materials domains.展开更多
Alkali-activated cement(AAC)is either clinker-less or free,and it is also environmentally friendly due to its low carbon footprint and wide range sources.Industrial wastes,like steel slag and blastfurnace slag,usually...Alkali-activated cement(AAC)is either clinker-less or free,and it is also environmentally friendly due to its low carbon footprint and wide range sources.Industrial wastes,like steel slag and blastfurnace slag,usually have latent hydraulic reactivity,and can be used as precursors of AAC.Both clinkerless and clinker-free AAC were prepared from the mixture of steel slag and blastfurnace slag by using water glass as an activator,and four different recipes which satisfied the strength requirement of 42.5R Portland cement were obtained.Each recipe of AAC exhibited better resistance to sulfate attack and frost attack than Portland cement.AAC showed huge drying shrinkage,but it was equivalent to that of Portland cement as steel slag content increased to 40%.The AAC also had quite low risk of alkali-aggregate reaction.Microstructure analysis showed that the major products were calcium silicate hydrate(C–S–H),calcium aluminosilicate hydrate(C–A–S–H)and zeolite-like phases.Ettringite was also detected in the binder when gypsum was contained in the precursors.展开更多
基金funded by the Natural Sciences and Engineering Research Council of Canada(NSERC RGPIN-2017-05537).
文摘The unconfined compressive strength(UCS)of alkali-activated slag(AAS)-based cemented paste backfill(CPB)is influenced by multiple design parameters.However,the experimental methods are limited to understanding the relationships between a single design parameter and the UCS,independently of each other.Although machine learning(ML)methods have proven efficient in understanding relationships between multiple parameters and the UCS of ordinary Portland cement(OPC)-based CPB,there is a lack of ML research on AAS-based CPB.In this study,two ensemble ML methods,comprising gradient boosting regression(GBR)and random forest(RF),were built on a dataset collected from literature alongside two other single ML methods,support vector regression(SVR)and artificial neural network(ANN).The results revealed that the ensemble learning methods outperformed the single learning methods in predicting the UCS of AAS-based CPB.Relative importance analysis based on the bestperforming model(GBR)indicated that curing time and water-to-binder ratio were the most critical input parameters in the model.Finally,the GBR model with the highest accuracy was proposed for the UCS predictions of AAS-based CPB.
基金supported by the National Natural Science Foundation of China (Grant No. 51139001)the Natural Science Foundation of Jiangsu Province, China (Grant No. BK2009345)the Fundamental Research Funds for the Central Universities from the Ministry of Education of China (Grant No.2010B19914)
文摘The effect of magnesia bumt at 800-950℃ on the properties, especially the shrinkage, of alkali-activated slag cement (AASC.) was experimentally studied. Experimental results show that, although adding 4%-8% lightly-burnt magnesia may shorten the setting time and slightly reduce the compressive strength of AASC, it c, an remarkably reduce the shrinkage of AASC. The results also show that the setting time of AASC with a certain amount of magnesia increases with the buming temperature, and that the flexural and compressive strengths of AASC decrease with the increase of the additive amount of magnesia. Generally, the adverse effect of magnesia decreases with the increase of the burning temperature:, and the shrinkage-reducing effect of magnesia increases with the additive amount of magnesia. X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses show that some magnesia particles in the hardened AASC paste at a 28-d age remained unhydrated, and that the compactness decreased a little as magnesia was added. We can also conclude that magnesia bumt at 850-950℃ can be used to reduce the shrinkage of AASC only when its additive amount does not exceed 8%; otherwise, the setting time may be too short, and the flexural and compressive strengths may severely decrease.
文摘The dielectric performance of alkali activated slag (AAS) cement paste was investigated in the frequency range of 1 to 1000 MHz. The experimental results showed the unstable dielectric properties of harden paste were mostly influenced by the fraction of free water in paste or absorbed water from ambient, but not including hydration water and microstructure. The free water was completely eliminated by heat treatment at 105 ℃ about 4 hours, and then its dielectric loss was depressed; but with the exposure time in air increasing, the free water adsorption in ambient air made the dielectric property of harden cement paste to be bad. The temperature and relative humidity of environment was the key factors of free water adsorption; hence, if the influence of free water on dielectric constant was measured or eliminated, the cement-based materials may be applied in humidity sensitive materials or dielectric materials domains.
基金supported by the Natural Science Foundation Project of Chongqing(cstc2020jcyj-msxmX0954)the Chongqing Outstanding Youth Project(cstc2019JCYJQX0024)the National Natural Science Foundation of China(52204415.U1902217)。
文摘Alkali-activated cement(AAC)is either clinker-less or free,and it is also environmentally friendly due to its low carbon footprint and wide range sources.Industrial wastes,like steel slag and blastfurnace slag,usually have latent hydraulic reactivity,and can be used as precursors of AAC.Both clinkerless and clinker-free AAC were prepared from the mixture of steel slag and blastfurnace slag by using water glass as an activator,and four different recipes which satisfied the strength requirement of 42.5R Portland cement were obtained.Each recipe of AAC exhibited better resistance to sulfate attack and frost attack than Portland cement.AAC showed huge drying shrinkage,but it was equivalent to that of Portland cement as steel slag content increased to 40%.The AAC also had quite low risk of alkali-aggregate reaction.Microstructure analysis showed that the major products were calcium silicate hydrate(C–S–H),calcium aluminosilicate hydrate(C–A–S–H)and zeolite-like phases.Ettringite was also detected in the binder when gypsum was contained in the precursors.