High temperature resistance of self compacting alkali activated slag/portland cement composite using lightweight aggregate

Dener, Murat; Karataş, Mehmet; Mohabbi, Mehrzad

doi:10.1016/j.conbuildmat.2021.123250

Cited by 50 publications

(22 citation statements)

References 28 publications

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“…e influence on strength of AAS should be from both alkali activator and slag, as well as their proportion. Considering the importance of the influencing parameters, alkali concentration of WG (Na 2 O%), modulus of WG (Ms), water/binder ratio (W/B), surface area of slag (SA), and basicity index of slag (K b ) were taken as the input parameters of the models [7][8][9][10][11][12][13]. Other parameters, such as binder content, which are less important and then not typically considered in the literature, are not adopted in this study for model establishment.…”

Section: Data Collection and Modelingmentioning

confidence: 99%

Compressive Strength Prediction of Alkali‐Activated Slag Concretes by Using Artificial Neural Network (ANN) and Alternating Conditional Expectation (ACE)

Qin

Guo

et al. 2022

Advances in Civil Engineering

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Compressive strength of alkali-activated slag (AAS) concrete is influenced by multi-factors in a nonlinear way. Both artificial neural network (ANN) and alternating conditional expectation (ACE) models of 3-day (3 d) and 28-day (28 d) compressive strength of AAS were established in this study by using the data reported in related literature, where alkali concentration of activator (Na2O%), modulus of activator (Ms), water/binder ratio (W/B), surface area of slag (SA), and basicity index of slag (Kb) were taken as input parameters. The models were employed later to predict 3 d and 28 d compressive strength of AAS concretes, respectively, and the results were validated by experimental work. The results show that both the ANN and the ACE models had adequate accuracy, no matter 3 d or 28 d compressive strength was considered. Compared to the 3 d compressive strength, due to data scattering that increased with the increase of data size, both the models did not yield a higher accuracy in the case of 28 d strength. However, also due to the increase in data size, both the models were more feasible to implement 28 d strength prediction as a result of sufficient learning and training during modeling. In addition, based on ACE analysis, the weight-influencing compressive strength of AAS decreased in a sequence of Na2O% > Ms > W/B > Kb > SA. If data size was sufficiently large, it was more suitable to establish an ANN model for compressive strength prediction of AAS concretes. Otherwise, ACE could be considered as an alternative to yield an acceptable result.

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Section: Data Collection and Modelingmentioning

confidence: 99%

Compressive Strength Prediction of Alkali‐Activated Slag Concretes by Using Artificial Neural Network (ANN) and Alternating Conditional Expectation (ACE)

Qin

Guo

et al. 2022

Advances in Civil Engineering

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“…Meanwhile, polycarboxylate-based superplasticizers have been demonstrated in some studies showing promising performance in AAM [ 77 , 78 , 79 ]. The polycarboxylate-based superplasticizer has also been adopted [ 30 , 79 , 80 ]. Success in workability improvement has been achieved after adding superplasticizer, but the addition amount is much higher than in cement concrete.…”

Section: Materials and Formulationsmentioning

confidence: 99%

“…This is attributed to the porosity increase caused by a boost in unreacted FA particles. Dener et al [ 80 ] studied the influence of aggregate, in which pumice was used as lightweight aggregate. It was reported that the increasing pumice aggregate directly enhanced the water absorption values.…”

Section: Property Of Hardened Scaamsmentioning

confidence: 99%

Self-Compacting Alkali-Activated Materials: Progress and Perspectives

et al. 2021

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Alkali-activated materials (AAMs) are considered to be alternative cementitious materials for civil infrastructures. Nowadays, efforts have been made in developing AAMs with self-compacting ability. The obtained self-compacting AAMs (SCAAMs) accomplish superior passing and filling properties as well as excellent mechanical and environmental advantages. This work critically revisits recent progresses in SCAAMs including mixture proportions, fresh properties, mechanical strength, microstructure, acid and sulfate resistance, high temperature behaviors, impact resistance and interface shear strength. To facilitate direct comparison and interpretation of data from different publications, mixture proportions were normalized in terms of the content of key reactive components from precursors and activators, and correlation with mechanical behaviors was made. Moreover, special attention was paid to current research challenges and perspectives to promote further investigation and field application of SCAAMs as advanced construction material.

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“…At present, domestic and foreign scholars studied cementing slurry systems suitable for heavy oil thermal recovery, mainly in the following two directions: one is the optimization of the chemical composition of cement to increase the relative content of high-temperature resistant hydration products in cement hydration products (Dener et al, 2021;Yang et al, 2021;Frías et al, 2022); the other is the introduction of materials with high strength and high thermal conductivity at high temperatures to optimize the internal microstructure of cement paste (Jiang et al, 2021a;Jiang et al, 2021b;Zhang et al, 2021c). However, most of the existing studies focused on addressing the problem of strength decline at high temperatures, but ignored the damage to the cement sheath caused by CO 2 corrosion.…”

Section: Introductionmentioning

confidence: 99%

Effect of CO2 on the Hydration of Aluminate Cement Under Conditions of Burning Reservoir in Heavy Oil Thermal Recovery

Wu¹,

Wu²,

Xing³

et al. 2022

Front. Mater.

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Under conditions of heavy oil thermal recovery, cement sheaths often suffer high-temperature performance degradation and CO2 corrosion. The performance of Class G oil well cement commonly used for cementing, deteriorates significantly at high temperatures and in CO2 environments, which can easily cause accidents. By contrast aluminate cement (CAC), at the same time, has good high-temperature resistance and corrosion resistance. Therefore, this study explored the mechanical properties and permeability of CAC with a high-temperature stabiliser cement slurry system (C1), pure CAC slurry system (C2) and Portland cement with sand cement slurry system (C3) before and after corrosion at 50, 300, 400, 500, and 600°C. The micromorphology, hydration products and pore structure of the cement paste before and after corrosion were analyzed using scanning electron microscopy, X-ray diffraction, thermogravimetry and nitrogen adsorption specific surface area and pore diameter analysis; additionally, the hydration mechanism of CAC under high temperatures and in CO2 environments was explored. The results show that the degree of degradation of the mechanical properties of C1 cement slurry system at high temperatures and under CO2 corrosive environments is significantly lower than that of the C3 cement slurry system. At a curing high temperature of 400°C, the maximum strength of the C1 cement paste reached 36.39 ± 0.37 MPa. The addition of a high-temperature stabiliser improved the mechanical properties of CAC at low temperatures, reduced the formation of C3ASH4 in the cement paste at high temperatures, and improved the strength of the cement paste after high-temperature curing. Compared with the C3 cement slurry system, the C1 cement slurry system had better high-temperature resistance and corrosion resistance and was more suitable for application under conditions of a burning reservoir in heavy oil thermal recovery.

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High temperature resistance of self compacting alkali activated slag/portland cement composite using lightweight aggregate

Cited by 50 publications

References 28 publications

Compressive Strength Prediction of Alkali‐Activated Slag Concretes by Using Artificial Neural Network (ANN) and Alternating Conditional Expectation (ACE)

Compressive Strength Prediction of Alkali‐Activated Slag Concretes by Using Artificial Neural Network (ANN) and Alternating Conditional Expectation (ACE)

Self-Compacting Alkali-Activated Materials: Progress and Perspectives

Effect of CO2 on the Hydration of Aluminate Cement Under Conditions of Burning Reservoir in Heavy Oil Thermal Recovery

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