scholarly journals A Machine Learning-Assisted Numerical Predictor for Compressive Strength of Geopolymer Concrete Based on Experimental Data and Sensitivity Analysis

2020 ◽  
Vol 10 (21) ◽  
pp. 7726
Author(s):  
An Thao Huynh ◽  
Quang Dang Nguyen ◽  
Qui Lieu Xuan ◽  
Bryan Magee ◽  
TaeChoong Chung ◽  
...  

Geopolymer concrete offers a favourable alternative to conventional Portland concrete due to its reduced embodied carbon dioxide (CO2) content. Engineering properties of geopolymer concrete, such as compressive strength, are commonly characterised based on experimental practices requiring large volumes of raw materials, time for sample preparation, and costly equipment. To help address this inefficiency, this study proposes machine learning-assisted numerical methods to predict compressive strength of fly ash-based geopolymer (FAGP) concrete. Methods assessed included artificial neural network (ANN), deep neural network (DNN), and deep residual network (ResNet), based on experimentally collected data. Performance of the proposed approaches were evaluated using various statistical measures including R-squared (R2), root mean square error (RMSE), and mean absolute percentage error (MAPE). Sensitivity analysis was carried out to identify effects of the following six input variables on the compressive strength of FAGP concrete: sodium hydroxide/sodium silicate ratio, fly ash/aggregate ratio, alkali activator/fly ash ratio, concentration of sodium hydroxide, curing time, and temperature. Fly ash/aggregate ratio was found to significantly affect compressive strength of FAGP concrete. Results obtained indicate that the proposed approaches offer reliable methods for FAGP design and optimisation. Of note was ResNet, which demonstrated the highest R2 and lowest RMSE and MAPE values.

2020 ◽  
Vol 13 (1) ◽  
pp. 117-122
Author(s):  
Addepalli Mallinadh Kashyap ◽  
Tanimki Chandra Sekhar Rao ◽  
N.V. Ramana Rao

Carbon dioxide is liberated in huge amounts by the manufacturing of Portland Pozzolana Cement. Normally, conventional concrete is manufactured with Portland cement, which acts as a binder. The production of cement emits CO2 into the atmosphere, which is a green house gas and causes the environmental pollution. Considering this as a serious environmental problem, there is a need to develop sustainable alternatives to Portland cement utilizing the industrial byproducts such as fly ash, ground granulated blast furnace slag and Metakaoline which are pozzolonic in nature. It has been established that fly ash can replace cement partially. In this context, a new material was developed known as ‖Geopolymer‖. In this study, the various parameters on the short term engineering properties of fresh and hardened properties of Geopolymer Mortar were studied. In the present investigation, cement is replaced by geopolymer source material and water is replaced by alkaline activator consisting of Sodium Silicate and Sodium Hydroxide of molarity (12M). The ratio of sodium silicate to sodium hydroxide adopted was 2.5. The test results showed that final setting time decreases as the GGBS content in the mix increases and also increase in compressive strength. Where as in the case of metakaoline, as the content increases, there is a decrease in compressive strength and setting times of the geopolymer concrete.


Materials ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 983 ◽  
Author(s):  
Dong Dao ◽  
Hai-Bang Ly ◽  
Son Trinh ◽  
Tien-Thinh Le ◽  
Binh Pham

Geopolymer concrete (GPC) has been used as a partial replacement of Portland cement concrete (PCC) in various construction applications. In this paper, two artificial intelligence approaches, namely adaptive neuro fuzzy inference (ANFIS) and artificial neural network (ANN), were used to predict the compressive strength of GPC, where coarse and fine waste steel slag were used as aggregates. The prepared mixtures contained fly ash, sodium hydroxide in solid state, sodium silicate solution, coarse and fine steel slag aggregates as well as water, in which four variables (fly ash, sodium hydroxide, sodium silicate solution, and water) were used as input parameters for modeling. A total number of 210 samples were prepared with target-specified compressive strength at standard age of 28 days of 25, 35, and 45 MPa. Such values were obtained and used as targets for the two AI prediction tools. Evaluation of the model’s performance was achieved via criteria such as mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). The results showed that both ANN and ANFIS models have strong potential for predicting the compressive strength of GPC but ANFIS (MAE = 1.655 MPa, RMSE = 2.265 MPa, and R2 = 0.879) is better than ANN (MAE = 1.989 MPa, RMSE = 2.423 MPa, and R2 = 0.851). Sensitivity analysis was then carried out, and it was found that reducing one input parameter could only make a small change to the prediction performance.


2021 ◽  
Vol 30 (3) ◽  
pp. 464-476
Author(s):  
Haider Owaid ◽  
Haider Al-Baghdadi ◽  
Muna Al-Rubaye

Large quantities of paper and wood waste are generated every day, the disposal of these waste products is a problem because it requires huge space for their disposal. The possibility of using these wastes can mitigate the environmental problems related to them. This study presents an investigation on the feasibility of inclusion of waste paper ash (WPA) or wood ash (WA) as replacement materials for fly ash (FA) class F in preparation geopolymer concrete (GC). The developed geopolymer concretes for this study were prepared at replacement ratios of FA by WPA or WA of 25, 50, 75 and 100% in addition to a control mix containing 100% of FA. Sodium hydroxide (NaOH) solutions and sodium silicate (Na2SiO3) are used as alkaline activators with 1M and 10M of sodium hydroxide solution.The geopolymer concretes have been evaluated with respect to the workability, the compressive strength, splitting tensile strength and flexural strength. The results indicated that there were no significant differences in the workability of the control GC mix and the developed GC mixes incorporating WPA or WA. Also, the results showed that, by incorporating of 25–50% PWA or 25% WA, the mechanical properties (compressive strength, splitting tensile strength and flexural strength) of GC mixes slightly decreased. While replacement with 75–100% WPA or with 50–100% WA has reduced these mechanical properties of GC mixes. As a result, there is a feasibility of partial replacement of FA by up to 50% WPA or 25% WA in preparation of the geopolymer concrete.


Materials ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7375
Author(s):  
Xiaoshuang Shi ◽  
Cong Zhang ◽  
Yongchen Liang ◽  
Jinqian Luo ◽  
Xiaoqi Wang ◽  
...  

Geopolymer concrete (GPC) has drawn widespread attention as a universally accepted ideal green material to improve environmental conditions in recent years. The present study systematically quantifies and compares the environmental impact of fly ash GPC and ordinary Portland cement (OPC) concrete under different strength grades by conducting life cycle assessment (LCA). The alkali activator solution to fly ash ratio (S/F), sodium hydroxide concentration (CNaOH), and sodium silicate to sodium hydroxide ratio (SS/SH) were further used as three key parameters to consider their sensitivity to strength and CO2 emissions. The correlation and influence rules were analyzed by Multivariate Analysis of Variance (MANOVA) and Gray Relational Analysis (GRA). The results indicated that the CO2 emission of GPC can be reduced by 62.73%, and the correlation between CO2 emission and compressive strength is not significant for GPC. The degree of influence of the three factors on the compressive strength is CNaOH (66.5%) > SS/SH (20.7%) > S/F (9%) and on CO2 emissions is S/F (87.2%) > SS/SH (10.3%) > CNaOH (2.4%). Fly ash GPC effectively controls the environmental deterioration without compromising its compressive strength; in fact, it even in favor.


2022 ◽  
Vol 955 (1) ◽  
pp. 012010
Author(s):  
A Kustirini ◽  
Antonius ◽  
P Setiyawan

Abstract Geopolymer concrete is concrete that uses environmentally friendly materials, using fly ash from waste materials from the coal industry as a substitute for cement. To produce geopolymer concrete, an alkaline activator is required, with a mixture of Sodium Hydroxide and Sodium Silicate. This research is an experimental study to determine the effect of variations in the concentration of sodium hydroxide (NaOH) 8 Mol, 10 Mol, 12 Mol, and 14 Mol on the compressive strength of geopolymer concrete. Mortar Geopolymer uses a mixture of 1: 3 for the ratio of fly ash and sand, 2.5: 0.45 for the ratio of sodium silicate and sodium hydroxide as an alkaline solution. The specimens used a cube mold having dimension 5 cm x 5 cm x 5 cm, then tested at 7 days and 28 days. The test resulted that concentration of NaOH 12 Mol obtained the maximum compressive strength of geopolymer concrete, that is 38.54 MPa. At concentrations of 12 Mol NaOH and exceeding 12M, the compressive strength of geopolymer concrete decreased.


2019 ◽  
Vol 296 ◽  
pp. 105-111 ◽  
Author(s):  
Quang Minh Do ◽  
Thu Ha Bui ◽  
Hoc Thang Nguyen

This paper illustrates a special investigation on geopolymer concrete synthesized from fly ash, sand, coarse aggregates (solid phases) in conditions of sodium silicate solution and seawater (liquid phases). The mixtures of geopolymer concrete were designed with proportion changes of among materials to evaluate effects of the proportions to engineering properties of products. The specimens were molded into cylinder with 200 mm in length and 100 mm in diameter, and then cured at room condition (28 °C, 80 % of humidity) for testing engineering properties for 7 days, 28 days, 90 days, and 180 days. The engineering properties of geopolymer concrete samples included compressive strength (MPa), water absorption (kg/m3), and volumetric weight (kg/m3). The results showed that the fly ash-based geopolymer concrete using sodium silicate solution and seawater was very good performance with value of 180 day-compressive strength at 58 MPa, water absorption and volumetric weight were at 180 kg/m3 and 2200 kg/m3, respectively.


Author(s):  
Nurul Aida Mohd Mortar ◽  
H. Kamarudin ◽  
R. A. Rafiza ◽  
T.A.F Meor ◽  
M Rosnita

2021 ◽  
Author(s):  
Hemn Unis Ahmed ◽  
Azad A. Mohammed ◽  
Ahmed S. Mohammed

Abstract The growing concern about global climate change and its adverse impacts on societies is putting severe pressure on the construction industry as one of the largest producers of greenhouse gases. Given the environmental issues associated with cement production, geopolymer concrete has emerged as a sustainable construction material. Geopolymer concrete is cementless concrete that uses industrial or agro by-product ashes as the main binder instead of ordinary Portland cement; this leads to being an eco-efficient and environmentally friendly construction material. Compressive strength is one of the most important mechanical property for all types of concrete composites including geopolymer concrete, and it is affected by several parameters like an alkaline solution to binder ratio (l/b), fly ash (FA) content, SiO2/Al2O3 (Si/Al) of the FA, fine aggregate (F) and coarse aggregate (C) content, sodium hydroxide (SH) and sodium silicate (SS) content, ratio of sodium silicate to sodium hydroxide (SS/SH), molarity (M), curing temperature (T), curing duration (CD) inside the oven and specimen ages (A). In this regard, a comprehensive systematic review was carried out to show the effect of these different parameters on the compressive strength of the fly ash-based geopolymer concrete (FA-GPC). In addition, multi-scale models such as Artificial Neural Network (ANN), M5P-tree (M5P), Linear Regression (LR), and Multi-logistic Regression (MLR) models were developed to predict the compressive strength of FA-GPC composites. For the first time, in the modeling process, twelve effective parameters including l/b, FA, Si/Al, F, C, SH, SS, SS/SH, M, T, CD, and A were considered the modeling input parameters. Then, the efficiency of the developed models was assessed by various statistical assessment tools like Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Scatter Index (SI), OBJ value, and the Coefficient of determination (R2). Results show that the curing temperature, sodium silicate content, and ratio of the alkaline solution to the binder content are the most significant independent parameters that influence on the compressive strength of the FA-GPC, and the ANN model has better performance for predicting the compressive strength of FA-GPC in compared to the other developed models.


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