Mechanical Behaviour and Microstructural Investigation of Geopolymer Concrete After Exposure to Elevated Temperatures

Short-term residual characteristics of ambient-cured green geopolymer mortar exposed to elevated temperatures

Every structure might be exposed to fire at some point in its lifecycle. The ability of geopolymer composites to withstand the effects of fire damage early before it is put out is of great importance. This study examined the effects of fire on geopolymer composite samples made with high-calcium fly ash and alkaline solution synthesised from waste banana peduncle and silica fume. A ratio of 0.30, 0.35, and 0.4 was used in the study for the alkaline solution to fly ash. Also used were ratios of 0.5, 0.75, and 1 for silica oxide (silica fume) to potassium hydroxide ratio. The strength loss, residual compressive strength, percentage strength loss, relative residual compressive strength, ultrasonic pulse velocity, and microstructural properties of the thirteen mortar mixes were measured after exposure to temperatures of 200, 400, 600, and 800 °C for 1 h, respectively. The results reveal that geopolymer samples exposed to elevated temperatures showed great dimensional stability with no visible surface cracks. There was a colour transition from dark grey to whitish brown for the green geopolymer mortar and brown to whitish brown for the control sample. As the temperature rose, weight loss became more pronounced, with 800 °C producing the most significant weight reduction. The optimum mixes had a residual compressive strength of 25.02 MPa after being exposed to 200 °C, 18.72 MPa after being exposed to 400 °C, 14.04 MPa after being exposed to 600 °C, and 7.41 MPa after being exposed to 800 °C. The control had a residual compressive strength of 8.45 MPa after being exposed to 200 °C, 6.67 MPa after being exposed to 400 °C, 3.16 MPa after being exposed to 600 °C, and 2.23 MPa after being exposed to 800 °C. The relative residual compressive strength decreases for green geopolymer mortar are most significant at 600 and 800 °C, with an average decrease of 0.47 and 0.30, respectively. The microstructure of the samples revealed various phase changes and new product formations as the temperature increased.

Estimation of compressive strength of waste concrete utilizing fly ash/slag in concrete with interpretable approaches: optimization and graphical user interface (GUI)

Geo-polymer concrete has a significant influence on the environmental condition and thus its use in the civil industry leads to a decrease in carbon dioxide (CO2) emission. However, problems lie with its mixed design and casting in the field. This study utilizes supervised artificial-based machine learning algorithms (MLAs) to anticipate the mechanical characteristic of fly ash/slag-based geopolymer concrete (FASBGPC) by utilizing AdaBoost and Bagging on MLPNN to make an ensemble model with 156 data points. The data consist of GGBS (kg/m3), Alkaline activator (kg/m3), Fly ash (kg/m3), SP dosage (kg/m3), NaOH Molarity, Aggregate (kg/m3), Temperature (°C) and compressive strength as output parameter. Python programming is utilized in Anaconda Navigator using Spyder version 5.0 to predict the mechanical response. Statistical measures and validation of data are done by splitting the dataset into 80/20 percent and K-Fold CV is employed to check the accurateness of the model by using MAE, RMSE, and R2. Statistical analysis relies on errors, and tests against external indicators help determine how well models function in terms of robustness. The most important factor in compressive strength measurements is examined using permutation characteristics. The result reveals that ANN with AdaBoost is outclassed by giving maximum enhancement with R2 = 0.914 and shows the least error with statistical and external validations. Shapley analysis shows that GGBS, NaOH Molarity, and temperature are the most influential parameter that has significant content in making FASBGPC. Thus, ensemble methods are suitable for constructing prediction models because of their strong and reliable performance. Furthermore, the graphical user interface (GUI) is generated through the process of training a model that forecasts the desired outcome values when the corresponding inputs are provided. It streamlines the process and provides a useful tool for applying the model's abilities in the field of civil engineering.

Performance Evaluation of Reinforced Concrete Columns under Simultaneously Combined Fire and Cyclic Loads

Reinforced concrete (RC) structures could suffer from the combined action of fires, earthquakes, and other loads during their life cycle; more importantly, coupled disasters lead to further deterioration and damage to structural performance. This paper investigated the multiple performances and distinguished the safe working conditions of the RC column subjected to simultaneously combined fire and cyclic loads. The numerical model considered the degradation of the mechanical properties of steel and concrete and the bond-slip performance between steel and concrete at high temperatures. The results show that the performance of RC columns with different section sizes, longitudinal reinforcement ratios, cover thicknesses, axial load ratios, and cyclic loads differs greatly under simultaneously combined fire-cyclic loads. In specific, when the cyclic load application time is less than 2 h, the cyclic load has little effect on the response of the RC column. According to the different characteristics of RC columns when subjected to combined fire-cyclic loads, the firing process of RC columns is divided into four stages. To avoid the excessive performance degradation of RC columns, the minimum designed fire resistance time of RC columns is recommended to be 2.5 times the fire resistance time of the RC column under static loads.

Elevated-Temperature Performance, Combustibility and Fire Propagation Index of Fly Ash-Metakaolin Blend Geopolymers with Addition of Monoaluminium Phosphate (MAP) and Aluminum Dihydrogen Triphosphate (ATP)

Thermal performance, combustibility, and fire propagation of fly ash-metakaolin (FA-MK) blended geopolymer with the addition of aluminum triphosphate, ATP (Al(H₂PO₄)₃), and monoaluminium phosphate, MAP (AlPO₄) were evaluated in this paper. To prepare the geopolymer mix, fly ash and metakaolin with a ratio of 1:1 were added with ATP and MAP in a range of 0-3% by weight. The fire/heat resistance was evaluated by comparing the residual compressive strengths after the elevated temperature exposure. Besides, combustibility and fire propagation tests were conducted to examine the thermal performance and the applicability of the geopolymers as passive fire protection. Experimental results revealed that the blended geopolymers with 1 wt.% of ATP and MAP exhibited higher compressive strength and denser geopolymer matrix than control geopolymers. The effect of ATP and MAP addition was more obvious in unheated geopolymer and little improvement was observed for geopolymer subjected to elevated temperature. ATP and MAP at 3 wt.% did not help in enhancing the elevated-temperature performance of blended geopolymers. Even so, all blended geopolymers, regardless of the addition of ATP and MAP, were regarded as the noncombustible materials with negligible (0-0.1) fire propagation index.