A novel hybrid soft computing model using stacking with ensemble method for estimation of compressive strength of geopolymer composite

Gupta, Priyanka; Gupta, Nakul; Saxena, Kuldeep K.; Goyal, Sudhir Kumar

doi:10.1080/2374068x.2021.1945271

Cited by 6 publications

(4 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the study, concrete of grades M-20, M-25, and M-30 was prepared following the mix design specifications outlined in IS : 10262. The mixing process was conducted using a concrete mixer, and cubes measuring 150 mm × 150 mm × 150 mm were cast for testing [27]. After one day the specimens were demoulded and were kept in a curing tank filled with water, where they underwent a curing process for durations of 3, 14, and 28 days.…”

Section: Procedures Of Compressive Strength Test Of Concrete Cubesmentioning

confidence: 99%

Analysing Indirect Methods for Comparatively Determining the Compressive Strength of Materials with Various Properties

Raman,

Dasari,

Chandrashekar

et al. 2024

E3S Web of Conf.

View full text Add to dashboard Cite

The properties and compressive strength of hardened concrete are examined by destructive and non-destructive testing methods. There was no direct relationship between non-destructive testing results for existing concrete structures. This article describes the comparison between rebound and compression hammer tests of hardened concrete. It also describes the comparison of strength and cube compressive strength as well as the comparison of modulus of elasticity according to different standards.Destructive and non-destructive techniques were used in an experimental programme on various concrete mixtures, including M20, M25, and M30. A comprehensive technique was used for evaluating the compressive strength properties of concrete grades M20, M25, and M30, using both destructive and non-destructive testing methods. The impact strength, maximum load, Schmidt hammer, and uniaxial compression test findings have been also reviewed within the examination. The study’s primary purpose was to clarify the connections between specific evaluations technique and actual grades. Similarly, those connections were subjected to an in-depth validation technique using previously advanced formulation from previous research, which produced precious statistics about the assessment of concrete strength. These findings increase our understanding of concrete’s behaviour and provide essential path for destiny packages inside the engineering and construction industries, enabling properly-informed decision-making in those domains.

show abstract

Section: Procedures Of Compressive Strength Test Of Concrete Cubesmentioning

confidence: 99%

Analysing Indirect Methods for Comparatively Determining the Compressive Strength of Materials with Various Properties

Raman,

Dasari,

Chandrashekar

et al. 2024

E3S Web of Conf.

View full text Add to dashboard Cite

show abstract

“…It has been established that the addition of polymer fibres to a geopolymer composite may significantly increase both the strength and toughness of the composite. [83][84][85][86] Various polymer fibres are common kinds of materials that are used to reinforce the geopolymer matrix.…”

Section: Ultrasonic Pulse Velocity Test (Upvt)mentioning

confidence: 99%

Investigation on the impact of elevated temperature on sustainable geopolymer composite

Verma,

Meena,

Singh

et al. 2023

Advances in Mechanical Engineering

View full text Add to dashboard Cite

Geopolymer concrete (GPC) is an eco-friendly, sustainable, cementless and green concrete. It could be an alternative to the conventional concrete. In alkaline circumstances, the alumina and silica concentration in geopolymer concrete creates the geopolymer bond, while regular concrete creates C-S-H (calcium silicate hydrate bond). The final result of the geopolymer bond does not include any water. At elevated temperatures, geopolymer concrete would thus be more stable. Due to its greater strength and durability quality, geopolymer concrete may be the ideal replacement for ordinary portland cement (OPC) concrete. This research intends to examine how specimens of geopolymer concrete and regular concrete respond to exposure to increased temperatures between 100°C and 800°C. Mass loss, ultrasonic pulse velocity, compressive strength, X-ray diffraction, thermogravimetric analysis and derivative thermogravimetric analysis were all examined throughout the experimental examination. Both concrete specimens lose mass or weight as the exposure temperature rises; OPC concrete samples spalls at 600°C, while GPC sample fail at 800°C. GPC specimens lose around 12% of their original mass after being exposed to temperatures of 800°C, while OPC specimens lose about 7%. The GPC specimens maintained 60% of their initial compressive strength after being exposed to a temperature of 700°C, but the OPC concrete specimens only kept 52%. With each increase in exposure to extreme temperatures, the peaks of quartz and cristobalite are lowered. Only the form or structure of the mineral oxide would change; the chemical linkages would remain. The GPC samples subjected to temperatures of 100°C exhibit effective thermal stability than all other specimens exposed to extreme temperatures. As the exposure temperature rises, the GPC specimens become more thermally stable. According to the experimental findings, the GPC specimens’ bonding structure makes them more resistant to high temperatures than regular concrete specimens. Micropores are present in the voids of the geopolymer matrix, while mesopores and micropores are present in the voids of the OPC matrix. While OPC bonding is C-S-H formed by the hydration of lime and silica contained in the cement, the geopolymer bonding did not include the water content in the final or end result of geopolymerisation for strengthening.

show abstract

“…Ahmad [ 34 ] et al used the bagging model to predict the compressive strength of concrete containing supplementary cementing materials. Gupta [ 35 ] et al estimated the compressive strength of geopolymer composites by using the stacking model.…”

Section: Introductionmentioning

confidence: 99%

Ensemble Machine-Learning-Based Prediction Models for the Compressive Strength of Recycled Powder Mortar

et al. 2023

View full text Add to dashboard Cite

Recycled powder (RP) serves as a potential and prospective substitute for cementitious materials in concrete. The compressive strength of RP mortar is a pivotal factor affecting the mechanical properties of RP concrete. The application of machine learning (ML) approaches in the engineering problems, particularly for predicting the mechanical properties of construction materials, leads to high prediction accuracy and low experimental costs. In this study, 204 groups of RP mortar compression experimental data are collected from the literature to establish a dataset for ML, including 163 groups in the training set and 41 groups in the test set. Four ensemble ML models, namely eXtreme Gradient-Boosting (XGBoost), Random Forest (RF), Light Gradient-Boosting Machine (LightGBM) and Adaptive Boosting (AdaBoost), were selected to predict the compressive strength of RP mortar. The comparative results demonstrate that XGBoost has the highest prediction accuracy when the a10-index, MAE, RMSE and R2 of the training set are 0.926, 1.596, 2.155 and 0.950 and the a10-index, MAE, RMSE and R2 of the test set are 0.659, 3.182, 4.285 and 0.842, respectively. SHapley Additive exPlanation (SHAP) is adopted to interpret the prediction process of XGBoost and explain the influence of influencing factors on the compressive strength of RP mortar. According to the importance of influencing factors, the order is the mass replacement rate of RP, the size of RP, the kind of RP and the water binder ratio of RP. The compressive strength of RP mortar decreases with the increase in the RP mass replacement rate. The compressive strength of RBP mortar is slightly higher than that of RCP mortar. Machine learning technologies will benefit the construction industry by facilitating the rapid and cost-effective evaluation of RP material properties.

show abstract

A novel hybrid soft computing model using stacking with ensemble method for estimation of compressive strength of geopolymer composite

Cited by 6 publications

References 45 publications

Analysing Indirect Methods for Comparatively Determining the Compressive Strength of Materials with Various Properties

Analysing Indirect Methods for Comparatively Determining the Compressive Strength of Materials with Various Properties

Investigation on the impact of elevated temperature on sustainable geopolymer composite

Ensemble Machine-Learning-Based Prediction Models for the Compressive Strength of Recycled Powder Mortar

Contact Info

Product

Resources

About