ORCID Profile
0000-0002-6139-6833
Current Organisation
National University of Sciences and Technology
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Publisher: MDPI AG
Date: 27-04-2022
DOI: 10.3390/MA15093166
Abstract: The entraining and distribution of air voids in the concrete matrix is a complex process that makes the mechanical properties of lightweight foamed concrete (LFC) highly unpredictable. To study the complex nature of aerated concrete, a reliable and robust prediction model is required, employing different machine learning (ML) techniques. This study aims to predict the compressive strength of LFC by using a support vector machine (SVM) as an in idual learner along with bagging, boosting, and random forest (RF) as a modified ensemble learner. For that purpose, a database of 191 data points was collected from published literature, where the mix design ingredients, i.e., cement content, sand content, water to cement ratio, and foam volume, were chosen to predict the compressive strength of LFC. The 10-K fold cross-validation method and different statistical error and regression tools, i.e., mean absolute error (MAE), root means square error (RMSE), and coefficient of determinant (R2), were used to evaluate the performance of the developed ML models. The modified ensemble learner (RF) outperforms all models by yielding a strong correlation of R2 = 0.96 along with the lowest statistical error values of MAE = 1.84 MPa and RMSE = 2.52 MPa. Overall, the result suggests that the ensemble learners would significantly enhance the performance and robustness of ML models.
Publisher: Elsevier BV
Date: 09-2022
Publisher: Thomas Telford Ltd.
Date: 08-2022
Abstract: An experimental investigation was carried out on a novel type of concrete-filled tube column, which used geopolymer concrete and basalt-fibre-reinforced-polymer reinforcing bars and confinement tube. Geopolymer concrete was used in place of ordinary Portland cement concrete to counter the sustainability challenges of conventional cement manufacture. Longitudinal basalt-fibre-reinforced-polymer bars were used to replace steel reinforcement to avoid corrosion, while basalt-fibre-reinforced-polymer tube confinement was used to replace the conventionally used steel helix to enhance strength and ductility. Compressive load–deformation behaviour of 200 mm dia., 800 mm high specimens under concentric, 25 mm eccentric, 50 mm eccentric and four-point bending loads was experimentally investigated. Experimental axial load–bending moment diagrams were then produced. Although geopolymer concrete is normally considered to be more brittle than Portland cement concrete, the test results showed that the specimens with geopolymer concrete were more ductile compared to those with Portland cement concrete. It was also found that increased load eccentricity resulted in ductility enhancement in specimens with both types of concrete with basalt-fibre-reinforced-polymer bars and tubes, while steel-reinforced specimens suffered loss of ductility with increased load eccentricity.
Publisher: American Concrete Institute
Date: 2021
DOI: 10.14359/51728094
Publisher: Elsevier BV
Date: 10-2021
Publisher: Wiley
Date: 07-2023
Abstract: Geopolymer concrete (GC) has emerged as an environmentally friendly alternative to ordinary concrete, resulting from the alkalination of an Alumino‐Silicate (Al‐Si) source material. Large‐scale applications of GC are predicated on a suitable supply of Al‐Si sources, however rapid depletion of traditional sources like fly ash imposes a challenge therein and alternative source materials need to be identified. Agricultural waste ashes (AGWA) also exhibit high Al‐Si content therefore, in this study, two AGWA, that is, Corn Cob Ash (CCA) and Sugarcane Bagasse Ash (SCBA) were used in lieu of fly ash for GC synthesis. The results for workability and mechanical testing showed that properties of GC remained intact for up to 20% and 10% CCA and SCBA, respectively. Life cycle assessment showed that AGWA‐based GC reduced the greenhouse gas emissions of ordinary concrete by 49% and can be used as an environmentally friendly alternative thereof, thus contributing to the circular economy.
Publisher: Springer Science and Business Media LLC
Date: 26-12-2017
Publisher: Elsevier BV
Date: 10-2021
Publisher: Informa UK Limited
Date: 03-07-2018
Publisher: IGI Global
Date: 07-2018
Abstract: This article describes Dhajji Dewari which is a non-engineered traditional construction method mostly used in the northern parts of Pakistan. This method consists of a timber frame filled with the stones in a mud slurry. This article is aimed to assess the effects of different infills on the lateral load capacity of Dhajji Dewari. For this purpose, three full scale Dhajji Dewari panels were constructed and unidirectional in-plane lateral load was applied. One panel was without infill, two other panels with different type of infills. Results of the experimentation showed that the infill presence effects the lateral load resisting performance of the Dhajji Dewari.
Publisher: Elsevier BV
Date: 12-2021
No related grants have been discovered for Junaid Ahmad.