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Zhang GY, Wang XY. Carbon Peaking and Carbon Neutrality in the Cement-Based Materials. MATERIALS (BASEL, SWITZERLAND) 2023; 16:4705. [PMID: 37445018 DOI: 10.3390/ma16134705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 06/28/2023] [Indexed: 07/15/2023]
Abstract
The cement industry plays a significant role in global carbon emissions, accounting for approximately 8% of global anthropogenic carbon dioxide (CO2) emissions [...].
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Affiliation(s)
- Gui-Yu Zhang
- Department of Integrated Energy and Infra System, Kangwon National University, Chuncheon-si 24341, Republic of Korea
| | - Xiao-Yong Wang
- Department of Integrated Energy and Infra System, Kangwon National University, Chuncheon-si 24341, Republic of Korea
- Department of Architectural Engineering, Kangwon National University, Chuncheon-si 24341, Republic of Korea
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Khan K, Ahmad W, Amin MN, Rafiq MI, Abu Arab AM, Alabdullah IA, Alabduljabbar H, Mohamed A. Evaluating the effectiveness of waste glass powder for the compressive strength improvement of cement mortar using experimental and machine learning methods. Heliyon 2023; 9:e16288. [PMID: 37234626 PMCID: PMC10208832 DOI: 10.1016/j.heliyon.2023.e16288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Revised: 05/06/2023] [Accepted: 05/11/2023] [Indexed: 05/28/2023] Open
Abstract
This study utilized both experimental testing and machine learning (ML) strategies to assess the effectiveness of waste glass powder (WGP) on the compressive strength (CS) of cement mortar. The cement-to-sand ratio was kept 1:1 with a water-to-cement ratio of 0.25. The superplasticizer content was 4% by cement mass, and the proportion of silica fume was 15%, 20%, and 25% by cement mass in three different mixes. WGP was added to cement mortar at replacement contents from 0 to 15% for sand and cement with a 2.5% increment. Initially, using an experimental method, the CS of WGP-based cement mortar at the age of 28 days was calculated. The obtained data were then used to forecast the CS using ML techniques. For CS estimation, two ML approaches, namely decision tree and AdaBoost, were applied. The ML model's performance was assessed by calculating the coefficient of determination (R2), performing statistical tests and k-fold validation, and assessing the variance between the experimental and model outcomes. The use of WGP enhanced the CS of cement mortar, as noted from the experimental results. Maximum CS was attained by substituting 10% WGP for cement and 15% WGP for sand. The findings of the modeling techniques demonstrated that the decision tree had a reasonable level of accuracy, while the AdaBoost predicted the CS of WGP-based cement mortar with a higher level of accuracy. Utilizing ML approaches will benefit the construction industry by providing efficient and economic approaches for assessing the properties of materials.
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Affiliation(s)
- Kaffayatullah Khan
- Department of Civil and Environmental Engineering, College of Engineering, King Faisal University, Al-Ahsa, 31982, Saudi Arabia
| | - Waqas Ahmad
- Department of Civil Engineering, COMSATS University Islamabad, Abbottabad, 22060, Pakistan
| | - Muhammad Nasir Amin
- Department of Civil and Environmental Engineering, College of Engineering, King Faisal University, Al-Ahsa, 31982, Saudi Arabia
| | - Muhammad Isfar Rafiq
- Department of Civil Engineering, COMSATS University Islamabad, Abbottabad, 22060, Pakistan
| | - Abdullah Mohammad Abu Arab
- Department of Civil and Environmental Engineering, College of Engineering, King Faisal University, Al-Ahsa, 31982, Saudi Arabia
| | | | - Hisham Alabduljabbar
- Department of Civil Engineering, College of Engineering in Al-Kharj, Prince Sattam Bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia
| | - Abdullah Mohamed
- Research Centre, Future University in Egypt, New Cairo, 11835, Egypt
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