Impact of Self-Vacuuming of Lithoid-Pumice Aggregate on Concrete Properties

2021 ◽  
pp. 229-238
Author(s):  
Ashot Antonyan
Keyword(s):  
Concrete Properties

Utilization of waste engine oil for expanded clay aggregate production and assessment of its influence on lightweight concrete properties

2020 ◽  
pp. 121677
Author(s):  
Claudia Burbano-Garcia ◽  
Ana Hurtado ◽  
Yimmy Fernando Silva ◽  
Silvio Delvasto ◽  
Gerardo Araya-Letelier
Keyword(s):  
Lightweight Concrete ◽  
Engine Oil ◽  
Aggregate Production ◽  
Waste Engine Oil ◽  
Concrete Properties

scholarly journals Performance Evaluation of Soft Computing for Modeling the Strength Properties of Waste Substitute Green Concrete

2021 ◽  
Vol 13 (5) ◽  
pp. 2867
Author(s):  
Muhammad Izhar Shah ◽  
Muhammad Nasir Amin ◽  
Kaffayatullah Khan ◽  
Muhammad Sohaib Khan Niazi ◽  
Fahid Aslam ◽  
...  
Keyword(s):  
Predictive Models ◽  
Parametric Study ◽  
Cross Validation ◽  
Strength Properties ◽  
Fine Aggregate ◽  
Agricultural Industry ◽  
Green Concrete ◽  
Concrete Properties ◽  
Water To Cement Ratio ◽  
Sugarcane Bagasse Ash

The waste disposal crisis and development of various types of concrete simulated by the construction industry has encouraged further research to safely utilize the wastes and develop accurate predictive models for estimation of concrete properties. In the present study, sugarcane bagasse ash (SCBA), a by-product from the agricultural industry, was processed and used in the production of green concrete. An advanced variant of machine learning, i.e., multi expression programming (MEP), was then used to develop predictive models for modeling the mechanical properties of SCBA substitute concrete. The most significant parameters, i.e., water-to-cement ratio, SCBA replacement percentage, amount of cement, and quantity of coarse and fine aggregate, were used as modeling inputs. The MEP models were developed and trained by the data acquired from the literature; furthermore, the modeling outcome was validated through laboratory obtained results. The accuracy of the models was then assessed by statistical criteria. The results revealed a good approximation capacity of the trained MEP models with correlation coefficient above 0.9 and root means squared error (RMSE) value below 3.5 MPa. The results of cross-validation confirmed a generalized outcome and the resolved modeling overfitting. The parametric study has reflected the effect of inputs in the modeling process. Hence, the MEP-based modeling followed by validation with laboratory results, cross-validation, and parametric study could be an effective approach for accurate modeling of the concrete properties.

The influence of waste of concrete masonry units as coarse aggregate on concrete properties

2021 ◽  
Author(s):  
Hadeel R. Khatab ◽  
Mohanad IA. AL-Samaraie ◽  
Zaid Q. Mohammed ◽  
Abdullah A. AL-Samaraie
Keyword(s):  
Coarse Aggregate ◽  
Concrete Properties ◽  
Concrete Masonry ◽  
Masonry Units

An evaluation of iron ore tailings characteristics and iron ore tailings concrete properties

2021 ◽  
Vol 286 ◽  
pp. 122968
Author(s):  
Jiangshan Zhao ◽  
Kun Ni ◽  
Youpo Su ◽  
Yunxing Shi
Keyword(s):  
Iron Ore ◽  
Concrete Properties ◽  
Iron Ore Tailings

Effect of the addition of polypropylene fiber on concrete properties

2021 ◽  
pp. 1-25
Author(s):  
Mujeebul Rahman Latifi ◽  
Öznur Biricik ◽  
Ali Mardani Aghabaglou
Keyword(s):  
Polypropylene Fiber ◽  
Concrete Properties

Influence of concrete properties on the initial biological colonisation of marine artificial structures

2021 ◽  
Vol 159 ◽  
pp. 106104
Author(s):  
Atteyeh S. Natanzi ◽  
Bryan J. Thompson ◽  
Paul R. Brooks ◽  
Tasman P. Crowe ◽  
Ciaran McNally
Keyword(s):  
Artificial Structures ◽  
Concrete Properties
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