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Comparative environmental assessment of natural and recycled aggregate concrete
(Waste Management, 2010)
Constant and rapid increase in construction and demolition (C&D) waste generation and consumption of natural aggregate for concrete production became one of the biggest environmental problems in the construction industry. ...
Punching failure mechanism at edge columns of post-tensioned lift slabs
(Engineering Structures, 2008)
A test program designed to evaluate the punching shear strength of unbonded post-tensioned lift flat slabs at edge columns is described. Three isolated specimens, which represented a part of the edge panel in the vicinity ...
Landslide susceptibility assessment using SVM machine learning algorithm
(Engineering Geology, 2011)
This paper introduces the current machine learning approach to solving spatial modeling problems in the domain of landslide susceptibility assessment. The latter is introduced as a classification problem, having multiple ...
Further insight into the mechanism of heavy metals partitioning in stormwater runoff
(Academic Press, 2016)
Various particles and materials, including pollutants, deposited on urban surfaces are washed off by stormwater runoff during rain events. The interactions between the solid and dissolved compounds in stormwater runoff are ...
Flexural behavior of reinforced recycled aggregate concrete beams under short-term loading
(Materials and Structures, 2013)
Recycling of waste concrete is one of the sustainable solutions for the growing waste disposal crisis and depletion of natural aggregate sources. As a result, recycled concrete aggregate (RCA) is produced, and so far it ...
Flexural reinforcement of glulam beams with CFRP plates
(Kluwer Academic Publishers, 2016)
In recent years the use of fiber reinforced polymer composites for strengthening and repairing structural elements has significantly increased. This paper shows an experimental study carried out in order to demonstrate the ...
Rapid earthquake loss assessment based on machine learning and representative sampling
(Earthquake Spectra, 2021)
This paper proposes a new framework for rapid earthquake loss assessment based on a machine learning damage classification model and a representative sampling algorithm. A Random Forest classification model predicts a ...