2021
DOI: 10.9734/ijecc/2021/v11i530415
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Management of Construction and Demolished Waste as an Aggregate Substitute in Cement Concrete

Abstract: India is in the process of modernization in the construction sector by repairing, renovation, up-gradation. Presently concrete, the universal building materials whose main ingredient is coarse aggregate.  The local natural resources like stone products and sand may exhaust and put the sector deficient of aggregates.  The wise use is to reuse recycled concrete and demolition wastes generated from the construction sectors due to shift from horizontal to vertical growth of urban areas. The replacement of recycled… Show more

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Cited by 9 publications
(1 citation statement)
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“…e main aim of Pellegrino and Costantino was to understand whether the learning effect explaining productivity gains in subsequent cycles of a given repetitive construction process is primarily attributable to pure worker learning [3]. Mahakud et al's project deals with the reuse of concrete blocks dismantled from C&D waste in the form of recycled coarse aggregate (RCA), which is replacing natural coarse aggregate in concrete and is used in the construction industry [4]. In Dimitriou et al's paper, the widely recognized feedforward artificial neural network (FFANN) intelligence is used to process real-world data from 68 concrete highway bridges and provide an alternative model for accurate Bill of Quantity (BoQ) estimation [5].…”
Section: Related Workmentioning
confidence: 99%
“…e main aim of Pellegrino and Costantino was to understand whether the learning effect explaining productivity gains in subsequent cycles of a given repetitive construction process is primarily attributable to pure worker learning [3]. Mahakud et al's project deals with the reuse of concrete blocks dismantled from C&D waste in the form of recycled coarse aggregate (RCA), which is replacing natural coarse aggregate in concrete and is used in the construction industry [4]. In Dimitriou et al's paper, the widely recognized feedforward artificial neural network (FFANN) intelligence is used to process real-world data from 68 concrete highway bridges and provide an alternative model for accurate Bill of Quantity (BoQ) estimation [5].…”
Section: Related Workmentioning
confidence: 99%